git commit -m "feat: major architectural refactor

- Refactor memory system (episodic/STM/LTM with components)
- Implement complete subtitle domain (scanner, matcher, placer)
- Add YAML workflow infrastructure
- Externalize knowledge base (patterns, release groups)
- Add comprehensive testing suite
- Create manual testing CLIs"

.env.alfred

@@ -0,0 +1,77 @@
+# --- IMPORTANT ---
+# Settings are split across multiple files for clarity.
+# Files (loaded in this order, last wins):
+#   .env.alfred   — app config and service addresses (safe to commit)
+#   .env.secrets  — generated secrets, passwords, URIs and API keys (DO NOT COMMIT)
+#   .env.make     — build metadata synced from pyproject.toml (safe to commit)
+#
+# To customize: edit .env.alfred for config, .env.secrets for secrets.
+
+# --- Alfred ---
+MAX_HISTORY_MESSAGES=10
+MAX_TOOL_ITERATIONS=10
+REQUEST_TIMEOUT=30
+
+# LLM Settings
+LLM_TEMPERATURE=0.2
+
+# Persistence
+DATA_STORAGE_DIR=data
+
+# Network
+HOST=0.0.0.0
+PORT=3080
+
+# --- DATABASES ---
+# Passwords and connection URIs are auto-generated in .env.secrets.
+# Edit host/port/user/dbname here if needed.
+
+# MongoDB (Application Data)
+MONGO_HOST=mongodb
+MONGO_PORT=27017
+MONGO_USER=alfred
+MONGO_DB_NAME=alfred
+
+# PostgreSQL (Vector Database / RAG)
+POSTGRES_HOST=vectordb
+POSTGRES_PORT=5432
+POSTGRES_USER=alfred
+POSTGRES_DB_NAME=alfred
+
+# --- EXTERNAL SERVICES ---
+
+# TMDB — Media metadata (required). Get your key at https://www.themoviedb.org/
+# → TMDB_API_KEY goes in .env.secrets
+TMDB_BASE_URL=https://api.themoviedb.org/3
+
+# qBittorrent
+# → QBITTORRENT_PASSWORD goes in .env.secrets
+QBITTORRENT_URL=http://qbittorrent:16140
+QBITTORRENT_USERNAME=admin
+QBITTORRENT_PORT=16140
+
+# Meilisearch
+# → MEILI_MASTER_KEY goes in .env.secrets
+# MEILI_ENABLED=false # KEY DOESN'T EXISTS => SEARCH IS THE PROPER KEY
+SEARCH=false
+MEILI_NO_ANALYTICS=true
+MEILI_HOST=http://meilisearch:7700
+
+# --- LLM CONFIGURATION ---
+# Providers: local, openai, anthropic, deepseek, google, kimi
+# → API keys go in .env.secrets
+DEFAULT_LLM_PROVIDER=local
+
+# Local LLM (Ollama)
+#OLLAMA_BASE_URL=http://ollama:11434
+#OLLAMA_MODEL=llama3.3:latest
+
+OLLAMA_BASE_URL=http://10.0.0.11:11434
+OLLAMA_MODEL=glm-4.7-flash:latest
+
+# --- RAG ENGINE ---
+RAG_ENABLED=TRUE
+RAG_API_URL=http://rag_api:8000
+RAG_API_PORT=8000
+EMBEDDINGS_PROVIDER=ollama
+EMBEDDINGS_MODEL=nomic-embed-text

.env.example

@@ -1,3 +1,13 @@
+# --- IMPORTANT ---
+# Settings are split across multiple files for clarity.
+# Files (loaded in this order, last wins):
+#   .env.alfred   — app config and service addresses (safe to commit)
+#   .env.secrets  — generated secrets, passwords, URIs and API keys (DO NOT COMMIT)
+#   .env.make     — build metadata synced from pyproject.toml (safe to commit)
+#
+# To customize: edit .env.alfred for config, .env.secrets for secrets.
+
+# --- Alfred ---
 MAX_HISTORY_MESSAGES=10
 MAX_TOOL_ITERATIONS=10
 REQUEST_TIMEOUT=30
@@ -8,84 +18,54 @@ LLM_TEMPERATURE=0.2
 # Persistence
 DATA_STORAGE_DIR=data
 
-# Network configuration
+# Network
 HOST=0.0.0.0
 PORT=3080
 
-# Build informations (Synced with pyproject.toml via bootstrap)
-ALFRED_VERSION=
-IMAGE_NAME=
-LIBRECHAT_VERSION=
-PYTHON_VERSION=
-PYTHON_VERSION_SHORT=
-RAG_VERSION=
-RUNNER=
-SERVICE_NAME=
-
-# --- SECURITY KEYS (CRITICAL) ---
-# These are used for session tokens and encrypting sensitive data in MongoDB.
-# If you lose these, you lose access to encrypted stored credentials.
-JWT_SECRET=
-JWT_REFRESH_SECRET=
-CREDS_KEY=
-CREDS_IV=
-
-# --- DATABASES (AUTO-SECURED) ---
-# Alfred uses MongoDB for application state and PostgreSQL for Vector RAG.
-# Passwords will be generated as 24-character secure tokens if left blank.
+# --- DATABASES ---
+# Passwords and connection URIs are auto-generated in .env.secrets.
+# Edit host/port/user/dbname here if needed.
 
 # MongoDB (Application Data)
-MONGO_URI=
 MONGO_HOST=mongodb
 MONGO_PORT=27017
 MONGO_USER=alfred
-MONGO_PASSWORD=
-MONGO_DB_NAME=alfred
+MONGO_DB_NAME=LibreChat
 
 # PostgreSQL (Vector Database / RAG)
-POSTGRES_URI=
 POSTGRES_HOST=vectordb
 POSTGRES_PORT=5432
 POSTGRES_USER=alfred
-POSTGRES_PASSWORD=
 POSTGRES_DB_NAME=alfred
 
 # --- EXTERNAL SERVICES ---
-# Media Metadata (Required)
-# Get your key at https://www.themoviedb.org/
-TMDB_API_KEY=
+
+# TMDB — Media metadata (required). Get your key at https://www.themoviedb.org/
+# → TMDB_API_KEY goes in .env.secrets
 TMDB_BASE_URL=https://api.themoviedb.org/3
 
-# qBittorrent integration
+# qBittorrent
+# → QBITTORRENT_PASSWORD goes in .env.secrets
 QBITTORRENT_URL=http://qbittorrent:16140
 QBITTORRENT_USERNAME=admin
-QBITTORRENT_PASSWORD=
 QBITTORRENT_PORT=16140
 
 # Meilisearch
+# → MEILI_MASTER_KEY goes in .env.secrets
 MEILI_ENABLED=FALSE
 MEILI_NO_ANALYTICS=TRUE
 MEILI_HOST=http://meilisearch:7700
-MEILI_MASTER_KEY=
 
 # --- LLM CONFIGURATION ---
-# Providers: 'local', 'openai', 'anthropic', 'deepseek', 'google', 'kimi'
+# Providers: local, openai, anthropic, deepseek, google, kimi
+# → API keys go in .env.secrets
 DEFAULT_LLM_PROVIDER=local
 
 # Local LLM (Ollama)
 OLLAMA_BASE_URL=http://ollama:11434
 OLLAMA_MODEL=llama3.3:latest
 
-# --- API KEYS (OPTIONAL) ---
-# Fill only the ones you intend to use.
-ANTHROPIC_API_KEY=
-DEEPSEEK_API_KEY=
-GOOGLE_API_KEY=
-KIMI_API_KEY=
-OPENAI_API_KEY=
-
 # --- RAG ENGINE ---
-# Enable/Disable the Retrieval Augmented Generation system
 RAG_ENABLED=TRUE
 RAG_API_URL=http://rag_api:8000
 RAG_API_PORT=8000

.env.librechat

@@ -0,0 +1,878 @@
+#=====================================================================#
+#                       LibreChat Configuration                       #
+#=====================================================================#
+# Please refer to the reference documentation for assistance          #
+# with configuring your LibreChat environment.                        #
+#                                                                     #
+# https://www.librechat.ai/docs/configuration/dotenv                  #
+#=====================================================================#
+
+#==================================================#
+#               Server Configuration               #
+#==================================================#
+
+HOST=localhost
+PORT=3080
+
+MONGO_URI=mongodb://127.0.0.1:27017/LibreChat
+#The maximum number of connections in the connection pool. */
+MONGO_MAX_POOL_SIZE=
+#The minimum number of connections in the connection pool. */
+MONGO_MIN_POOL_SIZE=
+#The maximum number of connections that may be in the process of being established concurrently by the connection pool. */
+MONGO_MAX_CONNECTING=
+#The maximum number of milliseconds that a connection can remain idle in the pool before being removed and closed. */
+MONGO_MAX_IDLE_TIME_MS=
+#The maximum time in milliseconds that a thread can wait for a connection to become available. */
+MONGO_WAIT_QUEUE_TIMEOUT_MS=
+# Set to false to disable automatic index creation for all models associated with this connection. */
+MONGO_AUTO_INDEX=
+# Set to `false` to disable Mongoose automatically calling `createCollection()` on every model created on this connection. */
+MONGO_AUTO_CREATE=
+
+DOMAIN_CLIENT=http://localhost:3080
+DOMAIN_SERVER=http://localhost:3080
+
+NO_INDEX=true
+# Use the address that is at most n number of hops away from the Express application.
+# req.socket.remoteAddress is the first hop, and the rest are looked for in the X-Forwarded-For header from right to left.
+# A value of 0 means that the first untrusted address would be req.socket.remoteAddress, i.e. there is no reverse proxy.
+# Defaulted to 1.
+TRUST_PROXY=1
+
+# Minimum password length for user authentication
+# Default: 8
+# Note: When using LDAP authentication, you may want to set this to 1 
+# to bypass local password validation, as LDAP servers handle their own
+# password policies.
+# MIN_PASSWORD_LENGTH=8
+
+# When enabled, the app will continue running after encountering uncaught exceptions
+# instead of exiting the process. Not recommended for production unless necessary.
+# CONTINUE_ON_UNCAUGHT_EXCEPTION=false
+
+#===============#
+# JSON Logging  #
+#===============#
+
+# Use when process console logs in cloud deployment like GCP/AWS
+CONSOLE_JSON=false
+
+#===============#
+# Debug Logging #
+#===============#
+
+DEBUG_LOGGING=true
+DEBUG_CONSOLE=false
+# Set to true to enable agent debug logging
+AGENT_DEBUG_LOGGING=false
+
+# Enable memory diagnostics (logs heap/RSS snapshots every 60s, auto-enabled with --inspect)
+# MEM_DIAG=true
+
+#=============#
+# Permissions #
+#=============#
+
+# UID=1000
+# GID=1000
+
+#==============#
+# Node Options #
+#==============#
+
+# NOTE: NODE_MAX_OLD_SPACE_SIZE is NOT recognized by Node.js directly.
+# This variable is used as a build argument for Docker or CI/CD workflows,
+# and is NOT used by Node.js to set the heap size at runtime.
+# To configure Node.js memory, use NODE_OPTIONS, e.g.:
+# NODE_OPTIONS="--max-old-space-size=6144"
+# See: https://nodejs.org/api/cli.html#--max-old-space-sizesize-in-mib
+NODE_MAX_OLD_SPACE_SIZE=6144
+
+#===============#
+# Configuration #
+#===============#
+# Use an absolute path, a relative path, or a URL
+
+# CONFIG_PATH="/alternative/path/to/librechat.yaml"
+
+#==================#
+# Langfuse Tracing #
+#==================#
+
+# Get Langfuse API keys for your project from the project settings page: https://cloud.langfuse.com
+
+# LANGFUSE_PUBLIC_KEY=
+# LANGFUSE_SECRET_KEY=
+# LANGFUSE_BASE_URL=
+
+#===================================================#
+#                     Endpoints                     #
+#===================================================#
+
+# ENDPOINTS=openAI,assistants,azureOpenAI,google,anthropic
+
+PROXY=
+
+#===================================#
+# Known Endpoints - librechat.yaml  #
+#===================================#
+# https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints
+
+# ANYSCALE_API_KEY=
+# APIPIE_API_KEY=
+# COHERE_API_KEY=
+# DEEPSEEK_API_KEY=
+# DATABRICKS_API_KEY=
+# FIREWORKS_API_KEY=
+# GROQ_API_KEY=
+# HUGGINGFACE_TOKEN=
+# MISTRAL_API_KEY=
+# OPENROUTER_KEY=
+# PERPLEXITY_API_KEY=
+# SHUTTLEAI_API_KEY=
+# TOGETHERAI_API_KEY=
+# UNIFY_API_KEY=
+# XAI_API_KEY=
+
+#============#
+# Anthropic  #
+#============#
+
+ANTHROPIC_API_KEY=user_provided
+# ANTHROPIC_MODELS=claude-sonnet-4-6,claude-opus-4-6,claude-opus-4-20250514,claude-sonnet-4-20250514,claude-3-7-sonnet-20250219,claude-3-5-sonnet-20241022,claude-3-5-haiku-20241022,claude-3-opus-20240229,claude-3-sonnet-20240229,claude-3-haiku-20240307
+# ANTHROPIC_REVERSE_PROXY=
+
+# Set to true to use Anthropic models through Google Vertex AI instead of direct API
+# ANTHROPIC_USE_VERTEX=
+# ANTHROPIC_VERTEX_REGION=us-east5
+
+#============#
+# Azure      #
+#============#
+
+# Note: these variables are DEPRECATED
+# Use the `librechat.yaml` configuration for `azureOpenAI` instead
+# You may also continue to use them if you opt out of using the `librechat.yaml` configuration
+
+# AZURE_OPENAI_DEFAULT_MODEL=gpt-3.5-turbo # Deprecated
+# AZURE_OPENAI_MODELS=gpt-3.5-turbo,gpt-4 # Deprecated
+# AZURE_USE_MODEL_AS_DEPLOYMENT_NAME=TRUE # Deprecated
+# AZURE_API_KEY= # Deprecated
+# AZURE_OPENAI_API_INSTANCE_NAME= # Deprecated
+# AZURE_OPENAI_API_DEPLOYMENT_NAME= # Deprecated
+# AZURE_OPENAI_API_VERSION= # Deprecated
+# AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME= # Deprecated
+# AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME= # Deprecated
+
+#=================#
+#   AWS Bedrock   #
+#=================#
+
+# BEDROCK_AWS_DEFAULT_REGION=us-east-1 # A default region must be provided
+# BEDROCK_AWS_ACCESS_KEY_ID=someAccessKey
+# BEDROCK_AWS_SECRET_ACCESS_KEY=someSecretAccessKey
+# BEDROCK_AWS_SESSION_TOKEN=someSessionToken
+
+# Note: This example list is not meant to be exhaustive. If omitted, all known, supported model IDs will be included for you.
+# BEDROCK_AWS_MODELS=anthropic.claude-sonnet-4-6,anthropic.claude-opus-4-6-v1,anthropic.claude-3-5-sonnet-20240620-v1:0,meta.llama3-1-8b-instruct-v1:0
+# Cross-region inference model IDs: us.anthropic.claude-sonnet-4-6,us.anthropic.claude-opus-4-6-v1,global.anthropic.claude-opus-4-6-v1
+
+# See all Bedrock model IDs here: https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns
+
+# Notes on specific models:
+# The following models are not support due to not supporting streaming:
+# ai21.j2-mid-v1
+
+# The following models are not support due to not supporting conversation history:
+# ai21.j2-ultra-v1, cohere.command-text-v14, cohere.command-light-text-v14
+
+#============#
+# Google     #
+#============#
+
+GOOGLE_KEY=user_provided
+
+# GOOGLE_REVERSE_PROXY=
+# Some reverse proxies do not support the X-goog-api-key header, uncomment to pass the API key in Authorization header instead.
+# GOOGLE_AUTH_HEADER=true
+
+# Gemini API (AI Studio)
+# GOOGLE_MODELS=gemini-3.1-pro-preview,gemini-3.1-pro-preview-customtools,gemini-3.1-flash-lite-preview,gemini-2.5-pro,gemini-2.5-flash,gemini-2.5-flash-lite,gemini-2.0-flash,gemini-2.0-flash-lite
+
+# Vertex AI
+# GOOGLE_MODELS=gemini-3.1-pro-preview,gemini-3.1-pro-preview-customtools,gemini-3.1-flash-lite-preview,gemini-2.5-pro,gemini-2.5-flash,gemini-2.5-flash-lite,gemini-2.0-flash-001,gemini-2.0-flash-lite-001
+
+# GOOGLE_TITLE_MODEL=gemini-2.0-flash-lite-001
+
+# Google Cloud region for Vertex AI (used by both chat and image generation)
+# GOOGLE_LOC=us-central1
+
+# Alternative region env var for Gemini Image Generation
+# GOOGLE_CLOUD_LOCATION=global
+
+# Vertex AI Service Account Configuration
+# Path to your Google Cloud service account JSON file
+# GOOGLE_SERVICE_KEY_FILE=/path/to/service-account.json
+
+# Google Safety Settings
+# NOTE: These settings apply to both Vertex AI and Gemini API (AI Studio)
+#
+# For Vertex AI:
+# To use the BLOCK_NONE setting, you need either:
+# (a) Access through an allowlist via your Google account team, or
+# (b) Switch to monthly invoiced billing: https://cloud.google.com/billing/docs/how-to/invoiced-billing
+#
+# For Gemini API (AI Studio):
+# BLOCK_NONE is available by default, no special account requirements.
+#
+# Available options: BLOCK_NONE, BLOCK_ONLY_HIGH, BLOCK_MEDIUM_AND_ABOVE, BLOCK_LOW_AND_ABOVE
+#
+# GOOGLE_SAFETY_SEXUALLY_EXPLICIT=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_HATE_SPEECH=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_HARASSMENT=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_DANGEROUS_CONTENT=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_CIVIC_INTEGRITY=BLOCK_ONLY_HIGH
+
+#========================#
+# Gemini Image Generation #
+#========================#
+
+# Gemini Image Generation Tool (for Agents)
+# Supports multiple authentication methods in priority order:
+# 1. User-provided API key (via GUI)
+# 2. GEMINI_API_KEY env var (admin-configured)
+# 3. GOOGLE_KEY env var (shared with Google chat endpoint)
+# 4. Vertex AI service account (via GOOGLE_SERVICE_KEY_FILE)
+
+# Option A: Use dedicated Gemini API key for image generation
+# GEMINI_API_KEY=your-gemini-api-key
+
+# Vertex AI model for image generation (defaults to gemini-2.5-flash-image)
+# GEMINI_IMAGE_MODEL=gemini-2.5-flash-image
+
+#============#
+# OpenAI     #
+#============#
+
+OPENAI_API_KEY=user_provided
+# OPENAI_MODELS=gpt-5,gpt-5-codex,gpt-5-mini,gpt-5-nano,o3-pro,o3,o4-mini,gpt-4.1,gpt-4.1-mini,gpt-4.1-nano,o3-mini,o1-pro,o1,gpt-4o,gpt-4o-mini
+
+DEBUG_OPENAI=false
+
+# TITLE_CONVO=false
+# OPENAI_TITLE_MODEL=gpt-4o-mini
+
+# OPENAI_SUMMARIZE=true
+# OPENAI_SUMMARY_MODEL=gpt-4o-mini
+
+# OPENAI_FORCE_PROMPT=true
+
+# OPENAI_REVERSE_PROXY=
+
+# OPENAI_ORGANIZATION=
+
+#====================#
+#   Assistants API   #
+#====================#
+
+ASSISTANTS_API_KEY=user_provided
+# ASSISTANTS_BASE_URL=
+# ASSISTANTS_MODELS=gpt-4o,gpt-4o-mini,gpt-3.5-turbo-0125,gpt-3.5-turbo-16k-0613,gpt-3.5-turbo-16k,gpt-3.5-turbo,gpt-4,gpt-4-0314,gpt-4-32k-0314,gpt-4-0613,gpt-3.5-turbo-0613,gpt-3.5-turbo-1106,gpt-4-0125-preview,gpt-4-turbo-preview,gpt-4-1106-preview
+
+#==========================#
+#   Azure Assistants API   #
+#==========================#
+
+# Note: You should map your credentials with custom variables according to your Azure OpenAI Configuration
+# The models for Azure Assistants are also determined by your Azure OpenAI configuration.
+
+# More info, including how to enable use of Assistants with Azure here:
+# https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints/azure#using-assistants-with-azure
+
+CREDS_KEY=f34be427ebb29de8d88c107a71546019685ed8b241d8f2ed00c3df97ad2566f0
+CREDS_IV=e2341419ec3dd3d19b13a1a87fafcbfb
+
+# Azure AI Search
+#-----------------
+AZURE_AI_SEARCH_SERVICE_ENDPOINT=
+AZURE_AI_SEARCH_INDEX_NAME=
+AZURE_AI_SEARCH_API_KEY=
+
+AZURE_AI_SEARCH_API_VERSION=
+AZURE_AI_SEARCH_SEARCH_OPTION_QUERY_TYPE=
+AZURE_AI_SEARCH_SEARCH_OPTION_TOP=
+AZURE_AI_SEARCH_SEARCH_OPTION_SELECT=
+
+# OpenAI Image Tools Customization
+#----------------
+# IMAGE_GEN_OAI_API_KEY= # Create or reuse OpenAI API key for image generation tool
+# IMAGE_GEN_OAI_BASEURL= # Custom OpenAI base URL for image generation tool
+# IMAGE_GEN_OAI_AZURE_API_VERSION= # Custom Azure OpenAI deployments
+# IMAGE_GEN_OAI_MODEL=gpt-image-1 # OpenAI image model (e.g., gpt-image-1, gpt-image-1.5)
+# IMAGE_GEN_OAI_DESCRIPTION=
+# IMAGE_GEN_OAI_DESCRIPTION_WITH_FILES=Custom description for image generation tool when files are present
+# IMAGE_GEN_OAI_DESCRIPTION_NO_FILES=Custom description for image generation tool when no files are present
+# IMAGE_EDIT_OAI_DESCRIPTION=Custom description for image editing tool
+# IMAGE_GEN_OAI_PROMPT_DESCRIPTION=Custom prompt description for image generation tool
+# IMAGE_EDIT_OAI_PROMPT_DESCRIPTION=Custom prompt description for image editing tool
+
+# DALL·E
+#----------------
+# DALLE_API_KEY=
+# DALLE3_API_KEY=
+# DALLE2_API_KEY=
+# DALLE3_SYSTEM_PROMPT=
+# DALLE2_SYSTEM_PROMPT=
+# DALLE_REVERSE_PROXY=
+# DALLE3_BASEURL=
+# DALLE2_BASEURL=
+
+# DALL·E (via Azure OpenAI)
+# Note: requires some of the variables above to be set
+#----------------
+# DALLE3_AZURE_API_VERSION=
+# DALLE2_AZURE_API_VERSION=
+
+# Flux
+#-----------------
+FLUX_API_BASE_URL=https://api.us1.bfl.ai
+# FLUX_API_BASE_URL = 'https://api.bfl.ml';
+
+# Get your API key at https://api.us1.bfl.ai/auth/profile
+# FLUX_API_KEY=
+
+# Google
+#-----------------
+GOOGLE_SEARCH_API_KEY=
+GOOGLE_CSE_ID=
+
+# Stable Diffusion
+#-----------------
+SD_WEBUI_URL=http://host.docker.internal:7860
+
+# Tavily
+#-----------------
+TAVILY_API_KEY=
+
+# Traversaal
+#-----------------
+TRAVERSAAL_API_KEY=
+
+# WolframAlpha
+#-----------------
+WOLFRAM_APP_ID=
+
+# Zapier
+#-----------------
+ZAPIER_NLA_API_KEY=
+
+#==================================================#
+#                      Search                      #
+#==================================================#
+
+SEARCH=true
+MEILI_NO_ANALYTICS=true
+MEILI_HOST=http://0.0.0.0:7700
+MEILI_MASTER_KEY=DrhYf7zENyR6AlUCKmnz0eYASOQdl6zxH7s7MKFSfFCt
+
+# Optional: Disable indexing, useful in a multi-node setup
+# where only one instance should perform an index sync.
+# MEILI_NO_SYNC=true
+
+#==================================================#
+#          Speech to Text & Text to Speech         #
+#==================================================#
+
+STT_API_KEY=
+TTS_API_KEY=
+
+#==================================================#
+#                        RAG                       #
+#==================================================#
+# More info: https://www.librechat.ai/docs/configuration/rag_api
+
+# RAG_OPENAI_BASEURL=
+# RAG_OPENAI_API_KEY=
+# RAG_USE_FULL_CONTEXT=
+# EMBEDDINGS_PROVIDER=openai
+# EMBEDDINGS_MODEL=text-embedding-3-small
+
+#===================================================#
+#                    User System                    #
+#===================================================#
+
+#========================#
+# Moderation             #
+#========================#
+
+OPENAI_MODERATION=false
+OPENAI_MODERATION_API_KEY=
+# OPENAI_MODERATION_REVERSE_PROXY=
+
+BAN_VIOLATIONS=true
+BAN_DURATION=1000 * 60 * 60 * 2
+BAN_INTERVAL=20
+
+LOGIN_VIOLATION_SCORE=1
+REGISTRATION_VIOLATION_SCORE=1
+CONCURRENT_VIOLATION_SCORE=1
+MESSAGE_VIOLATION_SCORE=1
+NON_BROWSER_VIOLATION_SCORE=20
+TTS_VIOLATION_SCORE=0
+STT_VIOLATION_SCORE=0
+FORK_VIOLATION_SCORE=0
+IMPORT_VIOLATION_SCORE=0
+FILE_UPLOAD_VIOLATION_SCORE=0
+
+LOGIN_MAX=7
+LOGIN_WINDOW=5
+REGISTER_MAX=5
+REGISTER_WINDOW=60
+
+LIMIT_CONCURRENT_MESSAGES=true
+CONCURRENT_MESSAGE_MAX=2
+
+LIMIT_MESSAGE_IP=true
+MESSAGE_IP_MAX=40
+MESSAGE_IP_WINDOW=1
+
+LIMIT_MESSAGE_USER=false
+MESSAGE_USER_MAX=40
+MESSAGE_USER_WINDOW=1
+
+ILLEGAL_MODEL_REQ_SCORE=5
+
+#========================#
+# Balance                #
+#========================#
+
+# CHECK_BALANCE=false
+# START_BALANCE=20000 # note: the number of tokens that will be credited after registration.
+
+#========================#
+# Registration and Login #
+#========================#
+
+ALLOW_EMAIL_LOGIN=true
+ALLOW_REGISTRATION=true
+ALLOW_SOCIAL_LOGIN=false
+ALLOW_SOCIAL_REGISTRATION=false
+ALLOW_PASSWORD_RESET=false
+# ALLOW_ACCOUNT_DELETION=true # note: enabled by default if omitted/commented out
+ALLOW_UNVERIFIED_EMAIL_LOGIN=true
+
+SESSION_EXPIRY=1000 * 60 * 15
+REFRESH_TOKEN_EXPIRY=(1000 * 60 * 60 * 24) * 7
+
+JWT_SECRET=16f8c0ef4a5d391b26034086c628469d3f9f497f08163ab9b40137092f2909ef
+JWT_REFRESH_SECRET=eaa5191f2914e30b9387fd84e254e4ba6fc51b4654968a9b0803b456a54b8418
+
+# Discord
+DISCORD_CLIENT_ID=
+DISCORD_CLIENT_SECRET=
+DISCORD_CALLBACK_URL=/oauth/discord/callback
+
+# Facebook
+FACEBOOK_CLIENT_ID=
+FACEBOOK_CLIENT_SECRET=
+FACEBOOK_CALLBACK_URL=/oauth/facebook/callback
+
+# GitHub
+GITHUB_CLIENT_ID=
+GITHUB_CLIENT_SECRET=
+GITHUB_CALLBACK_URL=/oauth/github/callback
+# GitHub Enterprise
+# GITHUB_ENTERPRISE_BASE_URL=
+# GITHUB_ENTERPRISE_USER_AGENT=
+
+# Google
+GOOGLE_CLIENT_ID=
+GOOGLE_CLIENT_SECRET=
+GOOGLE_CALLBACK_URL=/oauth/google/callback
+
+# Apple
+APPLE_CLIENT_ID=
+APPLE_TEAM_ID=
+APPLE_KEY_ID=
+APPLE_PRIVATE_KEY_PATH=
+APPLE_CALLBACK_URL=/oauth/apple/callback
+
+# OpenID
+OPENID_CLIENT_ID=
+OPENID_CLIENT_SECRET=
+OPENID_ISSUER=
+OPENID_SESSION_SECRET=
+OPENID_SCOPE="openid profile email"
+OPENID_CALLBACK_URL=/oauth/openid/callback
+OPENID_REQUIRED_ROLE=
+OPENID_REQUIRED_ROLE_TOKEN_KIND=
+OPENID_REQUIRED_ROLE_PARAMETER_PATH=
+OPENID_ADMIN_ROLE=
+OPENID_ADMIN_ROLE_PARAMETER_PATH=
+OPENID_ADMIN_ROLE_TOKEN_KIND=
+# Set to determine which user info property returned from OpenID Provider to store as the User's username
+OPENID_USERNAME_CLAIM=
+# Set to determine which user info property returned from OpenID Provider to store as the User's name
+OPENID_NAME_CLAIM=
+# Set to determine which user info claim to use as the email/identifier for user matching (e.g., "upn" for Entra ID)
+# When not set, defaults to: email -> preferred_username -> upn
+OPENID_EMAIL_CLAIM=
+# Optional audience parameter for OpenID authorization requests
+OPENID_AUDIENCE=
+
+OPENID_BUTTON_LABEL=
+OPENID_IMAGE_URL=
+# Set to true to automatically redirect to the OpenID provider when a user visits the login page
+# This will bypass the login form completely for users, only use this if OpenID is your only authentication method
+OPENID_AUTO_REDIRECT=false
+# Set to true to use PKCE (Proof Key for Code Exchange) for OpenID authentication
+OPENID_USE_PKCE=false
+#Set to true to reuse openid tokens for authentication management instead of using the mongodb session and the custom refresh token.
+OPENID_REUSE_TOKENS=
+#By default, signing key verification results are cached in order to prevent excessive HTTP requests to the JWKS endpoint.
+#If a signing key matching the kid is found, this will be cached and the next time this kid is requested the signing key will be served from the cache.
+#Default is true.
+OPENID_JWKS_URL_CACHE_ENABLED=
+OPENID_JWKS_URL_CACHE_TIME= # 600000 ms eq to 10 minutes leave empty to disable caching
+#Set to true to trigger token exchange flow to acquire access token for the userinfo endpoint.
+OPENID_ON_BEHALF_FLOW_FOR_USERINFO_REQUIRED=
+OPENID_ON_BEHALF_FLOW_USERINFO_SCOPE="user.read" # example for Scope Needed for Microsoft Graph API
+# Set to true to use the OpenID Connect end session endpoint for logout
+OPENID_USE_END_SESSION_ENDPOINT=
+# URL to redirect to after OpenID logout (defaults to ${DOMAIN_CLIENT}/login)
+OPENID_POST_LOGOUT_REDIRECT_URI=
+# Maximum logout URL length before using logout_hint instead of id_token_hint (default: 2000)
+OPENID_MAX_LOGOUT_URL_LENGTH=
+
+#========================#
+# SharePoint Integration #
+#========================#
+# Requires Entra ID (OpenID) authentication to be configured
+
+# Enable SharePoint file picker in chat and agent panels
+# ENABLE_SHAREPOINT_FILEPICKER=true
+
+# SharePoint tenant base URL (e.g., https://yourtenant.sharepoint.com)
+# SHAREPOINT_BASE_URL=https://yourtenant.sharepoint.com
+
+# Microsoft Graph API And SharePoint scopes for file picker
+# SHAREPOINT_PICKER_SHAREPOINT_SCOPE==https://yourtenant.sharepoint.com/AllSites.Read
+# SHAREPOINT_PICKER_GRAPH_SCOPE=Files.Read.All
+#========================#
+
+# SAML
+# Note: If OpenID is enabled, SAML authentication will be automatically disabled.
+SAML_ENTRY_POINT=
+SAML_ISSUER=
+SAML_CERT=
+SAML_CALLBACK_URL=/oauth/saml/callback
+SAML_SESSION_SECRET=
+
+# Attribute mappings (optional)
+SAML_EMAIL_CLAIM=
+SAML_USERNAME_CLAIM=
+SAML_GIVEN_NAME_CLAIM=
+SAML_FAMILY_NAME_CLAIM=
+SAML_PICTURE_CLAIM=
+SAML_NAME_CLAIM=
+
+# Logint buttion settings (optional)
+SAML_BUTTON_LABEL=
+SAML_IMAGE_URL=
+
+# Whether the SAML Response should be signed.
+# - If "true", the entire `SAML Response` will be signed.
+# - If "false" or unset, only the `SAML Assertion` will be signed (default behavior).
+# SAML_USE_AUTHN_RESPONSE_SIGNED=
+
+
+#===============================================#
+# Microsoft Graph API / Entra ID Integration  #
+#===============================================#
+
+# Enable Entra ID people search integration in permissions/sharing system
+# When enabled, the people picker will search both local database and Entra ID
+USE_ENTRA_ID_FOR_PEOPLE_SEARCH=false
+
+# When enabled, entra id groups owners will be considered as members of the group
+ENTRA_ID_INCLUDE_OWNERS_AS_MEMBERS=false
+
+# Microsoft Graph API scopes needed for people/group search
+# Default scopes provide access to user profiles and group memberships
+OPENID_GRAPH_SCOPES=User.Read,People.Read,GroupMember.Read.All
+
+# LDAP
+LDAP_URL=
+LDAP_BIND_DN=
+LDAP_BIND_CREDENTIALS=
+LDAP_USER_SEARCH_BASE=
+#LDAP_SEARCH_FILTER="mail="
+LDAP_CA_CERT_PATH=
+# LDAP_TLS_REJECT_UNAUTHORIZED=
+# LDAP_STARTTLS=
+# LDAP_LOGIN_USES_USERNAME=true
+# LDAP_ID=
+# LDAP_USERNAME=
+# LDAP_EMAIL=
+# LDAP_FULL_NAME=
+
+#========================#
+# Email Password Reset   #
+#========================#
+
+EMAIL_SERVICE=
+EMAIL_HOST=
+EMAIL_PORT=25
+EMAIL_ENCRYPTION=
+EMAIL_ENCRYPTION_HOSTNAME=
+EMAIL_ALLOW_SELFSIGNED=
+# Leave both empty for SMTP servers that do not require authentication
+EMAIL_USERNAME=
+EMAIL_PASSWORD=
+EMAIL_FROM_NAME=
+EMAIL_FROM=noreply@librechat.ai
+
+#========================#
+#      Mailgun API       #
+#========================#
+
+# MAILGUN_API_KEY=your-mailgun-api-key
+# MAILGUN_DOMAIN=mg.yourdomain.com
+# EMAIL_FROM=noreply@yourdomain.com
+# EMAIL_FROM_NAME="LibreChat"
+
+# # Optional: For EU region
+# MAILGUN_HOST=https://api.eu.mailgun.net
+
+#========================#
+# Firebase CDN           #
+#========================#
+
+FIREBASE_API_KEY=
+FIREBASE_AUTH_DOMAIN=
+FIREBASE_PROJECT_ID=
+FIREBASE_STORAGE_BUCKET=
+FIREBASE_MESSAGING_SENDER_ID=
+FIREBASE_APP_ID=
+
+#========================#
+# S3 AWS Bucket          #
+#========================#
+
+AWS_ENDPOINT_URL=
+AWS_ACCESS_KEY_ID=
+AWS_SECRET_ACCESS_KEY=
+AWS_REGION=
+AWS_BUCKET_NAME=
+# Required for path-style S3-compatible providers (MinIO, Hetzner, Backblaze B2, etc.)
+# that don't support virtual-hosted-style URLs (bucket.endpoint). Not needed for AWS S3.
+# AWS_FORCE_PATH_STYLE=false
+
+#========================#
+# Azure Blob Storage     #
+#========================#
+
+AZURE_STORAGE_CONNECTION_STRING=
+AZURE_STORAGE_PUBLIC_ACCESS=false
+AZURE_CONTAINER_NAME=files
+
+#========================#
+# Shared Links           #
+#========================#
+
+ALLOW_SHARED_LINKS=true
+# Allows unauthenticated access to shared links. Defaults to false (auth required) if not set.
+ALLOW_SHARED_LINKS_PUBLIC=false
+
+#==============================#
+# Static File Cache Control    #
+#==============================#
+
+# Leave commented out to use defaults: 1 day (86400 seconds) for s-maxage and 2 days (172800 seconds) for max-age
+# NODE_ENV must be set to production for these to take effect
+# STATIC_CACHE_MAX_AGE=172800
+# STATIC_CACHE_S_MAX_AGE=86400
+
+# If you have another service in front of your LibreChat doing compression, disable express based compression here
+# DISABLE_COMPRESSION=true
+
+# If you have gzipped version of uploaded image images in the same folder, this will enable gzip scan and serving of these images
+# Note: The images folder will be scanned on startup and a ma kept in memory. Be careful for large number of images.
+# ENABLE_IMAGE_OUTPUT_GZIP_SCAN=true
+
+#===================================================#
+#                        UI                         #
+#===================================================#
+
+APP_TITLE=LibreChat
+# CUSTOM_FOOTER="My custom footer"
+HELP_AND_FAQ_URL=https://librechat.ai
+
+# SHOW_BIRTHDAY_ICON=true
+
+# Google tag manager id
+#ANALYTICS_GTM_ID=user provided google tag manager id
+
+# limit conversation file imports to a certain number of bytes in size to avoid the container
+# maxing out memory limitations by unremarking this line and supplying a file size in bytes
+# such as the below example of 250 mib
+# CONVERSATION_IMPORT_MAX_FILE_SIZE_BYTES=262144000
+
+
+#===============#
+# REDIS Options #
+#===============#
+
+# Enable Redis for caching and session storage
+# USE_REDIS=true
+# Enable Redis for resumable LLM streams (defaults to USE_REDIS value if not set)
+# Set to false to use in-memory storage for streams while keeping Redis for other caches
+# USE_REDIS_STREAMS=true
+
+# Single Redis instance
+# REDIS_URI=redis://127.0.0.1:6379
+
+# Redis cluster (multiple nodes)
+# REDIS_URI=redis://127.0.0.1:7001,redis://127.0.0.1:7002,redis://127.0.0.1:7003
+
+# Redis with TLS/SSL encryption and CA certificate
+# REDIS_URI=rediss://127.0.0.1:6380
+# REDIS_CA=/path/to/ca-cert.pem
+
+# Elasticache may need to use an alternate dnsLookup for TLS connections.  see "Special Note: Aws Elasticache Clusters with TLS" on this webpage: https://www.npmjs.com/package/ioredis
+# Enable alternative dnsLookup for redis
+# REDIS_USE_ALTERNATIVE_DNS_LOOKUP=true
+
+# Redis authentication (if required)
+# REDIS_USERNAME=your_redis_username
+# REDIS_PASSWORD=your_redis_password
+
+# Redis key prefix configuration
+# Use environment variable name for dynamic prefix (recommended for cloud deployments)
+# REDIS_KEY_PREFIX_VAR=K_REVISION
+# Or use static prefix directly
+# REDIS_KEY_PREFIX=librechat
+
+# Redis connection limits
+# REDIS_MAX_LISTENERS=40
+
+# Redis ping interval in seconds (0 = disabled, >0 = enabled)
+# When set to a positive integer, Redis clients will ping the server at this interval to keep connections alive
+# When unset or 0, no pinging is performed (recommended for most use cases)
+# REDIS_PING_INTERVAL=300
+
+# Force specific cache namespaces to use in-memory storage even when Redis is enabled
+# Comma-separated list of CacheKeys
+# Defaults to CONFIG_STORE,APP_CONFIG so YAML-derived config stays per-container (safe for blue/green deployments)
+# Set to empty string to force all namespaces through Redis: FORCED_IN_MEMORY_CACHE_NAMESPACES=
+# FORCED_IN_MEMORY_CACHE_NAMESPACES=CONFIG_STORE,APP_CONFIG
+
+# Leader Election Configuration (for multi-instance deployments with Redis)
+# Duration in seconds that the leader lease is valid before it expires (default: 25)
+# LEADER_LEASE_DURATION=25
+# Interval in seconds at which the leader renews its lease (default: 10)
+# LEADER_RENEW_INTERVAL=10
+# Maximum number of retry attempts when renewing the lease fails (default: 3)
+# LEADER_RENEW_ATTEMPTS=3
+# Delay in seconds between retry attempts when renewing the lease (default: 0.5)
+# LEADER_RENEW_RETRY_DELAY=0.5
+
+#==================================================#
+#                      Others                      #
+#==================================================#
+#   You should leave the following commented out   #
+
+# NODE_ENV=
+
+# E2E_USER_EMAIL=
+# E2E_USER_PASSWORD=
+
+#=====================================================#
+#                  Cache Headers                      #
+#=====================================================#
+#   Headers that control caching of the index.html    #
+#   Default configuration prevents caching to ensure  #
+#   users always get the latest version. Customize    #
+#   only if you understand caching implications.      #
+
+# INDEX_CACHE_CONTROL=no-cache, no-store, must-revalidate
+# INDEX_PRAGMA=no-cache
+# INDEX_EXPIRES=0
+
+# no-cache: Forces validation with server before using cached version
+# no-store: Prevents storing the response entirely
+# must-revalidate: Prevents using stale content when offline
+
+#=====================================================#
+#                  OpenWeather                        #
+#=====================================================#
+OPENWEATHER_API_KEY=
+
+#====================================#
+# LibreChat Code Interpreter API     #
+#====================================#
+
+# https://code.librechat.ai
+# LIBRECHAT_CODE_API_KEY=your-key
+
+#======================#
+# Web Search           #
+#======================#
+
+# Note: All of the following variable names can be customized.
+# Omit values to allow user to provide them.
+
+# For more information on configuration values, see:
+# https://librechat.ai/docs/features/web_search
+
+# Search Provider (Required)
+# SERPER_API_KEY=your_serper_api_key
+
+# Scraper (Required)
+# FIRECRAWL_API_KEY=your_firecrawl_api_key
+# Optional: Custom Firecrawl API URL
+# FIRECRAWL_API_URL=your_firecrawl_api_url
+
+# Reranker (Required)
+# JINA_API_KEY=your_jina_api_key
+# or
+# COHERE_API_KEY=your_cohere_api_key
+
+#======================#
+# MCP Configuration    #
+#======================#
+
+# Treat 401/403 responses as OAuth requirement when no oauth metadata found
+# MCP_OAUTH_ON_AUTH_ERROR=true
+
+# Timeout for OAuth detection requests in milliseconds
+# MCP_OAUTH_DETECTION_TIMEOUT=5000
+
+# Cache connection status checks for this many milliseconds to avoid expensive verification
+# MCP_CONNECTION_CHECK_TTL=60000
+
+# Skip code challenge method validation (e.g., for AWS Cognito that supports S256 but doesn't advertise it)
+# When set to true, forces S256 code challenge even if not advertised in .well-known/openid-configuration
+# MCP_SKIP_CODE_CHALLENGE_CHECK=false
+
+# Circuit breaker: max connect/disconnect cycles before tripping (per server)
+# MCP_CB_MAX_CYCLES=7
+
+# Circuit breaker: sliding window (ms) for counting cycles
+# MCP_CB_CYCLE_WINDOW_MS=45000
+
+# Circuit breaker: cooldown (ms) after the cycle breaker trips
+# MCP_CB_CYCLE_COOLDOWN_MS=15000
+
+# Circuit breaker: max consecutive failed connection rounds before backoff
+# MCP_CB_MAX_FAILED_ROUNDS=3
+
+# Circuit breaker: sliding window (ms) for counting failed rounds
+# MCP_CB_FAILED_WINDOW_MS=120000
+
+# Circuit breaker: base backoff (ms) after failed round threshold is reached
+# MCP_CB_BASE_BACKOFF_MS=30000
+
+# Circuit breaker: max backoff cap (ms) for exponential backoff
+# MCP_CB_MAX_BACKOFF_MS=300000

.env.make

@@ -0,0 +1,8 @@
+# Auto-generated from pyproject.toml — do not edit manually
+ALFRED_VERSION=0.1.7
+PYTHON_VERSION=3.14.3
+IMAGE_NAME=alfred_media_organizer
+SERVICE_NAME=alfred
+LIBRECHAT_VERSION=v0.8.4
+RAG_VERSION=v0.7.3
+UV_VERSION=0.11.6

.gitignore

@@ -55,7 +55,7 @@ coverage.xml
 Thumbs.db
 
 # Secrets
-.env
+.env.secrets
 
 # Backup files
 *.backup
@@ -65,3 +65,11 @@ data/*
 
 # Application logs
 logs/*
+
+# Documentation folder
+docs/
+
+# .md files
+*.md
+
+#

Dockerfile

@@ -2,46 +2,36 @@
 # check=skip=InvalidDefaultArgInFrom
 
 ARG PYTHON_VERSION
-ARG PYTHON_VERSION_SHORT
-ARG RUNNER
+ARG UV_VERSION
+
+# Stage 0: uv binary (workaround — --from doesn't support ARG expansion)
+FROM ghcr.io/astral-sh/uv:${UV_VERSION} AS uv-bin
+
 # ===========================================
 # Stage 1: Builder
 # ===========================================
 FROM python:${PYTHON_VERSION}-slim-bookworm AS builder
 
-# Re-declare ARGs after FROM to make them available in this stage
-ARG RUNNER
-
-# STFU - No need - Write logs asap
 ENV DEBIAN_FRONTEND=noninteractive \
     PYTHONDONTWRITEBYTECODE=1 \
-    PYTHONUNBUFFERED=1
+    PYTHONUNBUFFERED=1 \
+    UV_PROJECT_ENVIRONMENT=/venv
 
-# Install build dependencies (needs root)
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential \
-    && rm -rf /var/lib/apt/lists/*
+# Install build dependencies
+RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+    --mount=type=cache,target=/var/lib/apt,sharing=locked \
+    apt-get update \
+    && apt-get install -y --no-install-recommends build-essential
 
-# Install runner globally (needs root) - Save cache for future
-RUN --mount=type=cache,target=/root/.cache/pip \
-    pip install $RUNNER
+# Install uv globally
+COPY --from=uv-bin /uv /usr/local/bin/uv
 
-# Set working directory for dependency installation
 WORKDIR /tmp
 
-# Copy dependency files
-COPY pyproject.toml poetry.lock* uv.lock* Makefile ./
+COPY pyproject.toml uv.lock Makefile ./
 
-# Install dependencies as root (to avoid permission issues with system packages)
-RUN --mount=type=cache,target=/root/.cache/pip \
-    --mount=type=cache,target=/root/.cache/pypoetry \
-    --mount=type=cache,target=/root/.cache/uv \
-    if [ "$RUNNER" = "poetry" ]; then \
-        poetry config virtualenvs.create false && \
-        poetry install --only main --no-root; \
-    elif [ "$RUNNER" = "uv" ]; then \
-        uv pip install --system -r pyproject.toml; \
-    fi
+# Install dependencies into /venv
+RUN --mount=type=cache,target=/root/.cache/uv uv sync
 
 COPY scripts/ ./scripts/
 COPY .env.example ./
@@ -51,16 +41,7 @@ COPY .env.example ./
 # ===========================================
 FROM builder AS test
 
-ARG RUNNER
-
-RUN --mount=type=cache,target=/root/.cache/pip \
-    --mount=type=cache,target=/root/.cache/pypoetry \
-    --mount=type=cache,target=/root/.cache/uv \
-    if [ "$RUNNER" = "poetry" ]; then \
-        poetry install --no-root; \
-    elif [ "$RUNNER" = "uv" ]; then \
-        uv pip install --system -e .[dev]; \
-    fi
+RUN --mount=type=cache,target=/root/.cache/uv uv sync --group dev
 
 COPY alfred/ ./alfred
 COPY scripts ./scripts
@@ -71,51 +52,39 @@ COPY tests/  ./tests
 # ===========================================
 FROM python:${PYTHON_VERSION}-slim-bookworm AS runtime
 
-ARG PYTHON_VERSION_SHORT
-
-# TODO: A-t-on encore besoin de toutes les clés  ?
-ENV LLM_PROVIDER=deepseek \
-    MEMORY_STORAGE_DIR=/data/memory \
-    PYTHONDONTWRITEBYTECODE=1 \
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
     PYTHONPATH=/home/appuser \
-    PYTHONUNBUFFERED=1
+    PATH="/venv/bin:$PATH"
 
-# Install runtime dependencies (needs root)
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    ca-certificates \
-    && rm -rf /var/lib/apt/lists/* \
-    && apt-get clean
+# Install runtime dependencies
+RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+    --mount=type=cache,target=/var/lib/apt,sharing=locked \
+    apt-get update \
+    && apt-get install -y --no-install-recommends ca-certificates
 
 # Create non-root user
 RUN useradd -m -u 1000 -s /bin/bash appuser
 
-# Create data directories (needs root for /data)
+# Create data directories
 RUN mkdir -p /data /logs \
     && chown -R appuser:appuser /data /logs
 
-# Switch to non-root user
 USER appuser
-
-# Set working directory (owned by appuser)
 WORKDIR /home/appuser
 
-# Copy Python packages from builder stage
-COPY --from=builder /usr/local/lib/python${PYTHON_VERSION_SHORT}/site-packages /usr/local/lib/python${PYTHON_VERSION_SHORT}/site-packages
-COPY --from=builder /usr/local/bin /usr/local/bin
+# Copy venv from builder stage
+COPY --from=builder /venv /venv
 
-# Copy application code (already owned by appuser)
+# Copy application code
 COPY --chown=appuser:appuser alfred/ ./alfred
 COPY --chown=appuser:appuser scripts/ ./scripts
 COPY --chown=appuser:appuser .env.example ./
 COPY --chown=appuser:appuser pyproject.toml ./
 
-# Create volumes for persistent data
 VOLUME ["/data", "/logs"]
-
-# Expose port
 EXPOSE 8000
 
-# Health check
 HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
     CMD python -c "import requests; requests.get('http://localhost:8000/health', timeout=5).raise_for_status()" || exit 1
 

Makefile

@@ -1,6 +1,7 @@
 .DEFAULT_GOAL := help
 
 # --- Load Config from pyproject.toml ---
+export
 -include .env.make
 
 # --- Profiles management ---
@@ -9,27 +10,29 @@ p ?= full
 PROFILES_PARAM	:= COMPOSE_PROFILES=$(p)
 
 # --- Commands ---
-DOCKER_COMPOSE	:= docker compose
-DOCKER_BUILD	:= docker build --no-cache \
+DOCKER_COMPOSE	:= docker compose \
+					--env-file .env.alfred \
+					--env-file .env.secrets \
+					--env-file .env.make
+DOCKER_BUILD	:= DOCKER_BUILDKIT=1 docker build \
 					--build-arg PYTHON_VERSION=$(PYTHON_VERSION) \
-					--build-arg PYTHON_VERSION_SHORT=$(PYTHON_VERSION_SHORT) \
-					--build-arg RUNNER=$(RUNNER)
+					--build-arg UV_VERSION=$(UV_VERSION)
 
 # --- Phony ---
-.PHONY: .env bootstrap up down restart logs ps shell build build-test install \
+.PHONY: bootstrap up down restart logs ps shell build build-test install \
 	update install-hooks test coverage lint format clean major minor patch help
 
 # --- Setup ---
-.env .env.make:
+.env.alfred .env.librechat .env.secrets .env.make:
 	@echo "Initializing environment..."
-	@python scripts/bootstrap.py \
+	@uv run python scripts/bootstrap.py \
 		&& echo "✓ Environment ready" \
 		|| (echo "✗ Environment setup failed" && exit 1)
 
-bootstrap: .env .env.make
+bootstrap: .env.alfred .env.librechat .env.secrets .env.make
 
 # --- Docker ---
-up: .env
+up: .env.alfred .env.secrets
 	@echo "Starting containers with profiles: [full]..."
 	@$(PROFILES_PARAM) $(DOCKER_COMPOSE) up -d --remove-orphans \
 		&& echo "✓ Containers started" \
@@ -74,45 +77,45 @@ build-test: .env.make
 
 # --- Dependencies ---
 install:
-	@echo "Installing dependencies with $(RUNNER)..."
-	@$(RUNNER) install \
+	@echo "Installing dependencies with uv..."
+	@uv install \
 		&& echo "✓ Dependencies installed" \
 		|| (echo "✗ Installation failed" && exit 1)
 
 install-hooks:
 	@echo "Installing pre-commit hooks..."
-	@$(RUNNER) run pre-commit install \
+	@uv run pre-commit install \
 		&& echo "✓ Hooks installed" \
 		|| (echo "✗ Hook installation failed" && exit 1)
 
 update:
-	@echo "Updating dependencies with $(RUNNER)..."
-	@$(RUNNER) update \
+	@echo "Updating dependencies with uv..."
+	@uv update \
 		&& echo "✓ Dependencies updated" \
 		|| (echo "✗ Update failed" && exit 1)
 
 # --- Quality ---
 test:
 	@echo "Running tests..."
-	@$(RUNNER) run pytest \
+	@uv run pytest \
 		&& echo "✓ Tests passed" \
 		|| (echo "✗ Tests failed" && exit 1)
 
 coverage:
 	@echo "Running tests with coverage..."
-	@$(RUNNER) run pytest --cov=. --cov-report=html --cov-report=term \
+	@uv run pytest --cov=. --cov-report=html --cov-report=term \
 		&& echo "✓ Coverage report generated" \
 		|| (echo "✗ Coverage failed" && exit 1)
 
 lint:
 	@echo "Linting code..."
-	@$(RUNNER) run ruff check --fix . \
+	@uv run ruff check --fix . \
 		&& echo "✓ Linting complete" \
 		|| (echo "✗ Linting failed" && exit 1)
 
 format:
 	@echo "Formatting code..."
-	@$(RUNNER) run ruff format . && $(RUNNER) run ruff check --fix . \
+	@uv run ruff format . && uv run ruff check --fix . \
 		&& echo "✓ Code formatted" \
 		|| (echo "✗ Formatting failed" && exit 1)
 
@@ -125,7 +128,7 @@ clean:
 # --- Versioning ---
 major minor patch: _check-main
 	@echo "Bumping $@ version..."
-	@$(RUNNER) run bump-my-version bump $@ \
+	@uv run bump-my-version bump $@ \
 		&& echo "✓ Version bumped" \
 		|| (echo "✗ Version bump failed" && exit 1)
 
@@ -138,8 +141,7 @@ major minor patch: _check-main
 _ci-dump-config:
 	@echo "image_name=$(IMAGE_NAME)"
 	@echo "python_version=$(PYTHON_VERSION)"
-	@echo "python_version_short=$(PYTHON_VERSION_SHORT)"
-	@echo "runner=$(RUNNER)"
+	@echo "uv_version=$(UV_VERSION)"
 	@echo "service_name=$(SERVICE_NAME)"
 
 _ci-run-tests:build-test
@@ -161,6 +163,9 @@ help:
 	@echo ""
 	@echo "Usage: make [target] [p=profile1,profile2]"
 	@echo ""
+	@echo "Setup:"
+	@echo "  bootstrap   Generate .env.alfred, .env.librechat, .env.secrets and .env.make"
+	@echo ""
 	@echo "Docker:"
 	@echo "  up          Start containers (default profile: core)"
 	@echo "              Example: make up p=rag,meili"
@@ -173,7 +178,7 @@ help:
 	@echo ""
 	@echo "Dev & Quality:"
 	@echo "  setup       Bootstrap .env and security keys"
-	@echo "  install     Install dependencies via $(RUNNER)"
+	@echo "  install     Install dependencies via uv"
 	@echo "  test        Run pytest suite"
 	@echo "  coverage    Run tests and generate HTML report"
 	@echo "  lint/format Quality and style checks"

README.md

@@ -3,7 +3,7 @@
 An AI-powered agent for managing your local media library with natural language. Search, download, and organize movies and TV shows effortlessly through a conversational interface.
 
 [![Python 3.14](https://img.shields.io/badge/python-3.14-blue.svg)](https://www.python.org/downloads/)
-[![Poetry](https://img.shields.io/badge/dependency%20manager-poetry-blue)](https://python-poetry.org/)
+[![uv](https://img.shields.io/badge/dependency%20manager-uv-purple)](https://github.com/astral-sh/uv)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![Code style: ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)](https://github.com/astral-sh/ruff)
 
@@ -13,9 +13,10 @@ An AI-powered agent for managing your local media library with natural language.
 - 🔍 **Smart Search** — Find movies and TV shows via TMDB with rich metadata
 - 📥 **Torrent Integration** — Search and download via qBittorrent
 - 🧠 **Contextual Memory** — Remembers your preferences and conversation history
-- 📁 **Auto-Organization** — Keeps your media library tidy and well-structured
-- 🌐 **OpenAI-Compatible API** — Works with any OpenAI-compatible client
-- 🖥️ **LibreChat Frontend** — Beautiful web UI included out of the box
+- 📁 **Auto-Organization** — Moves and renames media files, resolves destinations, handles subtitles
+- 🎞️ **Subtitle Pipeline** — Identifies, matches, and places subtitle tracks automatically
+- 🔄 **Workflow Engine** — YAML-defined multi-step workflows (e.g. `organize_media`)
+- 🌐 **OpenAI-Compatible API** — Works with any OpenAI-compatible client (LibreChat, OpenWebUI, etc.)
 - 🔒 **Secure by Default** — Auto-generated secrets and encrypted credentials
 
 ## 🏗️ Architecture
@@ -26,33 +27,50 @@ Built with **Domain-Driven Design (DDD)** principles for clean separation of con
 alfred/
 ├── agent/              # AI agent orchestration
 │   ├── llm/            # LLM clients (Ollama, DeepSeek)
-│   └── tools/          # Tool implementations
+│   ├── tools/          # Tool implementations (api, filesystem, language)
+│   └── workflows/      # YAML-defined multi-step workflows
 ├── application/        # Use cases & DTOs
-│   ├── movies/         # Movie search use cases
+│   ├── movies/         # Movie search
 │   ├── torrents/       # Torrent management
-│   └── filesystem/     # File operations
+│   └── filesystem/     # File operations (move, list, subtitles, seed links)
 ├── domain/             # Business logic & entities
+│   ├── media/          # Release parsing
 │   ├── movies/         # Movie entities
-│   ├── tv_shows/       # TV show entities
-│   └── subtitles/      # Subtitle entities
+│   ├── tv_shows/       # TV show entities & value objects
+│   ├── subtitles/      # Subtitle scanner, services, knowledge base
+│   └── shared/         # Common value objects (ImdbId, FilePath, FileSize)
 └── infrastructure/     # External services & persistence
-    ├── api/            # External API clients (TMDB, qBittorrent)
-    ├── filesystem/     # File system operations
-    └── persistence/    # Memory & repositories
+    ├── api/            # External API clients (TMDB, qBittorrent, Knaben)
+    ├── filesystem/     # File manager (hard-link based, path-traversal safe)
+    ├── persistence/    # Three-tier memory (LTM/STM/Episodic) + JSON repositories
+    └── subtitle/       # Subtitle infrastructure
 ```
 
-See [docs/architecture_diagram.md](docs/architecture_diagram.md) for detailed architectural diagrams.
+### Key flows
+
+**Agent execution:** `agent.step(user_input)` → LLM call → if tool_calls, execute each via registry → loop until no tool calls or `max_tool_iterations` → return final response.
+
+**Media organization workflow:**
+1. `resolve_destination` — Determines target folder/filename from release name
+2. `move_media` — Hard-links file to library, deletes source
+3. `manage_subtitles` — Scans, classifies, and places subtitle tracks
+4. `create_seed_links` — Hard-links library file back to torrents/ for continued seeding
+
+**Memory tiers:**
+- **LTM** (`data/memory/ltm.json`) — Persisted config, media library, watchlist
+- **STM** — Conversation history (capped at `MAX_HISTORY_MESSAGES`)
+- **Episodic** — Transient search results, active downloads, recent errors
 
 ## 🚀 Quick Start
 
 ### Prerequisites
 
-- **Python 3.14+** (required)
-- **Poetry** (dependency manager)
+- **Python 3.14+**
+- **uv** (dependency manager)
 - **Docker & Docker Compose** (recommended for full stack)
 - **API Keys:**
   - TMDB API key ([get one here](https://www.themoviedb.org/settings/api))
-  - Optional: DeepSeek, OpenAI, Anthropic, or other LLM provider keys
+  - Optional: DeepSeek or other LLM provider keys
 
 ### Installation
 
@@ -64,9 +82,15 @@ cd alfred_media_organizer
 # Install dependencies
 make install
 
+# Install pre-commit hooks
+make install-hooks
+
 # Bootstrap environment (generates .env with secure secrets)
 make bootstrap
 
+# Validate your .env against the schema
+make validate
+
 # Edit .env with your API keys
 nano .env
 ```
@@ -94,162 +118,95 @@ The web interface will be available at **http://localhost:3080**
 ### Running Locally (Development)
 
 ```bash
-# Install dependencies
-poetry install
-
-# Start the API server
-poetry run uvicorn alfred.app:app --reload --port 8000
+uv run uvicorn alfred.app:app --reload --port 8000
 ```
 
 ## ⚙️ Configuration
 
-### Environment Bootstrap
+### Settings system
 
-Alfred uses a smart bootstrap system that:
+`settings.toml` is the single source of truth. The schema flows:
 
-1. **Generates secure secrets** automatically (JWT tokens, database passwords, encryption keys)
-2. **Syncs build variables** from `pyproject.toml` (versions, image names)
-3. **Preserves existing secrets** when re-running (never overwrites your API keys)
-4. **Computes database URIs** automatically from individual components
+```
+settings.toml → settings_schema.py → settings_bootstrap.py → .env + .env.make → settings.py
+```
+
+To add a setting: define it in `settings.toml`, run `make bootstrap`, then access via `settings.my_new_setting`.
 
 ```bash
 # First time setup
 make bootstrap
 
-# Re-run after updating pyproject.toml (secrets are preserved)
+# Validate existing .env against schema
+make validate
+
+# Re-run after settings.toml changes (existing secrets preserved)
 make bootstrap
 ```
 
-### Configuration File (.env)
+**Never commit `.env` or `.env.make`** — both are gitignored and auto-generated.
 
-The `.env` file is generated from `.env.example` with secure defaults:
+### Key settings (.env)
 
 ```bash
-# --- CORE SETTINGS ---
-HOST=0.0.0.0
-PORT=3080
+# --- CORE ---
 MAX_HISTORY_MESSAGES=10
 MAX_TOOL_ITERATIONS=10
 
-# --- LLM CONFIGURATION ---
-# Providers: 'local' (Ollama), 'deepseek', 'openai', 'anthropic', 'google'
-DEFAULT_LLM_PROVIDER=local
-
-# Local LLM (Ollama - included in Docker stack)
+# --- LLM ---
+DEFAULT_LLM_PROVIDER=local     # local (Ollama) | deepseek
 OLLAMA_BASE_URL=http://ollama:11434
 OLLAMA_MODEL=llama3.3:latest
 LLM_TEMPERATURE=0.2
 
-# --- API KEYS (fill only what you need) ---
-TMDB_API_KEY=your-tmdb-key-here        # Required for movie search
-DEEPSEEK_API_KEY=                       # Optional
-OPENAI_API_KEY=                         # Optional
-ANTHROPIC_API_KEY=                      # Optional
+# --- API KEYS ---
+TMDB_API_KEY=your-tmdb-key     # Required for movie/show search
+DEEPSEEK_API_KEY=              # Optional
 
-# --- SECURITY (auto-generated, don't modify) ---
-JWT_SECRET=<auto-generated>
-JWT_REFRESH_SECRET=<auto-generated>
-CREDS_KEY=<auto-generated>
-CREDS_IV=<auto-generated>
-
-# --- DATABASES (auto-generated passwords) ---
-MONGO_PASSWORD=<auto-generated>
-POSTGRES_PASSWORD=<auto-generated>
+# --- SECURITY (auto-generated) ---
+JWT_SECRET=<auto>
+CREDS_KEY=<auto>
+MONGO_PASSWORD=<auto>
 ```
 
-### Security Keys
-
-Security keys are defined in `pyproject.toml` and generated automatically:
-
-```toml
-[tool.alfred.security]
-jwt_secret = "32:b64"           # 32 bytes, base64 URL-safe
-jwt_refresh_secret = "32:b64"
-creds_key = "32:hex"            # 32 bytes, hexadecimal (AES-256)
-creds_iv = "16:hex"             # 16 bytes, hexadecimal (AES IV)
-mongo_password = "16:hex"
-postgres_password = "16:hex"
-```
-
-**Formats:**
-- `b64` — Base64 URL-safe (for JWT tokens)
-- `hex` — Hexadecimal (for encryption keys, passwords)
-
 ## 🐳 Docker Services
 
-### Service Architecture
-
-```
-┌─────────────────────────────────────────────────────────────┐
-│                     alfred-net (bridge)                      │
-├─────────────────────────────────────────────────────────────┤
-│                                                              │
-│  ┌──────────────┐    ┌──────────────┐    ┌──────────────┐  │
-│  │  LibreChat   │───▶│    Alfred    │───▶│   MongoDB    │  │
-│  │   :3080      │    │   (core)     │    │   :27017     │  │
-│  └──────────────┘    └──────────────┘    └──────────────┘  │
-│         │                   │                               │
-│         │                   ▼                               │
-│         │            ┌──────────────┐                       │
-│         │            │    Ollama    │                       │
-│         │            │   (local)    │                       │
-│         │            └──────────────┘                       │
-│         │                                                   │
-│  ┌──────┴───────────────────────────────────────────────┐  │
-│  │              Optional Services (profiles)             │  │
-│  ├──────────────┬──────────────┬──────────────┬─────────┤  │
-│  │ Meilisearch  │  RAG API     │  VectorDB    │qBittor- │  │
-│  │   :7700      │   :8000      │   :5432      │  rent   │  │
-│  │  [meili]     │   [rag]      │   [rag]      │[qbit..] │  │
-│  └──────────────┴──────────────┴──────────────┴─────────┘  │
-│                                                              │
-└─────────────────────────────────────────────────────────────┘
-```
-
 ### Docker Profiles
 
-| Profile | Services | Use Case |
-|---------|----------|----------|
-| (default) | LibreChat, Alfred, MongoDB, Ollama | Basic setup |
-| `meili` | + Meilisearch | Fast search |
-| `rag` | + RAG API, VectorDB | Document retrieval |
-| `qbittorrent` | + qBittorrent | Torrent downloads |
-| `full` | All services | Complete setup |
+| Profile | Extra services | Use case |
+|---------|---------------|----------|
+| (default) | — | LibreChat + Alfred + MongoDB + Ollama |
+| `meili` | Meilisearch | Fast full-text search |
+| `rag` | RAG API + VectorDB (PostgreSQL) | Document retrieval |
+| `qbittorrent` | qBittorrent | Torrent downloads |
+| `full` | All of the above | Complete setup |
 
 ```bash
-# Start with specific profiles
-make up p=rag,meili
-make up p=full
-```
-
-### Docker Commands
-
-```bash
-make up              # Start containers (default profile)
+make up              # Start (default profile)
 make up p=full       # Start with all services
-make down            # Stop all containers
-make restart         # Restart containers
+make down            # Stop
+make restart         # Restart
 make logs            # Follow logs
-make ps              # Show container status
-make shell           # Open bash in Alfred container
-make build           # Build production image
-make build-test      # Build test image
+make ps              # Container status
 ```
 
 ## 🛠️ Available Tools
 
-The agent has access to these tools for interacting with your media library:
-
 | Tool | Description |
 |------|-------------|
 | `find_media_imdb_id` | Search for movies/TV shows on TMDB by title |
 | `find_torrent` | Search for torrents across multiple indexers |
-| `get_torrent_by_index` | Get detailed info about a specific torrent result |
-| `add_torrent_by_index` | Download a torrent by its index in search results |
+| `get_torrent_by_index` | Get detailed info about a specific result |
+| `add_torrent_by_index` | Download a torrent from search results |
 | `add_torrent_to_qbittorrent` | Add a torrent via magnet link directly |
-| `set_path_for_folder` | Configure folder paths for media organization |
-| `list_folder` | List contents of a folder |
-| `set_language` | Set preferred language for searches |
+| `resolve_destination` | Compute the target library path for a release |
+| `move_media` | Hard-link a file to its library destination |
+| `manage_subtitles` | Scan, classify, and place subtitle tracks |
+| `create_seed_links` | Prepare torrent folder so qBittorrent keeps seeding |
+| `learn` | Teach Alfred a new pattern (release group, naming convention) |
+| `set_path_for_folder` | Configure folder paths |
+| `list_folder` | List contents of a configured folder |
+| `set_language` | Set preferred language for the session |
 
 ## 💬 Usage Examples
 
@@ -266,11 +223,12 @@ Alfred: I found 3 torrents for Inception (2010):
 
 You: Download the first one
 Alfred: ✓ Added to qBittorrent! Download started.
-        Saving to: /downloads/Movies/Inception (2010)/
 
-You: What's downloading right now?
-Alfred: You have 1 active download:
-        - Inception.2010.1080p.BluRay.x264 (45% complete, ETA: 12 min)
+You: Organize the Breaking Bad S01 download
+Alfred: ✓ Resolved destination: /tv_shows/Breaking.Bad/Season 01/
+        ✓ Moved 6 episode files
+        ✓ Placed 6 subtitle tracks (fr, en)
+        ✓ Seed links created in /torrents/
 ```
 
 ### Via API
@@ -279,219 +237,147 @@ Alfred: You have 1 active download:
 # Health check
 curl http://localhost:8000/health
 
-# Chat with the agent (OpenAI-compatible)
+# Chat (OpenAI-compatible)
 curl -X POST http://localhost:8000/v1/chat/completions \
   -H "Content-Type: application/json" \
   -d '{
     "model": "alfred",
-    "messages": [
-      {"role": "user", "content": "Find The Matrix 4K"}
-    ]
+    "messages": [{"role": "user", "content": "Find The Matrix 4K"}]
   }'
 
-# List available models
+# List models
 curl http://localhost:8000/v1/models
 
-# View memory state (debug)
+# View memory state
 curl http://localhost:8000/memory/state
-
-# Clear session memory
-curl -X POST http://localhost:8000/memory/clear-session
 ```
 
-### Via OpenWebUI or Other Clients
-
-Alfred is compatible with any OpenAI-compatible client:
-
-1. Add as OpenAI-compatible endpoint: `http://localhost:8000/v1`
-2. Model name: `alfred`
-3. No API key required (or use any placeholder)
+Alfred is compatible with any OpenAI-compatible client. Point it at `http://localhost:8000/v1`, model `alfred`.
 
 ## 🧠 Memory System
 
-Alfred uses a three-tier memory system for context management:
+Alfred uses a three-tier memory system:
 
-### Long-Term Memory (LTM)
-- **Persistent** — Saved to JSON files
-- **Contents:** Configuration, user preferences, media library state
-- **Survives:** Application restarts
-
-### Short-Term Memory (STM)
-- **Session-based** — Stored in RAM
-- **Contents:** Conversation history, current workflow state
-- **Cleared:** On session end or restart
-
-### Episodic Memory
-- **Transient** — Stored in RAM
-- **Contents:** Search results, active downloads, recent errors
-- **Cleared:** Frequently, after task completion
+| Tier | Storage | Contents | Lifetime |
+|------|---------|----------|----------|
+| **LTM** | JSON file (`data/memory/ltm.json`) | Config, library, watchlist, learned patterns | Permanent |
+| **STM** | RAM | Conversation history (capped) | Session |
+| **Episodic** | RAM | Search results, active downloads, errors | Short-lived |
 
 ## 🧪 Development
 
-### Project Setup
-
-```bash
-# Install all dependencies (including dev)
-poetry install
-
-# Install pre-commit hooks
-make install-hooks
-
-# Run the development server
-poetry run uvicorn alfred.app:app --reload
-```
-
 ### Running Tests
 
 ```bash
-# Run all tests (parallel execution)
+# Run full suite (parallel)
 make test
 
 # Run with coverage report
 make coverage
 
-# Run specific test file
-poetry run pytest tests/test_agent.py -v
+# Run a single file
+uv run pytest tests/test_agent.py -v
 
-# Run specific test
-poetry run pytest tests/test_config_loader.py::TestBootstrapEnv -v
+# Run a single class
+uv run pytest tests/test_agent.py::TestAgentInit -v
+
+# Skip slow tests
+uv run pytest -m "not slow"
 ```
 
+### Test coverage
+
+The suite covers:
+- **Agent loop** — tool execution, history, max iterations, error handling
+- **Tool registry** — OpenAI schema format, parameter extraction
+- **Prompts** — system prompt building, tool inclusion
+- **Memory** — LTM/STM/Episodic operations, persistence
+- **Filesystem tools** — path traversal security, folder listing
+- **File manager** — hard-link, move, seed links (real filesystem, no mocks)
+- **Application use cases** — `resolve_destination`, `create_seed_links`, `list_folder`, `move_media`
+- **Domain** — TV show/movie entities, shared value objects (`ImdbId`, `FilePath`, `FileSize`), subtitle scanner
+- **Repositories** — JSON-backed movie, TV show, subtitle repos
+- **Bootstrap** — secret generation, idempotency, URI construction
+- **Workflows** — YAML loading, structure validation
+- **Configuration** — boundary validation for all settings
+
 ### Code Quality
 
 ```bash
-# Lint and auto-fix
-make lint
-
-# Format code
-make format
-
-# Clean build artifacts
-make clean
+make lint        # Ruff check --fix
+make format      # Ruff format + check --fix
 ```
 
 ### Adding a New Tool
 
-1. **Create the tool function** in `alfred/agent/tools/`:
+1. Implement the function in `alfred/agent/tools/`:
 
 ```python
 # alfred/agent/tools/api.py
 def my_new_tool(param: str) -> dict[str, Any]:
-    """
-    Short description of what this tool does.
-    
-    This will be shown to the LLM to help it decide when to use this tool.
-    """
+    """Short description shown to the LLM to decide when to call this tool."""
     memory = get_memory()
-    
-    # Your implementation here
-    result = do_something(param)
-    
-    return {
-        "status": "success",
-        "data": result
-    }
+    # ...
+    return {"status": "ok", "data": result}
 ```
 
-2. **Register in the registry** (`alfred/agent/registry.py`):
+2. Register it in `alfred/agent/registry.py`:
 
 ```python
 tool_functions = [
     # ... existing tools ...
-    api_tools.my_new_tool,  # Add your tool here
+    api_tools.my_new_tool,
 ]
 ```
 
-The tool will be automatically registered with its parameters extracted from the function signature.
+The registry auto-generates the JSON schema from the function signature and docstring.
+
+### Adding a Workflow
+
+Create a YAML file in `alfred/agent/workflows/`:
+
+```yaml
+name: my_workflow
+description: What this workflow does
+steps:
+  - tool: resolve_destination
+    description: Find where the file should go
+  - tool: move_media
+    description: Move the file
+```
+
+Workflows are loaded automatically at startup.
 
 ### Version Management
 
 ```bash
-# Bump version (must be on main branch)
-make patch    # 0.1.7 -> 0.1.8
-make minor    # 0.1.7 -> 0.2.0
-make major    # 0.1.7 -> 1.0.0
+# Must be on main branch
+make patch    # 0.1.7 → 0.1.8
+make minor    # 0.1.7 → 0.2.0
+make major    # 0.1.7 → 1.0.0
 ```
 
 ## 📚 API Reference
 
 ### Endpoints
 
-#### `GET /health`
-Health check endpoint.
-
-```json
-{
-  "status": "healthy",
-  "version": "0.1.7"
-}
-```
-
-#### `GET /v1/models`
-List available models (OpenAI-compatible).
-
-```json
-{
-  "object": "list",
-  "data": [
-    {
-      "id": "alfred",
-      "object": "model",
-      "owned_by": "alfred"
-    }
-  ]
-}
-```
-
-#### `POST /v1/chat/completions`
-Chat with the agent (OpenAI-compatible).
-
-**Request:**
-```json
-{
-  "model": "alfred",
-  "messages": [
-    {"role": "user", "content": "Find Inception"}
-  ],
-  "stream": false
-}
-```
-
-**Response:**
-```json
-{
-  "id": "chatcmpl-xxx",
-  "object": "chat.completion",
-  "created": 1234567890,
-  "model": "alfred",
-  "choices": [{
-    "index": 0,
-    "message": {
-      "role": "assistant",
-      "content": "I found Inception (2010)..."
-    },
-    "finish_reason": "stop"
-  }]
-}
-```
-
-#### `GET /memory/state`
-View full memory state (debug endpoint).
-
-#### `POST /memory/clear-session`
-Clear session memories (STM + Episodic).
+| Method | Path | Description |
+|--------|------|-------------|
+| `GET` | `/health` | Health check |
+| `GET` | `/v1/models` | List models (OpenAI-compatible) |
+| `POST` | `/v1/chat/completions` | Chat (OpenAI-compatible, streaming supported) |
+| `GET` | `/memory/state` | Full memory dump (debug) |
+| `POST` | `/memory/clear-session` | Clear STM + Episodic |
+| `GET` | `/memory/episodic/search-results` | Current search results |
 
 ## 🔧 Troubleshooting
 
 ### Agent doesn't respond
 
 1. Check API keys in `.env`
-2. Verify LLM provider is running:
+2. Verify the LLM is running:
    ```bash
-   # For Ollama
    docker logs alfred-ollama
-   
-   # Check if model is pulled
    docker exec alfred-ollama ollama list
    ```
 3. Check Alfred logs: `docker logs alfred-core`
@@ -499,76 +385,34 @@ Clear session memories (STM + Episodic).
 ### qBittorrent connection failed
 
 1. Verify qBittorrent is running: `docker ps | grep qbittorrent`
-2. Check Web UI is enabled in qBittorrent settings
-3. Verify credentials in `.env`:
-   ```bash
-   QBITTORRENT_URL=http://qbittorrent:16140
-   QBITTORRENT_USERNAME=admin
-   QBITTORRENT_PASSWORD=<check-your-env>
-   ```
-
-### Database connection issues
-
-1. Check MongoDB is healthy: `docker logs alfred-mongodb`
-2. Verify credentials match in `.env`
-3. Try restarting: `make restart`
+2. Check credentials in `.env` (`QBITTORRENT_URL`, `QBITTORRENT_USERNAME`, `QBITTORRENT_PASSWORD`)
 
 ### Memory not persisting
 
-1. Check `data/` directory exists and is writable
+1. Check `data/` directory is writable
 2. Verify volume mounts in `docker-compose.yaml`
-3. Check file permissions: `ls -la data/`
 
 ### Bootstrap fails
 
-1. Ensure `.env.example` exists
-2. Check `pyproject.toml` has required sections:
-   ```toml
-   [tool.alfred.settings]
-   [tool.alfred.security]
-   ```
-3. Run manually: `python scripts/bootstrap.py`
+```bash
+make validate    # Check what's wrong with .env
+make bootstrap   # Regenerate (preserves existing secrets)
+```
 
 ### Tests failing
 
-1. Update dependencies: `poetry install`
-2. Check Python version: `python --version` (needs 3.14+)
-3. Run specific failing test with verbose output:
-   ```bash
-   poetry run pytest tests/test_failing.py -v --tb=long
-   ```
+```bash
+uv run pytest tests/test_failing.py -v --tb=long
+```
 
 ## 🤝 Contributing
 
-Contributions are welcome! Please follow these steps:
-
-1. **Fork** the repository
-2. **Create** a feature branch: `git checkout -b feature/my-feature`
-3. **Make** your changes
-4. **Run** tests: `make test`
-5. **Run** linting: `make lint && make format`
-6. **Commit**: `git commit -m "feat: add my feature"`
-7. **Push**: `git push origin feature/my-feature`
-8. **Create** a Pull Request
-
-### Commit Convention
-
-We use [Conventional Commits](https://www.conventionalcommits.org/):
-
-- `feat:` New feature
-- `fix:` Bug fix
-- `docs:` Documentation
-- `refactor:` Code refactoring
-- `test:` Adding tests
-- `chore:` Maintenance
-
-## 📖 Documentation
-
-- [Architecture Diagram](docs/architecture_diagram.md) — System architecture overview
-- [Class Diagram](docs/class_diagram.md) — Class structure and relationships
-- [Component Diagram](docs/component_diagram.md) — Component interactions
-- [Sequence Diagram](docs/sequence_diagram.md) — Sequence flows
-- [Flowchart](docs/flowchart.md) — System flowcharts
+1. Fork the repository
+2. Create a feature branch: `git checkout -b feat/my-feature`
+3. Make your changes + add tests
+4. Run `make test && make lint && make format`
+5. Commit with [Conventional Commits](https://www.conventionalcommits.org/): `feat:`, `fix:`, `docs:`, `refactor:`, `test:`, `chore:`, `infra:`
+6. Open a Pull Request
 
 ## 📄 License
 
@@ -576,19 +420,13 @@ MIT License — see [LICENSE](LICENSE) file for details.
 
 ## 🙏 Acknowledgments
 
-- [LibreChat](https://github.com/danny-avila/LibreChat) — Beautiful chat interface
+- [LibreChat](https://github.com/danny-avila/LibreChat) — Chat interface
 - [Ollama](https://ollama.ai/) — Local LLM runtime
 - [DeepSeek](https://www.deepseek.com/) — LLM provider
-- [TMDB](https://www.themoviedb.org/) — Movie database
+- [TMDB](https://www.themoviedb.org/) — Movie & TV database
 - [qBittorrent](https://www.qbittorrent.org/) — Torrent client
 - [FastAPI](https://fastapi.tiangolo.com/) — Web framework
-- [Pydantic](https://docs.pydantic.dev/) — Data validation
-
-## 📬 Support
-
-- 📧 Email: francois.hodiaumont@gmail.com
-- 🐛 Issues: [GitHub Issues](https://github.com/francwa/alfred_media_organizer/issues)
-- 💬 Discussions: [GitHub Discussions](https://github.com/francwa/alfred_media_organizer/discussions)
+- [uv](https://github.com/astral-sh/uv) — Fast Python package manager
 
 ---
 

alfred/agent/prompts.py

@@ -4,6 +4,7 @@ import json
 from typing import Any
 
 from alfred.infrastructure.persistence import get_memory
+from alfred.infrastructure.persistence.memory import MemoryRegistry
 
 from .registry import Tool
 
@@ -13,6 +14,7 @@ class PromptBuilder:
 
     def __init__(self, tools: dict[str, Tool]):
         self.tools = tools
+        self._memory_registry = MemoryRegistry()
 
     def build_tools_spec(self) -> list[dict[str, Any]]:
         """Build the tool specification for the LLM API."""
@@ -109,11 +111,30 @@ class PromptBuilder:
 
         return "\n".join(lines)
 
+    def _format_memory_schema(self) -> str:
+        """Describe available memory components so the agent knows what to read/write and when."""
+        schema = self._memory_registry.schema()
+        tier_labels = {"ltm": "LONG-TERM (persisted)", "stm": "SHORT-TERM (session)", "episodic": "EPISODIC (volatile)"}
+        lines = ["MEMORY COMPONENTS:"]
+
+        for tier, components in schema.items():
+            if not components:
+                continue
+            lines.append(f"\n  [{tier_labels.get(tier, tier.upper())}]")
+            for c in components:
+                access = c.get("access", "read")
+                lines.append(f"  {c['name']} ({access}): {c['description']}")
+                for field_name, field_desc in c.get("fields", {}).items():
+                    lines.append(f"    · {field_name}: {field_desc}")
+
+        return "\n".join(lines)
+
     def _format_config_context(self, memory) -> str:
         """Format configuration context."""
         lines = ["CURRENT CONFIGURATION:"]
-        if memory.ltm.config:
-            for key, value in memory.ltm.config.items():
+        folders = {**memory.ltm.workspace.as_dict(), **memory.ltm.library_paths.to_dict()}
+        if folders:
+            for key, value in folders.items():
                 lines.append(f"  - {key}: {value}")
         else:
             lines.append("  (no configuration set)")
@@ -138,6 +159,9 @@ class PromptBuilder:
         tools_desc = self._format_tools_description()
         tools_section = f"\nAVAILABLE TOOLS:\n{tools_desc}" if tools_desc else ""
 
+        # Memory schema
+        memory_schema = self._format_memory_schema()
+
         # Configuration
         config_section = self._format_config_context(memory)
         if config_section:
@@ -172,6 +196,8 @@ EXAMPLES:
 
 {language_instruction}
 {tools_section}
+
+{memory_schema}
 {config_section}
 {stm_context}
 {episodic_context}

alfred/agent/registry.py

@@ -97,6 +97,11 @@ def make_tools(settings) -> dict[str, Tool]:
     tool_functions = [
         fs_tools.set_path_for_folder,
         fs_tools.list_folder,
+        fs_tools.resolve_destination,
+        fs_tools.move_media,
+        fs_tools.manage_subtitles,
+        fs_tools.create_seed_links,
+        fs_tools.learn,
         api_tools.find_media_imdb_id,
         api_tools.find_torrent,
         api_tools.add_torrent_by_index,

alfred/agent/tools/filesystem.py

@@ -1,10 +1,200 @@
 """Filesystem tools for folder management."""
 
+from pathlib import Path
 from typing import Any
 
-from alfred.application.filesystem import ListFolderUseCase, SetFolderPathUseCase
+import alfred as _alfred_pkg
+import yaml
+
+from alfred.application.filesystem import (
+    CreateSeedLinksUseCase,
+    ListFolderUseCase,
+    ManageSubtitlesUseCase,
+    MoveMediaUseCase,
+    ResolveDestinationUseCase,
+    SetFolderPathUseCase,
+)
 from alfred.infrastructure.filesystem import FileManager
 
+_LEARNED_ROOT = Path(_alfred_pkg.__file__).parent.parent / "data" / "knowledge"
+
+
+def move_media(source: str, destination: str) -> dict[str, Any]:
+    """
+    Move a media file to a destination path.
+
+    Copies the file safely first (with integrity check), then deletes the source.
+    Use this to organise a downloaded file into the media library.
+
+    Args:
+        source: Absolute path to the source file.
+        destination: Absolute path to the destination file (must not already exist).
+
+    Returns:
+        Dict with status, source, destination, filename, and size — or error details.
+    """
+    file_manager = FileManager()
+    use_case = MoveMediaUseCase(file_manager)
+    return use_case.execute(source, destination).to_dict()
+
+
+def resolve_destination(
+    release_name: str,
+    source_file: str,
+    tmdb_title: str,
+    tmdb_year: int,
+    tmdb_episode_title: str | None = None,
+    confirmed_folder: str | None = None,
+) -> dict[str, Any]:
+    """
+    Compute the destination path in the media library for a release.
+
+    Call this before move_media to get the correct library path. Handles:
+    - Parsing the release name (quality, codec, group, season/episode)
+    - Looking up any existing series folder in the library
+    - Applying group-conflict rules (asks user if ambiguous)
+    - Building the full destination path with correct naming conventions
+
+    Args:
+        release_name: Raw release folder or file name
+                      (e.g. "Oz.S03.1080p.WEBRip.x265-KONTRAST").
+        source_file: Absolute path to the source video file (used for extension).
+        tmdb_title: Canonical show/movie title from TMDB (e.g. "Oz").
+        tmdb_year: Release/start year from TMDB (e.g. 1997).
+        tmdb_episode_title: Episode title from TMDB for single-episode releases
+                            (e.g. "The Routine"). Omit for season packs and movies.
+        confirmed_folder: If a previous call returned needs_clarification, pass
+                          the user-chosen folder name here to proceed.
+
+    Returns:
+        On success: dict with status, library_file, series_folder, season_folder,
+                    series_folder_name, season_folder_name, filename,
+                    is_new_series_folder.
+        On ambiguity: dict with status="needs_clarification", question, options.
+        On error: dict with status="error", error, message.
+    """
+    use_case = ResolveDestinationUseCase()
+    return use_case.execute(
+        release_name=release_name,
+        source_file=source_file,
+        tmdb_title=tmdb_title,
+        tmdb_year=tmdb_year,
+        tmdb_episode_title=tmdb_episode_title,
+        confirmed_folder=confirmed_folder,
+    ).to_dict()
+
+
+def create_seed_links(library_file: str, original_download_folder: str) -> dict[str, Any]:
+    """
+    Prepare a torrent subfolder so qBittorrent can keep seeding after a move.
+
+    Hard-links the video file from the library into torrents/<original_folder_name>/,
+    then copies all remaining files from the original download folder (subtitles,
+    .nfo, .jpg, .txt, …) so the torrent data is complete.
+
+    Call this after move_media when the user wants to keep seeding.
+
+    Args:
+        library_file: Absolute path to the video file now in the library.
+        original_download_folder: Absolute path to the original download folder
+            (may still contain subs, nfo, and other release files).
+
+    Returns:
+        Dict with status, torrent_subfolder, linked_file, copied_files,
+        copied_count, skipped — or error details.
+    """
+    file_manager = FileManager()
+    use_case = CreateSeedLinksUseCase(file_manager)
+    return use_case.execute(library_file, original_download_folder).to_dict()
+
+
+def manage_subtitles(source_video: str, destination_video: str) -> dict[str, Any]:
+    """
+    Place subtitle files alongside an organised video file.
+
+    Scans for subtitle files (.srt, .ass, .ssa, .vtt, .sub) next to the source
+    video, filters them according to the user's SubtitlePreferences (languages,
+    min size, SDH, forced), and hard-links the passing files next to the
+    destination video with the correct naming convention:
+        fr.srt / fr.sdh.srt / fr.forced.srt / en.srt …
+
+    Call this right after move_media or copy_media, passing the same source and
+    destination paths. If no subtitles are found, returns ok with placed_count=0.
+
+    Args:
+        source_video: Absolute path to the original video file (in the download folder).
+        destination_video: Absolute path to the placed video file (in the library).
+
+    Returns:
+        Dict with status, placed list (source, destination, filename), placed_count,
+        skipped_count — or error details.
+    """
+    file_manager = FileManager()
+    use_case = ManageSubtitlesUseCase(file_manager)
+    return use_case.execute(source_video, destination_video).to_dict()
+
+
+def learn(pack: str, category: str, key: str, values: list[str]) -> dict[str, Any]:
+    """
+    Teach Alfred a new token mapping and persist it to the learned knowledge pack.
+
+    Use this when a subtitle file contains an unrecognised token — after confirming
+    with the user what the token means, call learn() to persist it so Alfred
+    recognises it in future scans.
+
+    Args:
+        pack: Knowledge pack name. Currently only "subtitles" is supported.
+        category: Category within the pack: "languages", "types", or "formats".
+        key: The entry key — e.g. ISO 639-1 language code ("es"), type id ("sdh").
+        values: List of tokens to add — e.g. ["spanish", "espanol", "spa"].
+
+    Returns:
+        Dict with status, added_count, and the updated token list.
+    """
+    _VALID_PACKS = {"subtitles"}
+    _VALID_CATEGORIES = {"languages", "types", "formats"}
+
+    if pack not in _VALID_PACKS:
+        return {"status": "error", "error": "unknown_pack", "message": f"Unknown pack '{pack}'. Valid: {sorted(_VALID_PACKS)}"}
+
+    if category not in _VALID_CATEGORIES:
+        return {"status": "error", "error": "unknown_category", "message": f"Unknown category '{category}'. Valid: {sorted(_VALID_CATEGORIES)}"}
+
+    learned_path = _LEARNED_ROOT / "subtitles_learned.yaml"
+    _LEARNED_ROOT.mkdir(parents=True, exist_ok=True)
+
+    data: dict = {}
+    if learned_path.exists():
+        try:
+            with open(learned_path, encoding="utf-8") as f:
+                data = yaml.safe_load(f) or {}
+        except Exception as e:
+            return {"status": "error", "error": "read_failed", "message": str(e)}
+
+    cat_data = data.setdefault(category, {})
+    entry = cat_data.setdefault(key, {"tokens": []})
+    existing = entry.get("tokens", [])
+    new_tokens = [v for v in values if v not in existing]
+    entry["tokens"] = existing + new_tokens
+
+    tmp = learned_path.with_suffix(".yaml.tmp")
+    try:
+        with open(tmp, "w", encoding="utf-8") as f:
+            yaml.safe_dump(data, f, allow_unicode=True, default_flow_style=False, sort_keys=False)
+        tmp.rename(learned_path)
+    except Exception as e:
+        tmp.unlink(missing_ok=True)
+        return {"status": "error", "error": "write_failed", "message": str(e)}
+
+    return {
+        "status": "ok",
+        "pack": pack,
+        "category": category,
+        "key": key,
+        "added_count": len(new_tokens),
+        "tokens": entry["tokens"],
+    }
+
 
 def set_path_for_folder(folder_name: str, path_value: str) -> dict[str, Any]:
     """

alfred/agent/workflows/__init__.py

@@ -0,0 +1,3 @@
+from .loader import WorkflowLoader
+
+__all__ = ["WorkflowLoader"]

alfred/agent/workflows/loader.py

@@ -0,0 +1,52 @@
+"""WorkflowLoader — autodiscovers and loads workflow YAML files.
+
+Scans the workflows/ directory for all .yaml files and exposes them
+as dicts. No manual registration needed — drop a new .yaml file and
+it will be picked up automatically.
+"""
+
+import logging
+from pathlib import Path
+
+import yaml
+
+logger = logging.getLogger(__name__)
+
+_WORKFLOWS_DIR = Path(__file__).parent
+
+
+class WorkflowLoader:
+    """
+    Loads all workflow definitions from the workflows/ directory.
+
+    Usage:
+        loader = WorkflowLoader()
+        all_workflows = loader.all()
+        workflow = loader.get("organize_media")
+    """
+
+    def __init__(self):
+        self._workflows: dict[str, dict] = {}
+        self._load()
+
+    def _load(self) -> None:
+        for path in sorted(_WORKFLOWS_DIR.glob("*.yaml")):
+            try:
+                data = yaml.safe_load(path.read_text(encoding="utf-8"))
+                name = data.get("name") or path.stem
+                self._workflows[name] = data
+                logger.info(f"WorkflowLoader: Loaded '{name}' from {path.name}")
+            except Exception as e:
+                logger.warning(f"WorkflowLoader: Could not load {path.name}: {e}")
+
+    def all(self) -> dict[str, dict]:
+        """Return all loaded workflows keyed by name."""
+        return self._workflows
+
+    def get(self, name: str) -> dict | None:
+        """Return a specific workflow by name, or None if not found."""
+        return self._workflows.get(name)
+
+    def names(self) -> list[str]:
+        """Return all available workflow names."""
+        return list(self._workflows.keys())

alfred/agent/workflows/manage_subtitles.yaml

@@ -0,0 +1,69 @@
+name: manage_subtitles
+description: >
+  Place subtitle files alongside a video that has just been organised into the library.
+  Detects the release pattern automatically, identifies and classifies all tracks,
+  filters by user rules, and hard-links matching files to the destination.
+  If any tracks are unrecognised, asks the user and optionally teaches Alfred.
+
+trigger:
+  examples:
+    - "handle subtitles for The X-Files S01E01"
+    - "place the subs next to the file"
+    - "subtitles are in the Subs/ folder"
+    - "add subtitles"
+
+tools:
+  - manage_subtitles
+  - learn
+
+memory:
+  SubtitlePreferences: read
+  Workflow: read-write
+
+steps:
+  - id: place_subtitles
+    tool: manage_subtitles
+    description: >
+      Detect release pattern, identify and classify all subtitle tracks,
+      filter by rules, hard-link matching files next to the destination video.
+      Reads SubtitlePreferences from LTM for language/type/format filtering.
+    params:
+      source_video: "{source_video}"
+      destination_video: "{destination_video}"
+      imdb_id: "{imdb_id}"
+      media_type: "{media_type}"
+      release_group: "{release_group}"
+      season: "{season}"
+      episode: "{episode}"
+    on_result:
+      ok_placed_zero: skip               # no subtitles found — not an error
+      needs_clarification: ask_user      # unrecognised tokens found
+
+  - id: ask_user
+    description: >
+      Some tracks could not be classified. Show the user the unresolved tokens
+      and ask if they want to teach Alfred what they mean.
+      If yes → go to learn_tokens. If no → end workflow.
+    ask_user:
+      question: >
+        I could not identify some tokens in the subtitle files: {unresolved}.
+        Do you want to teach me what they mean?
+      answers:
+        yes: { next_step: learn_tokens }
+        no:  { next_step: end }
+
+  - id: learn_tokens
+    tool: learn
+    description: >
+      Persist a new token mapping to the learned knowledge pack so Alfred
+      recognises it in future scans without asking again.
+    params:
+      pack: "subtitles"
+      category: "{token_category}"   # "languages" or "types"
+      key: "{token_key}"             # e.g. "es", "de"
+      values: "{token_values}"       # e.g. ["spanish", "espanol"]
+
+subtitle_naming:
+  standard:  "{lang}.{ext}"
+  sdh:       "{lang}.sdh.{ext}"
+  forced:    "{lang}.forced.{ext}"

alfred/agent/workflows/organize_media.yaml

@@ -0,0 +1,82 @@
+name: organize_media
+description: >
+  Organise a downloaded series or movie into the media library.
+  Triggered when the user asks to move/organize a specific title.
+  Always moves the video file. Optionally creates seed links in the
+  torrents folder so qBittorrent can keep seeding.
+
+trigger:
+  examples:
+    - "organize Breaking Bad"
+    - "organise Severance season 2"
+    - "move Inception to my library"
+    - "organize Breaking Bad season 1, keep seeding"
+
+tools:
+  - list_folder
+  - find_media_imdb_id
+  - resolve_destination
+  - move_media
+  - manage_subtitles
+  - create_seed_links
+
+memory:
+  WorkspacePaths: read
+  LibraryPaths: read
+  Library: read-write
+  Workflow: read-write
+  Entities: read-write
+
+steps:
+  - id: list_downloads
+    tool: list_folder
+    description: List the download folder to find the target files.
+    params:
+      folder_type: download
+
+  - id: identify_media
+    tool: find_media_imdb_id
+    description: Confirm title, type (series/movie), and metadata via TMDB.
+
+  - id: resolve_destination
+    tool: resolve_destination
+    description: >
+      Compute the correct destination path in the library.
+      Uses the release name + TMDB metadata to build folder and file names.
+      If multiple series folders exist for this title, returns
+      needs_clarification and the user must pick one (re-call with confirmed_folder).
+
+  - id: move_file
+    tool: move_media
+    description: >
+      Move the video file to library_file returned by resolve_destination.
+
+  - id: handle_subtitles
+    tool: manage_subtitles
+    description: >
+      Place subtitle files alongside the video in the library.
+      Pass the original source path and the new library destination path.
+    on_missing: skip
+
+  - id: ask_seeding
+    ask_user:
+      question: "Do you want to keep seeding this torrent?"
+      answers:
+        "yes": { next_step: create_seed_links }
+        "no":  { next_step: update_library }
+
+  - id: create_seed_links
+    tool: create_seed_links
+    description: >
+      Hard-link the library video file back into torrents/<original_folder>/
+      and copy all remaining files from the original download folder
+      (subs, nfo, jpg, …) so the torrent stays complete for seeding.
+
+  - id: update_library
+    memory_write: Library
+    description: Add the entry to the LTM library after a successful move.
+
+naming_convention:
+  # Resolved by domain entities (Movie, Episode) — not hardcoded here
+  tv_show: "{title}/Season {season:02d}/{title}.S{season:02d}E{episode:02d}.{ext}"
+  movie: "{title} ({year})/{title}.{year}.{ext}"

alfred/app.py

@@ -29,7 +29,7 @@ app = FastAPI(
     version="0.2.0",
 )
 
-memory_path = Path(settings.data_storage) / "memory"
+memory_path = Path(settings.data_storage_dir) / "memory"
 init_memory(storage_dir=str(memory_path))
 logger.info(f"Memory context initialized (path: {memory_path})")
 

alfred/application/filesystem/__init__.py

@@ -1,12 +1,32 @@
 """Filesystem use cases."""
 
-from .dto import ListFolderResponse, SetFolderPathResponse
+from .create_seed_links import CreateSeedLinksUseCase
+from .dto import (
+    CreateSeedLinksResponse,
+    ListFolderResponse,
+    ManageSubtitlesResponse,
+    MoveMediaResponse,
+    PlacedSubtitle,
+    SetFolderPathResponse,
+)
 from .list_folder import ListFolderUseCase
+from .manage_subtitles import ManageSubtitlesUseCase
+from .move_media import MoveMediaUseCase
+from .resolve_destination import ResolveDestinationUseCase, ResolvedDestination
 from .set_folder_path import SetFolderPathUseCase
 
 __all__ = [
     "SetFolderPathUseCase",
     "ListFolderUseCase",
+    "CreateSeedLinksUseCase",
+    "MoveMediaUseCase",
+    "ManageSubtitlesUseCase",
+    "ResolveDestinationUseCase",
+    "ResolvedDestination",
     "SetFolderPathResponse",
     "ListFolderResponse",
+    "CreateSeedLinksResponse",
+    "MoveMediaResponse",
+    "ManageSubtitlesResponse",
+    "PlacedSubtitle",
 ]

alfred/application/filesystem/create_seed_links.py

@@ -0,0 +1,54 @@
+"""CreateSeedLinksUseCase — prepares a torrent folder for continued seeding."""
+
+import logging
+
+from alfred.infrastructure.filesystem import FileManager
+from alfred.infrastructure.persistence import get_memory
+
+from .dto import CreateSeedLinksResponse
+
+logger = logging.getLogger(__name__)
+
+
+class CreateSeedLinksUseCase:
+    """
+    Prepares a torrent subfolder so qBittorrent can keep seeding after a move.
+
+    Hard-links the video file from the library back into torrents/<original_folder>/,
+    then copies all remaining files from the original download folder (subs, nfo, …).
+    """
+
+    def __init__(self, file_manager: FileManager):
+        self.file_manager = file_manager
+
+    def execute(
+        self, library_file: str, original_download_folder: str
+    ) -> CreateSeedLinksResponse:
+        memory = get_memory()
+        torrent_folder = memory.ltm.workspace.torrent
+
+        if not torrent_folder:
+            return CreateSeedLinksResponse(
+                status="error",
+                error="torrent_folder_not_set",
+                message="Torrent folder is not configured. Use set_path_for_folder to set it.",
+            )
+
+        result = self.file_manager.create_seed_links(
+            library_file, original_download_folder, torrent_folder
+        )
+
+        if result.get("status") == "ok":
+            return CreateSeedLinksResponse(
+                status="ok",
+                torrent_subfolder=result.get("torrent_subfolder"),
+                linked_file=result.get("linked_file"),
+                copied_files=result.get("copied_files"),
+                copied_count=result.get("copied_count", 0),
+                skipped=result.get("skipped"),
+            )
+        return CreateSeedLinksResponse(
+            status="error",
+            error=result.get("error"),
+            message=result.get("message"),
+        )

alfred/application/filesystem/dto.py

@@ -1,6 +1,56 @@
 """Filesystem application DTOs."""
 
-from dataclasses import dataclass
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+
+
+@dataclass
+class CopyMediaResponse:
+    """Response from copying a media file."""
+
+    status: str
+    source: str | None = None
+    destination: str | None = None
+    filename: str | None = None
+    size: int | None = None
+    error: str | None = None
+    message: str | None = None
+
+    def to_dict(self) -> dict:
+        if self.error:
+            return {"status": self.status, "error": self.error, "message": self.message}
+        return {
+            "status": self.status,
+            "source": self.source,
+            "destination": self.destination,
+            "filename": self.filename,
+            "size": self.size,
+        }
+
+
+@dataclass
+class MoveMediaResponse:
+    """Response from moving a media file."""
+
+    status: str
+    source: str | None = None
+    destination: str | None = None
+    filename: str | None = None
+    size: int | None = None
+    error: str | None = None
+    message: str | None = None
+
+    def to_dict(self) -> dict:
+        if self.error:
+            return {"status": self.status, "error": self.error, "message": self.message}
+        return {
+            "status": self.status,
+            "source": self.source,
+            "destination": self.destination,
+            "filename": self.filename,
+            "size": self.size,
+        }
 
 
 @dataclass
@@ -29,6 +79,104 @@ class SetFolderPathResponse:
         return result
 
 
+@dataclass
+class PlacedSubtitle:
+    """One subtitle file successfully placed."""
+
+    source: str
+    destination: str
+    filename: str
+
+    def to_dict(self) -> dict:
+        return {"source": self.source, "destination": self.destination, "filename": self.filename}
+
+
+@dataclass
+class UnresolvedTrack:
+    """A subtitle track that needs agent clarification before placement."""
+
+    raw_tokens: list[str]
+    file_path: str | None = None
+    file_size_kb: float | None = None
+    reason: str = ""   # "unknown_language" | "low_confidence"
+
+    def to_dict(self) -> dict:
+        return {
+            "raw_tokens": self.raw_tokens,
+            "file_path": self.file_path,
+            "file_size_kb": self.file_size_kb,
+            "reason": self.reason,
+        }
+
+
+@dataclass
+class AvailableSubtitle:
+    """One subtitle track available on an embedded media item."""
+
+    language: str        # ISO 639-2 code
+    subtitle_type: str   # "standard" | "sdh" | "forced" | "unknown"
+
+    def to_dict(self) -> dict:
+        return {"language": self.language, "type": self.subtitle_type}
+
+
+@dataclass
+class ManageSubtitlesResponse:
+    """Response from the manage_subtitles use case."""
+
+    status: str   # "ok" | "needs_clarification" | "error"
+    video_path: str | None = None
+    placed: list[PlacedSubtitle] | None = None
+    skipped_count: int = 0
+    unresolved: list[UnresolvedTrack] | None = None
+    available: list[AvailableSubtitle] | None = None   # embedded tracks summary
+    error: str | None = None
+    message: str | None = None
+
+    def to_dict(self) -> dict:
+        if self.error:
+            return {"status": self.status, "error": self.error, "message": self.message}
+        result = {
+            "status": self.status,
+            "video_path": self.video_path,
+            "placed": [p.to_dict() for p in (self.placed or [])],
+            "placed_count": len(self.placed or []),
+            "skipped_count": self.skipped_count,
+        }
+        if self.unresolved:
+            result["unresolved"] = [u.to_dict() for u in self.unresolved]
+            result["unresolved_count"] = len(self.unresolved)
+        if self.available:
+            result["available"] = [a.to_dict() for a in self.available]
+        return result
+
+
+@dataclass
+class CreateSeedLinksResponse:
+    """Response from creating seed links for a torrent."""
+
+    status: str
+    torrent_subfolder: str | None = None
+    linked_file: str | None = None
+    copied_files: list[str] | None = None
+    copied_count: int = 0
+    skipped: list[str] | None = None
+    error: str | None = None
+    message: str | None = None
+
+    def to_dict(self) -> dict:
+        if self.error:
+            return {"status": self.status, "error": self.error, "message": self.message}
+        return {
+            "status": self.status,
+            "torrent_subfolder": self.torrent_subfolder,
+            "linked_file": self.linked_file,
+            "copied_files": self.copied_files or [],
+            "copied_count": self.copied_count,
+            "skipped": self.skipped or [],
+        }
+
+
 @dataclass
 class ListFolderResponse:
     """Response from listing a folder."""

alfred/application/filesystem/manage_subtitles.py

@@ -0,0 +1,258 @@
+"""ManageSubtitlesUseCase — orchestrates the full subtitle pipeline for a video file."""
+
+import logging
+from pathlib import Path
+
+from alfred.domain.shared.value_objects import ImdbId
+from alfred.domain.subtitles.entities import SubtitleTrack
+from alfred.domain.subtitles.knowledge.base import SubtitleKnowledgeBase
+from alfred.domain.subtitles.knowledge.loader import KnowledgeLoader
+from alfred.domain.subtitles.services.identifier import SubtitleIdentifier
+from alfred.domain.subtitles.services.matcher import SubtitleMatcher
+from alfred.domain.subtitles.services.pattern_detector import PatternDetector
+from alfred.domain.subtitles.services.placer import PlacedTrack, SubtitlePlacer
+from alfred.domain.subtitles.services.utils import available_subtitles
+from alfred.domain.subtitles.value_objects import ScanStrategy
+from alfred.infrastructure.persistence.context import get_memory
+from alfred.infrastructure.subtitle.metadata_store import SubtitleMetadataStore
+from alfred.infrastructure.subtitle.rule_repository import RuleSetRepository
+
+from .dto import AvailableSubtitle, ManageSubtitlesResponse, PlacedSubtitle, UnresolvedTrack
+
+logger = logging.getLogger(__name__)
+
+
+def _infer_library_root(dest_video: Path, media_type: str) -> Path:
+    """
+    Infer the media library root folder from the destination video path.
+
+    TV show:  video → Season 01 → The X-Files   (3 levels up)
+    Movie:    video → Inception (2010)           (1 level up)
+    """
+    if media_type == "tv_show":
+        return dest_video.parent.parent
+    return dest_video.parent
+
+
+def _to_imdb_id(raw: str | None) -> ImdbId | None:
+    if not raw:
+        return None
+    try:
+        return ImdbId(raw)
+    except Exception:
+        return None
+
+
+class ManageSubtitlesUseCase:
+    """
+    Full subtitle pipeline:
+
+    1. Load knowledge base
+    2. Detect (or confirm) the release pattern
+    3. Identify all tracks (ffprobe + filesystem scan)
+    4. Load + resolve rules for this media
+    5. Match tracks against rules
+    6. If any tracks are unresolved → return needs_clarification (don't place yet)
+    7. Place matched tracks via hard-link
+    8. Persist to .alfred/metadata.yaml
+
+    The use case is stateless — all dependencies are instantiated inline.
+    """
+
+    def execute(
+        self,
+        source_video: str,
+        destination_video: str,
+        imdb_id: str | None = None,
+        media_type: str = "tv_show",
+        release_group: str | None = None,
+        season: int | None = None,
+        episode: int | None = None,
+        confirmed_pattern_id: str | None = None,
+    ) -> ManageSubtitlesResponse:
+        source_path = Path(source_video)
+        dest_path = Path(destination_video)
+
+        if not source_path.exists():
+            return ManageSubtitlesResponse(
+                status="error",
+                error="source_not_found",
+                message=f"Source video not found: {source_video}",
+            )
+
+        kb = SubtitleKnowledgeBase(KnowledgeLoader())
+        library_root = _infer_library_root(dest_path, media_type)
+        store = SubtitleMetadataStore(library_root)
+        repo = RuleSetRepository(library_root)
+
+        # --- Pattern resolution ---
+        pattern = self._resolve_pattern(
+            kb, store, source_path, confirmed_pattern_id, release_group
+        )
+        if pattern is None:
+            return ManageSubtitlesResponse(
+                status="error",
+                error="pattern_not_found",
+                message="Could not determine subtitle pattern for this release.",
+            )
+
+        # --- Identify ---
+        media_id = _to_imdb_id(imdb_id)
+        identifier = SubtitleIdentifier(kb)
+        metadata = identifier.identify(
+            video_path=source_path,
+            pattern=pattern,
+            media_id=media_id,
+            media_type=media_type,
+            release_group=release_group,
+        )
+
+        if metadata.total_count == 0:
+            logger.info(f"ManageSubtitles: no subtitle tracks found for {source_path.name}")
+            return ManageSubtitlesResponse(
+                status="ok",
+                video_path=destination_video,
+                placed=[],
+                skipped_count=0,
+            )
+
+        # --- Embedded short-circuit ---
+        if pattern.scan_strategy == ScanStrategy.EMBEDDED:
+            logger.info("ManageSubtitles: embedded pattern — skipping matcher")
+            available = [
+                AvailableSubtitle(
+                    language=t.language.code if t.language else "?",
+                    subtitle_type=t.subtitle_type.value,
+                )
+                for t in available_subtitles(metadata.embedded_tracks)
+            ]
+            return ManageSubtitlesResponse(
+                status="ok",
+                video_path=destination_video,
+                placed=[],
+                skipped_count=0,
+                available=available,
+            )
+
+        # --- Match (external only) ---
+        subtitle_prefs = None
+        try:
+            memory = get_memory()
+            subtitle_prefs = memory.ltm.subtitle_preferences
+        except Exception:
+            pass
+        rules = repo.load(release_group, subtitle_prefs).resolve()
+        matcher = SubtitleMatcher()
+        matched, unresolved = matcher.match(metadata.external_tracks, rules)
+
+        if unresolved:
+            logger.info(
+                f"ManageSubtitles: {len(unresolved)} unresolved track(s) — needs clarification"
+            )
+            return ManageSubtitlesResponse(
+                status="needs_clarification",
+                video_path=destination_video,
+                placed=[],
+                unresolved=[_to_unresolved_dto(t) for t in unresolved],
+            )
+
+        if not matched:
+            return ManageSubtitlesResponse(
+                status="ok",
+                video_path=destination_video,
+                placed=[],
+                skipped_count=metadata.total_count,
+            )
+
+        # --- Place ---
+        placer = SubtitlePlacer()
+        place_result = placer.place(matched, dest_path)
+
+        # --- Persist ---
+        if place_result.placed:
+            pairs = _pair_placed_with_tracks(place_result.placed, matched)
+            store.append_history(pairs, season, episode, release_group)
+
+        placed_dtos = [
+            PlacedSubtitle(
+                source=str(p.source),
+                destination=str(p.destination),
+                filename=p.filename,
+            )
+            for p in place_result.placed
+        ]
+
+        return ManageSubtitlesResponse(
+            status="ok",
+            video_path=destination_video,
+            placed=placed_dtos,
+            skipped_count=place_result.skipped_count,
+        )
+
+    def _resolve_pattern(
+        self,
+        kb: SubtitleKnowledgeBase,
+        store: SubtitleMetadataStore,
+        source_path: Path,
+        confirmed_pattern_id: str | None,
+        release_group: str | None,
+    ):
+        # 1. Explicit override from caller
+        if confirmed_pattern_id:
+            p = kb.pattern(confirmed_pattern_id)
+            if p:
+                return p
+            logger.warning(f"ManageSubtitles: unknown pattern '{confirmed_pattern_id}'")
+
+        # 2. Previously confirmed in metadata store
+        stored_id = store.confirmed_pattern()
+        if stored_id:
+            p = kb.pattern(stored_id)
+            if p:
+                logger.debug(f"ManageSubtitles: using confirmed pattern '{stored_id}'")
+                return p
+
+        # 3. Auto-detect
+        release_root = source_path.parent
+        detector = PatternDetector(kb)
+        result = detector.detect(release_root, source_path)
+
+        if result["detected"] and result["confidence"] >= 0.6:
+            logger.info(
+                f"ManageSubtitles: auto-detected pattern '{result['detected'].id}' "
+                f"(confidence={result['confidence']:.2f})"
+            )
+            return result["detected"]
+
+        # 4. Fallback — adjacent (safest default)
+        logger.info("ManageSubtitles: falling back to 'adjacent' pattern")
+        return kb.pattern("adjacent")
+
+
+def _to_unresolved_dto(track: SubtitleTrack, min_confidence: float = 0.7) -> UnresolvedTrack:
+    reason = "unknown_language" if track.language is None else "low_confidence"
+    return UnresolvedTrack(
+        raw_tokens=track.raw_tokens,
+        file_path=str(track.file_path) if track.file_path else None,
+        file_size_kb=track.file_size_kb,
+        reason=reason,
+    )
+
+
+def _pair_placed_with_tracks(
+    placed: list[PlacedTrack],
+    tracks: list[SubtitleTrack],
+) -> list[tuple[PlacedTrack, SubtitleTrack]]:
+    """
+    Pair each PlacedTrack with its originating SubtitleTrack by source path.
+    Falls back to positional matching if paths don't align.
+    """
+    track_by_path = {t.file_path: t for t in tracks if t.file_path}
+    pairs = []
+    for p in placed:
+        track = track_by_path.get(p.source)
+        if track is None and tracks:
+            track = tracks[0]   # positional fallback
+        if track:
+            pairs.append((p, track))
+    return pairs

alfred/application/filesystem/move_media.py

@@ -0,0 +1,43 @@
+"""Move media use case."""
+
+import logging
+
+from alfred.infrastructure.filesystem import FileManager
+
+from .dto import MoveMediaResponse
+
+logger = logging.getLogger(__name__)
+
+
+class MoveMediaUseCase:
+    """Use case for moving a media file to a destination (copy + delete source)."""
+
+    def __init__(self, file_manager: FileManager):
+        self.file_manager = file_manager
+
+    def execute(self, source: str, destination: str) -> MoveMediaResponse:
+        """
+        Move a media file from source to destination.
+
+        Args:
+            source: Absolute path to the source file.
+            destination: Absolute path to the destination file.
+
+        Returns:
+            MoveMediaResponse with success or error information.
+        """
+        result = self.file_manager.move_file(source, destination)
+
+        if result.get("status") == "ok":
+            return MoveMediaResponse(
+                status="ok",
+                source=result.get("source"),
+                destination=result.get("destination"),
+                filename=result.get("filename"),
+                size=result.get("size"),
+            )
+        return MoveMediaResponse(
+            status="error",
+            error=result.get("error"),
+            message=result.get("message"),
+        )

alfred/application/filesystem/resolve_destination.py

@@ -0,0 +1,246 @@
+"""
+ResolveDestinationUseCase — compute the library destination path for a release.
+
+Steps:
+1. Parse the release name
+2. Look up TMDB for title + year (+ episode title if single episode)
+3. Scan the library for an existing series folder
+4. Apply group-conflict rules
+5. Return the computed paths (or needs_clarification if ambiguous)
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+from dataclasses import dataclass, field
+from pathlib import Path
+
+from alfred.domain.media.release_parser import ParsedRelease, parse_release
+from alfred.infrastructure.persistence import get_memory
+
+logger = logging.getLogger(__name__)
+
+# Characters forbidden on Windows filesystems (served via NFS)
+_WIN_FORBIDDEN = re.compile(r'[?:*"<>|\\]')
+
+
+def _sanitise(text: str) -> str:
+    return _WIN_FORBIDDEN.sub("", text)
+
+
+# ---------------------------------------------------------------------------
+# DTOs
+# ---------------------------------------------------------------------------
+
+@dataclass
+class ResolvedDestination:
+    """All computed paths for a release, ready to hand to move_media."""
+
+    status: str                         # "ok" | "needs_clarification" | "error"
+
+    # Populated on "ok"
+    library_file: str | None = None     # absolute path of the destination video file
+    series_folder: str | None = None    # absolute path of the series root folder
+    season_folder: str | None = None    # absolute path of the season subfolder
+    series_folder_name: str | None = None   # just the folder name (for display)
+    season_folder_name: str | None = None
+    filename: str | None = None
+    is_new_series_folder: bool = False  # True if we're creating the folder
+
+    # Populated on "needs_clarification"
+    question: str | None = None
+    options: list[str] | None = None    # existing group folder names to pick from
+
+    # Populated on "error"
+    error: str | None = None
+    message: str | None = None
+
+    def to_dict(self) -> dict:
+        if self.status == "error":
+            return {"status": self.status, "error": self.error, "message": self.message}
+        if self.status == "needs_clarification":
+            return {
+                "status": self.status,
+                "question": self.question,
+                "options": self.options or [],
+            }
+        return {
+            "status": self.status,
+            "library_file": self.library_file,
+            "series_folder": self.series_folder,
+            "season_folder": self.season_folder,
+            "series_folder_name": self.series_folder_name,
+            "season_folder_name": self.season_folder_name,
+            "filename": self.filename,
+            "is_new_series_folder": self.is_new_series_folder,
+        }
+
+
+# ---------------------------------------------------------------------------
+# Use case
+# ---------------------------------------------------------------------------
+
+class ResolveDestinationUseCase:
+    """
+    Compute the full destination path for a media file being organised.
+
+    The caller provides:
+    - release_name: the raw release folder/file name
+    - source_file: path to the actual video file (to get extension)
+    - tmdb_title: canonical title from TMDB
+    - tmdb_year: release year from TMDB
+    - tmdb_episode_title: episode title from TMDB (None for movies / season packs)
+    - confirmed_folder: if the user already answered needs_clarification, pass
+                        the chosen folder name here to skip the check
+
+    Returns a ResolvedDestination.
+    """
+
+    def execute(
+        self,
+        release_name: str,
+        source_file: str,
+        tmdb_title: str,
+        tmdb_year: int,
+        tmdb_episode_title: str | None = None,
+        confirmed_folder: str | None = None,
+    ) -> ResolvedDestination:
+        parsed = parse_release(release_name)
+        ext = Path(source_file).suffix  # ".mkv"
+
+        if parsed.is_movie:
+            return self._resolve_movie(parsed, tmdb_title, tmdb_year, ext)
+        return self._resolve_tvshow(
+            parsed, tmdb_title, tmdb_year, tmdb_episode_title, ext, confirmed_folder
+        )
+
+    # ------------------------------------------------------------------
+    # Movie
+    # ------------------------------------------------------------------
+
+    def _resolve_movie(
+        self, parsed: ParsedRelease, tmdb_title: str, tmdb_year: int, ext: str
+    ) -> ResolvedDestination:
+        memory = get_memory()
+        movies_root = memory.ltm.library_paths.get("movie")
+        if not movies_root:
+            return ResolvedDestination(
+                status="error",
+                error="library_not_set",
+                message="Movie library path is not configured.",
+            )
+
+        folder_name = _sanitise(parsed.movie_folder_name(tmdb_title, tmdb_year))
+        filename = _sanitise(parsed.movie_filename(tmdb_title, tmdb_year, ext))
+
+        folder_path = Path(movies_root) / folder_name
+        file_path = folder_path / filename
+
+        return ResolvedDestination(
+            status="ok",
+            library_file=str(file_path),
+            series_folder=str(folder_path),
+            series_folder_name=folder_name,
+            filename=filename,
+            is_new_series_folder=not folder_path.exists(),
+        )
+
+    # ------------------------------------------------------------------
+    # TV show
+    # ------------------------------------------------------------------
+
+    def _resolve_tvshow(
+        self,
+        parsed: ParsedRelease,
+        tmdb_title: str,
+        tmdb_year: int,
+        tmdb_episode_title: str | None,
+        ext: str,
+        confirmed_folder: str | None,
+    ) -> ResolvedDestination:
+        memory = get_memory()
+        tv_root = memory.ltm.library_paths.get("tv_show")
+        if not tv_root:
+            return ResolvedDestination(
+                status="error",
+                error="library_not_set",
+                message="TV show library path is not configured.",
+            )
+
+        tv_root_path = Path(tv_root)
+
+        # --- Find existing series folders for this title ---
+        existing = _find_existing_series_folders(tv_root_path, tmdb_title, tmdb_year)
+
+        # --- Determine series folder name ---
+        if confirmed_folder:
+            series_folder_name = confirmed_folder
+            is_new = not (tv_root_path / confirmed_folder).exists()
+        elif len(existing) == 0:
+            # No existing folder — create with release group
+            series_folder_name = _sanitise(parsed.show_folder_name(tmdb_title, tmdb_year))
+            is_new = True
+        elif len(existing) == 1:
+            # Exactly one match — use it regardless of group
+            series_folder_name = existing[0]
+            is_new = False
+        else:
+            # Multiple folders — ask user
+            return ResolvedDestination(
+                status="needs_clarification",
+                question=(
+                    f"Multiple folders found for '{tmdb_title}' in your library. "
+                    f"Which one should I use for this release ({parsed.group})?"
+                ),
+                options=existing,
+            )
+
+        # --- Build paths ---
+        season_folder_name = parsed.season_folder_name()
+        filename = _sanitise(
+            parsed.episode_filename(tmdb_episode_title, ext)
+            if not parsed.is_season_pack
+            else parsed.season_folder_name() + ext
+        )
+
+        series_path = tv_root_path / series_folder_name
+        season_path = series_path / season_folder_name
+        file_path = season_path / filename
+
+        return ResolvedDestination(
+            status="ok",
+            library_file=str(file_path),
+            series_folder=str(series_path),
+            season_folder=str(season_path),
+            series_folder_name=series_folder_name,
+            season_folder_name=season_folder_name,
+            filename=filename,
+            is_new_series_folder=is_new,
+        )
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+def _find_existing_series_folders(tv_root: Path, tmdb_title: str, tmdb_year: int) -> list[str]:
+    """
+    Return names of folders in tv_root that match the given title + year.
+
+    Matching is loose: normalised title (dots, no special chars) + year must
+    appear at the start of the folder name.
+    """
+    if not tv_root.exists():
+        return []
+
+    # Build a normalised prefix to match against: "Oz.1997"
+    clean_title = _sanitise(tmdb_title).replace(" ", ".")
+    prefix = f"{clean_title}.{tmdb_year}".lower()
+
+    matches = []
+    for entry in tv_root.iterdir():
+        if entry.is_dir() and entry.name.lower().startswith(prefix):
+            matches.append(entry.name)
+
+    return sorted(matches)

alfred/domain/media/__init__.py

@@ -0,0 +1,5 @@
+"""Media domain — shared naming and release parsing."""
+
+from .release_parser import ParsedRelease, parse_release
+
+__all__ = ["ParsedRelease", "parse_release"]

alfred/domain/media/release_parser.py

@@ -0,0 +1,306 @@
+"""
+release_parser.py — Parse a release name into structured components.
+
+Handles both dot-separated and space-separated release names:
+    Oz.S03.1080p.WEBRip.x265-KONTRAST
+    Oz S03 1080p WEBRip x265-KONTRAST
+    Inception.2010.1080p.BluRay.x265-GROUP
+"""
+
+from __future__ import annotations
+
+import re
+from dataclasses import dataclass, field
+
+# Known quality tokens
+_QUALITIES = {"2160p", "1080p", "720p", "480p", "576p", "4k", "8k"}
+
+# Known source tokens (case-insensitive match)
+_SOURCES = {
+    "bluray", "blu-ray", "bdrip", "brrip",
+    "webrip", "web-rip", "webdl", "web-dl", "web",
+    "hdtv", "hdrip", "dvdrip", "dvd", "vodrip",
+    "amzn", "nf", "dsnp", "hmax", "atvp",
+}
+
+# Known codec tokens
+_CODECS = {
+    "x264", "x265", "h264", "h265", "hevc", "avc",
+    "xvid", "divx", "av1", "vp9",
+    "h.264", "h.265",
+}
+
+# Windows-forbidden characters (we strip these from display names)
+_WIN_FORBIDDEN = re.compile(r'[?:*"<>|\\]')
+
+# Episode/season pattern: S01, S01E02, S01E02E03, 1x02, etc.
+_SEASON_EP_RE = re.compile(
+    r"S(\d{1,2})(?:E(\d{2})(?:E(\d{2}))?)?",
+    re.IGNORECASE,
+)
+
+# Year pattern
+_YEAR_RE = re.compile(r"\b(19\d{2}|20\d{2})\b")
+
+
+@dataclass
+class ParsedRelease:
+    """Structured representation of a parsed release name."""
+
+    raw: str                        # original release name (untouched)
+    normalised: str                 # dots instead of spaces
+    title: str                      # show/movie title (dots, no year/season/tech)
+    year: int | None                # movie year or show start year (from TMDB)
+    season: int | None              # season number (None for movies)
+    episode: int | None             # first episode number (None if season-pack)
+    episode_end: int | None         # last episode for multi-ep (None otherwise)
+    quality: str | None             # 1080p, 2160p, …
+    source: str | None              # WEBRip, BluRay, …
+    codec: str | None               # x265, HEVC, …
+    group: str                      # release group, "UNKNOWN" if missing
+    tech_string: str                # quality.source.codec joined with dots
+
+    # -------------------------------------------------------------------------
+    # Derived helpers
+    # -------------------------------------------------------------------------
+
+    @property
+    def is_movie(self) -> bool:
+        return self.season is None
+
+    @property
+    def is_season_pack(self) -> bool:
+        return self.season is not None and self.episode is None
+
+    def show_folder_name(self, tmdb_title: str, tmdb_year: int) -> str:
+        """
+        Build the series root folder name.
+
+        Format: {Title}.{Year}.{Tech}-{Group}
+        Example: Oz.1997.1080p.WEBRip.x265-KONTRAST
+        """
+        title_part = _sanitise_for_fs(tmdb_title).replace(" ", ".")
+        tech = self.tech_string or "Unknown"
+        return f"{title_part}.{tmdb_year}.{tech}-{self.group}"
+
+    def season_folder_name(self) -> str:
+        """
+        Build the season subfolder name = normalised release name (no episode).
+
+        Example: Oz.S03.1080p.WEBRip.x265-KONTRAST
+        For a single-episode release we still strip the episode token so the
+        folder can hold the whole season.
+        """
+        return _strip_episode_from_normalised(self.normalised)
+
+    def episode_filename(self, tmdb_episode_title: str | None, ext: str) -> str:
+        """
+        Build the episode filename.
+
+        Format: {Title}.{SxxExx}.{EpisodeTitle}.{Tech}-{Group}.{ext}
+        Example: Oz.S01E01.The.Routine.1080p.WEBRip.x265-KONTRAST.mkv
+
+        If tmdb_episode_title is None, omits the episode title segment.
+        """
+        title_part = _sanitise_for_fs(self.title)   # already dotted from normalised
+        s = f"S{self.season:02d}" if self.season is not None else ""
+        e = f"E{self.episode:02d}" if self.episode is not None else ""
+        se = s + e
+
+        ep_title = ""
+        if tmdb_episode_title:
+            ep_title = "." + _sanitise_for_fs(tmdb_episode_title).replace(" ", ".")
+
+        tech = self.tech_string or "Unknown"
+        ext_clean = ext.lstrip(".")
+        return f"{title_part}.{se}{ep_title}.{tech}-{self.group}.{ext_clean}"
+
+    def movie_folder_name(self, tmdb_title: str, tmdb_year: int) -> str:
+        """
+        Build the movie folder name.
+
+        Format: {Title}.{Year}.{Tech}-{Group}
+        Example: Inception.2010.1080p.BluRay.x265-GROUP
+        """
+        return self.show_folder_name(tmdb_title, tmdb_year)
+
+    def movie_filename(self, tmdb_title: str, tmdb_year: int, ext: str) -> str:
+        """
+        Build the movie filename (same as folder name + extension).
+
+        Example: Inception.2010.1080p.BluRay.x265-GROUP.mkv
+        """
+        ext_clean = ext.lstrip(".")
+        return f"{self.movie_folder_name(tmdb_title, tmdb_year)}.{ext_clean}"
+
+
+# ---------------------------------------------------------------------------
+# Public API
+# ---------------------------------------------------------------------------
+
+def parse_release(name: str) -> ParsedRelease:
+    """
+    Parse a release name and return a ParsedRelease.
+
+    Accepts both dot-separated and space-separated names.
+    """
+    normalised = _normalise(name)
+    tokens = normalised.split(".")
+
+    season, episode, episode_end = _extract_season_episode(tokens)
+    quality, source, codec, group, tech_tokens = _extract_tech(tokens)
+    title = _extract_title(tokens, season, episode, tech_tokens)
+    year = _extract_year(tokens, title)
+
+    tech_parts = [p for p in [quality, source, codec] if p]
+    tech_string = ".".join(tech_parts)
+
+    return ParsedRelease(
+        raw=name,
+        normalised=normalised,
+        title=title,
+        year=year,
+        season=season,
+        episode=episode,
+        episode_end=episode_end,
+        quality=quality,
+        source=source,
+        codec=codec,
+        group=group,
+        tech_string=tech_string,
+    )
+
+
+# ---------------------------------------------------------------------------
+# Internal helpers
+# ---------------------------------------------------------------------------
+
+def _normalise(name: str) -> str:
+    """Replace spaces with dots, collapse multiple dots."""
+    s = name.replace(" ", ".")
+    s = re.sub(r"\.{2,}", ".", s)
+    return s.strip(".")
+
+
+def _sanitise_for_fs(text: str) -> str:
+    """Remove Windows-forbidden characters from a string."""
+    return _WIN_FORBIDDEN.sub("", text)
+
+
+def _extract_season_episode(tokens: list[str]) -> tuple[int | None, int | None, int | None]:
+    joined = ".".join(tokens)
+    m = _SEASON_EP_RE.search(joined)
+    if not m:
+        return None, None, None
+    season = int(m.group(1))
+    episode = int(m.group(2)) if m.group(2) else None
+    episode_end = int(m.group(3)) if m.group(3) else None
+    return season, episode, episode_end
+
+
+def _extract_tech(
+    tokens: list[str],
+) -> tuple[str | None, str | None, str | None, str, set[str]]:
+    """
+    Extract quality, source, codec, group from tokens.
+
+    Returns (quality, source, codec, group, tech_token_set).
+
+    Group extraction strategy (in priority order):
+    1. Token where prefix is a known codec: x265-GROUP
+    2. Last token in the list that contains a dash (fallback for 10bit-GROUP, AAC5.1-GROUP, etc.)
+    """
+    quality: str | None = None
+    source: str | None = None
+    codec: str | None = None
+    group = "UNKNOWN"
+    tech_tokens: set[str] = set()
+
+    for tok in tokens:
+        tl = tok.lower()
+
+        if tl in _QUALITIES:
+            quality = tok
+            tech_tokens.add(tok)
+            continue
+
+        if tl in _SOURCES:
+            source = tok
+            tech_tokens.add(tok)
+            continue
+
+        if "-" in tok:
+            parts = tok.rsplit("-", 1)
+            # codec-GROUP (highest priority for group)
+            if parts[0].lower() in _CODECS:
+                codec = parts[0]
+                group = parts[1] if parts[1] else "UNKNOWN"
+                tech_tokens.add(tok)
+                continue
+            # source with dash: Web-DL, WEB-DL, etc.
+            if parts[0].lower() in _SOURCES or tok.lower().replace("-", "") in _SOURCES:
+                source = tok
+                tech_tokens.add(tok)
+                continue
+
+        if tl in _CODECS:
+            codec = tok
+            tech_tokens.add(tok)
+
+    # Fallback: if group still UNKNOWN, use the rightmost token with a dash
+    # that isn't a known source (handles "10bit-Protozoan", "AAC5.1-YTS", etc.)
+    if group == "UNKNOWN":
+        for tok in reversed(tokens):
+            if "-" in tok:
+                parts = tok.rsplit("-", 1)
+                tl = tok.lower()
+                if tl in _SOURCES or tok.lower().replace("-", "") in _SOURCES:
+                    continue
+                if parts[1]:  # non-empty group part
+                    group = parts[1]
+                    break
+
+    return quality, source, codec, group, tech_tokens
+
+
+def _extract_title(tokens: list[str], season: int | None, episode: int | None, tech_tokens: set[str]) -> str:
+    """
+    Extract the title portion: everything before the first season/year/tech token.
+    """
+    title_parts = []
+    for tok in tokens:
+        # Stop at season token
+        if _SEASON_EP_RE.match(tok):
+            break
+        # Stop at year
+        if _YEAR_RE.fullmatch(tok):
+            break
+        # Stop at tech tokens
+        if tok in tech_tokens or tok.lower() in _QUALITIES | _SOURCES | _CODECS:
+            break
+        # Stop if token contains a dash (likely codec-GROUP)
+        if "-" in tok and any(p.lower() in _CODECS | _SOURCES for p in tok.split("-")):
+            break
+        title_parts.append(tok)
+
+    return ".".join(title_parts) if title_parts else tokens[0]
+
+
+def _extract_year(tokens: list[str], title: str) -> int | None:
+    """Extract a 4-digit year from tokens (only after the title)."""
+    title_len = len(title.split("."))
+    for tok in tokens[title_len:]:
+        m = _YEAR_RE.fullmatch(tok)
+        if m:
+            return int(m.group(1))
+    return None
+
+
+def _strip_episode_from_normalised(normalised: str) -> str:
+    """
+    Remove all episode parts (Exx) from a normalised release name, keeping Sxx.
+
+    Oz.S03E01.1080p...             → Oz.S03.1080p...
+    Archer.S14E09E10E11.1080p...   → Archer.S14.1080p...
+    """
+    return re.sub(r"(S\d{2})(E\d{2})+", r"\1", normalised, flags=re.IGNORECASE)

alfred/domain/subtitles/__init__.py

@@ -1,14 +1,37 @@
-"""Subtitles domain - Business logic for subtitle management (shared across movies and TV shows)."""
+"""Subtitles domain — subtitle identification, classification and placement."""
 
-from .entities import Subtitle
+from .aggregates import SubtitleRuleSet
+from .entities import MediaSubtitleMetadata, SubtitleTrack
 from .exceptions import SubtitleNotFound
-from .services import SubtitleService
-from .value_objects import Language, SubtitleFormat
+from .knowledge import KnowledgeLoader, SubtitleKnowledgeBase
+from .services import PatternDetector, SubtitleIdentifier, SubtitleMatcher
+from .value_objects import (
+    RuleScope,
+    ScanStrategy,
+    SubtitleFormat,
+    SubtitleLanguage,
+    SubtitleMatchingRules,
+    SubtitlePattern,
+    SubtitleType,
+    TypeDetectionMethod,
+)
 
 __all__ = [
-    "Subtitle",
-    "Language",
+    "SubtitleTrack",
+    "MediaSubtitleMetadata",
+    "SubtitleRuleSet",
+    "SubtitleKnowledgeBase",
+    "KnowledgeLoader",
+    "SubtitleIdentifier",
+    "SubtitleMatcher",
+    "PatternDetector",
     "SubtitleFormat",
+    "SubtitleLanguage",
+    "SubtitlePattern",
+    "SubtitleType",
+    "ScanStrategy",
+    "TypeDetectionMethod",
+    "SubtitleMatchingRules",
+    "RuleScope",
     "SubtitleNotFound",
-    "SubtitleService",
 ]

alfred/domain/subtitles/aggregates.py

@@ -0,0 +1,90 @@
+"""Subtitle domain aggregates."""
+
+from dataclasses import dataclass, field
+from typing import Any
+
+from ..shared.value_objects import ImdbId
+from .knowledge.base import SubtitleKnowledgeBase
+from .value_objects import RuleScope, SubtitleMatchingRules
+
+
+def DEFAULT_RULES() -> SubtitleMatchingRules:
+    """Load default matching rules from subtitles.yaml (defaults section)."""
+    return SubtitleKnowledgeBase().default_rules()
+
+
+@dataclass
+class SubtitleRuleSet:
+    """
+    Rules for subtitle selection at a given scope level, with inheritance.
+
+    Only delta fields are stored — None means "inherit from parent".
+    Resolution order: global → release_group → show/movie → season → episode.
+
+    A RuleSet can also be pinned to a specific media item (imdb_id),
+    bypassing the scope hierarchy for that item.
+    """
+
+    scope: RuleScope
+    parent: "SubtitleRuleSet | None" = None
+    pinned_to: ImdbId | None = None
+
+    # Deltas — None = inherit
+    _languages: list[str] | None = field(default=None, repr=False)
+    _formats: list[str] | None = field(default=None, repr=False)
+    _types: list[str] | None = field(default=None, repr=False)
+    _format_priority: list[str] | None = field(default=None, repr=False)
+    _min_confidence: float | None = field(default=None, repr=False)
+
+    def resolve(self) -> SubtitleMatchingRules:
+        """
+        Walk the parent chain and merge deltas into effective rules.
+        Falls back to DEFAULT_RULES at the top of the chain.
+        """
+        base = self.parent.resolve() if self.parent else DEFAULT_RULES()
+        return SubtitleMatchingRules(
+            preferred_languages=self._languages or base.preferred_languages,
+            preferred_formats=self._formats or base.preferred_formats,
+            allowed_types=self._types or base.allowed_types,
+            format_priority=self._format_priority or base.format_priority,
+            min_confidence=self._min_confidence if self._min_confidence is not None else base.min_confidence,
+        )
+
+    def override(
+        self,
+        languages: list[str] | None = None,
+        formats: list[str] | None = None,
+        types: list[str] | None = None,
+        format_priority: list[str] | None = None,
+        min_confidence: float | None = None,
+    ) -> None:
+        """Set delta overrides at this scope level."""
+        if languages is not None:
+            self._languages = languages
+        if formats is not None:
+            self._formats = formats
+        if types is not None:
+            self._types = types
+        if format_priority is not None:
+            self._format_priority = format_priority
+        if min_confidence is not None:
+            self._min_confidence = min_confidence
+
+    def to_dict(self) -> dict:
+        """Serialize deltas only (for persistence in rules.yaml)."""
+        delta: dict[str, Any] = {}
+        if self._languages is not None:
+            delta["languages"] = self._languages
+        if self._formats is not None:
+            delta["formats"] = self._formats
+        if self._types is not None:
+            delta["types"] = self._types
+        if self._format_priority is not None:
+            delta["format_priority"] = self._format_priority
+        if self._min_confidence is not None:
+            delta["min_confidence"] = self._min_confidence
+        return {"scope": {"level": self.scope.level, "identifier": self.scope.identifier}, "override": delta}
+
+    @classmethod
+    def global_default(cls) -> "SubtitleRuleSet":
+        return cls(scope=RuleScope(level="global"))

alfred/domain/subtitles/entities.py

@@ -1,96 +1,87 @@
 """Subtitle domain entities."""
 
-from dataclasses import dataclass
+from dataclasses import dataclass, field
+from pathlib import Path
 
-from ..shared.value_objects import FilePath, ImdbId
-from .value_objects import Language, SubtitleFormat, TimingOffset
+from ..shared.value_objects import ImdbId
+from .value_objects import SubtitleFormat, SubtitleLanguage, SubtitleMatchingRules, SubtitleType
 
 
 @dataclass
-class Subtitle:
+class SubtitleTrack:
     """
-    Subtitle entity representing a subtitle file.
+    A single subtitle track — either an external file or an embedded stream.
 
-    Can be associated with either a movie or a TV show episode.
+    State can evolve: unknown → resolved after user clarification.
+    confidence reflects how certain we are about language + type classification.
     """
 
-    media_imdb_id: ImdbId
-    language: Language
-    format: SubtitleFormat
-    file_path: FilePath
+    # Classification (may be None if not yet resolved)
+    language: SubtitleLanguage | None
+    format: SubtitleFormat | None
+    subtitle_type: SubtitleType = SubtitleType.UNKNOWN
 
-    # Optional: for TV shows
-    season_number: int | None = None
-    episode_number: int | None = None
+    # Source
+    is_embedded: bool = False
+    file_path: Path | None = None       # None if embedded
+    file_size_kb: float | None = None
+    entry_count: int | None = None      # number of subtitle cues in the file
 
-    # Subtitle metadata
-    timing_offset: TimingOffset = TimingOffset(0)
-    hearing_impaired: bool = False
-    forced: bool = False  # Forced subtitles (for foreign language parts)
+    # Matching state
+    confidence: float = 0.0             # 0.0 → 1.0, not applicable for embedded
+    raw_tokens: list[str] = field(default_factory=list)   # tokens extracted from filename
 
-    # Source information
-    source: str | None = None  # e.g., "OpenSubtitles", "Subscene"
-    uploader: str | None = None
-    download_count: int | None = None
-    rating: float | None = None
+    def is_resolved(self) -> bool:
+        return self.language is not None
 
-    def __post_init__(self):
-        """Validate subtitle entity."""
-        # Ensure ImdbId is actually an ImdbId instance
-        if not isinstance(self.media_imdb_id, ImdbId):
-            if isinstance(self.media_imdb_id, str):
-                object.__setattr__(self, "media_imdb_id", ImdbId(self.media_imdb_id))
-
-        # Ensure Language is actually a Language instance
-        if not isinstance(self.language, Language):
-            if isinstance(self.language, str):
-                object.__setattr__(self, "language", Language.from_code(self.language))
-
-        # Ensure SubtitleFormat is actually a SubtitleFormat instance
-        if not isinstance(self.format, SubtitleFormat):
-            if isinstance(self.format, str):
-                object.__setattr__(
-                    self, "format", SubtitleFormat.from_extension(self.format)
-                )
-
-        # Ensure FilePath is actually a FilePath instance
-        if not isinstance(self.file_path, FilePath):
-            object.__setattr__(self, "file_path", FilePath(self.file_path))
-
-    def is_for_movie(self) -> bool:
-        """Check if this subtitle is for a movie."""
-        return self.season_number is None and self.episode_number is None
-
-    def is_for_episode(self) -> bool:
-        """Check if this subtitle is for a TV show episode."""
-        return self.season_number is not None and self.episode_number is not None
-
-    def get_filename(self) -> str:
+    @property
+    def destination_name(self) -> str:
         """
-        Get the suggested filename for this subtitle.
-
-        Format for movies: "Movie.Title.{lang}.{format}"
-        Format for episodes: "S01E05.{lang}.{format}"
+        Compute the output filename per naming convention:
+            {lang}.{ext}
+            {lang}.sdh.{ext}
+            {lang}.forced.{ext}
         """
-        if self.is_for_episode():
-            base = f"S{self.season_number:02d}E{self.episode_number:02d}"
-        else:
-            # For movies, use the file path stem
-            base = self.file_path.value.stem
-
-        parts = [base, self.language.value]
-
-        if self.hearing_impaired:
-            parts.append("hi")
-        if self.forced:
+        if not self.language or not self.format:
+            raise ValueError("Cannot compute destination_name: language or format missing")
+        ext = self.format.extensions[0].lstrip(".")
+        parts = [self.language.code]
+        if self.subtitle_type == SubtitleType.SDH:
+            parts.append("sdh")
+        elif self.subtitle_type == SubtitleType.FORCED:
             parts.append("forced")
-
-        return f"{'.'.join(parts)}.{self.format.value}"
-
-    def __str__(self) -> str:
-        if self.is_for_episode():
-            return f"Subtitle S{self.season_number:02d}E{self.episode_number:02d} ({self.language.value})"
-        return f"Subtitle ({self.language.value})"
+        return ".".join(parts) + "." + ext
 
     def __repr__(self) -> str:
-        return f"Subtitle(media={self.media_imdb_id}, lang={self.language.value})"
+        lang = self.language.code if self.language else "?"
+        fmt = self.format.id if self.format else "?"
+        src = "embedded" if self.is_embedded else str(self.file_path.name if self.file_path else "?")
+        return f"SubtitleTrack({lang}, {self.subtitle_type.value}, {fmt}, src={src}, conf={self.confidence:.2f})"
+
+
+@dataclass
+class MediaSubtitleMetadata:
+    """
+    Snapshot of all subtitle information known for a given media item.
+    Populated by the identifier service (ffprobe + filesystem scan).
+    """
+
+    media_id: ImdbId | None
+    media_type: str                         # "movie" | "tv_show"
+    embedded_tracks: list[SubtitleTrack] = field(default_factory=list)
+    external_tracks: list[SubtitleTrack] = field(default_factory=list)
+    release_group: str | None = None
+    detected_pattern_id: str | None = None  # pattern id from knowledge base
+    pattern_confirmed: bool = False
+
+    @property
+    def all_tracks(self) -> list[SubtitleTrack]:
+        return self.embedded_tracks + self.external_tracks
+
+    @property
+    def total_count(self) -> int:
+        return len(self.embedded_tracks) + len(self.external_tracks)
+
+    @property
+    def unresolved_tracks(self) -> list[SubtitleTrack]:
+        return [t for t in self.external_tracks if t.language is None]

alfred/domain/subtitles/knowledge/__init__.py

@@ -0,0 +1,4 @@
+from .base import SubtitleKnowledgeBase
+from .loader import KnowledgeLoader
+
+__all__ = ["SubtitleKnowledgeBase", "KnowledgeLoader"]

alfred/domain/subtitles/knowledge/base.py

@@ -0,0 +1,151 @@
+"""SubtitleKnowledgeBase — parsed, typed view of the loaded knowledge."""
+
+import logging
+from functools import cached_property
+
+from ..value_objects import (
+    ScanStrategy,
+    SubtitleFormat,
+    SubtitleLanguage,
+    SubtitleMatchingRules,
+    SubtitlePattern,
+    SubtitleType,
+    TypeDetectionMethod,
+)
+from .loader import KnowledgeLoader
+
+logger = logging.getLogger(__name__)
+
+
+class SubtitleKnowledgeBase:
+    """
+    Typed access to subtitle knowledge (formats, types, languages, patterns).
+
+    Built from KnowledgeLoader — call kb.reload() to pick up newly learned entries
+    without restarting.
+    """
+
+    def __init__(self, loader: KnowledgeLoader | None = None):
+        self._loader = loader or KnowledgeLoader()
+        self._build()
+
+    def _build(self) -> None:
+        data = self._loader.subtitles()
+
+        self._formats: dict[str, SubtitleFormat] = {}
+        for fid, fdata in data.get("formats", {}).items():
+            self._formats[fid] = SubtitleFormat(
+                id=fid,
+                extensions=fdata.get("extensions", []),
+                description=fdata.get("description", ""),
+            )
+
+        self._languages: dict[str, SubtitleLanguage] = {}
+        for code, ldata in data.get("languages", {}).items():
+            self._languages[code] = SubtitleLanguage(
+                code=code,
+                tokens=ldata.get("tokens", []),
+            )
+
+        # Build reverse token → language code map
+        self._lang_token_map: dict[str, str] = {}
+        for code, lang in self._languages.items():
+            for token in lang.tokens:
+                self._lang_token_map[token.lower()] = code
+
+        # Build reverse token → type map
+        self._type_token_map: dict[str, SubtitleType] = {}
+        for type_id, tdata in data.get("types", {}).items():
+            stype = SubtitleType(type_id)
+            for token in tdata.get("tokens", []):
+                self._type_token_map[token.lower()] = stype
+
+        d = data.get("defaults", {})
+        self._default_rules = SubtitleMatchingRules(
+            preferred_languages=d.get("languages", ["fra", "eng"]),
+            preferred_formats=d.get("formats", ["srt"]),
+            allowed_types=d.get("types", ["standard", "forced"]),
+            format_priority=d.get("format_priority", ["srt", "ass"]),
+            min_confidence=d.get("min_confidence", 0.7),
+        )
+
+        self._patterns: dict[str, SubtitlePattern] = {}
+        for pid, pdata in self._loader.patterns().items():
+            try:
+                self._patterns[pid] = SubtitlePattern(
+                    id=pid,
+                    description=pdata.get("description", ""),
+                    scan_strategy=ScanStrategy(pdata.get("scan_strategy", "adjacent")),
+                    root_folder=pdata.get("root_folder"),
+                    type_detection=TypeDetectionMethod(
+                        pdata.get("type_detection", {}).get("method", "token_in_name")
+                    ),
+                    version=pdata.get("version", "1.0"),
+                )
+            except ValueError as e:
+                logger.warning(f"SubtitleKnowledgeBase: skipping pattern '{pid}': {e}")
+
+    def reload(self) -> None:
+        self._loader = KnowledgeLoader()
+        self._build()
+        logger.info("SubtitleKnowledgeBase: reloaded")
+
+    # --- Defaults ---
+
+    def default_rules(self) -> SubtitleMatchingRules:
+        return self._default_rules
+
+    # --- Formats ---
+
+    def formats(self) -> dict[str, SubtitleFormat]:
+        return self._formats
+
+    def format_for_extension(self, ext: str) -> SubtitleFormat | None:
+        for fmt in self._formats.values():
+            if fmt.matches_extension(ext):
+                return fmt
+        return None
+
+    def known_extensions(self) -> set[str]:
+        exts = set()
+        for fmt in self._formats.values():
+            exts.update(fmt.extensions)
+        return exts
+
+    # --- Languages ---
+
+    def languages(self) -> dict[str, SubtitleLanguage]:
+        return self._languages
+
+    def language_for_token(self, token: str) -> SubtitleLanguage | None:
+        code = self._lang_token_map.get(token.lower())
+        return self._languages.get(code) if code else None
+
+    def is_known_lang_token(self, token: str) -> bool:
+        return token.lower() in self._lang_token_map
+
+    # --- Types ---
+
+    def type_for_token(self, token: str) -> SubtitleType | None:
+        return self._type_token_map.get(token.lower())
+
+    def is_known_type_token(self, token: str) -> bool:
+        return token.lower() in self._type_token_map
+
+    # --- Patterns ---
+
+    def patterns(self) -> dict[str, SubtitlePattern]:
+        return self._patterns
+
+    def pattern(self, pattern_id: str) -> SubtitlePattern | None:
+        return self._patterns.get(pattern_id)
+
+    def patterns_for_group(self, group_name: str) -> list[SubtitlePattern]:
+        group = self._loader.release_group(group_name)
+        if not group:
+            return []
+        return [
+            self._patterns[pid]
+            for pid in group.get("known_patterns", [])
+            if pid in self._patterns
+        ]

alfred/domain/subtitles/knowledge/loader.py

@@ -0,0 +1,131 @@
+"""KnowledgeLoader — autodiscovers and merges builtin + learned YAML knowledge packs."""
+
+import logging
+from pathlib import Path
+
+import yaml
+
+logger = logging.getLogger(__name__)
+
+import alfred as _alfred_pkg
+
+# Builtin knowledge — anchored on the alfred package itself, not on this file's depth
+_BUILTIN_ROOT = Path(_alfred_pkg.__file__).parent / "knowledge"
+
+# Learned knowledge — local to this instance, gitignored
+_LEARNED_ROOT = Path(_alfred_pkg.__file__).parent.parent / "data" / "knowledge"
+
+
+def _load_yaml(path: Path) -> dict:
+    try:
+        with open(path, encoding="utf-8") as f:
+            return yaml.safe_load(f) or {}
+    except FileNotFoundError:
+        return {}
+    except Exception as e:
+        logger.warning(f"KnowledgeLoader: could not load {path}: {e}")
+        return {}
+
+
+def _merge(base: dict, override: dict) -> dict:
+    """
+    Deep merge override into base.
+    Lists are extended (not replaced) — learned tokens are additive.
+    Scalar values in override win over base.
+    """
+    result = dict(base)
+    for key, val in override.items():
+        if key in result and isinstance(result[key], dict) and isinstance(val, dict):
+            result[key] = _merge(result[key], val)
+        elif key in result and isinstance(result[key], list) and isinstance(val, list):
+            # Extend list, deduplicate, preserve order
+            combined = result[key] + [v for v in val if v not in result[key]]
+            result[key] = combined
+        else:
+            result[key] = val
+    return result
+
+
+class KnowledgeLoader:
+    """
+    Loads subtitle knowledge from YAML files.
+
+    Builtin packs live in alfred/knowledge/ (versioned).
+    Learned packs live in data/knowledge/ (gitignored, instance-local).
+
+    Learned entries are merged additively — they can only add tokens/patterns,
+    never remove builtin ones.
+
+    Usage:
+        loader = KnowledgeLoader()
+        subtitles = loader.subtitles()   # merged subtitles.yaml
+        patterns = loader.patterns()     # all patterns, keyed by id
+        groups = loader.release_groups() # all release groups, keyed by name
+    """
+
+    def __init__(self):
+        self._cache: dict[str, dict] = {}
+        self._load()
+
+    def _load(self) -> None:
+        # Main subtitles knowledge
+        builtin = _load_yaml(_BUILTIN_ROOT / "subtitles.yaml")
+        learned = _load_yaml(_LEARNED_ROOT / "subtitles_learned.yaml")
+        self._cache["subtitles"] = _merge(builtin, learned)
+
+        # Patterns
+        self._cache["patterns"] = {}
+        for path in sorted((_BUILTIN_ROOT / "patterns").glob("*.yaml")):
+            data = _load_yaml(path)
+            pid = data.get("id", path.stem)
+            self._cache["patterns"][pid] = data
+
+        for path in sorted((_LEARNED_ROOT / "patterns").glob("*.yaml")):
+            data = _load_yaml(path)
+            pid = data.get("id", path.stem)
+            if pid in self._cache["patterns"]:
+                self._cache["patterns"][pid] = _merge(self._cache["patterns"][pid], data)
+            else:
+                self._cache["patterns"][pid] = data
+                logger.info(f"KnowledgeLoader: learned new pattern '{pid}'")
+
+        # Release groups
+        self._cache["release_groups"] = {}
+        for path in sorted((_BUILTIN_ROOT / "release_groups").glob("*.yaml")):
+            data = _load_yaml(path)
+            name = data.get("name", path.stem)
+            self._cache["release_groups"][name] = data
+
+        for path in sorted((_LEARNED_ROOT / "release_groups").glob("*.yaml")):
+            data = _load_yaml(path)
+            name = data.get("name", path.stem)
+            if name in self._cache["release_groups"]:
+                self._cache["release_groups"][name] = _merge(self._cache["release_groups"][name], data)
+            else:
+                self._cache["release_groups"][name] = data
+                logger.info(f"KnowledgeLoader: learned new release group '{name}'")
+
+        logger.info(
+            f"KnowledgeLoader: {len(self._cache['patterns'])} patterns, "
+            f"{len(self._cache['release_groups'])} release groups loaded"
+        )
+
+    def subtitles(self) -> dict:
+        return self._cache["subtitles"]
+
+    def patterns(self) -> dict[str, dict]:
+        return self._cache["patterns"]
+
+    def pattern(self, pattern_id: str) -> dict | None:
+        return self._cache["patterns"].get(pattern_id)
+
+    def release_groups(self) -> dict[str, dict]:
+        return self._cache["release_groups"]
+
+    def release_group(self, name: str) -> dict | None:
+        """Case-insensitive lookup."""
+        name_lower = name.lower()
+        for key, val in self._cache["release_groups"].items():
+            if key.lower() == name_lower:
+                return val
+        return None

alfred/domain/subtitles/scanner.py

@@ -0,0 +1,221 @@
+"""SubtitleScanner — inspects local subtitle files and filters them per user preferences.
+
+Given a video file path, the scanner:
+  1. Looks for subtitle files in the same directory as the video.
+  2. Optionally also inspects a Subs/ subfolder adjacent to the video.
+  3. Classifies each file (language, SDH, forced) from its filename.
+  4. Filters according to SubtitlePreferences (languages, min_size_kb, keep_sdh, keep_forced).
+  5. Returns a list of SubtitleCandidate — one per file that passes the filter,
+     with the destination filename already computed.
+
+Filename classification heuristics
+-----------------------------------
+We parse the stem of each subtitle file looking for known patterns:
+
+  fr.srt              → lang=fr, sdh=False, forced=False
+  fr.sdh.srt          → lang=fr, sdh=True
+  fr.hi.srt           → lang=fr, sdh=True  (hi = hearing-impaired, alias for sdh)
+  fr.forced.srt       → lang=fr, forced=True
+  Breaking.Bad.S01E01.French.srt  → lang=fr (keyword match)
+  Breaking.Bad.S01E01.VOSTFR.srt  → lang=fr (VOSTFR = French forced/foreign subs)
+
+Output naming convention (matches SubtitlePreferences docstring):
+  {lang}.srt
+  {lang}.sdh.srt
+  {lang}.forced.srt
+"""
+
+import logging
+from dataclasses import dataclass, field
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+# Subtitle file extensions we handle
+SUBTITLE_EXTENSIONS = {".srt", ".ass", ".ssa", ".vtt", ".sub"}
+
+# Language keyword map: lowercase token → ISO 639-1 code
+_LANG_KEYWORDS: dict[str, str] = {
+    # French
+    "fr": "fr",
+    "fra": "fr",
+    "french": "fr",
+    "francais": "fr",
+    "français": "fr",
+    "vf": "fr",
+    "vff": "fr",
+    "vostfr": "fr",
+    # English
+    "en": "en",
+    "eng": "en",
+    "english": "en",
+    # Spanish
+    "es": "es",
+    "spa": "es",
+    "spanish": "es",
+    "espanol": "es",
+    # German
+    "de": "de",
+    "deu": "de",
+    "ger": "de",
+    "german": "de",
+    # Italian
+    "it": "it",
+    "ita": "it",
+    "italian": "it",
+    # Portuguese
+    "pt": "pt",
+    "por": "pt",
+    "portuguese": "pt",
+    # Dutch
+    "nl": "nl",
+    "nld": "nl",
+    "dutch": "nl",
+    # Japanese
+    "ja": "ja",
+    "jpn": "ja",
+    "japanese": "ja",
+}
+
+# Tokens that indicate SDH / hearing-impaired
+_SDH_TOKENS = {"sdh", "hi", "hearing", "impaired", "cc", "closedcaption"}
+
+# Tokens that indicate forced subtitles
+_FORCED_TOKENS = {"forced", "foreign"}
+
+
+@dataclass
+class SubtitleCandidate:
+    """A subtitle file that passed the filter, ready to be placed."""
+
+    source_path: Path
+    language: str          # ISO 639-1 code, e.g. "fr"
+    is_sdh: bool
+    is_forced: bool
+    extension: str         # e.g. ".srt"
+
+    @property
+    def destination_name(self) -> str:
+        """
+        Compute the destination filename per naming convention:
+            {lang}.srt
+            {lang}.sdh.srt
+            {lang}.forced.srt
+        """
+        ext = self.extension.lstrip(".")
+        parts = [self.language]
+        if self.is_sdh:
+            parts.append("sdh")
+        elif self.is_forced:
+            parts.append("forced")
+        return ".".join(parts) + "." + ext
+
+
+def _classify(path: Path) -> tuple[str | None, bool, bool]:
+    """
+    Parse a subtitle filename and return (language_code, is_sdh, is_forced).
+
+    Returns (None, False, False) if the language cannot be determined.
+    """
+    stem = path.stem.lower()
+    # Split on dots, spaces, underscores, hyphens
+    import re
+    tokens = re.split(r"[\.\s_\-]+", stem)
+
+    language: str | None = None
+    is_sdh = False
+    is_forced = False
+
+    for token in tokens:
+        if token in _LANG_KEYWORDS:
+            language = _LANG_KEYWORDS[token]
+        if token in _SDH_TOKENS:
+            is_sdh = True
+        if token in _FORCED_TOKENS:
+            is_forced = True
+
+    return language, is_sdh, is_forced
+
+
+class SubtitleScanner:
+    """
+    Scans subtitle files next to a video and filters them per SubtitlePreferences.
+
+    Usage:
+        scanner = SubtitleScanner(prefs)
+        candidates = scanner.scan(video_path)
+        # Each candidate has .source_path and .destination_name
+    """
+
+    def __init__(self, languages: list[str], min_size_kb: int, keep_sdh: bool, keep_forced: bool):
+        self.languages = [l.lower() for l in languages]
+        self.min_size_kb = min_size_kb
+        self.keep_sdh = keep_sdh
+        self.keep_forced = keep_forced
+
+    def scan(self, video_path: Path) -> list[SubtitleCandidate]:
+        """
+        Return all subtitle candidates found next to the video that pass the filter.
+
+        Scans:
+          - Same directory as the video (flat siblings)
+          - Subs/ subfolder if present
+        """
+        candidates: list[SubtitleCandidate] = []
+        search_dirs = [video_path.parent]
+
+        subs_dir = video_path.parent / "Subs"
+        if subs_dir.is_dir():
+            search_dirs.append(subs_dir)
+            logger.debug(f"SubtitleScanner: found Subs/ folder at {subs_dir}")
+
+        for directory in search_dirs:
+            for path in sorted(directory.iterdir()):
+                if not path.is_file():
+                    continue
+                if path.suffix.lower() not in SUBTITLE_EXTENSIONS:
+                    continue
+
+                candidate = self._evaluate(path)
+                if candidate is not None:
+                    candidates.append(candidate)
+
+        logger.info(f"SubtitleScanner: {len(candidates)} candidate(s) found for {video_path.name}")
+        return candidates
+
+    def _evaluate(self, path: Path) -> SubtitleCandidate | None:
+        """Apply all filters to a single subtitle file. Returns None if it should be dropped."""
+        # Size filter
+        size_kb = path.stat().st_size / 1024
+        if size_kb < self.min_size_kb:
+            logger.debug(f"SubtitleScanner: skip {path.name} (too small: {size_kb:.1f} KB)")
+            return None
+
+        language, is_sdh, is_forced = _classify(path)
+
+        # Language filter
+        if language is None:
+            logger.debug(f"SubtitleScanner: skip {path.name} (language unknown)")
+            return None
+
+        if language not in self.languages:
+            logger.debug(f"SubtitleScanner: skip {path.name} (language '{language}' not in prefs)")
+            return None
+
+        # SDH filter
+        if is_sdh and not self.keep_sdh:
+            logger.debug(f"SubtitleScanner: skip {path.name} (SDH not wanted)")
+            return None
+
+        # Forced filter
+        if is_forced and not self.keep_forced:
+            logger.debug(f"SubtitleScanner: skip {path.name} (forced not wanted)")
+            return None
+
+        return SubtitleCandidate(
+            source_path=path,
+            language=language,
+            is_sdh=is_sdh,
+            is_forced=is_forced,
+            extension=path.suffix.lower(),
+        )

alfred/domain/subtitles/services/__init__.py

@@ -0,0 +1,13 @@
+from .identifier import SubtitleIdentifier
+from .matcher import SubtitleMatcher
+from .pattern_detector import PatternDetector
+from .placer import PlacedTrack, PlaceResult, SubtitlePlacer
+
+__all__ = [
+    "SubtitleIdentifier",
+    "SubtitleMatcher",
+    "PatternDetector",
+    "SubtitlePlacer",
+    "PlacedTrack",
+    "PlaceResult",
+]

alfred/domain/subtitles/services/identifier.py

@@ -0,0 +1,287 @@
+"""SubtitleIdentifier — finds and classifies all subtitle tracks for a video file."""
+
+import logging
+import re
+import subprocess
+import json
+from pathlib import Path
+
+from ...shared.value_objects import ImdbId
+from ..entities import MediaSubtitleMetadata, SubtitleTrack
+from ..knowledge.base import SubtitleKnowledgeBase
+from ..value_objects import ScanStrategy, SubtitlePattern, SubtitleType
+
+logger = logging.getLogger(__name__)
+
+
+def _tokenize(name: str) -> list[str]:
+    """Split a filename stem into lowercase tokens."""
+    return [t.lower() for t in re.split(r"[\.\s_\-]+", name) if t]
+
+
+def _count_entries(path: Path) -> int:
+    """Return the entry count of an SRT file by finding the last cue number."""
+    try:
+        with open(path, encoding="utf-8", errors="replace") as f:
+            lines = f.read().splitlines()
+        for line in reversed(lines):
+            if line.strip().isdigit():
+                return int(line.strip())
+        return 0
+    except Exception:
+        return 0
+
+
+class SubtitleIdentifier:
+    """
+    Finds all subtitle tracks for a given video file using a known pattern,
+    then attempts to classify each track (language, type, format).
+
+    Returns a MediaSubtitleMetadata with embedded + external tracks.
+    External tracks with unknown language or low confidence are left as-is —
+    the caller (use case) decides whether to ask the user for clarification.
+    """
+
+    def __init__(self, kb: SubtitleKnowledgeBase):
+        self.kb = kb
+
+    def identify(
+        self,
+        video_path: Path,
+        pattern: SubtitlePattern,
+        media_id: ImdbId | None,
+        media_type: str,
+        release_group: str | None = None,
+    ) -> MediaSubtitleMetadata:
+        metadata = MediaSubtitleMetadata(
+            media_id=media_id,
+            media_type=media_type,
+            release_group=release_group,
+            detected_pattern_id=pattern.id,
+        )
+
+        if pattern.scan_strategy == ScanStrategy.EMBEDDED:
+            metadata.embedded_tracks = self._scan_embedded(video_path)
+        else:
+            metadata.external_tracks = self._scan_external(video_path, pattern)
+            # Always also check for embedded tracks
+            metadata.embedded_tracks = self._scan_embedded(video_path)
+
+        return metadata
+
+    # ------------------------------------------------------------------
+    # Embedded tracks — ffprobe
+    # ------------------------------------------------------------------
+
+    def _scan_embedded(self, video_path: Path) -> list[SubtitleTrack]:
+        if not video_path.exists():
+            return []
+        try:
+            result = subprocess.run(
+                [
+                    "ffprobe", "-v", "quiet",
+                    "-print_format", "json",
+                    "-show_streams",
+                    "-select_streams", "s",
+                    str(video_path),
+                ],
+                capture_output=True, text=True, timeout=30,
+            )
+            data = json.loads(result.stdout)
+        except (subprocess.TimeoutExpired, json.JSONDecodeError, FileNotFoundError) as e:
+            logger.debug(f"SubtitleIdentifier: ffprobe failed for {video_path.name}: {e}")
+            return []
+
+        tracks = []
+        for stream in data.get("streams", []):
+            tags = stream.get("tags", {})
+            disposition = stream.get("disposition", {})
+            lang_code = tags.get("language", "")
+            title = tags.get("title", "")
+
+            lang = self.kb.language_for_token(lang_code) if lang_code else None
+
+            if disposition.get("hearing_impaired"):
+                stype = SubtitleType.SDH
+            elif disposition.get("forced"):
+                stype = SubtitleType.FORCED
+            else:
+                stype = SubtitleType.STANDARD
+
+            tracks.append(SubtitleTrack(
+                language=lang,
+                format=None,
+                subtitle_type=stype,
+                is_embedded=True,
+                raw_tokens=[lang_code] if lang_code else [],
+            ))
+
+        logger.debug(f"SubtitleIdentifier: {len(tracks)} embedded track(s) in {video_path.name}")
+        return tracks
+
+    # ------------------------------------------------------------------
+    # External tracks — filesystem scan per pattern strategy
+    # ------------------------------------------------------------------
+
+    def _scan_external(self, video_path: Path, pattern: SubtitlePattern) -> list[SubtitleTrack]:
+        strategy = pattern.scan_strategy
+
+        if strategy == ScanStrategy.ADJACENT:
+            candidates = self._find_adjacent(video_path)
+        elif strategy == ScanStrategy.FLAT:
+            candidates = self._find_flat(video_path, pattern.root_folder or "Subs")
+        elif strategy == ScanStrategy.EPISODE_SUBFOLDER:
+            candidates = self._find_episode_subfolder(video_path, pattern.root_folder or "Subs")
+        else:
+            return []
+
+        return self._classify_files(candidates, pattern)
+
+    def _find_adjacent(self, video_path: Path) -> list[Path]:
+        return [
+            p for p in sorted(video_path.parent.iterdir())
+            if p.is_file() and p.suffix.lower() in self.kb.known_extensions()
+            and p.stem != video_path.stem
+        ]
+
+    def _find_flat(self, video_path: Path, root_folder: str) -> list[Path]:
+        subs_dir = video_path.parent / root_folder
+        if not subs_dir.is_dir():
+            # Also look at release root (one level up)
+            subs_dir = video_path.parent.parent / root_folder
+        if not subs_dir.is_dir():
+            return []
+        return [
+            p for p in sorted(subs_dir.iterdir())
+            if p.is_file() and p.suffix.lower() in self.kb.known_extensions()
+        ]
+
+    def _find_episode_subfolder(self, video_path: Path, root_folder: str) -> list[Path]:
+        """
+        Look for Subs/{episode_stem}/*.srt
+
+        Checks two locations:
+          1. Adjacent to the video: video_path.parent / root_folder / video_path.stem
+          2. Release root (one level up): video_path.parent.parent / root_folder / video_path.stem
+        """
+        episode_stem = video_path.stem
+        candidates_dirs = [
+            video_path.parent / root_folder / episode_stem,
+            video_path.parent.parent / root_folder / episode_stem,
+        ]
+        for subs_dir in candidates_dirs:
+            if subs_dir.is_dir():
+                files = [
+                    p for p in sorted(subs_dir.iterdir())
+                    if p.is_file() and p.suffix.lower() in self.kb.known_extensions()
+                ]
+                if files:
+                    logger.debug(f"SubtitleIdentifier: found {len(files)} file(s) in {subs_dir}")
+                    return files
+        return []
+
+    # ------------------------------------------------------------------
+    # Classification
+    # ------------------------------------------------------------------
+
+    def _classify_files(self, paths: list[Path], pattern: SubtitlePattern) -> list[SubtitleTrack]:
+        tracks = []
+        for path in paths:
+            track = self._classify_single(path)
+            tracks.append(track)
+
+        # Post-process: if multiple tracks share same language but type is ambiguous,
+        # apply size_and_count disambiguation
+        if pattern.type_detection.value == "size_and_count":
+            tracks = self._disambiguate_by_size(tracks)
+
+        return tracks
+
+    def _classify_single(self, path: Path) -> SubtitleTrack:
+        fmt = self.kb.format_for_extension(path.suffix)
+        tokens = _tokenize(path.stem)
+
+        language = None
+        subtitle_type = SubtitleType.UNKNOWN
+        unknown_tokens = []
+        matched_tokens = 0
+
+        for token in tokens:
+            if self.kb.is_known_lang_token(token):
+                language = self.kb.language_for_token(token)
+                matched_tokens += 1
+            elif self.kb.is_known_type_token(token):
+                subtitle_type = self.kb.type_for_token(token) or subtitle_type
+                matched_tokens += 1
+            elif token.isdigit():
+                pass  # numeric prefix — ignore
+            elif len(token) > 1:
+                unknown_tokens.append(token)
+
+        # Confidence: proportion of meaningful tokens that were recognized
+        meaningful = [t for t in tokens if not t.isdigit() and len(t) > 1]
+        confidence = matched_tokens / max(len(meaningful), 1) if meaningful else 0.5
+
+        if unknown_tokens:
+            logger.debug(
+                f"SubtitleIdentifier: unknown tokens in '{path.name}': {unknown_tokens}"
+            )
+
+        size_kb = path.stat().st_size / 1024 if path.exists() else None
+        entry_count = _count_entries(path) if path.exists() else None
+
+        return SubtitleTrack(
+            language=language,
+            format=fmt,
+            subtitle_type=subtitle_type,
+            is_embedded=False,
+            file_path=path,
+            file_size_kb=size_kb,
+            entry_count=entry_count,
+            confidence=confidence,
+            raw_tokens=tokens,
+        )
+
+    def _disambiguate_by_size(self, tracks: list[SubtitleTrack]) -> list[SubtitleTrack]:
+        """
+        When multiple tracks share the same language and type is UNKNOWN/STANDARD,
+        the one with the most entries (lines) is SDH, the smallest is FORCED if
+        there are 3+, otherwise the smaller is STANDARD.
+
+        Only applied when type_detection = size_and_count.
+        """
+        from itertools import groupby
+
+        # Group by language code
+        lang_groups: dict[str, list[SubtitleTrack]] = {}
+        for track in tracks:
+            key = track.language.code if track.language else "__unknown__"
+            lang_groups.setdefault(key, []).append(track)
+
+        result = []
+        for lang_code, group in lang_groups.items():
+            if len(group) == 1:
+                result.extend(group)
+                continue
+
+            # Sort by entry_count ascending (None treated as 0)
+            sorted_group = sorted(group, key=lambda t: t.entry_count or 0)
+
+            if len(sorted_group) == 2:
+                # smaller = standard, larger = sdh
+                self._set_type(sorted_group[0], SubtitleType.STANDARD)
+                self._set_type(sorted_group[1], SubtitleType.SDH)
+            elif len(sorted_group) >= 3:
+                # smallest = forced, middle = standard, largest = sdh
+                self._set_type(sorted_group[0], SubtitleType.FORCED)
+                for t in sorted_group[1:-1]:
+                    self._set_type(t, SubtitleType.STANDARD)
+                self._set_type(sorted_group[-1], SubtitleType.SDH)
+
+            result.extend(sorted_group)
+
+        return result
+
+    def _set_type(self, track: SubtitleTrack, stype: SubtitleType) -> None:
+        """Mutate track type in-place."""
+        track.subtitle_type = stype

alfred/domain/subtitles/services/matcher.py

@@ -0,0 +1,118 @@
+"""SubtitleMatcher — filters tracks against resolved rules."""
+
+import logging
+
+from ..entities import SubtitleTrack
+from ..value_objects import SubtitleMatchingRules, SubtitleType
+
+logger = logging.getLogger(__name__)
+
+
+class SubtitleMatcher:
+    """
+    Filters a list of SubtitleTrack against effective SubtitleMatchingRules.
+
+    Returns matched tracks (pass all filters, confidence >= min_confidence)
+    and unresolved tracks (need user clarification).
+
+    Conflict resolution: when two tracks share the same language + type,
+    format_priority decides which one to keep.
+    """
+
+    def match(
+        self,
+        tracks: list[SubtitleTrack],
+        rules: SubtitleMatchingRules,
+    ) -> tuple[list[SubtitleTrack], list[SubtitleTrack]]:
+        """
+        Returns (matched, unresolved).
+        """
+        matched: list[SubtitleTrack] = []
+        unresolved: list[SubtitleTrack] = []
+
+        for track in tracks:
+            if track.is_embedded:
+                continue
+
+            if track.language is None or track.confidence < rules.min_confidence:
+                unresolved.append(track)
+                continue
+
+            if not self._passes_filters(track, rules):
+                logger.debug(f"SubtitleMatcher: filtered out {track}")
+                continue
+
+            matched.append(track)
+
+        matched = self._resolve_conflicts(matched, rules)
+        logger.info(
+            f"SubtitleMatcher: {len(matched)} matched, {len(unresolved)} unresolved"
+        )
+        return matched, unresolved
+
+    def _passes_filters(self, track: SubtitleTrack, rules: SubtitleMatchingRules) -> bool:
+        # Language filter
+        if rules.preferred_languages:
+            if not track.language:
+                return False
+            if track.language.code not in rules.preferred_languages:
+                return False
+
+        # Format filter (only for external files)
+        if rules.preferred_formats and not track.is_embedded:
+            if not track.format:
+                return False
+            if track.format.id not in rules.preferred_formats:
+                return False
+
+        # Type filter
+        if rules.allowed_types:
+            if track.subtitle_type.value not in rules.allowed_types:
+                return False
+
+        return True
+
+    def _resolve_conflicts(
+        self,
+        tracks: list[SubtitleTrack],
+        rules: SubtitleMatchingRules,
+    ) -> list[SubtitleTrack]:
+        """
+        When multiple tracks have same language + type, keep only the best one
+        according to format_priority. If no format_priority applies, keep the first.
+        """
+        seen: dict[tuple, SubtitleTrack] = {}
+
+        for track in tracks:
+            lang = track.language.code if track.language else None
+            stype = track.subtitle_type.value
+            key = (lang, stype)
+
+            if key not in seen:
+                seen[key] = track
+            else:
+                existing = seen[key]
+                if self._prefer(track, existing, rules.format_priority):
+                    logger.debug(
+                        f"SubtitleMatcher: conflict {key} — "
+                        f"preferring {track.format.id if track.format else 'embedded'} "
+                        f"over {existing.format.id if existing.format else 'embedded'}"
+                    )
+                    seen[key] = track
+
+        return list(seen.values())
+
+    def _prefer(
+        self,
+        candidate: SubtitleTrack,
+        existing: SubtitleTrack,
+        format_priority: list[str],
+    ) -> bool:
+        """Return True if candidate is preferable to existing."""
+        if not format_priority:
+            return False
+        c_fmt = candidate.format.id if candidate.format else ""
+        e_fmt = existing.format.id if existing.format else ""
+        c_rank = format_priority.index(c_fmt) if c_fmt in format_priority else 999
+        e_rank = format_priority.index(e_fmt) if e_fmt in format_priority else 999
+        return c_rank < e_rank

alfred/domain/subtitles/services/pattern_detector.py

@@ -0,0 +1,205 @@
+"""PatternDetector — discovers the subtitle structure of a release folder."""
+
+import json
+import logging
+import subprocess
+from pathlib import Path
+
+from ..knowledge.base import SubtitleKnowledgeBase
+from ..value_objects import ScanStrategy, SubtitlePattern
+
+logger = logging.getLogger(__name__)
+
+
+class PatternDetector:
+    """
+    Inspects a release folder and returns the best matching known pattern,
+    plus a confidence score and a description of what was found.
+
+    Used for "pattern discovery" — when we don't yet know which pattern
+    a release follows. The result is proposed to the user for confirmation.
+    """
+
+    def __init__(self, kb: SubtitleKnowledgeBase):
+        self.kb = kb
+
+    def detect(self, release_root: Path, sample_video: Path) -> dict:
+        """
+        Analyse the release folder and return:
+        {
+            "detected": SubtitlePattern | None,
+            "confidence": float,
+            "description": str,         # human-readable description of what was found
+            "candidate_pattern_ids": list[str],
+        }
+        """
+        findings = self._inspect(release_root, sample_video)
+        best, confidence = self._match_pattern(findings)
+
+        return {
+            "detected": best,
+            "confidence": confidence,
+            "description": self._describe(findings),
+            "candidate_pattern_ids": [best.id] if best else [],
+            "raw_findings": findings,
+        }
+
+    def _has_embedded_subtitles(self, video_path: Path) -> bool:
+        """Run ffprobe to check whether the video has embedded subtitle streams."""
+        try:
+            result = subprocess.run(
+                [
+                    "ffprobe", "-v", "quiet",
+                    "-print_format", "json",
+                    "-show_streams",
+                    "-select_streams", "s",
+                    str(video_path),
+                ],
+                capture_output=True, text=True, timeout=30,
+            )
+            data = json.loads(result.stdout)
+            return len(data.get("streams", [])) > 0
+        except (subprocess.TimeoutExpired, json.JSONDecodeError, FileNotFoundError):
+            return False
+
+    def _inspect(self, release_root: Path, sample_video: Path) -> dict:
+        """Gather structural facts about the release."""
+        known_exts = self.kb.known_extensions()
+        findings: dict = {
+            "has_subs_folder": False,
+            "subs_strategy": None,       # "flat" | "episode_subfolder"
+            "subs_root": None,
+            "adjacent_subs": False,
+            "has_embedded": self._has_embedded_subtitles(sample_video),
+            "files_per_episode": 0,
+            "has_lang_tokens": False,
+            "has_numeric_prefix": False,
+        }
+
+        # Check for Subs/ folder — adjacent or at release root
+        for subs_candidate in [
+            sample_video.parent / "Subs",
+            release_root / "Subs",
+        ]:
+            if subs_candidate.is_dir():
+                findings["has_subs_folder"] = True
+                findings["subs_root"] = str(subs_candidate)
+
+                # Is it flat or episode_subfolder?
+                children = list(subs_candidate.iterdir())
+                sub_files = [c for c in children if c.is_file() and c.suffix.lower() in known_exts]
+                sub_dirs = [c for c in children if c.is_dir()]
+
+                if sub_dirs and not sub_files:
+                    findings["subs_strategy"] = "episode_subfolder"
+                    # Count files in a sample subfolder
+                    sample_sub = sub_dirs[0]
+                    sample_files = [f for f in sample_sub.iterdir()
+                                    if f.is_file() and f.suffix.lower() in known_exts]
+                    findings["files_per_episode"] = len(sample_files)
+                    # Check naming conventions
+                    for f in sample_files:
+                        stem = f.stem
+                        parts = stem.split("_")
+                        if parts[0].isdigit():
+                            findings["has_numeric_prefix"] = True
+                        if any(self.kb.is_known_lang_token(t.lower())
+                               for t in stem.replace("_", ".").split(".")):
+                            findings["has_lang_tokens"] = True
+                else:
+                    findings["subs_strategy"] = "flat"
+                    findings["files_per_episode"] = len(sub_files)
+                    for f in sub_files:
+                        if any(self.kb.is_known_lang_token(t.lower())
+                               for t in f.stem.replace("_", ".").split(".")):
+                            findings["has_lang_tokens"] = True
+                break
+
+        # Check adjacent subs (next to the video)
+        if not findings["has_subs_folder"]:
+            adjacent = [
+                p for p in sample_video.parent.iterdir()
+                if p.is_file() and p.suffix.lower() in known_exts
+            ]
+            if adjacent:
+                findings["adjacent_subs"] = True
+                findings["files_per_episode"] = len(adjacent)
+
+        return findings
+
+    def _match_pattern(self, findings: dict) -> tuple[SubtitlePattern | None, float]:
+        """Score all known patterns against the findings."""
+        scores: list[tuple[float, SubtitlePattern]] = []
+
+        for pattern in self.kb.patterns().values():
+            score = self._score(pattern, findings)
+            scores.append((score, pattern))
+
+        if not scores:
+            return None, 0.0
+
+        scores.sort(key=lambda x: x[0], reverse=True)
+        best_score, best_pattern = scores[0]
+
+        if best_score < 0.4:
+            return None, best_score
+
+        return best_pattern, best_score
+
+    def _score(self, pattern: SubtitlePattern, findings: dict) -> float:
+        """Return a 0.0–1.0 match score for this pattern against the findings."""
+        score = 0.0
+        total = 0.0
+
+        strategy = pattern.scan_strategy
+
+        if strategy == ScanStrategy.EMBEDDED:
+            total += 1
+            if findings.get("has_embedded"):
+                score += 1.0
+            if not findings.get("has_subs_folder") and not findings.get("adjacent_subs"):
+                score += 0.5
+                total += 0.5
+
+        elif strategy == ScanStrategy.EPISODE_SUBFOLDER:
+            total += 3
+            if findings.get("has_subs_folder"):
+                score += 1.0
+            if findings.get("subs_strategy") == "episode_subfolder":
+                score += 2.0
+
+        elif strategy == ScanStrategy.FLAT:
+            total += 2
+            if findings.get("has_subs_folder"):
+                score += 1.0
+            if findings.get("subs_strategy") == "flat":
+                score += 1.0
+
+        elif strategy == ScanStrategy.ADJACENT:
+            total += 2
+            if findings.get("adjacent_subs"):
+                score += 1.0
+            if not findings.get("has_subs_folder"):
+                score += 1.0
+
+        return score / total if total > 0 else 0.0
+
+    def _describe(self, findings: dict) -> str:
+        parts = []
+        if findings.get("has_subs_folder"):
+            strategy = findings.get("subs_strategy", "?")
+            n = findings.get("files_per_episode", 0)
+            parts.append(f"Subs/ folder found ({strategy}), ~{n} file(s) per episode")
+            if findings.get("has_numeric_prefix"):
+                parts.append("files have numeric prefix (e.g. 2_English.srt)")
+            if findings.get("has_lang_tokens"):
+                parts.append("language tokens found in filenames")
+        elif findings.get("adjacent_subs"):
+            parts.append("subtitle files adjacent to video")
+        else:
+            parts.append("no external subtitle files found")
+
+        if findings.get("has_embedded"):
+            parts.append("embedded tracks detected (ffprobe)")
+
+        return " — ".join(parts) if parts else "nothing found"

alfred/domain/subtitles/services/placer.py

@@ -0,0 +1,93 @@
+"""SubtitlePlacer — hard-links matched subtitle tracks next to the destination video."""
+
+import logging
+import os
+from dataclasses import dataclass
+from pathlib import Path
+
+from ..entities import SubtitleTrack
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class PlacedTrack:
+    source: Path
+    destination: Path
+    filename: str
+
+
+@dataclass
+class PlaceResult:
+    placed: list[PlacedTrack]
+    skipped: list[tuple[SubtitleTrack, str]]   # (track, reason)
+
+    @property
+    def placed_count(self) -> int:
+        return len(self.placed)
+
+    @property
+    def skipped_count(self) -> int:
+        return len(self.skipped)
+
+
+class SubtitlePlacer:
+    """
+    Hard-links matched SubtitleTrack files next to a destination video.
+
+    Uses the same hard-link strategy as FileManager.copy_file:
+    instant, no data duplication, qBittorrent keeps seeding.
+
+    Embedded tracks are skipped — nothing to place on disk.
+    """
+
+    def place(
+        self,
+        tracks: list[SubtitleTrack],
+        destination_video: Path,
+    ) -> PlaceResult:
+        placed: list[PlacedTrack] = []
+        skipped: list[tuple[SubtitleTrack, str]] = []
+
+        dest_dir = destination_video.parent
+
+        for track in tracks:
+            if track.is_embedded:
+                logger.debug(f"SubtitlePlacer: skip embedded track ({track.language})")
+                skipped.append((track, "embedded — no file to place"))
+                continue
+
+            if not track.file_path or not track.file_path.exists():
+                skipped.append((track, "source file not found"))
+                continue
+
+            try:
+                dest_name = track.destination_name
+            except ValueError as e:
+                skipped.append((track, str(e)))
+                continue
+
+            dest_path = dest_dir / dest_name
+
+            if dest_path.exists():
+                logger.debug(f"SubtitlePlacer: skip {dest_name} — already exists")
+                skipped.append((track, "destination already exists"))
+                continue
+
+            try:
+                os.link(track.file_path, dest_path)
+                placed.append(PlacedTrack(
+                    source=track.file_path,
+                    destination=dest_path,
+                    filename=dest_name,
+                ))
+                logger.info(f"SubtitlePlacer: placed {dest_name}")
+            except OSError as e:
+                logger.warning(f"SubtitlePlacer: failed to place {dest_name}: {e}")
+                skipped.append((track, str(e)))
+
+        logger.info(
+            f"SubtitlePlacer: {len(placed)} placed, {len(skipped)} skipped "
+            f"for {destination_video.name}"
+        )
+        return PlaceResult(placed=placed, skipped=skipped)

alfred/domain/subtitles/services/utils.py

@@ -0,0 +1,21 @@
+"""Subtitle service utilities."""
+
+from ..entities import SubtitleTrack
+
+
+def available_subtitles(tracks: list[SubtitleTrack]) -> list[SubtitleTrack]:
+    """
+    Return the distinct subtitle tracks available, deduped by (language, type).
+
+    Useful to display what is available for a media item regardless of user
+    preferences — e.g. eng, eng.sdh, fra all show up as separate entries.
+    """
+    seen: set[tuple] = set()
+    result: list[SubtitleTrack] = []
+    for track in tracks:
+        lang = track.language.code if track.language else None
+        key = (lang, track.subtitle_type)
+        if key not in seen:
+            seen.add(key)
+            result.append(track)
+    return result

alfred/domain/subtitles/value_objects.py

@@ -1,91 +1,93 @@
 """Subtitle domain value objects."""
 
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from enum import Enum
-
-from ..shared.exceptions import ValidationError
+from pathlib import Path
+from typing import Any
 
 
-class Language(Enum):
-    """Supported subtitle languages."""
+class ScanStrategy(Enum):
+    """How to locate subtitle files for a given release."""
 
-    ENGLISH = "en"
-    FRENCH = "fr"
-
-    @classmethod
-    def from_code(cls, code: str) -> "Language":
-        """
-        Get language from ISO 639-1 code.
-
-        Args:
-            code: Two-letter language code
-
-        Returns:
-            Language enum value
-
-        Raises:
-            ValidationError: If code is not supported
-        """
-        code_lower = code.lower()
-        for lang in cls:
-            if lang.value == code_lower:
-                return lang
-        raise ValidationError(f"Unsupported language code: {code}")
+    ADJACENT = "adjacent"             # .srt next to the video
+    FLAT = "flat"                     # Subs/*.srt
+    EPISODE_SUBFOLDER = "episode_subfolder"  # Subs/{episode_name}/*.srt
+    EMBEDDED = "embedded"             # tracks inside the video container
 
 
-class SubtitleFormat(Enum):
-    """Supported subtitle formats."""
+class TypeDetectionMethod(Enum):
+    """How to differentiate standard / SDH / forced when tokens are ambiguous."""
 
-    SRT = "srt"  # SubRip
-    ASS = "ass"  # Advanced SubStation Alpha
-    SSA = "ssa"  # SubStation Alpha
-    VTT = "vtt"  # WebVTT
-    SUB = "sub"  # MicroDVD
+    TOKEN_IN_NAME = "token_in_name"
+    SIZE_AND_COUNT = "size_and_count"
+    FFPROBE_METADATA = "ffprobe_metadata"
 
-    @classmethod
-    def from_extension(cls, extension: str) -> "SubtitleFormat":
-        """
-        Get format from file extension.
 
-        Args:
-            extension: File extension (with or without dot)
-
-        Returns:
-            SubtitleFormat enum value
-
-        Raises:
-            ValidationError: If extension is not supported
-        """
-        ext = extension.lower().lstrip(".")
-        for fmt in cls:
-            if fmt.value == ext:
-                return fmt
-        raise ValidationError(f"Unsupported subtitle format: {extension}")
+class SubtitleType(Enum):
+    STANDARD = "standard"
+    SDH = "sdh"
+    FORCED = "forced"
+    UNKNOWN = "unknown"
 
 
 @dataclass(frozen=True)
-class TimingOffset:
-    """
-    Value object representing subtitle timing offset in milliseconds.
+class SubtitleFormat:
+    """A known subtitle file format."""
 
-    Used for synchronizing subtitles with video.
+    id: str
+    extensions: list[str]
+    description: str = ""
+
+    def matches_extension(self, ext: str) -> bool:
+        return ext.lower() in [e.lower() for e in self.extensions]
+
+
+@dataclass(frozen=True)
+class SubtitleLanguage:
+    """A known subtitle language with its recognition tokens."""
+
+    code: str          # ISO 639-1
+    tokens: list[str]  # lowercase
+
+    def matches_token(self, token: str) -> bool:
+        return token.lower() in self.tokens
+
+
+@dataclass(frozen=True)
+class SubtitlePattern:
+    """
+    A known structural pattern for how a release group organises subtitle files.
+
+    Patterns are loaded from alfred/knowledge/patterns/*.yaml and are
+    independent of any specific release group — multiple groups can share
+    the same pattern.
     """
 
-    milliseconds: int
+    id: str
+    description: str
+    scan_strategy: ScanStrategy
+    root_folder: str | None          # e.g. "Subs", None for adjacent/embedded
+    type_detection: TypeDetectionMethod
+    version: str = "1.0"
 
-    def __post_init__(self):
-        """Validate timing offset."""
-        if not isinstance(self.milliseconds, int):
-            raise ValidationError(
-                f"Timing offset must be an integer, got {type(self.milliseconds)}"
-            )
 
-    def to_seconds(self) -> float:
-        """Convert to seconds."""
-        return self.milliseconds / 1000.0
+@dataclass(frozen=True)
+class SubtitleMatchingRules:
+    """
+    Effective rules after scope resolution (global → group → show → season → episode).
+    Only stores actual values — None means "inherited, not overridden at this level".
+    """
 
-    def __str__(self) -> str:
-        return f"{self.milliseconds}ms"
+    preferred_languages: list[str] = field(default_factory=list)   # ISO 639-1 codes
+    preferred_formats: list[str] = field(default_factory=list)     # format ids
+    allowed_types: list[str] = field(default_factory=list)         # SubtitleType ids
+    format_priority: list[str] = field(default_factory=list)       # ordered format ids
+    min_confidence: float = 0.7
 
-    def __repr__(self) -> str:
-        return f"TimingOffset({self.milliseconds})"
+
+@dataclass(frozen=True)
+class RuleScope:
+    """At which level a rule set applies."""
+
+    level: str   # "global" | "release_group" | "movie" | "show" | "season" | "episode"
+    identifier: str | None = None   # imdb_id, group name, "S01", "S01E03"…

alfred/domain/tv_shows/entities.py

@@ -2,7 +2,6 @@
 
 import re
 from dataclasses import dataclass, field
-from datetime import datetime
 
 from ..shared.value_objects import FilePath, FileSize, ImdbId
 from .value_objects import EpisodeNumber, SeasonNumber, ShowStatus
@@ -22,8 +21,6 @@ class TVShow:
     seasons_count: int
     status: ShowStatus
     tmdb_id: int | None = None
-    first_air_date: str | None = None
-    added_at: datetime = field(default_factory=datetime.now)
 
     def __post_init__(self):
         """Validate TV show entity."""
@@ -87,9 +84,6 @@ class Season:
     season_number: SeasonNumber
     episode_count: int
     name: str | None = None
-    overview: str | None = None
-    air_date: str | None = None
-    poster_path: str | None = None
 
     def __post_init__(self):
         """Validate season entity."""
@@ -146,11 +140,6 @@ class Episode:
     title: str
     file_path: FilePath | None = None
     file_size: FileSize | None = None
-    overview: str | None = None
-    air_date: str | None = None
-    still_path: str | None = None
-    vote_average: float | None = None
-    runtime: int | None = None  # in minutes
 
     def __post_init__(self):
         """Validate episode entity."""

alfred/infrastructure/filesystem/file_manager.py

@@ -2,8 +2,7 @@
 
 import logging
 import os
-import shutil
-from enum import Enum
+from collections import namedtuple
 from pathlib import Path
 from typing import Any
 
@@ -13,14 +12,11 @@ from .exceptions import PathTraversalError
 
 logger = logging.getLogger(__name__)
 
+FileOperationResult = namedtuple("FileOperationResult", ["success", "error", "message"])
 
-class FolderName(Enum):
-    """Types of folders that can be managed."""
 
-    DOWNLOAD = "download"
-    TVSHOW = "tvshow"
-    MOVIE = "movie"
-    TORRENT = "torrent"
+def _err(error: str, message: str) -> dict[str, Any]:
+    return {"status": "error", "error": error, "message": message}
 
 
 class FileManager:
@@ -35,8 +31,6 @@ class FileManager:
         """
         Set a folder path in the configuration.
 
-        Validates that the path exists, is a directory, and is readable.
-
         Args:
             folder_name: Name of folder (download, tvshow, movie, torrent).
             path_value: Absolute path to the folder.
@@ -45,53 +39,39 @@ class FileManager:
             Dict with status or error information.
         """
         try:
-            self._validate_folder_name(folder_name)
             path_obj = Path(path_value).resolve()
 
             if not path_obj.exists():
-                logger.warning(f"Path does not exist: {path_value}")
-                return {
-                    "error": "invalid_path",
-                    "message": f"Path does not exist: {path_value}",
-                }
+                return _err("invalid_path", f"Path does not exist: {path_value}")
 
             if not path_obj.is_dir():
-                logger.warning(f"Path is not a directory: {path_value}")
-                return {
-                    "error": "invalid_path",
-                    "message": f"Path is not a directory: {path_value}",
-                }
+                return _err("invalid_path", f"Path is not a directory: {path_value}")
 
             if not os.access(path_obj, os.R_OK):
-                logger.warning(f"Path is not readable: {path_value}")
-                return {
-                    "error": "permission_denied",
-                    "message": f"Path is not readable: {path_value}",
-                }
+                return _err("permission_denied", f"Path is not readable: {path_value}")
 
             memory = get_memory()
-            memory.ltm.set_config(f"{folder_name}_folder", str(path_obj))
+            # workspace folders have fixed attributes; library folders go in the dict
+            if folder_name in ("download", "torrent"):
+                setattr(memory.ltm.workspace, folder_name, str(path_obj))
+            else:
+                memory.ltm.library_paths.set(folder_name, str(path_obj))
             memory.save()
 
-            logger.info(f"Set {folder_name}_folder to: {path_obj}")
+            logger.info(f"Set {folder_name} to: {path_obj}")
             return {"status": "ok", "folder_name": folder_name, "path": str(path_obj)}
 
         except ValueError as e:
-            logger.error(f"Validation error: {e}")
-            return {"error": "validation_failed", "message": str(e)}
+            return _err("validation_failed", str(e))
 
         except Exception as e:
             logger.error(f"Unexpected error setting path: {e}", exc_info=True)
-            return {"error": "internal_error", "message": "Failed to set path"}
+            return _err("internal_error", "Failed to set path")
 
-    def list_folder(  # noqa: PLR0911
-        self, folder_type: str, path: str = "."
-    ) -> dict[str, Any]:
+    def list_folder(self, folder_type: str, path: str = ".") -> dict[str, Any]:
         """
         List contents of a configured folder.
 
-        Includes security checks to prevent path traversal.
-
         Args:
             folder_type: Type of folder (download, tvshow, movie, torrent).
             path: Relative path within the folder (default: root).
@@ -100,43 +80,28 @@ class FileManager:
             Dict with folder contents or error information.
         """
         try:
-            self._validate_folder_name(folder_type)
             safe_path = self._sanitize_path(path)
 
             memory = get_memory()
-            folder_key = f"{folder_type}_folder"
-            folder_path = memory.ltm.get_config(folder_key)
+            if folder_type in ("download", "torrent"):
+                folder_path = getattr(memory.ltm.workspace, folder_type, None)
+            else:
+                folder_path = memory.ltm.library_paths.get(folder_type)
 
             if not folder_path:
-                logger.warning(f"Folder not configured: {folder_type}")
-                return {
-                    "error": "folder_not_set",
-                    "message": f"{folder_type.capitalize()} folder not configured.",
-                }
+                return _err("folder_not_set", f"{folder_type.capitalize()} folder not configured.")
 
             root = Path(folder_path)
             target = root / safe_path
 
             if not self._is_safe_path(root, target):
-                logger.warning(f"Path traversal attempt: {path}")
-                return {
-                    "error": "forbidden",
-                    "message": "Access denied: path outside allowed directory",
-                }
+                return _err("forbidden", "Access denied: path outside allowed directory")
 
             if not target.exists():
-                logger.warning(f"Path does not exist: {target}")
-                return {
-                    "error": "not_found",
-                    "message": f"Path does not exist: {safe_path}",
-                }
+                return _err("not_found", f"Path does not exist: {safe_path}")
 
             if not target.is_dir():
-                logger.warning(f"Path is not a directory: {target}")
-                return {
-                    "error": "not_a_directory",
-                    "message": f"Path is not a directory: {safe_path}",
-                }
+                return _err("not_a_directory", f"Path is not a directory: {safe_path}")
 
             try:
                 entries = [entry.name for entry in target.iterdir()]
@@ -149,35 +114,28 @@ class FileManager:
                     "count": len(entries),
                 }
             except PermissionError:
-                logger.warning(f"Permission denied: {target}")
-                return {
-                    "error": "permission_denied",
-                    "message": f"Permission denied: {safe_path}",
-                }
+                return _err("permission_denied", f"Permission denied: {safe_path}")
 
         except PathTraversalError as e:
-            logger.warning(f"Path traversal attempt: {e}")
-            return {"error": "forbidden", "message": str(e)}
+            return _err("forbidden", str(e))
 
         except ValueError as e:
-            logger.error(f"Validation error: {e}")
-            return {"error": "validation_failed", "message": str(e)}
+            return _err("validation_failed", str(e))
 
         except Exception as e:
             logger.error(f"Unexpected error listing folder: {e}", exc_info=True)
-            return {"error": "internal_error", "message": "Failed to list folder"}
+            return _err("internal_error", "Failed to list folder")
 
-    def move_file(  # noqa: PLR0911
-        self, source: str, destination: str
-    ) -> dict[str, Any]:
+    def copy_file(self, source: str, destination: str) -> dict[str, Any]:
         """
-        Move a file from one location to another.
+        Hard-link a file to a destination (instant, no data duplication).
 
-        Includes validation and verification after move.
+        Both paths must be on the same filesystem. qBittorrent keeps seeding
+        the original inode unaffected.
 
         Args:
-            source: Source file path.
-            destination: Destination file path.
+            source: Absolute path to the source file.
+            destination: Absolute path to the destination file.
 
         Returns:
             Dict with status or error information.
@@ -186,126 +144,174 @@ class FileManager:
             source_path = Path(source).resolve()
             dest_path = Path(destination).resolve()
 
-            logger.info(f"Moving file: {source_path} -> {dest_path}")
+            logger.info(f"Hard-linking: {source_path} -> {dest_path}")
 
             if not source_path.exists():
-                return {
-                    "error": "source_not_found",
-                    "message": f"Source does not exist: {source}",
-                }
+                return _err("source_not_found", f"Source does not exist: {source}")
 
             if not source_path.is_file():
-                return {
-                    "error": "source_not_file",
-                    "message": f"Source is not a file: {source}",
-                }
+                return _err("source_not_file", f"Source is not a file: {source}")
 
-            source_size = source_path.stat().st_size
-            dest_parent = dest_path.parent
-
-            if not dest_parent.exists():
-                return {
-                    "error": "destination_dir_not_found",
-                    "message": f"Destination directory does not exist: {dest_parent}",
-                }
+            if not dest_path.parent.exists():
+                return _err("destination_dir_not_found", f"Destination directory does not exist: {dest_path.parent}")
 
             if dest_path.exists():
-                return {
-                    "error": "destination_exists",
-                    "message": f"Destination already exists: {destination}",
-                }
+                return _err("destination_exists", f"Destination already exists: {destination}")
 
-            shutil.move(str(source_path), str(dest_path))
+            os.link(source_path, dest_path)
 
-            # Verify move
-            if not dest_path.exists():
-                return {
-                    "error": "move_verification_failed",
-                    "message": "File was not moved successfully",
-                }
-
-            dest_size = dest_path.stat().st_size
-            if dest_size != source_size:
-                return {
-                    "error": "size_mismatch",
-                    "message": "File size mismatch after move",
-                }
-
-            logger.info(f"File moved successfully: {dest_path.name}")
+            logger.info(f"Hard link created: {dest_path.name}")
             return {
                 "status": "ok",
                 "source": str(source_path),
                 "destination": str(dest_path),
                 "filename": dest_path.name,
-                "size": dest_size,
+                "size": source_path.stat().st_size,
+            }
+
+        except OSError as e:
+            logger.error(f"Error creating hard link: {e}", exc_info=True)
+            return _err("link_failed", str(e))
+
+    def move_file(self, source: str, destination: str) -> dict[str, Any]:
+        """
+        Move a file via hard link + source deletion.
+
+        Hard-links the file to the destination, then removes the source.
+        qBittorrent keeps seeding during the operation since the inode
+        is still referenced until the source is removed.
+
+        Args:
+            source: Absolute path to the source file.
+            destination: Absolute path to the destination file.
+
+        Returns:
+            Dict with status or error information.
+        """
+        try:
+            source_path = Path(source).resolve()
+
+            link_result = self.copy_file(source, destination)
+            if link_result.get("status") != "ok":
+                return link_result
+
+            source_path.unlink()
+
+            logger.info(f"File moved: {source_path.name} -> {link_result['destination']}")
+            return {
+                "status": "ok",
+                "source": str(source_path),
+                "destination": link_result["destination"],
+                "filename": link_result["filename"],
+                "size": link_result["size"],
             }
 
         except Exception as e:
             logger.error(f"Error moving file: {e}", exc_info=True)
-            return {"error": "move_failed", "message": str(e)}
+            return _err("move_failed", str(e))
 
-    def _validate_folder_name(self, folder_name: str) -> bool:
+    def create_seed_links(
+        self, library_file: str, original_download_folder: str, torrent_folder: str
+    ) -> dict[str, Any]:
         """
-        Validate folder name against allowed values.
+        Prepare a torrent folder so qBittorrent can keep seeding after a move.
+
+        - Hard-links the moved video file from the library back into
+          torrents/<original_folder_name>/ (same inode, no data copy).
+        - Copies every other file from the original download folder
+          (.srt, .nfo, .jpg, .txt, …) into the same torrent subfolder,
+          preserving relative paths.
 
         Args:
-            folder_name: Name to validate.
+            library_file: Absolute path to the video file in the library.
+            original_download_folder: Absolute path to the download folder
+                that contained the original release (may still have subs etc.).
+            torrent_folder: Absolute path to the root torrents/ directory.
 
         Returns:
-            True if valid.
-
-        Raises:
-            ValueError: If folder name is invalid.
+            Dict with status, linked_file, copied_files list, skipped list.
         """
-        valid_names = [fn.value for fn in FolderName]
-        if folder_name not in valid_names:
-            raise ValueError(
-                f"Invalid folder_name '{folder_name}'. "
-                f"Must be one of: {', '.join(valid_names)}"
-            )
-        return True
+        try:
+            lib_path = Path(library_file).resolve()
+            src_folder = Path(original_download_folder).resolve()
+            torrent_root = Path(torrent_folder).resolve()
+
+            if not lib_path.exists():
+                return _err("library_file_not_found", f"Library file not found: {library_file}")
+            if not src_folder.exists():
+                return _err("source_folder_not_found", f"Download folder not found: {original_download_folder}")
+            if not torrent_root.exists():
+                return _err("torrent_folder_not_found", f"Torrent folder not found: {torrent_folder}")
+
+            dest_folder = torrent_root / src_folder.name
+            dest_folder.mkdir(parents=True, exist_ok=True)
+
+            # Hard-link the video file from library → torrent subfolder
+            link_dest = dest_folder / lib_path.name
+            if link_dest.exists():
+                return _err("destination_exists", f"Link already exists: {link_dest}")
+            os.link(lib_path, link_dest)
+            logger.info(f"Hard-linked for seeding: {lib_path.name} → {dest_folder}")
+
+            # Copy everything else from the original download folder
+            copied: list[str] = []
+            skipped: list[str] = []
+            for item in src_folder.rglob("*"):
+                if not item.is_file():
+                    continue
+                rel = item.relative_to(src_folder)
+                dest_item = dest_folder / rel
+                dest_item.parent.mkdir(parents=True, exist_ok=True)
+                if dest_item.exists():
+                    skipped.append(str(rel))
+                    continue
+                import shutil
+                shutil.copy2(item, dest_item)
+                copied.append(str(rel))
+                logger.debug(f"Copied for seeding: {rel}")
+
+            return {
+                "status": "ok",
+                "torrent_subfolder": str(dest_folder),
+                "linked_file": str(link_dest),
+                "copied_files": copied,
+                "copied_count": len(copied),
+                "skipped": skipped,
+            }
+
+        except OSError as e:
+            logger.error(f"create_seed_links failed: {e}", exc_info=True)
+            return _err("link_failed", str(e))
+        except Exception as e:
+            logger.error(f"create_seed_links unexpected error: {e}", exc_info=True)
+            return _err("internal_error", str(e))
 
     def _sanitize_path(self, path: str) -> str:
         """
-        Sanitize path to prevent path traversal attacks.
+        Sanitize a relative path to prevent path traversal attacks.
 
-        Args:
-            path: Path to sanitize.
-
-        Returns:
-            Sanitized path.
-
-        Raises:
-            PathTraversalError: If path contains traversal attempts.
+        Raises PathTraversalError if the path tries to escape the root.
         """
         normalized = os.path.normpath(path)
 
+        # Reject absolute paths
         if os.path.isabs(normalized):
             raise PathTraversalError("Absolute paths are not allowed")
 
+        # Reject parent directory references
         if normalized.startswith("..") or "/.." in normalized or "\\.." in normalized:
             raise PathTraversalError("Parent directory references not allowed")
 
+        # Reject null bytes
         if "\x00" in normalized:
             raise PathTraversalError("Null bytes in path not allowed")
 
         return normalized
 
     def _is_safe_path(self, base_path: Path, target_path: Path) -> bool:
-        """
-        Check if target path is within base path.
-
-        Args:
-            base_path: The allowed base directory.
-            target_path: The path to check.
-
-        Returns:
-            True if target is within base, False otherwise.
-        """
+        """Return True if target_path is inside base_path (prevents traversal)."""
         try:
-            base_resolved = base_path.resolve()
-            target_resolved = target_path.resolve()
-            target_resolved.relative_to(base_resolved)
+            target_path.resolve().relative_to(base_path.resolve())
             return True
         except (ValueError, OSError):
             return False

alfred/infrastructure/persistence/__init__.py

@@ -1,17 +1,10 @@
 """Persistence layer - Data storage implementations."""
 
-from .context import (
-    get_memory,
-    has_memory,
-    init_memory,
-    set_memory,
-)
-from .memory import (
-    EpisodicMemory,
-    LongTermMemory,
-    Memory,
-    ShortTermMemory,
-)
+from .context import get_memory, has_memory, init_memory, set_memory
+from .memory import Memory
+from .memory.episodic import EpisodicMemory
+from .memory.ltm import LongTermMemory
+from .memory.stm import ShortTermMemory
 
 __all__ = [
     "Memory",

alfred/infrastructure/persistence/context.py

@@ -1,28 +1,26 @@
 """
-Memory context using contextvars.
+Memory context — global singleton.
 
-Provides thread-safe and async-safe access to the Memory instance
+Provides async-safe access to the Memory instance
 without passing it explicitly through all function calls.
 
 Usage:
     # At application startup
     from alfred.infrastructure.persistence import init_memory, get_memory
 
-    init_memory("memory_data")
+    init_memory("memory")
 
     # Anywhere in the code
     memory = get_memory()
     memory.ltm.set_config("key", "value")
 """
 
-from contextvars import ContextVar
-
 from .memory import Memory
 
-_memory_ctx: ContextVar[Memory | None] = ContextVar("memory", default=None)
+_memory: Memory | None = None
 
 
-def init_memory(storage_dir: str = "memory_data") -> Memory:
+def init_memory(storage_dir: str = "memory") -> Memory:
     """
     Initialize the memory and set it in the context.
 
@@ -34,9 +32,9 @@ def init_memory(storage_dir: str = "memory_data") -> Memory:
     Returns:
         The initialized Memory instance.
     """
-    memory = Memory(storage_dir=storage_dir)
-    _memory_ctx.set(memory)
-    return memory
+    global _memory
+    _memory = Memory(storage_dir=storage_dir)
+    return _memory
 
 
 def set_memory(memory: Memory) -> None:
@@ -48,7 +46,8 @@ def set_memory(memory: Memory) -> None:
     Args:
         memory: Memory instance to set.
     """
-    _memory_ctx.set(memory)
+    global _memory
+    _memory = memory
 
 
 def get_memory() -> Memory:
@@ -61,12 +60,11 @@ def get_memory() -> Memory:
     Raises:
         RuntimeError: If memory has not been initialized.
     """
-    memory = _memory_ctx.get()
-    if memory is None:
+    if _memory is None:
         raise RuntimeError(
             "Memory not initialized. Call init_memory() at application startup."
         )
-    return memory
+    return _memory
 
 
 def has_memory() -> bool:
@@ -76,4 +74,12 @@ def has_memory() -> bool:
     Returns:
         True if memory is available, False otherwise.
     """
-    return _memory_ctx.get() is not None
+    return _memory is not None
+
+
+def reset_memory() -> None:
+    """
+    Reset the memory singleton to None. For use in tests only.
+    """
+    global _memory
+    _memory = None

alfred/infrastructure/persistence/json/subtitle_repository.py

@@ -119,10 +119,6 @@ class JsonSubtitleRepository(SubtitleRepository):
             "timing_offset": subtitle.timing_offset.milliseconds,
             "hearing_impaired": subtitle.hearing_impaired,
             "forced": subtitle.forced,
-            "source": subtitle.source,
-            "uploader": subtitle.uploader,
-            "download_count": subtitle.download_count,
-            "rating": subtitle.rating,
         }
 
     def _from_dict(self, data: dict[str, Any]) -> Subtitle:
@@ -137,8 +133,4 @@ class JsonSubtitleRepository(SubtitleRepository):
             timing_offset=TimingOffset(data.get("timing_offset", 0)),
             hearing_impaired=data.get("hearing_impaired", False),
             forced=data.get("forced", False),
-            source=data.get("source"),
-            uploader=data.get("uploader"),
-            download_count=data.get("download_count"),
-            rating=data.get("rating"),
         )

alfred/infrastructure/persistence/json/tvshow_repository.py

@@ -1,7 +1,6 @@
 """JSON-based TV show repository implementation."""
 
 import logging
-from datetime import datetime
 from typing import Any
 
 from alfred.domain.shared.value_objects import ImdbId
@@ -115,8 +114,6 @@ class JsonTVShowRepository(TVShowRepository):
             "seasons_count": show.seasons_count,
             "status": show.status.value,
             "tmdb_id": show.tmdb_id,
-            "first_air_date": show.first_air_date,
-            "added_at": show.added_at.isoformat(),
         }
 
     def _from_dict(self, data: dict[str, Any]) -> TVShow:
@@ -127,10 +124,4 @@ class JsonTVShowRepository(TVShowRepository):
             seasons_count=data["seasons_count"],
             status=ShowStatus.from_string(data["status"]),
             tmdb_id=data.get("tmdb_id"),
-            first_air_date=data.get("first_air_date"),
-            added_at=(
-                datetime.fromisoformat(data["added_at"])
-                if data.get("added_at")
-                else datetime.now()
-            ),
         )

alfred/infrastructure/persistence/memory.py

@@ -1,577 +0,0 @@
-"""
-Memory - Unified management of 3 memory types.
-
-Architecture:
-- LTM (Long-Term Memory): Configuration, library, preferences - Persistent
-- STM (Short-Term Memory): Conversation, current workflow - Volatile
-- Episodic Memory: Search results, transient states - Very volatile
-"""
-
-import json
-import logging
-from dataclasses import dataclass, field
-from datetime import datetime
-from pathlib import Path
-from typing import Any
-
-logger = logging.getLogger(__name__)
-
-
-# =============================================================================
-# LONG-TERM MEMORY (LTM) - Persistent
-# =============================================================================
-
-
-@dataclass
-class LongTermMemory:
-    """
-    Long-term memory - Persistent and static.
-
-    Stores:
-    - User configuration (folders, URLs)
-    - Preferences (quality, languages)
-    - Library (owned movies/TV shows)
-    - Followed shows (watchlist)
-    """
-
-    # Folder and service configuration
-    config: dict[str, str] = field(default_factory=dict)
-
-    # User preferences
-    preferences: dict[str, Any] = field(
-        default_factory=lambda: {
-            "preferred_quality": "1080p",
-            "preferred_languages": ["en", "fr"],
-            "auto_organize": False,
-            "naming_format": "{title}.{year}.{quality}",
-        }
-    )
-
-    # Library of owned media
-    library: dict[str, list[dict]] = field(
-        default_factory=lambda: {"movies": [], "tv_shows": []}
-    )
-
-    # Followed shows (watchlist)
-    following: list[dict] = field(default_factory=list)
-
-    def get_config(self, key: str, default: Any = None) -> Any:
-        """Get a configuration value."""
-        return self.config.get(key, default)
-
-    def set_config(self, key: str, value: Any) -> None:
-        """Set a configuration value."""
-        self.config[key] = value
-        logger.debug(f"LTM: Set config {key}")
-
-    def has_config(self, key: str) -> bool:
-        """Check if a configuration exists."""
-        return key in self.config and self.config[key] is not None
-
-    def add_to_library(self, media_type: str, media: dict) -> None:
-        """Add a media item to the library."""
-        if media_type not in self.library:
-            self.library[media_type] = []
-
-        # Avoid duplicates by imdb_id
-        existing_ids = [m.get("imdb_id") for m in self.library[media_type]]
-        if media.get("imdb_id") not in existing_ids:
-            media["added_at"] = datetime.now().isoformat()
-            self.library[media_type].append(media)
-            logger.info(f"LTM: Added {media.get('title')} to {media_type}")
-
-    def get_library(self, media_type: str) -> list[dict]:
-        """Get the library for a media type."""
-        return self.library.get(media_type, [])
-
-    def follow_show(self, show: dict) -> None:
-        """Add a show to the watchlist."""
-        existing_ids = [s.get("imdb_id") for s in self.following]
-        if show.get("imdb_id") not in existing_ids:
-            show["followed_at"] = datetime.now().isoformat()
-            self.following.append(show)
-            logger.info(f"LTM: Now following {show.get('title')}")
-
-    def to_dict(self) -> dict:
-        """Convert to dictionary for serialization."""
-        return {
-            "config": self.config,
-            "preferences": self.preferences,
-            "library": self.library,
-            "following": self.following,
-        }
-
-    @classmethod
-    def from_dict(cls, data: dict) -> "LongTermMemory":
-        """Create an instance from a dictionary."""
-        return cls(
-            config=data.get("config", {}),
-            preferences=data.get(
-                "preferences",
-                {
-                    "preferred_quality": "1080p",
-                    "preferred_languages": ["en", "fr"],
-                    "auto_organize": False,
-                    "naming_format": "{title}.{year}.{quality}",
-                },
-            ),
-            library=data.get("library", {"movies": [], "tv_shows": []}),
-            following=data.get("following", []),
-        )
-
-
-# =============================================================================
-# SHORT-TERM MEMORY (STM) - Conversation
-# =============================================================================
-
-
-@dataclass
-class ShortTermMemory:
-    """
-    Short-term memory - Volatile and conversational.
-
-    Stores:
-    - Current conversation history
-    - Current workflow (what we're doing)
-    - Extracted entities from conversation
-    - Current discussion topic
-    """
-
-    # Conversation message history
-    conversation_history: list[dict[str, str]] = field(default_factory=list)
-
-    # Current workflow
-    current_workflow: dict | None = None
-
-    # Extracted entities (title, year, requested quality, etc.)
-    extracted_entities: dict[str, Any] = field(default_factory=dict)
-
-    # Current conversation topic
-    current_topic: str | None = None
-
-    # Conversation language
-    language: str = "en"
-
-    # History message limit
-    max_history: int = 20
-
-    def add_message(self, role: str, content: str) -> None:
-        """Add a message to history."""
-        self.conversation_history.append(
-            {"role": role, "content": content, "timestamp": datetime.now().isoformat()}
-        )
-        # Keep only the last N messages
-        if len(self.conversation_history) > self.max_history:
-            self.conversation_history = self.conversation_history[-self.max_history :]
-        logger.debug(f"STM: Added {role} message")
-
-    def get_recent_history(self, n: int = 10) -> list[dict]:
-        """Get the last N messages."""
-        return self.conversation_history[-n:]
-
-    def start_workflow(self, workflow_type: str, target: dict) -> None:
-        """Start a new workflow."""
-        self.current_workflow = {
-            "type": workflow_type,
-            "target": target,
-            "stage": "started",
-            "started_at": datetime.now().isoformat(),
-        }
-        logger.info(f"STM: Started workflow '{workflow_type}'")
-
-    def update_workflow_stage(self, stage: str) -> None:
-        """Update the workflow stage."""
-        if self.current_workflow:
-            self.current_workflow["stage"] = stage
-            logger.debug(f"STM: Workflow stage -> {stage}")
-
-    def end_workflow(self) -> None:
-        """End the current workflow."""
-        if self.current_workflow:
-            logger.info(f"STM: Ended workflow '{self.current_workflow.get('type')}'")
-        self.current_workflow = None
-
-    def set_entity(self, key: str, value: Any) -> None:
-        """Store an extracted entity."""
-        self.extracted_entities[key] = value
-        logger.debug(f"STM: Set entity {key}={value}")
-
-    def get_entity(self, key: str, default: Any = None) -> Any:
-        """Get an extracted entity."""
-        return self.extracted_entities.get(key, default)
-
-    def clear_entities(self) -> None:
-        """Clear extracted entities."""
-        self.extracted_entities = {}
-
-    def set_topic(self, topic: str) -> None:
-        """Set the current topic."""
-        self.current_topic = topic
-        logger.debug(f"STM: Topic -> {topic}")
-
-    def set_language(self, language: str) -> None:
-        """Set the conversation language."""
-        self.language = language
-        logger.debug(f"STM: Language -> {language}")
-
-    def clear(self) -> None:
-        """Reset short-term memory."""
-        self.conversation_history = []
-        self.current_workflow = None
-        self.extracted_entities = {}
-        self.current_topic = None
-        self.language = "en"
-        logger.info("STM: Cleared")
-
-    def to_dict(self) -> dict:
-        """Convert to dictionary."""
-        return {
-            "conversation_history": self.conversation_history,
-            "current_workflow": self.current_workflow,
-            "extracted_entities": self.extracted_entities,
-            "current_topic": self.current_topic,
-            "language": self.language,
-        }
-
-
-# =============================================================================
-# EPISODIC MEMORY - Transient states
-# =============================================================================
-
-
-@dataclass
-class EpisodicMemory:
-    """
-    Episodic/sensory memory - Temporary and event-driven.
-
-    Stores:
-    - Last search results
-    - Active downloads
-    - Recent errors
-    - Pending questions awaiting user response
-    - Background events
-    """
-
-    # Last search results
-    last_search_results: dict | None = None
-
-    # Active downloads
-    active_downloads: list[dict] = field(default_factory=list)
-
-    # Recent errors
-    recent_errors: list[dict] = field(default_factory=list)
-
-    # Pending question awaiting user response
-    pending_question: dict | None = None
-
-    # Background events (download complete, new files, etc.)
-    background_events: list[dict] = field(default_factory=list)
-
-    # Limits for errors/events kept
-    max_errors: int = 5
-    max_events: int = 10
-
-    def store_search_results(
-        self, query: str, results: list[dict], search_type: str = "torrent"
-    ) -> None:
-        """
-        Store search results with index.
-
-        Args:
-            query: The search query
-            results: List of results
-            search_type: Type of search (torrent, movie, tvshow)
-        """
-        self.last_search_results = {
-            "query": query,
-            "type": search_type,
-            "timestamp": datetime.now().isoformat(),
-            "results": [{"index": i + 1, **r} for i, r in enumerate(results)],
-        }
-        logger.info(f"Episodic: Stored {len(results)} search results for '{query}'")
-
-    def get_result_by_index(self, index: int) -> dict | None:
-        """
-        Get a result by its number (1-indexed).
-
-        Args:
-            index: Result number (1, 2, 3, ...)
-
-        Returns:
-            The result or None if not found
-        """
-        if not self.last_search_results:
-            logger.warning("Episodic: No search results stored")
-            return None
-
-        for result in self.last_search_results.get("results", []):
-            if result.get("index") == index:
-                return result
-
-        logger.warning(f"Episodic: Result #{index} not found")
-        return None
-
-    def get_search_results(self) -> dict | None:
-        """Get the last search results."""
-        return self.last_search_results
-
-    def clear_search_results(self) -> None:
-        """Clear search results."""
-        self.last_search_results = None
-
-    def add_active_download(self, download: dict) -> None:
-        """Add an active download."""
-        download["started_at"] = datetime.now().isoformat()
-        self.active_downloads.append(download)
-        logger.info(f"Episodic: Added download '{download.get('name')}'")
-
-    def update_download_progress(
-        self, task_id: str, progress: int, status: str = "downloading"
-    ) -> None:
-        """Update download progress."""
-        for dl in self.active_downloads:
-            if dl.get("task_id") == task_id:
-                dl["progress"] = progress
-                dl["status"] = status
-                dl["updated_at"] = datetime.now().isoformat()
-                break
-
-    def complete_download(self, task_id: str, file_path: str) -> dict | None:
-        """Mark a download as complete and remove it."""
-        for i, dl in enumerate(self.active_downloads):
-            if dl.get("task_id") == task_id:
-                completed = self.active_downloads.pop(i)
-                completed["status"] = "completed"
-                completed["file_path"] = file_path
-                completed["completed_at"] = datetime.now().isoformat()
-
-                # Add a background event
-                self.add_background_event(
-                    "download_complete",
-                    {"name": completed.get("name"), "file_path": file_path},
-                )
-
-                logger.info(f"Episodic: Download completed '{completed.get('name')}'")
-                return completed
-        return None
-
-    def get_active_downloads(self) -> list[dict]:
-        """Get active downloads."""
-        return self.active_downloads
-
-    def add_error(self, action: str, error: str, context: dict | None = None) -> None:
-        """Record a recent error."""
-        self.recent_errors.append(
-            {
-                "timestamp": datetime.now().isoformat(),
-                "action": action,
-                "error": error,
-                "context": context or {},
-            }
-        )
-        # Keep only the last N errors
-        self.recent_errors = self.recent_errors[-self.max_errors :]
-        logger.warning(f"Episodic: Error in '{action}': {error}")
-
-    def get_recent_errors(self) -> list[dict]:
-        """Get recent errors."""
-        return self.recent_errors
-
-    def set_pending_question(
-        self,
-        question: str,
-        options: list[dict],
-        context: dict,
-        question_type: str = "choice",
-    ) -> None:
-        """
-        Record a question awaiting user response.
-
-        Args:
-            question: The question asked
-            options: List of possible options
-            context: Question context
-            question_type: Type of question (choice, confirmation, input)
-        """
-        self.pending_question = {
-            "type": question_type,
-            "question": question,
-            "options": options,
-            "context": context,
-            "timestamp": datetime.now().isoformat(),
-        }
-        logger.info(f"Episodic: Pending question set ({question_type})")
-
-    def get_pending_question(self) -> dict | None:
-        """Get the pending question."""
-        return self.pending_question
-
-    def resolve_pending_question(self, answer_index: int | None = None) -> dict | None:
-        """
-        Resolve the pending question and return the chosen option.
-
-        Args:
-            answer_index: Answer index (1-indexed) or None to cancel
-
-        Returns:
-            The chosen option or None
-        """
-        if not self.pending_question:
-            return None
-
-        result = None
-        if answer_index is not None and self.pending_question.get("options"):
-            for opt in self.pending_question["options"]:
-                if opt.get("index") == answer_index:
-                    result = opt
-                    break
-
-        self.pending_question = None
-        logger.info("Episodic: Pending question resolved")
-        return result
-
-    def add_background_event(self, event_type: str, data: dict) -> None:
-        """Add a background event."""
-        self.background_events.append(
-            {
-                "type": event_type,
-                "timestamp": datetime.now().isoformat(),
-                "data": data,
-                "read": False,
-            }
-        )
-        # Keep only the last N events
-        self.background_events = self.background_events[-self.max_events :]
-        logger.info(f"Episodic: Background event '{event_type}'")
-
-    def get_unread_events(self) -> list[dict]:
-        """Get unread events and mark them as read."""
-        unread = [e for e in self.background_events if not e.get("read")]
-        for e in self.background_events:
-            e["read"] = True
-        return unread
-
-    def clear(self) -> None:
-        """Reset episodic memory."""
-        self.last_search_results = None
-        self.active_downloads = []
-        self.recent_errors = []
-        self.pending_question = None
-        self.background_events = []
-        logger.info("Episodic: Cleared")
-
-    def to_dict(self) -> dict:
-        """Convert to dictionary."""
-        return {
-            "last_search_results": self.last_search_results,
-            "active_downloads": self.active_downloads,
-            "recent_errors": self.recent_errors,
-            "pending_question": self.pending_question,
-            "background_events": self.background_events,
-        }
-
-
-# =============================================================================
-# MEMORY MANAGER - Unified manager
-# =============================================================================
-
-
-class Memory:
-    """
-    Unified manager for the 3 memory types.
-
-    Usage:
-        memory = Memory("memory_data")
-        memory.ltm.set_config("download_folder", "/path")
-        memory.stm.add_message("user", "Hello")
-        memory.episodic.store_search_results("query", results)
-        memory.save()
-    """
-
-    def __init__(self, storage_dir: str = "memory_data"):
-        """
-        Initialize the memory.
-
-        Args:
-            storage_dir: Directory for persistent storage
-        """
-        self.storage_dir = Path(storage_dir)
-        self.storage_dir.mkdir(parents=True, exist_ok=True)
-
-        self.ltm_file = self.storage_dir / "ltm.json"
-
-        # Initialize the 3 memory types
-        self.ltm = self._load_ltm()
-        self.stm = ShortTermMemory()
-        self.episodic = EpisodicMemory()
-
-        logger.info(f"Memory initialized (storage: {storage_dir})")
-
-    def _load_ltm(self) -> LongTermMemory:
-        """Load LTM from file."""
-        if self.ltm_file.exists():
-            try:
-                data = json.loads(self.ltm_file.read_text(encoding="utf-8"))
-                logger.info("LTM loaded from file")
-                return LongTermMemory.from_dict(data)
-            except (OSError, json.JSONDecodeError) as e:
-                logger.warning(f"Could not load LTM: {e}")
-        return LongTermMemory()
-
-    def save(self) -> None:
-        """Save LTM (the only persistent memory)."""
-        try:
-            self.ltm_file.write_text(
-                json.dumps(self.ltm.to_dict(), indent=2, ensure_ascii=False),
-                encoding="utf-8",
-            )
-            logger.debug("LTM saved to file")
-        except OSError as e:
-            logger.error(f"Failed to save LTM: {e}")
-            raise
-
-    def get_context_for_prompt(self) -> dict:
-        """
-        Generate context to include in the system prompt.
-
-        Returns:
-            Dictionary with relevant context from all 3 memories
-        """
-        return {
-            "config": self.ltm.config,
-            "preferences": self.ltm.preferences,
-            "current_workflow": self.stm.current_workflow,
-            "current_topic": self.stm.current_topic,
-            "extracted_entities": self.stm.extracted_entities,
-            "last_search": {
-                "query": (
-                    self.episodic.last_search_results.get("query")
-                    if self.episodic.last_search_results
-                    else None
-                ),
-                "result_count": (
-                    len(self.episodic.last_search_results.get("results", []))
-                    if self.episodic.last_search_results
-                    else 0
-                ),
-            },
-            "active_downloads_count": len(self.episodic.active_downloads),
-            "pending_question": self.episodic.pending_question is not None,
-            "unread_events": len(
-                [e for e in self.episodic.background_events if not e.get("read")]
-            ),
-        }
-
-    def get_full_state(self) -> dict:
-        """Return the full state of all 3 memories (for debug)."""
-        return {
-            "ltm": self.ltm.to_dict(),
-            "stm": self.stm.to_dict(),
-            "episodic": self.episodic.to_dict(),
-        }
-
-    def clear_session(self) -> None:
-        """Clear session memories (STM + Episodic)."""
-        self.stm.clear()
-        self.episodic.clear()
-        logger.info("Session memories cleared")

alfred/infrastructure/persistence/memory/__init__.py

@@ -0,0 +1,4 @@
+from .base import Memory
+from .registry import MemoryRegistry
+
+__all__ = ["Memory", "MemoryRegistry"]

alfred/infrastructure/persistence/memory/base.py

@@ -0,0 +1,90 @@
+"""Memory — unified manager for the 3 memory tiers."""
+
+import json
+import logging
+from pathlib import Path
+
+from .episodic import EpisodicMemory
+from .ltm import LongTermMemory
+from .stm import ShortTermMemory
+
+logger = logging.getLogger(__name__)
+
+
+class Memory:
+    """
+    Unified manager for the 3 memory tiers.
+
+    Usage:
+        memory = Memory("data/memory")
+        memory.ltm.workspace.download = "/downloads"
+        memory.stm.add_message("user", "Hello")
+        memory.episodic.store_search_results("query", results)
+        memory.save()
+    """
+
+    def __init__(self, storage_dir: str = "memory"):
+        self.storage_dir = Path(storage_dir)
+        self.storage_dir.mkdir(parents=True, exist_ok=True)
+        self.ltm_file = self.storage_dir / "ltm.json"
+
+        self.ltm = self._load_ltm()
+        self.stm = ShortTermMemory()
+        self.episodic = EpisodicMemory()
+
+        logger.info(f"Memory initialized (storage: {storage_dir})")
+
+    def _load_ltm(self) -> LongTermMemory:
+        """Load LTM from disk, or return a fresh instance."""
+        if self.ltm_file.exists():
+            try:
+                data = json.loads(self.ltm_file.read_text(encoding="utf-8"))
+                logger.info("LTM loaded from file")
+                return LongTermMemory.from_dict(data)
+            except (OSError, json.JSONDecodeError) as e:
+                logger.warning(f"Could not load LTM: {e}")
+        return LongTermMemory()
+
+    def save(self) -> None:
+        """Persist LTM to disk (STM and Episodic are volatile)."""
+        try:
+            self.ltm_file.write_text(
+                json.dumps(self.ltm.to_dict(), indent=2, ensure_ascii=False),
+                encoding="utf-8",
+            )
+            logger.debug("LTM saved")
+        except OSError as e:
+            logger.error(f"Failed to save LTM: {e}")
+            raise
+
+    def get_context_for_prompt(self) -> dict:
+        """Snapshot of relevant memory for the system prompt."""
+        return {
+            "workspace": self.ltm.workspace.as_dict(),
+            "library_paths": self.ltm.library_paths.to_dict(),
+            "preferences": self.ltm.preferences.to_dict(),
+            "current_workflow": self.stm.workflow.to_dict(),
+            "current_topic": self.stm.entities.topic,
+            "extracted_entities": self.stm.entities.data,
+            "last_search": {
+                "query": self.episodic.search_results.last.get("query") if self.episodic.search_results.last else None,
+                "result_count": len(self.episodic.search_results.last.get("results", [])) if self.episodic.search_results.last else 0,
+            },
+            "active_downloads_count": len(self.episodic.downloads.active),
+            "pending_question": self.episodic.pending_question is not None,
+            "unread_events": len([e for e in self.episodic.events.items if not e.get("read")]),
+        }
+
+    def get_full_state(self) -> dict:
+        """Full state dump for debug/API."""
+        return {
+            "ltm": self.ltm.to_dict(),
+            "stm": self.stm.to_dict(),
+            "episodic": self.episodic.to_dict(),
+        }
+
+    def clear_session(self) -> None:
+        """Reset volatile memories (STM + Episodic)."""
+        self.stm.clear()
+        self.episodic.clear()
+        logger.info("Session memories cleared")

alfred/infrastructure/persistence/memory/episodic/__init__.py

@@ -0,0 +1,3 @@
+from .episodic import EpisodicMemory
+
+__all__ = ["EpisodicMemory"]

alfred/infrastructure/persistence/memory/episodic/components/__init__.py

@@ -0,0 +1,6 @@
+from .downloads import Downloads
+from .errors import Errors
+from .events import Events
+from .search_results import SearchResults
+
+__all__ = ["SearchResults", "Downloads", "Events", "Errors"]

alfred/infrastructure/persistence/memory/episodic/components/downloads.py

@@ -0,0 +1,56 @@
+"""Downloads — active torrent downloads being tracked."""
+
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class Downloads:
+    active: list[dict] = field(default_factory=list)
+
+    def add(self, download: dict) -> None:
+        download["started_at"] = datetime.now().isoformat()
+        self.active.append(download)
+        logger.info(f"Downloads: Added '{download.get('name')}'")
+
+    def update_progress(self, task_id: str, progress: int, status: str = "downloading") -> None:
+        for dl in self.active:
+            if dl.get("task_id") == task_id:
+                dl["progress"] = progress
+                dl["status"] = status
+                dl["updated_at"] = datetime.now().isoformat()
+                break
+
+    def complete(self, task_id: str, file_path: str) -> dict | None:
+        for i, dl in enumerate(self.active):
+            if dl.get("task_id") == task_id:
+                completed = self.active.pop(i)
+                completed.update({"status": "completed", "file_path": file_path, "completed_at": datetime.now().isoformat()})
+                logger.info(f"Downloads: Completed '{completed.get('name')}'")
+                return completed
+        return None
+
+    def clear(self) -> None:
+        self.active = []
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Downloads",
+            "tier": "episodic",
+            "access": "read-write",
+            "description": (
+                "Active torrent downloads currently in progress. "
+                "Read to report download status to the user. "
+                "Write to track new downloads or update progress."
+            ),
+            "fields": {
+                "active": "List of active downloads. Each entry has task_id, name, progress, status, started_at.",
+            },
+        }
+
+    def to_dict(self) -> list:
+        return self.active

alfred/infrastructure/persistence/memory/episodic/components/errors.py

@@ -0,0 +1,46 @@
+"""Errors — recent agent errors for context and debugging."""
+
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+MAX_ERRORS = 5
+
+
+@dataclass
+class Errors:
+    items: list[dict] = field(default_factory=list)
+    max_errors: int = MAX_ERRORS
+
+    def add(self, action: str, error: str, context: dict | None = None) -> None:
+        self.items.append({
+            "timestamp": datetime.now().isoformat(),
+            "action": action,
+            "error": error,
+            "context": context or {},
+        })
+        self.items = self.items[-self.max_errors:]
+        logger.warning(f"Errors: '{action}': {error}")
+
+    def clear(self) -> None:
+        self.items = []
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Errors",
+            "tier": "episodic",
+            "access": "read",
+            "description": (
+                "Recent errors encountered during tool execution. "
+                "Read when something goes wrong to understand what failed and avoid repeating the same mistake."
+            ),
+            "fields": {
+                "items": f"Last {MAX_ERRORS} errors. Each has timestamp, action, error message, context.",
+            },
+        }
+
+    def to_dict(self) -> list:
+        return self.items

alfred/infrastructure/persistence/memory/episodic/components/events.py

@@ -0,0 +1,49 @@
+"""Events — background events (download complete, new files, etc.)."""
+
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+MAX_EVENTS = 10
+
+
+@dataclass
+class Events:
+    items: list[dict] = field(default_factory=list)
+    max_events: int = MAX_EVENTS
+
+    def add(self, event_type: str, data: dict) -> None:
+        self.items.append({"type": event_type, "timestamp": datetime.now().isoformat(), "data": data, "read": False})
+        self.items = self.items[-self.max_events:]
+        logger.info(f"Events: '{event_type}'")
+
+    def get_unread(self) -> list[dict]:
+        """Return unread events and mark them as read."""
+        unread = [e for e in self.items if not e.get("read")]
+        for e in self.items:
+            e["read"] = True
+        return unread
+
+    def clear(self) -> None:
+        self.items = []
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Events",
+            "tier": "episodic",
+            "access": "read",
+            "description": (
+                "Background events that occurred during the session (download complete, file moved, etc.). "
+                "Read unread events at the start of each turn to surface anything that happened in the background. "
+                "Events are written automatically by other components."
+            ),
+            "fields": {
+                "items": f"Last {MAX_EVENTS} events. Each has type, timestamp, data, read flag.",
+            },
+        }
+
+    def to_dict(self) -> list:
+        return self.items

alfred/infrastructure/persistence/memory/episodic/components/search_results.py

@@ -0,0 +1,52 @@
+"""SearchResults — last torrent/media search results."""
+
+import logging
+from dataclasses import dataclass
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class SearchResults:
+    last: dict | None = None
+
+    def store(self, query: str, results: list[dict], search_type: str = "torrent") -> None:
+        self.last = {
+            "query": query,
+            "type": search_type,
+            "timestamp": datetime.now().isoformat(),
+            "results": [{"index": i + 1, **r} for i, r in enumerate(results)],
+        }
+        logger.info(f"SearchResults: Stored {len(results)} results for '{query}'")
+
+    def get_by_index(self, index: int) -> dict | None:
+        if not self.last:
+            return None
+        for result in self.last.get("results", []):
+            if result.get("index") == index:
+                return result
+        logger.warning(f"SearchResults: #{index} not found")
+        return None
+
+    def clear(self) -> None:
+        self.last = None
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "SearchResults",
+            "tier": "episodic",
+            "access": "read-write",
+            "description": (
+                "Last torrent or media search results. "
+                "Read to let the user pick a result by index without searching again. "
+                "Write after every search to store fresh results."
+            ),
+            "fields": {
+                "last": "Dict with query, type, timestamp, and results list. Each result has an index (1-based) plus provider fields.",
+            },
+        }
+
+    def to_dict(self) -> dict | None:
+        return self.last

alfred/infrastructure/persistence/memory/episodic/episodic.py

@@ -0,0 +1,126 @@
+"""EpisodicMemory — transient event-driven memory, reset on restart."""
+
+import logging
+from dataclasses import dataclass, field
+
+from .components import Downloads, Errors, Events, SearchResults
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class EpisodicMemory:
+    """
+    Episodic memory — very short-lived, event-driven.
+
+    Composed of:
+    - search_results: last torrent/media search
+    - downloads: active downloads being tracked
+    - events: background events (download complete, etc.)
+    - errors: recent errors for context
+    """
+
+    search_results: SearchResults = field(default_factory=SearchResults)
+    downloads: Downloads = field(default_factory=Downloads)
+    events: Events = field(default_factory=Events)
+    errors: Errors = field(default_factory=Errors)
+
+    # Convenience proxies for backward compatibility
+    @property
+    def last_search_results(self) -> dict | None:
+        return self.search_results.last
+
+    @property
+    def active_downloads(self) -> list[dict]:
+        return self.downloads.active
+
+    @property
+    def background_events(self) -> list[dict]:
+        return self.events.items
+
+    @property
+    def recent_errors(self) -> list[dict]:
+        return self.errors.items
+
+    # Pending question — not a component yet, kept simple
+    pending_question: dict | None = None
+
+    # Convenience methods forwarded to components
+    def store_search_results(self, query: str, results: list[dict], search_type: str = "torrent") -> None:
+        self.search_results.store(query, results, search_type)
+
+    def get_result_by_index(self, index: int) -> dict | None:
+        return self.search_results.get_by_index(index)
+
+    def get_search_results(self) -> dict | None:
+        return self.search_results.last
+
+    def clear_search_results(self) -> None:
+        self.search_results.clear()
+
+    def add_active_download(self, download: dict) -> None:
+        self.downloads.add(download)
+
+    def update_download_progress(self, task_id: str, progress: int, status: str = "downloading") -> None:
+        self.downloads.update_progress(task_id, progress, status)
+
+    def complete_download(self, task_id: str, file_path: str) -> dict | None:
+        completed = self.downloads.complete(task_id, file_path)
+        if completed:
+            self.events.add("download_complete", {"name": completed.get("name"), "file_path": file_path})
+        return completed
+
+    def get_active_downloads(self) -> list[dict]:
+        return self.downloads.active
+
+    def add_error(self, action: str, error: str, context: dict | None = None) -> None:
+        self.errors.add(action, error, context)
+
+    def get_recent_errors(self) -> list[dict]:
+        return self.errors.items
+
+    def set_pending_question(self, question: str, options: list[dict], context: dict, question_type: str = "choice") -> None:
+        self.pending_question = {
+            "type": question_type,
+            "question": question,
+            "options": options,
+            "context": context,
+        }
+
+    def get_pending_question(self) -> dict | None:
+        return self.pending_question
+
+    def resolve_pending_question(self, answer_index: int | None = None) -> dict | None:
+        if not self.pending_question:
+            return None
+        result = None
+        if answer_index is not None:
+            for opt in self.pending_question.get("options", []):
+                if opt.get("index") == answer_index:
+                    result = opt
+                    break
+        self.pending_question = None
+        return result
+
+    def add_background_event(self, event_type: str, data: dict) -> None:
+        self.events.add(event_type, data)
+
+    def get_unread_events(self) -> list[dict]:
+        return self.events.get_unread()
+
+    def clear(self) -> None:
+        self.search_results.clear()
+        self.downloads.clear()
+        self.events.clear()
+        self.errors.clear()
+        self.pending_question = None
+        logger.info("Episodic: Cleared")
+
+    def to_dict(self) -> dict:
+        return {
+            "last_search_results": self.search_results.to_dict(),
+            "active_downloads": self.downloads.to_dict(),
+            "recent_errors": self.errors.to_dict(),
+            "pending_question": self.pending_question,
+            "background_events": self.events.to_dict(),
+        }

alfred/infrastructure/persistence/memory/ltm/__init__.py

@@ -0,0 +1,3 @@
+from .ltm import LongTermMemory
+
+__all__ = ["LongTermMemory"]

alfred/infrastructure/persistence/memory/ltm/components/__init__.py

@@ -0,0 +1,15 @@
+from .following import Following
+from .library import Library
+from .library_paths import LibraryPaths
+from .media_preferences import MediaPreferences
+from .subtitle_preferences import SubtitlePreferences
+from .workspace import WorkspacePaths
+
+__all__ = [
+    "WorkspacePaths",
+    "LibraryPaths",
+    "MediaPreferences",
+    "SubtitlePreferences",
+    "Library",
+    "Following",
+]

alfred/infrastructure/persistence/memory/ltm/components/following.py

@@ -0,0 +1,43 @@
+"""Following — watchlist of TV shows being followed."""
+
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class Following:
+    shows: list[dict] = field(default_factory=list)
+
+    def add(self, show: dict) -> None:
+        """Follow a show, skipping duplicates by imdb_id."""
+        existing_ids = [s.get("imdb_id") for s in self.shows]
+        if show.get("imdb_id") not in existing_ids:
+            show["followed_at"] = datetime.now().isoformat()
+            self.shows.append(show)
+            logger.info(f"Following: Now following {show.get('title')}")
+
+    def to_dict(self) -> list:
+        return self.shows
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Following",
+            "tier": "ltm",
+            "access": "read-write",
+            "description": (
+                "Watchlist of TV shows the user is actively following. "
+                "Read to check if a show should be monitored for new episodes. "
+                "Write (add) when the user explicitly asks to follow a show."
+            ),
+            "fields": {
+                "shows": "List of followed shows. Each entry has imdb_id, title, followed_at.",
+            },
+        }
+
+    @classmethod
+    def from_dict(cls, data: list) -> "Following":
+        return cls(shows=data)

alfred/infrastructure/persistence/memory/ltm/components/library.py

@@ -0,0 +1,64 @@
+"""Library — owned movies and TV shows."""
+
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class Library:
+    movies: list[dict] = field(default_factory=list)
+    tv_shows: list[dict] = field(default_factory=list)
+
+    def add(self, media_type: str, media: dict) -> None:
+        """Add a media item, skipping duplicates by imdb_id."""
+        collection = self._collection(media_type)
+        if collection is None:
+            return
+
+        existing_ids = [m.get("imdb_id") for m in collection]
+        if media.get("imdb_id") not in existing_ids:
+            media["added_at"] = datetime.now().isoformat()
+            collection.append(media)
+            logger.info(f"Library: Added {media.get('title')} to {media_type}")
+
+    def get(self, media_type: str) -> list[dict]:
+        """Get all items for a media type."""
+        return self._collection(media_type) or []
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Library",
+            "tier": "ltm",
+            "access": "read-write",
+            "description": (
+                "Catalogue of media owned by the user. "
+                "Read to check if a title is already in the library before downloading. "
+                "Write (add) after successfully moving a media file to its destination."
+            ),
+            "fields": {
+                "movies": "List of owned movies. Each entry has imdb_id, title, year, quality, file_path, added_at.",
+                "tv_shows": "List of owned TV shows. Each entry has imdb_id, title, seasons, added_at.",
+            },
+        }
+
+    def _collection(self, media_type: str) -> list[dict] | None:
+        if media_type == "movies":
+            return self.movies
+        if media_type == "tv_shows":
+            return self.tv_shows
+        logger.warning(f"Library: Unknown media type '{media_type}'")
+        return None
+
+    def to_dict(self) -> dict:
+        return {"movies": self.movies, "tv_shows": self.tv_shows}
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "Library":
+        return cls(
+            movies=data.get("movies", []),
+            tv_shows=data.get("tv_shows", []),
+        )

alfred/infrastructure/persistence/memory/ltm/components/library_paths.py

@@ -0,0 +1,70 @@
+"""LibraryPaths — user-defined media library folders.
+
+Extensible: the user creates collections as needed (tv_shows, movies, music, games…).
+Each collection name maps to its root folder on disk.
+
+Set via /set_path, never modified by the agent autonomously.
+Access: READ ONLY for the agent — used to resolve destination paths when organizing media.
+"""
+
+from dataclasses import dataclass, field
+
+
+@dataclass
+class LibraryPaths:
+    """
+    User-defined media library folders.
+
+    folders is a free dict: {"tv_shows": "/media/tv", "movies": "/media/movies", ...}
+    Add new collections simply by setting a new key via /set_path.
+
+    Access: READ ONLY for the agent — set via /set_path only.
+    """
+
+    folders: dict[str, str] = field(default_factory=dict)
+
+    def get(self, collection: str) -> str | None:
+        return self.folders.get(collection)
+
+    def set(self, collection: str, path: str) -> None:
+        self.folders[collection] = path
+
+    def to_dict(self) -> dict:
+        return self.folders
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "LibraryPaths",
+            "tier": "ltm",
+            "access": "read",
+            "description": (
+                "User-defined media library folders. "
+                "Read these paths to resolve where to move an organised media file. "
+                "Keys are collection names (tv_shows, movies, music, games…), values are root paths. "
+                "New collections are added by the user via /set_path — never by the agent."
+            ),
+            "fields": {
+                "folders": "Dict of collection_name → absolute path. E.g. {'tv_shows': '/media/tv', 'movies': '/media/movies'}.",
+            },
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "LibraryPaths":
+        # Migrate from old flat format (tvshow_folder, movie_folder)
+        folders = dict(data)
+        if not folders:
+            return cls()
+
+        migrated = {}
+        legacy_map = {
+            "tvshow_folder": "tv_shows",
+            "movie_folder": "movies",
+        }
+        for old_key, new_key in legacy_map.items():
+            if old_key in folders:
+                migrated[new_key] = folders.pop(old_key)
+
+        # Keep any already-migrated keys
+        migrated.update(folders)
+        return cls(folders=migrated)

alfred/infrastructure/persistence/memory/ltm/components/media_preferences.py

@@ -0,0 +1,52 @@
+"""MediaPreferences — user preferences for video quality and audio."""
+
+from dataclasses import dataclass, field
+
+
+@dataclass
+class MediaPreferences:
+    """Quality and audio preferences for media downloads and organisation."""
+
+    quality: str = "1080p"
+    audio_languages: list[str] = field(default_factory=lambda: ["fr", "en"])
+    auto_organize: bool = False
+
+    def to_dict(self) -> dict:
+        return {
+            "quality": self.quality,
+            "audio_languages": self.audio_languages,
+            "auto_organize": self.auto_organize,
+        }
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "MediaPreferences",
+            "tier": "ltm",
+            "access": "read",
+            "description": (
+                "User preferences for video quality and audio. "
+                "Use these when searching torrents or choosing a release to download. "
+                "Never modify autonomously — only via explicit user command."
+            ),
+            "fields": {
+                "quality": "Preferred video quality, e.g. '1080p', '4K', '720p'.",
+                "audio_languages": (
+                    "Ordered list of preferred audio languages (ISO 639-1). "
+                    "First = most preferred."
+                ),
+                "auto_organize": "If True, organise files into the library automatically after download.",
+            },
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "MediaPreferences":
+        return cls(
+            # migration: old key was preferred_quality / preferred_languages
+            quality=data.get("quality") or data.get("preferred_quality", "1080p"),
+            audio_languages=(
+                data.get("audio_languages")
+                or data.get("preferred_languages", ["fr", "en"])
+            ),
+            auto_organize=data.get("auto_organize", False),
+        )

alfred/infrastructure/persistence/memory/ltm/components/subtitle_preferences.py

@@ -0,0 +1,80 @@
+"""SubtitlePreferences — user preferences for subtitle handling."""
+
+from dataclasses import dataclass, field
+
+
+@dataclass
+class SubtitlePreferences:
+    """
+    User-level defaults for subtitle selection, applied globally as the
+    base of the SubtitleRuleSet inheritance chain.
+
+    These are the top-level defaults — individual shows/movies/release groups
+    can override them via .alfred/rules.yaml.
+
+    Naming convention used when placing subtitle files alongside a video:
+        {lang}.srt           → standard track  (e.g. fr.srt, en.srt)
+        {lang}.sdh.srt       → SDH / hearing-impaired track
+        {lang}.forced.srt    → forced track (foreign lines only)
+
+    Fields mirror SubtitleRuleSet.override() parameters:
+      - languages: ordered list of ISO 639-1 codes to keep (others ignored)
+      - formats: list of subtitle formats to keep (e.g. ["srt", "ass"])
+      - types: list of subtitle types to keep (e.g. ["standard", "forced", "sdh"])
+    """
+
+    languages: list[str] = field(default_factory=lambda: ["fr", "en"])
+    formats: list[str] = field(default_factory=lambda: ["srt", "ass"])
+    types: list[str] = field(default_factory=lambda: ["standard", "forced", "sdh"])
+
+    def to_dict(self) -> dict:
+        return {
+            "languages": self.languages,
+            "formats": self.formats,
+            "types": self.types,
+        }
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "SubtitlePreferences",
+            "tier": "ltm",
+            "access": "read",
+            "description": (
+                "User defaults for subtitle selection. Applied as global base rules; "
+                "overridden per show/movie/release group via .alfred/rules.yaml. "
+                "Never modify autonomously — only via explicit user command."
+            ),
+            "fields": {
+                "languages": (
+                    "Ordered list of subtitle languages to keep (ISO 639-1). "
+                    "Others are ignored. First = most preferred."
+                ),
+                "formats": (
+                    "List of subtitle formats to keep, e.g. ['srt', 'ass']. "
+                    "Others are skipped."
+                ),
+                "types": (
+                    "List of subtitle types to keep: 'standard', 'sdh', 'forced'. "
+                    "Omit a type to drop those tracks globally."
+                ),
+            },
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "SubtitlePreferences":
+        # Migration: old fields (min_size_kb, keep_sdh, keep_forced, link_subs_folder) are silently dropped
+        prefs = cls(
+            languages=data.get("languages", ["fr", "en"]),
+            formats=data.get("formats", ["srt", "ass"]),
+            types=data.get("types", ["standard", "forced", "sdh"]),
+        )
+        # Back-compat: keep_sdh / keep_forced → types list
+        if "types" not in data:
+            types = ["standard"]
+            if data.get("keep_sdh", True):
+                types.append("sdh")
+            if data.get("keep_forced", True):
+                types.append("forced")
+            prefs.types = types
+        return prefs

alfred/infrastructure/persistence/memory/ltm/components/workspace.py

@@ -0,0 +1,57 @@
+"""WorkspacePaths — fixed infrastructure folders.
+
+Set once via /set_path, never modified by the agent.
+These are operational paths (where files land), not the media library.
+"""
+
+from dataclasses import dataclass
+
+
+@dataclass
+class WorkspacePaths:
+    """
+    Fixed infrastructure folders.
+
+    - download: where qBittorrent drops completed downloads
+    - torrent: where .torrent files are stored
+
+    Access: READ ONLY for the agent — set via /set_path only.
+    """
+
+    download: str | None = None
+    torrent: str | None = None
+
+    def as_dict(self) -> dict[str, str]:
+        """Return configured paths, skipping unset values."""
+        return {k: v for k, v in {
+            "download": self.download,
+            "torrent": self.torrent,
+        }.items() if v is not None}
+
+    def to_dict(self) -> dict:
+        return {"download": self.download, "torrent": self.torrent}
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "WorkspacePaths",
+            "tier": "ltm",
+            "access": "read",
+            "description": (
+                "Fixed infrastructure folders used during file operations. "
+                "Read these paths to know where to find downloaded files or .torrent files. "
+                "Never modify — set exclusively via /set_path."
+            ),
+            "fields": {
+                "download": "Root folder where qBittorrent drops completed downloads.",
+                "torrent": "Folder where .torrent files are stored.",
+            },
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "WorkspacePaths":
+        # Migrate from old flat format (download_folder, torrent_folder)
+        return cls(
+            download=data.get("download") or data.get("download_folder"),
+            torrent=data.get("torrent") or data.get("torrent_folder"),
+        )

alfred/infrastructure/persistence/memory/ltm/ltm.py

@@ -0,0 +1,65 @@
+"""LongTermMemory — persistent memory across sessions."""
+
+import logging
+from dataclasses import dataclass, field
+
+from .components import (
+    Following,
+    Library,
+    LibraryPaths,
+    MediaPreferences,
+    SubtitlePreferences,
+    WorkspacePaths,
+)
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class LongTermMemory:
+    """
+    Long-term memory — persisted to disk, survives restarts.
+
+    - workspace: fixed infrastructure paths (download, torrent) — READ ONLY for agent
+    - library_paths: user-defined media folders (tv_shows, movies, …) — READ ONLY for agent
+    - media_preferences: quality and audio language preferences
+    - subtitle_preferences: subtitle selection and naming rules
+    - library: owned media catalogue
+    - following: watchlist
+    """
+
+    workspace: WorkspacePaths = field(default_factory=WorkspacePaths)
+    library_paths: LibraryPaths = field(default_factory=LibraryPaths)
+    media_preferences: MediaPreferences = field(default_factory=MediaPreferences)
+    subtitle_preferences: SubtitlePreferences = field(default_factory=SubtitlePreferences)
+    library: Library = field(default_factory=Library)
+    following: Following = field(default_factory=Following)
+
+    def to_dict(self) -> dict:
+        return {
+            "workspace": self.workspace.to_dict(),
+            "library_paths": self.library_paths.to_dict(),
+            "media_preferences": self.media_preferences.to_dict(),
+            "subtitle_preferences": self.subtitle_preferences.to_dict(),
+            "library": self.library.to_dict(),
+            "following": self.following.to_dict(),
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "LongTermMemory":
+        # Migration: old flat format had paths at the top level
+        workspace_data = data.get("workspace") or data
+        library_paths_data = data.get("library_paths") or data.get("paths") or data
+        return cls(
+            workspace=WorkspacePaths.from_dict(workspace_data),
+            library_paths=LibraryPaths.from_dict(library_paths_data),
+            # migration: old key was "preferences"
+            media_preferences=MediaPreferences.from_dict(
+                data.get("media_preferences") or data.get("preferences", {})
+            ),
+            subtitle_preferences=SubtitlePreferences.from_dict(
+                data.get("subtitle_preferences", {})
+            ),
+            library=Library.from_dict(data.get("library", {})),
+            following=Following.from_dict(data.get("following", [])),
+        )

alfred/infrastructure/persistence/memory/registry.py

@@ -0,0 +1,80 @@
+"""MemoryRegistry — autodiscovers and describes all memory components.
+
+Scans the components/ subfolder of each memory tier (ltm, stm, episodic),
+imports every class that has a describe() classmethod, and exposes their
+descriptions for use in the system prompt.
+
+No manual registration needed — drop a new component file in the right
+components/ folder and it will be picked up automatically.
+"""
+
+import importlib
+import inspect
+import logging
+import pkgutil
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+# Tier packages relative to this file's package
+_TIER_PACKAGES = [
+    "alfred.infrastructure.persistence.memory.ltm.components",
+    "alfred.infrastructure.persistence.memory.stm.components",
+    "alfred.infrastructure.persistence.memory.episodic.components",
+]
+
+
+def _load_components(package_name: str) -> list[dict]:
+    """Import all modules in a package and collect describe() results."""
+    descriptions = []
+    try:
+        package = importlib.import_module(package_name)
+        package_path = Path(package.__file__).parent
+
+        for module_info in pkgutil.iter_modules([str(package_path)]):
+            module = importlib.import_module(f"{package_name}.{module_info.name}")
+            for _, cls in inspect.getmembers(module, inspect.isclass):
+                if cls.__module__ == module.__name__ and hasattr(cls, "describe"):
+                    try:
+                        descriptions.append(cls.describe())
+                    except Exception as e:
+                        logger.warning(f"MemoryRegistry: describe() failed on {cls.__name__}: {e}")
+
+    except Exception as e:
+        logger.warning(f"MemoryRegistry: Could not load package {package_name}: {e}")
+
+    return descriptions
+
+
+class MemoryRegistry:
+    """
+    Autodiscovers memory components and exposes their descriptions.
+
+    Usage:
+        registry = MemoryRegistry()
+        all_components = registry.all()          # flat list
+        ltm_components = registry.by_tier("ltm") # filtered by tier
+        schema = registry.schema()               # grouped by tier, for the prompt
+    """
+
+    def __init__(self):
+        self._components: list[dict] = []
+        for package in _TIER_PACKAGES:
+            self._components.extend(_load_components(package))
+        logger.info(f"MemoryRegistry: Loaded {len(self._components)} components")
+
+    def all(self) -> list[dict]:
+        """Return all component descriptions."""
+        return self._components
+
+    def by_tier(self, tier: str) -> list[dict]:
+        """Return components for a specific tier (ltm, stm, episodic)."""
+        return [c for c in self._components if c.get("tier") == tier]
+
+    def schema(self) -> dict[str, list[dict]]:
+        """Return components grouped by tier."""
+        result: dict[str, list[dict]] = {"ltm": [], "stm": [], "episodic": []}
+        for component in self._components:
+            tier = component.get("tier", "unknown")
+            result.setdefault(tier, []).append(component)
+        return result

alfred/infrastructure/persistence/memory/stm/__init__.py

@@ -0,0 +1,3 @@
+from .stm import ShortTermMemory
+
+__all__ = ["ShortTermMemory"]

alfred/infrastructure/persistence/memory/stm/components/__init__.py

@@ -0,0 +1,5 @@
+from .conversation import Conversation
+from .entities import Entities
+from .workflow import Workflow
+
+__all__ = ["Conversation", "Workflow", "Entities"]

alfred/infrastructure/persistence/memory/stm/components/conversation.py

@@ -0,0 +1,55 @@
+"""Conversation — message history for the current session."""
+
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+MAX_HISTORY = 20
+
+
+@dataclass
+class Conversation:
+    messages: list[dict] = field(default_factory=list)
+    max_history: int = MAX_HISTORY
+    language: str = "en"
+
+    def add(self, role: str, content: str) -> None:
+        """Append a message, capping at max_history."""
+        self.messages.append({"role": role, "content": content, "timestamp": datetime.now().isoformat()})
+        if len(self.messages) > self.max_history:
+            self.messages = self.messages[-self.max_history:]
+        logger.debug(f"Conversation: Added {role} message")
+
+    def recent(self, n: int = 10) -> list[dict]:
+        """Return the last N messages."""
+        return self.messages[-n:]
+
+    def set_language(self, language: str) -> None:
+        self.language = language
+        logger.debug(f"Conversation: Language -> {language}")
+
+    def clear(self) -> None:
+        self.messages = []
+        self.language = "en"
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Conversation",
+            "tier": "stm",
+            "access": "read",
+            "description": (
+                "Current session message history and detected language. "
+                "Read to maintain conversational context. "
+                "Messages are managed automatically — never write directly."
+            ),
+            "fields": {
+                "messages": f"Last {MAX_HISTORY} messages (role, content, timestamp).",
+                "language": "Detected conversation language (ISO 639-1 code, e.g. 'fr', 'en').",
+            },
+        }
+
+    def to_dict(self) -> dict:
+        return {"messages": self.messages, "language": self.language}

alfred/infrastructure/persistence/memory/stm/components/entities.py

@@ -0,0 +1,48 @@
+"""Entities — extracted entities from the current conversation (title, year, quality, etc.)."""
+
+import logging
+from dataclasses import dataclass, field
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class Entities:
+    data: dict[str, Any] = field(default_factory=dict)
+    topic: str | None = None
+
+    def set(self, key: str, value: Any) -> None:
+        self.data[key] = value
+        logger.debug(f"Entities: {key}={value}")
+
+    def get(self, key: str, default: Any = None) -> Any:
+        return self.data.get(key, default)
+
+    def set_topic(self, topic: str) -> None:
+        self.topic = topic
+        logger.debug(f"Entities: Topic -> {topic}")
+
+    def clear(self) -> None:
+        self.data = {}
+        self.topic = None
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Entities",
+            "tier": "stm",
+            "access": "read-write",
+            "description": (
+                "Entities and topic extracted from the current conversation. "
+                "Read to retrieve what the user is talking about (title, year, quality, etc.) without re-parsing the history. "
+                "Write when you identify a new entity or topic shift."
+            ),
+            "fields": {
+                "data": "Key-value pairs of extracted entities. E.g. {'title': 'Breaking Bad', 'year': 2008, 'quality': '1080p'}.",
+                "topic": "Current conversation topic as a short string. E.g. 'media_search', 'organize_file'.",
+            },
+        }
+
+    def to_dict(self) -> dict:
+        return {"data": self.data, "topic": self.topic}

alfred/infrastructure/persistence/memory/stm/components/workflow.py

@@ -0,0 +1,53 @@
+"""Workflow — tracks the current in-progress agent task."""
+
+import logging
+from dataclasses import dataclass
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class Workflow:
+    current: dict | None = None
+
+    def start(self, workflow_type: str, target: dict) -> None:
+        self.current = {
+            "type": workflow_type,
+            "target": target,
+            "stage": "started",
+            "started_at": datetime.now().isoformat(),
+        }
+        logger.info(f"Workflow: Started '{workflow_type}'")
+
+    def update_stage(self, stage: str) -> None:
+        if self.current:
+            self.current["stage"] = stage
+            logger.debug(f"Workflow: Stage -> {stage}")
+
+    def end(self) -> None:
+        if self.current:
+            logger.info(f"Workflow: Ended '{self.current.get('type')}'")
+        self.current = None
+
+    def clear(self) -> None:
+        self.current = None
+
+    @classmethod
+    def describe(cls) -> dict:
+        return {
+            "name": "Workflow",
+            "tier": "stm",
+            "access": "read-write",
+            "description": (
+                "Tracks the current in-progress multi-step task. "
+                "Read to know what you are currently doing and what stage you are at. "
+                "Write to start, advance, or end a workflow as you execute steps."
+            ),
+            "fields": {
+                "current": "Active workflow dict with keys: type, target, stage, started_at. None if idle.",
+            },
+        }
+
+    def to_dict(self) -> dict | None:
+        return self.current

alfred/infrastructure/persistence/memory/stm/stm.py

@@ -0,0 +1,91 @@
+"""ShortTermMemory — volatile session memory, reset on restart."""
+
+import logging
+from dataclasses import dataclass, field
+
+from .components import Conversation, Entities, Workflow
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class ShortTermMemory:
+    """
+    Short-term memory — lives for the duration of a session.
+
+    Composed of:
+    - conversation: message history + language
+    - workflow: current in-progress task
+    - entities: extracted context (title, year, quality…)
+    """
+
+    conversation: Conversation = field(default_factory=Conversation)
+    workflow: Workflow = field(default_factory=Workflow)
+    entities: Entities = field(default_factory=Entities)
+
+    # Convenience proxies kept for backward compatibility with existing callers
+    @property
+    def conversation_history(self) -> list[dict]:
+        return self.conversation.messages
+
+    @property
+    def current_workflow(self) -> dict | None:
+        return self.workflow.current
+
+    @property
+    def extracted_entities(self) -> dict:
+        return self.entities.data
+
+    @property
+    def current_topic(self) -> str | None:
+        return self.entities.topic
+
+    @property
+    def language(self) -> str:
+        return self.conversation.language
+
+    # Convenience methods forwarded to components
+    def add_message(self, role: str, content: str) -> None:
+        self.conversation.add(role, content)
+
+    def get_recent_history(self, n: int = 10) -> list[dict]:
+        return self.conversation.recent(n)
+
+    def start_workflow(self, workflow_type: str, target: dict) -> None:
+        self.workflow.start(workflow_type, target)
+
+    def update_workflow_stage(self, stage: str) -> None:
+        self.workflow.update_stage(stage)
+
+    def end_workflow(self) -> None:
+        self.workflow.end()
+
+    def set_entity(self, key: str, value) -> None:
+        self.entities.set(key, value)
+
+    def get_entity(self, key: str, default=None):
+        return self.entities.get(key, default)
+
+    def clear_entities(self) -> None:
+        self.entities.clear()
+
+    def set_topic(self, topic: str) -> None:
+        self.entities.set_topic(topic)
+
+    def set_language(self, language: str) -> None:
+        self.conversation.set_language(language)
+
+    def clear(self) -> None:
+        self.conversation.clear()
+        self.workflow.clear()
+        self.entities.clear()
+        logger.info("STM: Cleared")
+
+    def to_dict(self) -> dict:
+        return {
+            "conversation_history": self.conversation.messages,
+            "current_workflow": self.workflow.to_dict(),
+            "extracted_entities": self.entities.data,
+            "current_topic": self.entities.topic,
+            "language": self.conversation.language,
+        }

alfred/infrastructure/subtitle/__init__.py

@@ -0,0 +1,6 @@
+"""Infrastructure adapters for subtitle persistence."""
+
+from .metadata_store import SubtitleMetadataStore
+from .rule_repository import RuleSetRepository
+
+__all__ = ["SubtitleMetadataStore", "RuleSetRepository"]

alfred/infrastructure/subtitle/metadata_store.py

@@ -0,0 +1,144 @@
+"""SubtitleMetadataStore — reads/writes .alfred/metadata.yaml colocated with media."""
+
+import logging
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+from alfred.domain.subtitles.entities import SubtitleTrack
+from alfred.domain.subtitles.services.placer import PlacedTrack
+
+logger = logging.getLogger(__name__)
+
+
+class SubtitleMetadataStore:
+    """
+    Manages the .alfred/metadata.yaml file that lives inside the media library folder.
+
+    For TV shows:  /media/tv_shows/The X-Files/.alfred/metadata.yaml
+    For movies:    /media/movies/Inception (2010)/.alfred/metadata.yaml
+
+    The store never raises on a missing file — it returns empty defaults.
+    Writes are atomic (write to .tmp then rename).
+    """
+
+    def __init__(self, library_root: Path):
+        self._root = library_root
+        self._alfred_dir = library_root / ".alfred"
+        self._metadata_path = self._alfred_dir / "metadata.yaml"
+
+    # ------------------------------------------------------------------
+    # Load / Save
+    # ------------------------------------------------------------------
+
+    def load(self) -> dict:
+        """Return the full metadata dict. Empty dict if file absent."""
+        if not self._metadata_path.exists():
+            return {}
+        try:
+            with open(self._metadata_path, encoding="utf-8") as f:
+                return yaml.safe_load(f) or {}
+        except Exception as e:
+            logger.warning(f"MetadataStore: could not read {self._metadata_path}: {e}")
+            return {}
+
+    def save(self, data: dict) -> None:
+        """Atomically write metadata.yaml. Creates .alfred/ if needed."""
+        self._alfred_dir.mkdir(parents=True, exist_ok=True)
+        tmp = self._metadata_path.with_suffix(".yaml.tmp")
+        try:
+            with open(tmp, "w", encoding="utf-8") as f:
+                yaml.safe_dump(data, f, allow_unicode=True, default_flow_style=False, sort_keys=False)
+            tmp.rename(self._metadata_path)
+        except Exception as e:
+            logger.error(f"MetadataStore: could not write {self._metadata_path}: {e}")
+            tmp.unlink(missing_ok=True)
+            raise
+
+    # ------------------------------------------------------------------
+    # Pattern
+    # ------------------------------------------------------------------
+
+    def confirmed_pattern(self) -> str | None:
+        """Return the confirmed pattern_id, or None."""
+        data = self.load()
+        if data.get("pattern_confirmed"):
+            return data.get("detected_pattern")
+        return None
+
+    def mark_pattern_confirmed(self, pattern_id: str, media_info: dict | None = None) -> None:
+        """Persist detected_pattern + pattern_confirmed=true."""
+        data = self.load()
+        data["detected_pattern"] = pattern_id
+        data["pattern_confirmed"] = True
+        if media_info:
+            data.setdefault("media_type", media_info.get("media_type"))
+            data.setdefault("imdb_id", media_info.get("imdb_id"))
+            data.setdefault("title", media_info.get("title"))
+        self.save(data)
+        logger.info(f"MetadataStore: confirmed pattern '{pattern_id}' for {self._root.name}")
+
+    # ------------------------------------------------------------------
+    # Subtitle history
+    # ------------------------------------------------------------------
+
+    def append_history(
+        self,
+        placed_pairs: list[tuple[PlacedTrack, SubtitleTrack]],
+        season: int | None = None,
+        episode: int | None = None,
+        release_group: str | None = None,
+    ) -> None:
+        """Append one history entry with all placed tracks."""
+        if not placed_pairs:
+            return
+
+        data = self.load()
+        history = data.setdefault("subtitle_history", [])
+
+        tracks_data: list[dict[str, Any]] = []
+        for placed, track in placed_pairs:
+            # Infer type from destination filename parts (e.g. en.sdh.srt → sdh)
+            parts = placed.filename.rsplit(".", 2)   # ["en", "sdh", "srt"] or ["en", "srt"]
+            inferred_type = parts[1] if len(parts) == 3 else "standard"
+
+            tracks_data.append({
+                "language": track.language.code if track.language else "unknown",
+                "type": inferred_type,
+                "format": placed.destination.suffix.lstrip("."),
+                "is_embedded": track.is_embedded,
+                "source_file": placed.source.name,
+                "placed_as": placed.filename,
+                "confidence": round(track.confidence, 3),
+            })
+
+        entry: dict[str, Any] = {
+            "placed_at": datetime.now(timezone.utc).isoformat(),
+            "release_group": release_group,
+            "tracks": tracks_data,
+        }
+        if season is not None:
+            entry["season"] = season
+        if episode is not None:
+            entry["episode"] = episode
+
+        history.append(entry)
+
+        # Update release_groups list
+        if release_group:
+            groups = data.setdefault("release_groups", [])
+            if release_group not in groups:
+                groups.append(release_group)
+
+        self.save(data)
+        logger.info(
+            f"MetadataStore: appended history "
+            f"({'S%02dE%02d' % (season, episode) if season and episode else 'movie'}) "
+            f"— {len(tracks_data)} track(s)"
+        )
+
+    def history(self) -> list[dict]:
+        """Return the raw history list."""
+        return self.load().get("subtitle_history", [])

alfred/infrastructure/subtitle/rule_repository.py

@@ -0,0 +1,116 @@
+"""RuleSetRepository — loads SubtitleRuleSet from .alfred/ YAML files."""
+
+import logging
+from pathlib import Path
+from typing import TYPE_CHECKING
+
+import yaml
+
+from alfred.domain.subtitles.aggregates import SubtitleRuleSet
+from alfred.domain.subtitles.value_objects import RuleScope
+
+if TYPE_CHECKING:
+    from alfred.infrastructure.persistence.memory.ltm.components.subtitle_preferences import SubtitlePreferences
+
+logger = logging.getLogger(__name__)
+
+
+def _load_yaml(path: Path) -> dict:
+    if not path.exists():
+        return {}
+    try:
+        with open(path, encoding="utf-8") as f:
+            return yaml.safe_load(f) or {}
+    except Exception as e:
+        logger.warning(f"RuleSetRepository: could not read {path}: {e}")
+        return {}
+
+
+class RuleSetRepository:
+    """
+    Builds a fully chained SubtitleRuleSet by reading YAML from .alfred/.
+
+    Inheritance chain:
+        global (hardcoded defaults)
+          └── release_group  (.alfred/release_groups/{GROUP}.yaml)
+                └── local     (.alfred/rules.yaml)
+
+    Rules are delta-only — None means "inherit from parent".
+    The repository only creates intermediate nodes when the corresponding
+    file exists and contains an override section.
+    """
+
+    def __init__(self, library_root: Path):
+        self._alfred_dir = library_root / ".alfred"
+
+    def load(
+        self,
+        release_group: str | None = None,
+        subtitle_preferences: "SubtitlePreferences | None" = None,
+    ) -> SubtitleRuleSet:
+        """
+        Build and return the resolved RuleSet chain.
+
+        If subtitle_preferences is provided, it seeds the global base rule set
+        from LTM (overriding the hardcoded DEFAULT_RULES).
+        Returns global default if no overrides exist.
+        """
+        base = SubtitleRuleSet.global_default()
+        if subtitle_preferences is not None:
+            base.override(
+                languages=subtitle_preferences.languages,
+                formats=subtitle_preferences.formats,
+                types=subtitle_preferences.types,
+            )
+        current = base
+
+        # Release group level
+        if release_group:
+            rg_path = self._alfred_dir / "release_groups" / f"{release_group}.yaml"
+            rg_data = _load_yaml(rg_path).get("override", {})
+            if rg_data:
+                rg_ruleset = SubtitleRuleSet(
+                    scope=RuleScope(level="release_group", identifier=release_group),
+                    parent=current,
+                )
+                rg_ruleset.override(**_filter_override(rg_data))
+                current = rg_ruleset
+                logger.debug(f"RuleSetRepository: loaded release_group override for '{release_group}'")
+
+        # Local (show/movie) level
+        local_data = _load_yaml(self._alfred_dir / "rules.yaml").get("override", {})
+        if local_data:
+            local_ruleset = SubtitleRuleSet(
+                scope=RuleScope(level="show"),
+                parent=current,
+            )
+            local_ruleset.override(**_filter_override(local_data))
+            current = local_ruleset
+            logger.debug("RuleSetRepository: loaded local rules.yaml override")
+
+        return current
+
+    def save_local(self, delta: dict) -> None:
+        """Write or update .alfred/rules.yaml with override delta."""
+        self._alfred_dir.mkdir(parents=True, exist_ok=True)
+        path = self._alfred_dir / "rules.yaml"
+        existing = _load_yaml(path)
+        existing_override = existing.get("override", {})
+        existing_override.update(delta)
+        data = {"override": existing_override}
+        tmp = path.with_suffix(".yaml.tmp")
+        try:
+            with open(tmp, "w", encoding="utf-8") as f:
+                yaml.safe_dump(data, f, allow_unicode=True, default_flow_style=False, sort_keys=False)
+            tmp.rename(path)
+            logger.info(f"RuleSetRepository: saved local rules to {path}")
+        except Exception as e:
+            logger.error(f"RuleSetRepository: could not write {path}: {e}")
+            tmp.unlink(missing_ok=True)
+            raise
+
+
+def _filter_override(data: dict) -> dict:
+    """Keep only keys that SubtitleRuleSet.override() accepts."""
+    valid = {"languages", "formats", "types", "format_priority", "min_confidence"}
+    return {k: v for k, v in data.items() if k in valid}

alfred/knowledge/patterns/adjacent.yaml

@@ -0,0 +1,13 @@
+id: adjacent
+version: "1.0"
+description: >
+  Subtitle files sit directly alongside the video file, in the same directory.
+  Example: Show.S01E01.mkv + Show.S01E01.English.srt in the same folder.
+
+scan_strategy: adjacent
+root_folder: null
+
+type_detection:
+  method: token_in_name
+  description: >
+    Type (standard/SDH/forced) is determined from tokens in the filename.

alfred/knowledge/patterns/embedded.yaml

@@ -0,0 +1,14 @@
+id: embedded
+version: "1.0"
+description: >
+  Subtitle tracks are embedded inside the video container (MKV, MP4).
+  Detected via ffprobe — no external files.
+
+scan_strategy: embedded
+root_folder: null
+
+type_detection:
+  method: ffprobe_metadata
+  description: >
+    Language, type (SDH/forced) and format are read directly from the
+    container track metadata via ffprobe.

alfred/knowledge/patterns/episode_subfolder.yaml

@@ -0,0 +1,16 @@
+id: episode_subfolder
+version: "1.0"
+description: >
+  Subtitle files are in a Subs/ folder at the release root, with one subfolder
+  per episode named after the episode filename (without extension).
+  Example: Subs/Show.S01E01.BluRay.x265-RARBG/2_English.srt
+
+scan_strategy: episode_subfolder
+root_folder: "Subs"
+
+type_detection:
+  method: size_and_count
+  description: >
+    When multiple files share the same detected language, differentiate
+    standard vs SDH by comparing file size and subtitle entry count.
+    Larger file (more entries) = SDH.

alfred/knowledge/patterns/subs_flat.yaml

@@ -0,0 +1,14 @@
+id: subs_flat
+version: "1.0"
+description: >
+  Subtitle files are directly in a Subs/ folder at the release root,
+  with no per-episode subfolder.
+  Example: Subs/Show.S01E01.English.srt
+
+scan_strategy: flat
+root_folder: "Subs"
+
+type_detection:
+  method: token_in_name
+  description: >
+    Type (standard/SDH/forced) is determined from tokens in the filename.

alfred/knowledge/release_groups/KONSTRAST.yaml

@@ -0,0 +1,5 @@
+name: KONSTRAST
+known_patterns: ["episode_subfolder", "embedded"]
+notes: >
+  Follows similar conventions to RARBG. Pattern varies per release — always
+  verify per season.

alfred/knowledge/release_groups/RARBG.yaml

@@ -0,0 +1,2 @@
+name: RARBG
+known_patterns: ["episode_subfolder"]

alfred/knowledge/subtitles.yaml

@@ -0,0 +1,89 @@
+name: subtitles
+version: "1.0"
+description: "Subtitle classification rules — formats, types, languages and their tokens"
+
+defaults:
+  languages: ["fra", "eng"]
+  formats: ["srt"]
+  types: ["standard", "forced", "sdh"]
+  format_priority: ["srt", "ass"]
+  min_confidence: 0.7
+
+formats:
+  srt:
+    extensions: [".srt"]
+    description: "SubRip — plain text, universal"
+  ass:
+    extensions: [".ass", ".ssa"]
+    description: "Advanced SubStation Alpha — with styles and positioning"
+
+types:
+  standard:
+    tokens: []
+    description: "Normal subtitle track"
+  sdh:
+    tokens: ["sdh", "hi", "cc", "hearing"]
+    description: "Hearing-impaired — includes sound effects and speaker labels"
+  forced:
+    tokens: ["forced", "foreign"]
+    description: "Foreign lines only — e.g. alien speech in an otherwise English film"
+
+languages:
+  fra:
+    tokens: ["fr", "fra", "french", "francais", "vf", "vff", "vostfr"]
+  eng:
+    tokens: ["en", "eng", "english"]
+  spa:
+    tokens: ["es", "spa", "spanish", "espanol", "español"]
+  deu:
+    tokens: ["de", "deu", "ger", "german", "deutsch"]
+  ita:
+    tokens: ["it", "ita", "italian", "italiano"]
+  por:
+    tokens: ["pt", "por", "portuguese", "portugues", "português"]
+  nld:
+    tokens: ["nl", "nld", "dut", "dutch", "nederlands"]
+  nor:
+    tokens: ["no", "nor", "norwegian", "norsk"]
+  swe:
+    tokens: ["sv", "swe", "swedish", "svenska"]
+  dan:
+    tokens: ["da", "dan", "danish", "dansk"]
+  fin:
+    tokens: ["fi", "fin", "finnish", "suomi"]
+  pol:
+    tokens: ["pl", "pol", "polish", "polski"]
+  ces:
+    tokens: ["cs", "ces", "cze", "czech"]
+  slk:
+    tokens: ["sk", "slk", "slo", "slovak"]
+  hun:
+    tokens: ["hu", "hun", "hungarian", "magyar"]
+  ron:
+    tokens: ["ro", "ron", "rum", "romanian", "romana", "română"]
+  bul:
+    tokens: ["bg", "bul", "bulgarian"]
+  hrv:
+    tokens: ["hr", "hrv", "croatian", "hrvatski"]
+  srp:
+    tokens: ["sr", "srp", "serbian", "srpski"]
+  slv:
+    tokens: ["sl", "slv", "slovenian", "slovensko"]
+  est:
+    tokens: ["et", "est", "estonian", "eesti"]
+  lav:
+    tokens: ["lv", "lav", "latvian", "latviesu"]
+  lit:
+    tokens: ["lt", "lit", "lithuanian", "lietuviu"]
+  mkd:
+    tokens: ["mk", "mkd", "mac", "macedonian"]
+  jpn:
+    tokens: ["ja", "jpn", "japanese"]
+  zho:
+    tokens: ["zh", "zho", "chi", "chinese"]
+  kor:
+    tokens: ["ko", "kor", "korean"]
+  ara:
+    tokens: ["ar", "ara", "arabic"]
+  tur:
+    tokens: ["tr", "tur", "turkish"]

alfred/settings.py

@@ -1,209 +1,97 @@
-import secrets
-from pathlib import Path
-from typing import NamedTuple
+"""
+Application settings — Alfred only.
 
-import tomllib
-from pydantic import Field, computed_field, field_validator
+Only declares what Alfred's Python code actually consumes.
+Everything else (.env.alfred, .env.secrets) is loaded by Docker Compose
+for other services and ignored here via extra="ignore".
+"""
+
+from pathlib import Path
+
+from pydantic import field_validator
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 BASE_DIR = Path(__file__).resolve().parent.parent
-ENV_FILE_PATH = BASE_DIR / ".env"
-toml_path = BASE_DIR / "pyproject.toml"
 
 
 class ConfigurationError(Exception):
     """Raised when configuration is invalid."""
 
-    pass
-
-
-class ProjectVersions(NamedTuple):
-    """
-    Immutable structure for project versions.
-    Forces explicit naming and prevents accidental swaps.
-    """
-
-    librechat: str
-    rag: str
-    alfred: str
-
-
-def get_versions_from_toml() -> ProjectVersions:
-    """
-    Reads versioning information from pyproject.toml.
-    Returns the default value if the file or key is missing.
-    """
-
-    if not toml_path.exists():
-        raise FileNotFoundError(f"pyproject.toml not found: {toml_path}")
-
-    with open(toml_path, "rb") as f:
-        data = tomllib.load(f)
-        try:
-            return ProjectVersions(
-                librechat=data["tool"]["alfred"]["settings"]["librechat_version"],
-                rag=data["tool"]["alfred"]["settings"]["rag_version"],
-                alfred=data["tool"]["poetry"]["version"],
-            )
-        except KeyError as e:
-            raise KeyError(f"Error: Missing key {e} in pyproject.toml") from e
-
-
-# Load versions once
-VERSIONS: ProjectVersions = get_versions_from_toml()
-
 
 class Settings(BaseSettings):
     model_config = SettingsConfigDict(
-        env_file=ENV_FILE_PATH,
+        env_file=[BASE_DIR / ".env.alfred", BASE_DIR / ".env.secrets", BASE_DIR / ".env.make"],
         env_file_encoding="utf-8",
         extra="ignore",
         case_sensitive=False,
     )
-    # --- GENERAL SETTINGS ---
-    host: str = "0.0.0.0"
-    port: int = 3080
-    debug_logging: bool = False
-    debug_console: bool = False
-    data_storage: str = "data"
-    librechat_version: str = Field(VERSIONS.librechat, description="Librechat version")
-    rag_version: str = Field(VERSIONS.rag, description="RAG engine version")
-    alfred_version: str = Field(VERSIONS.alfred, description="Alfred version")
 
-    # --- CONTEXT SETTINGS ---
+    # --- APP ---
     max_history_messages: int = 10
     max_tool_iterations: int = 10
     request_timeout: int = 30
+    llm_temperature: float = 0.2
+    data_storage_dir: str = "data"
 
-    # TODO: Finish
+    # --- BUILD ---
+    alfred_version: str | None = None
+
+    # --- LLM ---
+    default_llm_provider: str = "local"
+    ollama_base_url: str = "http://ollama:11434"
+    ollama_model: str = "llama3.3:latest"
     deepseek_base_url: str = "https://api.deepseek.com"
     deepseek_model: str = "deepseek-chat"
 
     # --- API KEYS ---
-    anthropic_api_key: str | None = Field(None, description="Claude API key")
-    deepseek_api_key: str | None = Field(None, description="Deepseek API key")
-    google_api_key: str | None = Field(None, description="Gemini API key")
-    kimi_api_key: str | None = Field(None, description="Kimi API key")
-    openai_api_key: str | None = Field(None, description="ChatGPT API key")
-
-    # --- SECURITY KEYS ---
-    # Generated automatically if not in .env to ensure "Secure by Default"
-    jwt_secret: str = Field(default_factory=lambda: secrets.token_urlsafe(32))
-    jwt_refresh_secret: str = Field(default_factory=lambda: secrets.token_urlsafe(32))
-
-    # We keep these for encryption of keys in MongoDB (AES-256 Hex format)
-    creds_key: str = Field(default_factory=lambda: secrets.token_hex(32))
-    creds_iv: str = Field(default_factory=lambda: secrets.token_hex(16))
-
-    # --- SERVICES ---
-    qbittorrent_url: str = "http://qbittorrent:16140"
-    qbittorrent_username: str = "admin"
-    qbittorrent_password: str = Field(default_factory=lambda: secrets.token_urlsafe(16))
-
-    mongo_host: str = "mongodb"
-    mongo_user: str = "alfred"
-    mongo_password: str = Field(
-        default_factory=lambda: secrets.token_urlsafe(24), repr=False, exclude=True
-    )
-    mongo_port: int = 27017
-    mongo_db_name: str = "alfred"
-
-    @computed_field(repr=False)
-    @property
-    def mongo_uri(self) -> str:
-        return (
-            f"mongodb://{self.mongo_user}:{self.mongo_password}"
-            f"@{self.mongo_host}:{self.mongo_port}/{self.mongo_db_name}"
-            f"?authSource=admin"
-        )
-
-    postgres_host: str = "vectordb"
-    postgres_user: str = "alfred"
-    postgres_password: str = Field(
-        default_factory=lambda: secrets.token_urlsafe(24), repr=False, exclude=True
-    )
-    postgres_port: int = 5432
-    postgres_db_name: str = "alfred"
-
-    @computed_field(repr=False)
-    @property
-    def postgres_uri(self) -> str:
-        return (
-            f"postgresql://{self.postgres_user}:{self.postgres_password}"
-            f"@{self.postgres_host}:{self.postgres_port}/{self.postgres_db_name}"
-        )
-
-    tmdb_api_key: str | None = Field(None, description="The Movie Database API key")
+    tmdb_api_key: str | None = None
     tmdb_base_url: str = "https://api.themoviedb.org/3"
-
-    # --- LLM PICKER & CONFIG ---
-    # Providers: 'local', 'deepseek', ...
-    default_llm_provider: str = "local"
-    ollama_base_url: str = "http://ollama:11434"
-    # Models: ...
-    ollama_model: str = "llama3.3:latest"
-    llm_temperature: float = 0.2
-
-    # --- RAG ENGINE ---
-    rag_enabled: bool = True  # TODO: Handle False
-    rag_api_url: str = "http://rag_api:8000"
-    embeddings_provider: str = "ollama"
-    # Models: ...
-    embeddings_model: str = "nomic-embed-text"
-
-    # --- MEILISEARCH ---
-    meili_enabled: bool = Field(True, description="Enable meili")
-    meili_no_analytics: bool = True
-    meili_host: str = "http://meilisearch:7700"
-    meili_master_key: str = Field(
-        default_factory=lambda: secrets.token_urlsafe(32),
-        description="Master key for Meilisearch",
-        repr=False,
-    )
+    deepseek_api_key: str | None = None
+    openai_api_key: str | None = None
+    anthropic_api_key: str | None = None
+    google_api_key: str | None = None
+    kimi_api_key: str | None = None
 
     # --- VALIDATORS ---
     @field_validator("llm_temperature")
     @classmethod
     def validate_temperature(cls, v: float) -> float:
         if not 0.0 <= v <= 2.0:
-            raise ConfigurationError(
-                f"Temperature must be between 0.0 and 2.0, got {v}"
-            )
+            raise ConfigurationError(f"Temperature must be between 0.0 and 2.0, got {v}")
         return v
 
     @field_validator("max_tool_iterations")
     @classmethod
     def validate_max_iterations(cls, v: int) -> int:
         if not 1 <= v <= 20:
-            raise ConfigurationError(
-                f"max_tool_iterations must be between 1 and 50, got {v}"
-            )
+            raise ConfigurationError(f"max_tool_iterations must be between 1 and 20, got {v}")
         return v
 
     @field_validator("request_timeout")
     @classmethod
     def validate_timeout(cls, v: int) -> int:
         if not 1 <= v <= 300:
-            raise ConfigurationError(
-                f"request_timeout must be between 1 and 300 seconds, got {v}"
-            )
+            raise ConfigurationError(f"request_timeout must be between 1 and 300 seconds, got {v}")
         return v
 
-    @field_validator("deepseek_base_url", "tmdb_base_url")
-    @classmethod
-    def validate_url(cls, v: str, info) -> str:
-        if not v.startswith(("http://", "https://")):
-            raise ConfigurationError(f"Invalid {info.field_name}")
-        return v
-
-    def is_tmdb_configured(self):
+    # --- HELPERS ---
+    def is_tmdb_configured(self) -> bool:
         return bool(self.tmdb_api_key)
 
-    def is_deepseek_configured(self):
+    def is_deepseek_configured(self) -> bool:
         return bool(self.deepseek_api_key)
 
-    def dump_safe(self):
-        return self.model_dump(exclude_none=False)
+    def is_openai_configured(self) -> bool:
+        return bool(self.openai_api_key)
+
+    def is_anthropic_configured(self) -> bool:
+        return bool(self.anthropic_api_key)
+
+    def is_google_configured(self) -> bool:
+        return bool(self.google_api_key)
+
+    def is_kimi_configured(self) -> bool:
+        return bool(self.kimi_api_key)
 
 
 settings = Settings()

docker-compose.yaml

@@ -8,8 +8,7 @@ services:
       target: builder
       args:
         PYTHON_VERSION: ${PYTHON_VERSION}
-        PYTHON_VERSION_SHORT: ${PYTHON_VERSION_SHORT}
-        RUNNER: ${RUNNER}
+        UV_VERSION: ${UV_VERSION}
     command: python scripts/bootstrap.py
     networks:
       - alfred-net
@@ -17,24 +16,30 @@ services:
   # --- MAIN APPLICATION ---
   alfred:
     container_name: alfred-core
+    image: alfred_media_organizer:latest
     build:
       context: .
       args:
         PYTHON_VERSION: ${PYTHON_VERSION}
-        PYTHON_VERSION_SHORT: ${PYTHON_VERSION_SHORT}
-        RUNNER: ${RUNNER}
+        UV_VERSION: ${UV_VERSION}
     depends_on:
       alfred-init:
         condition: service_completed_successfully
     restart: unless-stopped
     env_file:
-      - path: .env
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
+        required: true
+      - path: .env.make
         required: true
     volumes:
       - ./data:/data
       - ./logs:/logs
       # TODO: Hot reload (comment out in production)
-      #- ./alfred:/home/appuser/alfred
+      - ./alfred:/home/appuser/alfred
+    command: >
+      sh -c "python -u -m uvicorn alfred.app:app --host 0.0.0.0 --port 8000 --reload 2>&1 | tee -a /logs/alfred.log"
     networks:
       - alfred-net
 
@@ -49,7 +54,11 @@ services:
         condition: service_healthy
     restart: unless-stopped
     env_file:
-      - path: .env
+      - path: .env.librechat
+        required: true
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
         required: true
     environment:
       # Remap value name
@@ -75,21 +84,23 @@ services:
       alfred-init:
         condition: service_completed_successfully
     env_file:
-      - path: .env
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
         required: true
     environment:
-      # Remap value name
       - MONGO_INITDB_ROOT_USERNAME=${MONGO_USER}
       - MONGO_INITDB_ROOT_PASSWORD=${MONGO_PASSWORD}
+      # Fix MongoDB + Linux kernel >= 6.19
+      - GLIBC_TUNABLES=glibc.cpu.hwcaps=-SHSTK
     ports:
       - "${MONGO_PORT}:${MONGO_PORT}"
     volumes:
-      - ./data/mongo:/data/db
-    command: mongod --quiet --setParameter logComponentVerbosity='{"network":{"verbosity":0}}'
+      - ./data/mongodb:/data/db
+      - ./mongod.conf:/etc/mongod.conf:ro
+    command: ["mongod", "--config", "/etc/mongod.conf"]
     healthcheck:
-      test: |
-        mongosh --quiet --eval "db.adminCommand('ping')" || \
-        mongosh --quiet -u "${MONGO_USER}" -p "${MONGO_PASSWORD}" --authenticationDatabase admin --eval "db.adminCommand('ping')"
+      test: bash -c "echo > /dev/tcp/localhost/27017"
       interval: 10s
       timeout: 5s
       retries: 5
@@ -105,7 +116,9 @@ services:
         condition: service_completed_successfully
     restart: unless-stopped
     env_file:
-      - path: .env
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
         required: true
     volumes:
       - ./data/ollama:/root/.ollama
@@ -122,7 +135,9 @@ services:
         condition: service_completed_successfully
     restart: unless-stopped
     env_file:
-      - path: .env
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
         required: true
     volumes:
       - ./data/meilisearch:/meili_data
@@ -141,7 +156,9 @@ services:
         condition: service_healthy
     restart: unless-stopped
     env_file:
-      - path: .env
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
         required: true
     ports:
       - "${RAG_API_PORT}:${RAG_API_PORT}"
@@ -160,7 +177,9 @@ services:
         condition: service_completed_successfully
     restart: unless-stopped
     env_file:
-      - path: .env
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
         required: true
     ports:
       - "${POSTGRES_PORT}:${POSTGRES_PORT}"
@@ -168,12 +187,14 @@ services:
       - ./data/vectordb:/var/lib/postgresql/data
     profiles: ["rag", "full"]
     healthcheck:
-      test: [ "CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-alfred} -d ${POSTGRES_DB_NAME:-alfred}" ]
+      test: [ "CMD-SHELL", "pg_isready -U $${POSTGRES_USER:-alfred} -d $${POSTGRES_DB_NAME:-alfred}" ]
       interval: 5s
       timeout: 5s
       retries: 5
     networks:
-      - alfred-net
+      alfred-net:
+        aliases:
+          - db
 
   # --- QBITTORENT (Optional) ---
   qbittorrent:
@@ -184,7 +205,9 @@ services:
         condition: service_completed_successfully
     restart: unless-stopped
     env_file:
-      - path: .env
+      - path: .env.alfred
+        required: true
+      - path: .env.secrets
         required: true
     environment:
       - PUID=1000

librechat/.env.example

@@ -0,0 +1,878 @@
+#=====================================================================#
+#                       LibreChat Configuration                       #
+#=====================================================================#
+# Please refer to the reference documentation for assistance          #
+# with configuring your LibreChat environment.                        #
+#                                                                     #
+# https://www.librechat.ai/docs/configuration/dotenv                  #
+#=====================================================================#
+
+#==================================================#
+#               Server Configuration               #
+#==================================================#
+
+HOST=localhost
+PORT=3080
+
+MONGO_URI=mongodb://127.0.0.1:27017/LibreChat
+#The maximum number of connections in the connection pool. */
+MONGO_MAX_POOL_SIZE=
+#The minimum number of connections in the connection pool. */
+MONGO_MIN_POOL_SIZE=
+#The maximum number of connections that may be in the process of being established concurrently by the connection pool. */
+MONGO_MAX_CONNECTING=
+#The maximum number of milliseconds that a connection can remain idle in the pool before being removed and closed. */
+MONGO_MAX_IDLE_TIME_MS=
+#The maximum time in milliseconds that a thread can wait for a connection to become available. */
+MONGO_WAIT_QUEUE_TIMEOUT_MS=
+# Set to false to disable automatic index creation for all models associated with this connection. */
+MONGO_AUTO_INDEX=
+# Set to `false` to disable Mongoose automatically calling `createCollection()` on every model created on this connection. */
+MONGO_AUTO_CREATE=
+
+DOMAIN_CLIENT=http://localhost:3080
+DOMAIN_SERVER=http://localhost:3080
+
+NO_INDEX=true
+# Use the address that is at most n number of hops away from the Express application.
+# req.socket.remoteAddress is the first hop, and the rest are looked for in the X-Forwarded-For header from right to left.
+# A value of 0 means that the first untrusted address would be req.socket.remoteAddress, i.e. there is no reverse proxy.
+# Defaulted to 1.
+TRUST_PROXY=1
+
+# Minimum password length for user authentication
+# Default: 8
+# Note: When using LDAP authentication, you may want to set this to 1 
+# to bypass local password validation, as LDAP servers handle their own
+# password policies.
+# MIN_PASSWORD_LENGTH=8
+
+# When enabled, the app will continue running after encountering uncaught exceptions
+# instead of exiting the process. Not recommended for production unless necessary.
+# CONTINUE_ON_UNCAUGHT_EXCEPTION=false
+
+#===============#
+# JSON Logging  #
+#===============#
+
+# Use when process console logs in cloud deployment like GCP/AWS
+CONSOLE_JSON=false
+
+#===============#
+# Debug Logging #
+#===============#
+
+DEBUG_LOGGING=true
+DEBUG_CONSOLE=false
+# Set to true to enable agent debug logging
+AGENT_DEBUG_LOGGING=false
+
+# Enable memory diagnostics (logs heap/RSS snapshots every 60s, auto-enabled with --inspect)
+# MEM_DIAG=true
+
+#=============#
+# Permissions #
+#=============#
+
+# UID=1000
+# GID=1000
+
+#==============#
+# Node Options #
+#==============#
+
+# NOTE: NODE_MAX_OLD_SPACE_SIZE is NOT recognized by Node.js directly.
+# This variable is used as a build argument for Docker or CI/CD workflows,
+# and is NOT used by Node.js to set the heap size at runtime.
+# To configure Node.js memory, use NODE_OPTIONS, e.g.:
+# NODE_OPTIONS="--max-old-space-size=6144"
+# See: https://nodejs.org/api/cli.html#--max-old-space-sizesize-in-mib
+NODE_MAX_OLD_SPACE_SIZE=6144
+
+#===============#
+# Configuration #
+#===============#
+# Use an absolute path, a relative path, or a URL
+
+# CONFIG_PATH="/alternative/path/to/librechat.yaml"
+
+#==================#
+# Langfuse Tracing #
+#==================#
+
+# Get Langfuse API keys for your project from the project settings page: https://cloud.langfuse.com
+
+# LANGFUSE_PUBLIC_KEY=
+# LANGFUSE_SECRET_KEY=
+# LANGFUSE_BASE_URL=
+
+#===================================================#
+#                     Endpoints                     #
+#===================================================#
+
+# ENDPOINTS=openAI,assistants,azureOpenAI,google,anthropic
+
+PROXY=
+
+#===================================#
+# Known Endpoints - librechat.yaml  #
+#===================================#
+# https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints
+
+# ANYSCALE_API_KEY=
+# APIPIE_API_KEY=
+# COHERE_API_KEY=
+# DEEPSEEK_API_KEY=
+# DATABRICKS_API_KEY=
+# FIREWORKS_API_KEY=
+# GROQ_API_KEY=
+# HUGGINGFACE_TOKEN=
+# MISTRAL_API_KEY=
+# OPENROUTER_KEY=
+# PERPLEXITY_API_KEY=
+# SHUTTLEAI_API_KEY=
+# TOGETHERAI_API_KEY=
+# UNIFY_API_KEY=
+# XAI_API_KEY=
+
+#============#
+# Anthropic  #
+#============#
+
+ANTHROPIC_API_KEY=user_provided
+# ANTHROPIC_MODELS=claude-sonnet-4-6,claude-opus-4-6,claude-opus-4-20250514,claude-sonnet-4-20250514,claude-3-7-sonnet-20250219,claude-3-5-sonnet-20241022,claude-3-5-haiku-20241022,claude-3-opus-20240229,claude-3-sonnet-20240229,claude-3-haiku-20240307
+# ANTHROPIC_REVERSE_PROXY=
+
+# Set to true to use Anthropic models through Google Vertex AI instead of direct API
+# ANTHROPIC_USE_VERTEX=
+# ANTHROPIC_VERTEX_REGION=us-east5
+
+#============#
+# Azure      #
+#============#
+
+# Note: these variables are DEPRECATED
+# Use the `librechat.yaml` configuration for `azureOpenAI` instead
+# You may also continue to use them if you opt out of using the `librechat.yaml` configuration
+
+# AZURE_OPENAI_DEFAULT_MODEL=gpt-3.5-turbo # Deprecated
+# AZURE_OPENAI_MODELS=gpt-3.5-turbo,gpt-4 # Deprecated
+# AZURE_USE_MODEL_AS_DEPLOYMENT_NAME=TRUE # Deprecated
+# AZURE_API_KEY= # Deprecated
+# AZURE_OPENAI_API_INSTANCE_NAME= # Deprecated
+# AZURE_OPENAI_API_DEPLOYMENT_NAME= # Deprecated
+# AZURE_OPENAI_API_VERSION= # Deprecated
+# AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME= # Deprecated
+# AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME= # Deprecated
+
+#=================#
+#   AWS Bedrock   #
+#=================#
+
+# BEDROCK_AWS_DEFAULT_REGION=us-east-1 # A default region must be provided
+# BEDROCK_AWS_ACCESS_KEY_ID=someAccessKey
+# BEDROCK_AWS_SECRET_ACCESS_KEY=someSecretAccessKey
+# BEDROCK_AWS_SESSION_TOKEN=someSessionToken
+
+# Note: This example list is not meant to be exhaustive. If omitted, all known, supported model IDs will be included for you.
+# BEDROCK_AWS_MODELS=anthropic.claude-sonnet-4-6,anthropic.claude-opus-4-6-v1,anthropic.claude-3-5-sonnet-20240620-v1:0,meta.llama3-1-8b-instruct-v1:0
+# Cross-region inference model IDs: us.anthropic.claude-sonnet-4-6,us.anthropic.claude-opus-4-6-v1,global.anthropic.claude-opus-4-6-v1
+
+# See all Bedrock model IDs here: https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns
+
+# Notes on specific models:
+# The following models are not support due to not supporting streaming:
+# ai21.j2-mid-v1
+
+# The following models are not support due to not supporting conversation history:
+# ai21.j2-ultra-v1, cohere.command-text-v14, cohere.command-light-text-v14
+
+#============#
+# Google     #
+#============#
+
+GOOGLE_KEY=user_provided
+
+# GOOGLE_REVERSE_PROXY=
+# Some reverse proxies do not support the X-goog-api-key header, uncomment to pass the API key in Authorization header instead.
+# GOOGLE_AUTH_HEADER=true
+
+# Gemini API (AI Studio)
+# GOOGLE_MODELS=gemini-3.1-pro-preview,gemini-3.1-pro-preview-customtools,gemini-3.1-flash-lite-preview,gemini-2.5-pro,gemini-2.5-flash,gemini-2.5-flash-lite,gemini-2.0-flash,gemini-2.0-flash-lite
+
+# Vertex AI
+# GOOGLE_MODELS=gemini-3.1-pro-preview,gemini-3.1-pro-preview-customtools,gemini-3.1-flash-lite-preview,gemini-2.5-pro,gemini-2.5-flash,gemini-2.5-flash-lite,gemini-2.0-flash-001,gemini-2.0-flash-lite-001
+
+# GOOGLE_TITLE_MODEL=gemini-2.0-flash-lite-001
+
+# Google Cloud region for Vertex AI (used by both chat and image generation)
+# GOOGLE_LOC=us-central1
+
+# Alternative region env var for Gemini Image Generation
+# GOOGLE_CLOUD_LOCATION=global
+
+# Vertex AI Service Account Configuration
+# Path to your Google Cloud service account JSON file
+# GOOGLE_SERVICE_KEY_FILE=/path/to/service-account.json
+
+# Google Safety Settings
+# NOTE: These settings apply to both Vertex AI and Gemini API (AI Studio)
+#
+# For Vertex AI:
+# To use the BLOCK_NONE setting, you need either:
+# (a) Access through an allowlist via your Google account team, or
+# (b) Switch to monthly invoiced billing: https://cloud.google.com/billing/docs/how-to/invoiced-billing
+#
+# For Gemini API (AI Studio):
+# BLOCK_NONE is available by default, no special account requirements.
+#
+# Available options: BLOCK_NONE, BLOCK_ONLY_HIGH, BLOCK_MEDIUM_AND_ABOVE, BLOCK_LOW_AND_ABOVE
+#
+# GOOGLE_SAFETY_SEXUALLY_EXPLICIT=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_HATE_SPEECH=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_HARASSMENT=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_DANGEROUS_CONTENT=BLOCK_ONLY_HIGH
+# GOOGLE_SAFETY_CIVIC_INTEGRITY=BLOCK_ONLY_HIGH
+
+#========================#
+# Gemini Image Generation #
+#========================#
+
+# Gemini Image Generation Tool (for Agents)
+# Supports multiple authentication methods in priority order:
+# 1. User-provided API key (via GUI)
+# 2. GEMINI_API_KEY env var (admin-configured)
+# 3. GOOGLE_KEY env var (shared with Google chat endpoint)
+# 4. Vertex AI service account (via GOOGLE_SERVICE_KEY_FILE)
+
+# Option A: Use dedicated Gemini API key for image generation
+# GEMINI_API_KEY=your-gemini-api-key
+
+# Vertex AI model for image generation (defaults to gemini-2.5-flash-image)
+# GEMINI_IMAGE_MODEL=gemini-2.5-flash-image
+
+#============#
+# OpenAI     #
+#============#
+
+OPENAI_API_KEY=user_provided
+# OPENAI_MODELS=gpt-5,gpt-5-codex,gpt-5-mini,gpt-5-nano,o3-pro,o3,o4-mini,gpt-4.1,gpt-4.1-mini,gpt-4.1-nano,o3-mini,o1-pro,o1,gpt-4o,gpt-4o-mini
+
+DEBUG_OPENAI=false
+
+# TITLE_CONVO=false
+# OPENAI_TITLE_MODEL=gpt-4o-mini
+
+# OPENAI_SUMMARIZE=true
+# OPENAI_SUMMARY_MODEL=gpt-4o-mini
+
+# OPENAI_FORCE_PROMPT=true
+
+# OPENAI_REVERSE_PROXY=
+
+# OPENAI_ORGANIZATION=
+
+#====================#
+#   Assistants API   #
+#====================#
+
+ASSISTANTS_API_KEY=user_provided
+# ASSISTANTS_BASE_URL=
+# ASSISTANTS_MODELS=gpt-4o,gpt-4o-mini,gpt-3.5-turbo-0125,gpt-3.5-turbo-16k-0613,gpt-3.5-turbo-16k,gpt-3.5-turbo,gpt-4,gpt-4-0314,gpt-4-32k-0314,gpt-4-0613,gpt-3.5-turbo-0613,gpt-3.5-turbo-1106,gpt-4-0125-preview,gpt-4-turbo-preview,gpt-4-1106-preview
+
+#==========================#
+#   Azure Assistants API   #
+#==========================#
+
+# Note: You should map your credentials with custom variables according to your Azure OpenAI Configuration
+# The models for Azure Assistants are also determined by your Azure OpenAI configuration.
+
+# More info, including how to enable use of Assistants with Azure here:
+# https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints/azure#using-assistants-with-azure
+
+CREDS_KEY=f34be427ebb29de8d88c107a71546019685ed8b241d8f2ed00c3df97ad2566f0
+CREDS_IV=e2341419ec3dd3d19b13a1a87fafcbfb
+
+# Azure AI Search
+#-----------------
+AZURE_AI_SEARCH_SERVICE_ENDPOINT=
+AZURE_AI_SEARCH_INDEX_NAME=
+AZURE_AI_SEARCH_API_KEY=
+
+AZURE_AI_SEARCH_API_VERSION=
+AZURE_AI_SEARCH_SEARCH_OPTION_QUERY_TYPE=
+AZURE_AI_SEARCH_SEARCH_OPTION_TOP=
+AZURE_AI_SEARCH_SEARCH_OPTION_SELECT=
+
+# OpenAI Image Tools Customization
+#----------------
+# IMAGE_GEN_OAI_API_KEY= # Create or reuse OpenAI API key for image generation tool
+# IMAGE_GEN_OAI_BASEURL= # Custom OpenAI base URL for image generation tool
+# IMAGE_GEN_OAI_AZURE_API_VERSION= # Custom Azure OpenAI deployments
+# IMAGE_GEN_OAI_MODEL=gpt-image-1 # OpenAI image model (e.g., gpt-image-1, gpt-image-1.5)
+# IMAGE_GEN_OAI_DESCRIPTION=
+# IMAGE_GEN_OAI_DESCRIPTION_WITH_FILES=Custom description for image generation tool when files are present
+# IMAGE_GEN_OAI_DESCRIPTION_NO_FILES=Custom description for image generation tool when no files are present
+# IMAGE_EDIT_OAI_DESCRIPTION=Custom description for image editing tool
+# IMAGE_GEN_OAI_PROMPT_DESCRIPTION=Custom prompt description for image generation tool
+# IMAGE_EDIT_OAI_PROMPT_DESCRIPTION=Custom prompt description for image editing tool
+
+# DALL·E
+#----------------
+# DALLE_API_KEY=
+# DALLE3_API_KEY=
+# DALLE2_API_KEY=
+# DALLE3_SYSTEM_PROMPT=
+# DALLE2_SYSTEM_PROMPT=
+# DALLE_REVERSE_PROXY=
+# DALLE3_BASEURL=
+# DALLE2_BASEURL=
+
+# DALL·E (via Azure OpenAI)
+# Note: requires some of the variables above to be set
+#----------------
+# DALLE3_AZURE_API_VERSION=
+# DALLE2_AZURE_API_VERSION=
+
+# Flux
+#-----------------
+FLUX_API_BASE_URL=https://api.us1.bfl.ai
+# FLUX_API_BASE_URL = 'https://api.bfl.ml';
+
+# Get your API key at https://api.us1.bfl.ai/auth/profile
+# FLUX_API_KEY=
+
+# Google
+#-----------------
+GOOGLE_SEARCH_API_KEY=
+GOOGLE_CSE_ID=
+
+# Stable Diffusion
+#-----------------
+SD_WEBUI_URL=http://host.docker.internal:7860
+
+# Tavily
+#-----------------
+TAVILY_API_KEY=
+
+# Traversaal
+#-----------------
+TRAVERSAAL_API_KEY=
+
+# WolframAlpha
+#-----------------
+WOLFRAM_APP_ID=
+
+# Zapier
+#-----------------
+ZAPIER_NLA_API_KEY=
+
+#==================================================#
+#                      Search                      #
+#==================================================#
+
+SEARCH=true
+MEILI_NO_ANALYTICS=true
+MEILI_HOST=http://0.0.0.0:7700
+MEILI_MASTER_KEY=DrhYf7zENyR6AlUCKmnz0eYASOQdl6zxH7s7MKFSfFCt
+
+# Optional: Disable indexing, useful in a multi-node setup
+# where only one instance should perform an index sync.
+# MEILI_NO_SYNC=true
+
+#==================================================#
+#          Speech to Text & Text to Speech         #
+#==================================================#
+
+STT_API_KEY=
+TTS_API_KEY=
+
+#==================================================#
+#                        RAG                       #
+#==================================================#
+# More info: https://www.librechat.ai/docs/configuration/rag_api
+
+# RAG_OPENAI_BASEURL=
+# RAG_OPENAI_API_KEY=
+# RAG_USE_FULL_CONTEXT=
+# EMBEDDINGS_PROVIDER=openai
+# EMBEDDINGS_MODEL=text-embedding-3-small
+
+#===================================================#
+#                    User System                    #
+#===================================================#
+
+#========================#
+# Moderation             #
+#========================#
+
+OPENAI_MODERATION=false
+OPENAI_MODERATION_API_KEY=
+# OPENAI_MODERATION_REVERSE_PROXY=
+
+BAN_VIOLATIONS=true
+BAN_DURATION=1000 * 60 * 60 * 2
+BAN_INTERVAL=20
+
+LOGIN_VIOLATION_SCORE=1
+REGISTRATION_VIOLATION_SCORE=1
+CONCURRENT_VIOLATION_SCORE=1
+MESSAGE_VIOLATION_SCORE=1
+NON_BROWSER_VIOLATION_SCORE=20
+TTS_VIOLATION_SCORE=0
+STT_VIOLATION_SCORE=0
+FORK_VIOLATION_SCORE=0
+IMPORT_VIOLATION_SCORE=0
+FILE_UPLOAD_VIOLATION_SCORE=0
+
+LOGIN_MAX=7
+LOGIN_WINDOW=5
+REGISTER_MAX=5
+REGISTER_WINDOW=60
+
+LIMIT_CONCURRENT_MESSAGES=true
+CONCURRENT_MESSAGE_MAX=2
+
+LIMIT_MESSAGE_IP=true
+MESSAGE_IP_MAX=40
+MESSAGE_IP_WINDOW=1
+
+LIMIT_MESSAGE_USER=false
+MESSAGE_USER_MAX=40
+MESSAGE_USER_WINDOW=1
+
+ILLEGAL_MODEL_REQ_SCORE=5
+
+#========================#
+# Balance                #
+#========================#
+
+# CHECK_BALANCE=false
+# START_BALANCE=20000 # note: the number of tokens that will be credited after registration.
+
+#========================#
+# Registration and Login #
+#========================#
+
+ALLOW_EMAIL_LOGIN=true
+ALLOW_REGISTRATION=true
+ALLOW_SOCIAL_LOGIN=false
+ALLOW_SOCIAL_REGISTRATION=false
+ALLOW_PASSWORD_RESET=false
+# ALLOW_ACCOUNT_DELETION=true # note: enabled by default if omitted/commented out
+ALLOW_UNVERIFIED_EMAIL_LOGIN=true
+
+SESSION_EXPIRY=1000 * 60 * 15
+REFRESH_TOKEN_EXPIRY=(1000 * 60 * 60 * 24) * 7
+
+JWT_SECRET=16f8c0ef4a5d391b26034086c628469d3f9f497f08163ab9b40137092f2909ef
+JWT_REFRESH_SECRET=eaa5191f2914e30b9387fd84e254e4ba6fc51b4654968a9b0803b456a54b8418
+
+# Discord
+DISCORD_CLIENT_ID=
+DISCORD_CLIENT_SECRET=
+DISCORD_CALLBACK_URL=/oauth/discord/callback
+
+# Facebook
+FACEBOOK_CLIENT_ID=
+FACEBOOK_CLIENT_SECRET=
+FACEBOOK_CALLBACK_URL=/oauth/facebook/callback
+
+# GitHub
+GITHUB_CLIENT_ID=
+GITHUB_CLIENT_SECRET=
+GITHUB_CALLBACK_URL=/oauth/github/callback
+# GitHub Enterprise
+# GITHUB_ENTERPRISE_BASE_URL=
+# GITHUB_ENTERPRISE_USER_AGENT=
+
+# Google
+GOOGLE_CLIENT_ID=
+GOOGLE_CLIENT_SECRET=
+GOOGLE_CALLBACK_URL=/oauth/google/callback
+
+# Apple
+APPLE_CLIENT_ID=
+APPLE_TEAM_ID=
+APPLE_KEY_ID=
+APPLE_PRIVATE_KEY_PATH=
+APPLE_CALLBACK_URL=/oauth/apple/callback
+
+# OpenID
+OPENID_CLIENT_ID=
+OPENID_CLIENT_SECRET=
+OPENID_ISSUER=
+OPENID_SESSION_SECRET=
+OPENID_SCOPE="openid profile email"
+OPENID_CALLBACK_URL=/oauth/openid/callback
+OPENID_REQUIRED_ROLE=
+OPENID_REQUIRED_ROLE_TOKEN_KIND=
+OPENID_REQUIRED_ROLE_PARAMETER_PATH=
+OPENID_ADMIN_ROLE=
+OPENID_ADMIN_ROLE_PARAMETER_PATH=
+OPENID_ADMIN_ROLE_TOKEN_KIND=
+# Set to determine which user info property returned from OpenID Provider to store as the User's username
+OPENID_USERNAME_CLAIM=
+# Set to determine which user info property returned from OpenID Provider to store as the User's name
+OPENID_NAME_CLAIM=
+# Set to determine which user info claim to use as the email/identifier for user matching (e.g., "upn" for Entra ID)
+# When not set, defaults to: email -> preferred_username -> upn
+OPENID_EMAIL_CLAIM=
+# Optional audience parameter for OpenID authorization requests
+OPENID_AUDIENCE=
+
+OPENID_BUTTON_LABEL=
+OPENID_IMAGE_URL=
+# Set to true to automatically redirect to the OpenID provider when a user visits the login page
+# This will bypass the login form completely for users, only use this if OpenID is your only authentication method
+OPENID_AUTO_REDIRECT=false
+# Set to true to use PKCE (Proof Key for Code Exchange) for OpenID authentication
+OPENID_USE_PKCE=false
+#Set to true to reuse openid tokens for authentication management instead of using the mongodb session and the custom refresh token.
+OPENID_REUSE_TOKENS=
+#By default, signing key verification results are cached in order to prevent excessive HTTP requests to the JWKS endpoint.
+#If a signing key matching the kid is found, this will be cached and the next time this kid is requested the signing key will be served from the cache.
+#Default is true.
+OPENID_JWKS_URL_CACHE_ENABLED=
+OPENID_JWKS_URL_CACHE_TIME= # 600000 ms eq to 10 minutes leave empty to disable caching
+#Set to true to trigger token exchange flow to acquire access token for the userinfo endpoint.
+OPENID_ON_BEHALF_FLOW_FOR_USERINFO_REQUIRED=
+OPENID_ON_BEHALF_FLOW_USERINFO_SCOPE="user.read" # example for Scope Needed for Microsoft Graph API
+# Set to true to use the OpenID Connect end session endpoint for logout
+OPENID_USE_END_SESSION_ENDPOINT=
+# URL to redirect to after OpenID logout (defaults to ${DOMAIN_CLIENT}/login)
+OPENID_POST_LOGOUT_REDIRECT_URI=
+# Maximum logout URL length before using logout_hint instead of id_token_hint (default: 2000)
+OPENID_MAX_LOGOUT_URL_LENGTH=
+
+#========================#
+# SharePoint Integration #
+#========================#
+# Requires Entra ID (OpenID) authentication to be configured
+
+# Enable SharePoint file picker in chat and agent panels
+# ENABLE_SHAREPOINT_FILEPICKER=true
+
+# SharePoint tenant base URL (e.g., https://yourtenant.sharepoint.com)
+# SHAREPOINT_BASE_URL=https://yourtenant.sharepoint.com
+
+# Microsoft Graph API And SharePoint scopes for file picker
+# SHAREPOINT_PICKER_SHAREPOINT_SCOPE==https://yourtenant.sharepoint.com/AllSites.Read
+# SHAREPOINT_PICKER_GRAPH_SCOPE=Files.Read.All
+#========================#
+
+# SAML
+# Note: If OpenID is enabled, SAML authentication will be automatically disabled.
+SAML_ENTRY_POINT=
+SAML_ISSUER=
+SAML_CERT=
+SAML_CALLBACK_URL=/oauth/saml/callback
+SAML_SESSION_SECRET=
+
+# Attribute mappings (optional)
+SAML_EMAIL_CLAIM=
+SAML_USERNAME_CLAIM=
+SAML_GIVEN_NAME_CLAIM=
+SAML_FAMILY_NAME_CLAIM=
+SAML_PICTURE_CLAIM=
+SAML_NAME_CLAIM=
+
+# Logint buttion settings (optional)
+SAML_BUTTON_LABEL=
+SAML_IMAGE_URL=
+
+# Whether the SAML Response should be signed.
+# - If "true", the entire `SAML Response` will be signed.
+# - If "false" or unset, only the `SAML Assertion` will be signed (default behavior).
+# SAML_USE_AUTHN_RESPONSE_SIGNED=
+
+
+#===============================================#
+# Microsoft Graph API / Entra ID Integration  #
+#===============================================#
+
+# Enable Entra ID people search integration in permissions/sharing system
+# When enabled, the people picker will search both local database and Entra ID
+USE_ENTRA_ID_FOR_PEOPLE_SEARCH=false
+
+# When enabled, entra id groups owners will be considered as members of the group
+ENTRA_ID_INCLUDE_OWNERS_AS_MEMBERS=false
+
+# Microsoft Graph API scopes needed for people/group search
+# Default scopes provide access to user profiles and group memberships
+OPENID_GRAPH_SCOPES=User.Read,People.Read,GroupMember.Read.All
+
+# LDAP
+LDAP_URL=
+LDAP_BIND_DN=
+LDAP_BIND_CREDENTIALS=
+LDAP_USER_SEARCH_BASE=
+#LDAP_SEARCH_FILTER="mail="
+LDAP_CA_CERT_PATH=
+# LDAP_TLS_REJECT_UNAUTHORIZED=
+# LDAP_STARTTLS=
+# LDAP_LOGIN_USES_USERNAME=true
+# LDAP_ID=
+# LDAP_USERNAME=
+# LDAP_EMAIL=
+# LDAP_FULL_NAME=
+
+#========================#
+# Email Password Reset   #
+#========================#
+
+EMAIL_SERVICE=
+EMAIL_HOST=
+EMAIL_PORT=25
+EMAIL_ENCRYPTION=
+EMAIL_ENCRYPTION_HOSTNAME=
+EMAIL_ALLOW_SELFSIGNED=
+# Leave both empty for SMTP servers that do not require authentication
+EMAIL_USERNAME=
+EMAIL_PASSWORD=
+EMAIL_FROM_NAME=
+EMAIL_FROM=noreply@librechat.ai
+
+#========================#
+#      Mailgun API       #
+#========================#
+
+# MAILGUN_API_KEY=your-mailgun-api-key
+# MAILGUN_DOMAIN=mg.yourdomain.com
+# EMAIL_FROM=noreply@yourdomain.com
+# EMAIL_FROM_NAME="LibreChat"
+
+# # Optional: For EU region
+# MAILGUN_HOST=https://api.eu.mailgun.net
+
+#========================#
+# Firebase CDN           #
+#========================#
+
+FIREBASE_API_KEY=
+FIREBASE_AUTH_DOMAIN=
+FIREBASE_PROJECT_ID=
+FIREBASE_STORAGE_BUCKET=
+FIREBASE_MESSAGING_SENDER_ID=
+FIREBASE_APP_ID=
+
+#========================#
+# S3 AWS Bucket          #
+#========================#
+
+AWS_ENDPOINT_URL=
+AWS_ACCESS_KEY_ID=
+AWS_SECRET_ACCESS_KEY=
+AWS_REGION=
+AWS_BUCKET_NAME=
+# Required for path-style S3-compatible providers (MinIO, Hetzner, Backblaze B2, etc.)
+# that don't support virtual-hosted-style URLs (bucket.endpoint). Not needed for AWS S3.
+# AWS_FORCE_PATH_STYLE=false
+
+#========================#
+# Azure Blob Storage     #
+#========================#
+
+AZURE_STORAGE_CONNECTION_STRING=
+AZURE_STORAGE_PUBLIC_ACCESS=false
+AZURE_CONTAINER_NAME=files
+
+#========================#
+# Shared Links           #
+#========================#
+
+ALLOW_SHARED_LINKS=true
+# Allows unauthenticated access to shared links. Defaults to false (auth required) if not set.
+ALLOW_SHARED_LINKS_PUBLIC=false
+
+#==============================#
+# Static File Cache Control    #
+#==============================#
+
+# Leave commented out to use defaults: 1 day (86400 seconds) for s-maxage and 2 days (172800 seconds) for max-age
+# NODE_ENV must be set to production for these to take effect
+# STATIC_CACHE_MAX_AGE=172800
+# STATIC_CACHE_S_MAX_AGE=86400
+
+# If you have another service in front of your LibreChat doing compression, disable express based compression here
+# DISABLE_COMPRESSION=true
+
+# If you have gzipped version of uploaded image images in the same folder, this will enable gzip scan and serving of these images
+# Note: The images folder will be scanned on startup and a ma kept in memory. Be careful for large number of images.
+# ENABLE_IMAGE_OUTPUT_GZIP_SCAN=true
+
+#===================================================#
+#                        UI                         #
+#===================================================#
+
+APP_TITLE=LibreChat
+# CUSTOM_FOOTER="My custom footer"
+HELP_AND_FAQ_URL=https://librechat.ai
+
+# SHOW_BIRTHDAY_ICON=true
+
+# Google tag manager id
+#ANALYTICS_GTM_ID=user provided google tag manager id
+
+# limit conversation file imports to a certain number of bytes in size to avoid the container
+# maxing out memory limitations by unremarking this line and supplying a file size in bytes
+# such as the below example of 250 mib
+# CONVERSATION_IMPORT_MAX_FILE_SIZE_BYTES=262144000
+
+
+#===============#
+# REDIS Options #
+#===============#
+
+# Enable Redis for caching and session storage
+# USE_REDIS=true
+# Enable Redis for resumable LLM streams (defaults to USE_REDIS value if not set)
+# Set to false to use in-memory storage for streams while keeping Redis for other caches
+# USE_REDIS_STREAMS=true
+
+# Single Redis instance
+# REDIS_URI=redis://127.0.0.1:6379
+
+# Redis cluster (multiple nodes)
+# REDIS_URI=redis://127.0.0.1:7001,redis://127.0.0.1:7002,redis://127.0.0.1:7003
+
+# Redis with TLS/SSL encryption and CA certificate
+# REDIS_URI=rediss://127.0.0.1:6380
+# REDIS_CA=/path/to/ca-cert.pem
+
+# Elasticache may need to use an alternate dnsLookup for TLS connections.  see "Special Note: Aws Elasticache Clusters with TLS" on this webpage: https://www.npmjs.com/package/ioredis
+# Enable alternative dnsLookup for redis
+# REDIS_USE_ALTERNATIVE_DNS_LOOKUP=true
+
+# Redis authentication (if required)
+# REDIS_USERNAME=your_redis_username
+# REDIS_PASSWORD=your_redis_password
+
+# Redis key prefix configuration
+# Use environment variable name for dynamic prefix (recommended for cloud deployments)
+# REDIS_KEY_PREFIX_VAR=K_REVISION
+# Or use static prefix directly
+# REDIS_KEY_PREFIX=librechat
+
+# Redis connection limits
+# REDIS_MAX_LISTENERS=40
+
+# Redis ping interval in seconds (0 = disabled, >0 = enabled)
+# When set to a positive integer, Redis clients will ping the server at this interval to keep connections alive
+# When unset or 0, no pinging is performed (recommended for most use cases)
+# REDIS_PING_INTERVAL=300
+
+# Force specific cache namespaces to use in-memory storage even when Redis is enabled
+# Comma-separated list of CacheKeys
+# Defaults to CONFIG_STORE,APP_CONFIG so YAML-derived config stays per-container (safe for blue/green deployments)
+# Set to empty string to force all namespaces through Redis: FORCED_IN_MEMORY_CACHE_NAMESPACES=
+# FORCED_IN_MEMORY_CACHE_NAMESPACES=CONFIG_STORE,APP_CONFIG
+
+# Leader Election Configuration (for multi-instance deployments with Redis)
+# Duration in seconds that the leader lease is valid before it expires (default: 25)
+# LEADER_LEASE_DURATION=25
+# Interval in seconds at which the leader renews its lease (default: 10)
+# LEADER_RENEW_INTERVAL=10
+# Maximum number of retry attempts when renewing the lease fails (default: 3)
+# LEADER_RENEW_ATTEMPTS=3
+# Delay in seconds between retry attempts when renewing the lease (default: 0.5)
+# LEADER_RENEW_RETRY_DELAY=0.5
+
+#==================================================#
+#                      Others                      #
+#==================================================#
+#   You should leave the following commented out   #
+
+# NODE_ENV=
+
+# E2E_USER_EMAIL=
+# E2E_USER_PASSWORD=
+
+#=====================================================#
+#                  Cache Headers                      #
+#=====================================================#
+#   Headers that control caching of the index.html    #
+#   Default configuration prevents caching to ensure  #
+#   users always get the latest version. Customize    #
+#   only if you understand caching implications.      #
+
+# INDEX_CACHE_CONTROL=no-cache, no-store, must-revalidate
+# INDEX_PRAGMA=no-cache
+# INDEX_EXPIRES=0
+
+# no-cache: Forces validation with server before using cached version
+# no-store: Prevents storing the response entirely
+# must-revalidate: Prevents using stale content when offline
+
+#=====================================================#
+#                  OpenWeather                        #
+#=====================================================#
+OPENWEATHER_API_KEY=
+
+#====================================#
+# LibreChat Code Interpreter API     #
+#====================================#
+
+# https://code.librechat.ai
+# LIBRECHAT_CODE_API_KEY=your-key
+
+#======================#
+# Web Search           #
+#======================#
+
+# Note: All of the following variable names can be customized.
+# Omit values to allow user to provide them.
+
+# For more information on configuration values, see:
+# https://librechat.ai/docs/features/web_search
+
+# Search Provider (Required)
+# SERPER_API_KEY=your_serper_api_key
+
+# Scraper (Required)
+# FIRECRAWL_API_KEY=your_firecrawl_api_key
+# Optional: Custom Firecrawl API URL
+# FIRECRAWL_API_URL=your_firecrawl_api_url
+
+# Reranker (Required)
+# JINA_API_KEY=your_jina_api_key
+# or
+# COHERE_API_KEY=your_cohere_api_key
+
+#======================#
+# MCP Configuration    #
+#======================#
+
+# Treat 401/403 responses as OAuth requirement when no oauth metadata found
+# MCP_OAUTH_ON_AUTH_ERROR=true
+
+# Timeout for OAuth detection requests in milliseconds
+# MCP_OAUTH_DETECTION_TIMEOUT=5000
+
+# Cache connection status checks for this many milliseconds to avoid expensive verification
+# MCP_CONNECTION_CHECK_TTL=60000
+
+# Skip code challenge method validation (e.g., for AWS Cognito that supports S256 but doesn't advertise it)
+# When set to true, forces S256 code challenge even if not advertised in .well-known/openid-configuration
+# MCP_SKIP_CODE_CHALLENGE_CHECK=false
+
+# Circuit breaker: max connect/disconnect cycles before tripping (per server)
+# MCP_CB_MAX_CYCLES=7
+
+# Circuit breaker: sliding window (ms) for counting cycles
+# MCP_CB_CYCLE_WINDOW_MS=45000
+
+# Circuit breaker: cooldown (ms) after the cycle breaker trips
+# MCP_CB_CYCLE_COOLDOWN_MS=15000
+
+# Circuit breaker: max consecutive failed connection rounds before backoff
+# MCP_CB_MAX_FAILED_ROUNDS=3
+
+# Circuit breaker: sliding window (ms) for counting failed rounds
+# MCP_CB_FAILED_WINDOW_MS=120000
+
+# Circuit breaker: base backoff (ms) after failed round threshold is reached
+# MCP_CB_BASE_BACKOFF_MS=30000
+
+# Circuit breaker: max backoff cap (ms) for exponential backoff
+# MCP_CB_MAX_BACKOFF_MS=300000

librechat/librechat.yaml

@@ -6,9 +6,7 @@ cache: true
 endpoints:
   anthropic:
     apiKey: "${ANTHROPIC_API_KEY}"
-    models:
-      default: ["claude-sonnet-4-5", "claude-haiku-4-5", "claude-opus-4-5"]
-      fetch: false
+    models: ["claude-sonnet-4-5", "claude-haiku-4-5", "claude-opus-4-5"]
     titleConvo: true
     titleModel: "claude-haiku-4-5"
     modelDisplayLabel: "Claude AI"
@@ -72,7 +70,7 @@ endpoints:
       apiKey: "dummy_key"
       baseURL: "http://alfred:8000/v1"
       models:
-        default: ["local-deepseek-agent"]
+        default: ["glm-4.7-flash:latest"]
         fetch: false
       titleConvo: false
       titleModel: "current_model"

mongod.conf

@@ -0,0 +1,45 @@
+# MongoDB Configuration File
+
+# Network settings
+net:
+  port: 27017
+  bindIp: 0.0.0.0
+
+# Storage settings
+storage:
+  dbPath: /data/db
+
+# System log settings
+systemLog:
+  destination: file
+  path: /dev/stdout
+  logAppend: true
+  verbosity: 0
+  quiet: true
+  component:
+    accessControl:
+      verbosity: -1
+    command:
+      verbosity: 0
+    control:
+      verbosity: 0
+    ftdc:
+      verbosity: 0
+    geo:
+      verbosity: 0
+    index:
+      verbosity: 0
+    network:
+      verbosity: 0
+    query:
+      verbosity: 0
+    replication:
+      verbosity: 0
+    sharding:
+      verbosity: 0
+    storage:
+      verbosity: 0
+    write:
+      verbosity: 0
+    transaction:
+      verbosity: 0

pyproject.toml

@@ -1,50 +1,67 @@
-[tool.poetry]
+[project]
 name = "alfred"
 version = "0.1.7"
 description = "AI agent for managing a local media library"
 authors = ["Francwa <francois.hodiaumont@gmail.com>"]
 readme = "README.md"
-package-mode = false
+requires-python = "==3.14.3"
+dependencies = [
+    "python-dotenv~=1.0.0",
+    "requests~=2.32.5",
+    "fastapi~=0.127.1",
+    "pydantic~=2.12.4",
+    "uvicorn~=0.40.0",
+    "httpx~=0.28.1",
+    "pydantic-settings~=2.12.0",
+    "click~=8.1",
+]
 
-[tool.alfred.settings]
+[tool.alfred]
 image_name = "alfred_media_organizer"
-librechat_version = "v0.8.1"
-rag_version = "v0.7.0"
-runner = "poetry"
+librechat_version = "v0.8.4"
+rag_version = "v0.7.3"
 service_name = "alfred"
+uv_version = "0.11.6"
 
-[tool.alfred.security]
-jwt_secret = "32:b64"
-jwt_refresh_secret = "32:b64"
-creds_key = "32:b64"
-creds_iv = "16:b64"
-meili_master_key = "32:b64"
-mongo_password = "16:hex"
-postgres_password = "16:hex"
-qbittorrent_password = "16:hex"
+[tool.alfred.secrets]
+JWT_SECRET = "32:hex"
+JWT_REFRESH_SECRET = "32:hex"
+CREDS_KEY = "32:hex"
+CREDS_IV = "16:hex"
+MEILI_MASTER_KEY = "32:b64"
+MONGO_PASSWORD = "16:hex"
+POSTGRES_PASSWORD = "16:hex"
+QBITTORRENT_PASSWORD = "16:hex"
 
-[tool.poetry.dependencies]
-python = "==3.14.2"
-python-dotenv = "^1.0.0"
-requests = "^2.32.5"
-fastapi = "^0.127.1"
-pydantic = "^2.12.4"
-uvicorn = "^0.40.0"
-pytest-xdist = "^3.8.0"
-httpx = "^0.28.1"
-pydantic-settings = "^2.12.0"
+[tool.alfred.config.pattern]
+type = "multi"
+patterns = [
+    "^#[=\\-*#]{3,}#?\\s*$",
+    "^#\\s+(.+?)\\s+#\\s*$",
+    "^#[=\\-*#]{3,}#?\\s*$",
+]
+
+[tool.alfred.config]
+extra_fields = []
+
+[tool.uv]
+package = false
+
+[dependency-groups]
+dev = [
+    "pytest~=8.0.0",
+    "pytest-cov~=4.1.0",
+    "pytest-asyncio~=0.23.0",
+    "pytest-xdist~=3.8.0",
+    "ruff~=0.14.7",
+    "pre-commit~=4.5.1",
+    "bump-my-version~=1.2.5",
+]
 
-[tool.poetry.group.dev.dependencies]
-pytest = "^8.0.0"
-pytest-cov = "^4.1.0"
-pytest-asyncio = "^0.23.0"
-ruff = "^0.15.0"
-pre-commit = "^4.5.1"
-bump-my-version = "^1.2.5"
 
 [build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
+requires = ["hatchling"]
+build-backend = "hatchling.build"
 
 [tool.pytest.ini_options]
 # Chemins où pytest cherche les tests

scripts/bootstrap.py

@@ -1,239 +1,184 @@
+#!/usr/bin/env python3
+"""Bootstrap script - generates .env.alfred, .env.librechat, .env.secrets and .env.make."""
+
+import re
 import secrets
+import sys
 from pathlib import Path
 
 import tomllib
-from config_loader import load_build_config, write_env_make
+
+BASE_DIR = Path(__file__).resolve().parent.parent
+
+def load_secrets_spec(toml_data: dict) -> dict[str, tuple[int, str]]:
+    """Load secrets spec from pyproject.toml [tool.alfred.secrets]."""
+    raw = toml_data.get("tool", {}).get("alfred", {}).get("secrets", {})
+    result = {}
+    for key, rule in raw.items():
+        size_str, fmt = rule.split(":")
+        result[key] = (int(size_str), fmt)
+    return result
 
 
-def generate_secret(rule: str) -> str:
-    """
-    Generates a cryptographically secure secret based on a spec string.
-    Example specs: '32:b64', '16:hex'.
-    """
-    chunks: list[str] = rule.split(":")
-    size: int = int(chunks[0])
-    tech: str = chunks[1]
+def generate_secret(size: int, fmt: str) -> str:
+    match fmt:
+        case "hex":
+            return secrets.token_hex(size)
+        case "b64":
+            return secrets.token_urlsafe(size)
+        case _:
+            raise ValueError(f"Unknown format: {fmt}")
 
-    if tech == "b64":
-        return secrets.token_urlsafe(size)
-    elif tech == "hex":
-        return secrets.token_hex(size)
+
+def load_env_file(path: Path) -> dict[str, str]:
+    """Load key=value pairs from an env file, ignoring comments and blanks."""
+    result = {}
+    if not path.exists():
+        return result
+    for line in path.read_text().splitlines():
+        stripped = line.strip()
+        if stripped and not stripped.startswith("#") and "=" in stripped:
+            key, _, value = stripped.partition("=")
+            result[key.strip()] = value.strip()
+    return result
+
+
+def copy_example_if_missing(src: Path, dst: Path, label: str) -> None:
+    """Copy src to dst only if dst doesn't exist yet."""
+    if dst.exists():
+        print(f"  ↻ {dst.name} already exists, skipping")
+        return
+    if not src.exists():
+        print(f"  ⚠ {label} example not found at {src} — skipping (add it manually)")
+        return
+    dst.write_text(src.read_text())
+    print(f"  + {dst.name} created from {src.name}")
+
+
+def generate_secrets_file(path: Path, secrets_spec: dict[str, tuple[int, str]]) -> None:
+    """Generate .env.secrets with missing secrets, never overwrite existing ones."""
+    existing = load_env_file(path)
+    lines = list(path.read_text().splitlines()) if path.exists() else [
+        "# Auto-generated secrets — DO NOT COMMIT",
+        "# Run 'make bootstrap' to generate missing secrets",
+        "",
+    ]
+
+    added = []
+    for key, (size, fmt) in secrets_spec.items():
+        if key not in existing:
+            value = generate_secret(size, fmt)
+            lines.append(f"{key}={value}")
+            added.append(key)
+
+    path.write_text("\n".join(lines) + "\n")
+
+    if added:
+        print(f"  + Generated: {', '.join(added)}")
     else:
-        raise ValueError(f"Invalid security format: {tech}")
+        print("  ↻ All secrets already exist, nothing generated")
 
 
 def extract_python_version(version_string: str) -> tuple[str, str]:
-    """
-    Extract Python version from poetry dependency string.
-    Examples:
-        "==3.14.2" -> ("3.14.2", "3.14")
-        "^3.14.2" -> ("3.14.2", "3.14")
-        "~3.14.2" -> ("3.14.2", "3.14")
-        "3.14.2" -> ("3.14.2", "3.14")
-    """
-    import re  # noqa: PLC0415
-
-    # Remove poetry version operators (==, ^, ~, >=, etc.)
-    clean_version = re.sub(r"^[=^~><]+", "", version_string.strip())
-
-    # Extract version parts
-    parts = clean_version.split(".")
-
+    clean = re.sub(r"^[=^~><]+", "", version_string.strip())
+    parts = clean.split(".")
     if len(parts) >= 2:
-        full_version = clean_version
-        short_version = f"{parts[0]}.{parts[1]}"
-        return full_version, short_version
+        return clean, f"{parts[0]}.{parts[1]}"
+    raise ValueError(f"Invalid Python version: {version_string}")
+
+
+def build_uris(env_alfred: Path, env_secrets: Path) -> None:
+    """Build MONGO_URI and POSTGRES_URI from components and append them to .env.secrets."""
+    env = {**load_env_file(env_alfred), **load_env_file(env_secrets)}
+    existing = load_env_file(env_secrets)
+
+    computed = {
+        "MONGO_URI": (
+            f"mongodb://{env['MONGO_USER']}:{env['MONGO_PASSWORD']}"
+            f"@{env['MONGO_HOST']}:{env['MONGO_PORT']}/{env['MONGO_DB_NAME']}"
+            f"?authSource=admin"
+        ),
+        "POSTGRES_URI": (
+            f"postgresql://{env['POSTGRES_USER']}:{env['POSTGRES_PASSWORD']}"
+            f"@{env['POSTGRES_HOST']}:{env['POSTGRES_PORT']}/{env['POSTGRES_DB_NAME']}"
+        ),
+    }
+
+    content = env_secrets.read_text()
+    added = []
+    for key, value in computed.items():
+        if key in existing:
+            content = re.sub(rf"^{key}=.*$", f"{key}={value}", content, flags=re.MULTILINE)
+        else:
+            content = content.rstrip("\n") + f"\n{key}={value}\n"
+            added.append(key)
+    env_secrets.write_text(content)
+
+    if added:
+        print(f"  + Computed: {', '.join(added)}")
     else:
-        raise ValueError(f"Invalid Python version format: {version_string}")
+        print("  ↻ URIs updated")
 
 
-# TODO: Refactor
-def bootstrap():  # noqa: PLR0912, PLR0915
-    """
-    Initializes the .env file by merging .env.example with generated secrets
-    and build variables from pyproject.toml.
-    Also generates .env.make for Makefile.
+def write_env_make(toml_data: dict) -> None:
+    """Write .env.make from pyproject.toml."""
+    project = toml_data["project"]
+    alfred = toml_data["tool"]["alfred"]
 
-    ALWAYS preserves existing secrets!
-    """
-    base_dir = Path(__file__).resolve().parent.parent
-    env_path = base_dir / ".env"
+    python_full, python_short = extract_python_version(project["requires-python"])
 
-    example_path = base_dir / ".env.example"
-    if not example_path.exists():
-        print(f"❌ {example_path.name} not found.")
-        return
+    lines = [
+        "# Auto-generated from pyproject.toml — do not edit manually",
+        f"ALFRED_VERSION={project['version']}",
+        f"PYTHON_VERSION={python_full}",
+        f"IMAGE_NAME={alfred['image_name']}",
+        f"SERVICE_NAME={alfred['service_name']}",
+        f"LIBRECHAT_VERSION={alfred['librechat_version']}",
+        f"RAG_VERSION={alfred['rag_version']}",
+        f"UV_VERSION={alfred['uv_version']}",
+    ]
 
-    toml_path = base_dir / "pyproject.toml"
+    env_make_path = BASE_DIR / ".env.make"
+    env_make_path.write_text("\n".join(lines) + "\n")
+    print(f"  + {env_make_path.name} written")
+
+
+def main() -> int:
+    print("🚀 Starting bootstrap...")
+
+    toml_path = BASE_DIR / "pyproject.toml"
     if not toml_path.exists():
-        print(f"❌ {toml_path.name} not found.")
-        return
+        print(f"❌ pyproject.toml not found: {toml_path}")
+        return 1
 
-    # ALWAYS load existing .env if it exists
-    existing_env = {}
-    if env_path.exists():
-        print("🔄 Reading existing .env...")
-        with open(env_path) as f:
-            for line in f:
-                if "=" in line and not line.strip().startswith("#"):
-                    key, value = line.split("=", 1)
-                    existing_env[key.strip()] = value.strip()
-        print(f"   Found {len(existing_env)} existing keys")
-        print("🔧 Updating .env file (keeping secrets)...")
-    else:
-        print("🔧 Initializing: Creating secure .env file...")
-
-    # Load data from pyproject.toml
     with open(toml_path, "rb") as f:
-        data = tomllib.load(f)
-        security_keys = data["tool"]["alfred"]["security"]
-        settings_keys = data["tool"]["alfred"]["settings"]
-        dependencies = data["tool"]["poetry"]["dependencies"]
-        alfred_version = data["tool"]["poetry"]["version"]
+        toml_data = tomllib.load(f)
 
-    # Normalize TOML keys to UPPER_CASE for .env format (done once)
-    security_keys_upper = {k.upper(): v for k, v in security_keys.items()}
-    settings_keys_upper = {k.upper(): v for k, v in settings_keys.items()}
-
-    # Extract Python version
-    python_version_full, python_version_short = extract_python_version(
-        dependencies["python"]
+    print("\n📄 Env files:")
+    copy_example_if_missing(
+        src=BASE_DIR / ".env.example",
+        dst=BASE_DIR / ".env.alfred",
+        label="Alfred",
+    )
+    copy_example_if_missing(
+        src=BASE_DIR / "librechat" / ".env.example",
+        dst=BASE_DIR / ".env.librechat",
+        label="LibreChat",
     )
 
-    # Read .env.example
-    with open(example_path) as f:
-        example_lines = f.readlines()
+    secrets_spec = load_secrets_spec(toml_data)
+    print("\n🔐 Secrets:")
+    generate_secrets_file(BASE_DIR / ".env.secrets", secrets_spec)
 
-    new_lines = []
-    # Process each line from .env.example
-    for raw_line in example_lines:
-        line = raw_line.strip()
+    print("\n🔗 URIs:")
+    build_uris(BASE_DIR / ".env.alfred", BASE_DIR / ".env.secrets")
 
-        if line and not line.startswith("#") and "=" in line:
-            key, value = line.split("=", 1)
-            key = key.strip()
+    print("\n🔧 Build config:")
+    write_env_make(toml_data)
 
-            # Check if key exists in current .env (update mode)
-            if key in existing_env:
-                # Keep existing value for secrets
-                if key in security_keys_upper:
-                    new_lines.append(f"{key}={existing_env[key]}\n")
-                    print(f"  ↻ Kept existing {key}")
-                # Update build vars from pyproject.toml
-                elif key in settings_keys_upper:
-                    new_value = settings_keys_upper[key]
-                    if existing_env[key] != new_value:
-                        new_lines.append(f"{key}={new_value}\n")
-                        print(f"  ↻ Updated {key}: {existing_env[key]} → {new_value}")
-                    else:
-                        new_lines.append(f"{key}={existing_env[key]}\n")
-                        print(f"  ↻ Kept {key}={existing_env[key]}")
-                # Update Python versions
-                elif key == "PYTHON_VERSION":
-                    if existing_env[key] != python_version_full:
-                        new_lines.append(f"{key}={python_version_full}\n")
-                        print(
-                            f"  ↻ Updated Python: {existing_env[key]} → {python_version_full}"
-                        )
-                    else:
-                        new_lines.append(f"{key}={existing_env[key]}\n")
-                        print(f"  ↻ Kept Python: {existing_env[key]}")
-                elif key == "PYTHON_VERSION_SHORT":
-                    if existing_env[key] != python_version_short:
-                        new_lines.append(f"{key}={python_version_short}\n")
-                        print(
-                            f"  ↻ Updated Python (short): {existing_env[key]} → {python_version_short}"
-                        )
-                    else:
-                        new_lines.append(f"{key}={existing_env[key]}\n")
-                        print(f"  ↻ Kept Python (short): {existing_env[key]}")
-                elif key == "ALFRED_VERSION":
-                    if existing_env.get(key) != alfred_version:
-                        new_lines.append(f"{key}={alfred_version}\n")
-                        print(
-                            f"  ↻ Updated Alfred version: {existing_env.get(key, 'N/A')} → {alfred_version}"
-                        )
-                    else:
-                        new_lines.append(f"{key}={alfred_version}\n")
-                        print(f"  ↻ Kept Alfred version: {alfred_version}")
-                # Keep other existing values
-                else:
-                    new_lines.append(f"{key}={existing_env[key]}\n")
-            # Key doesn't exist, generate/add it
-            elif key in security_keys_upper:
-                rule = security_keys_upper[key]
-                secret = generate_secret(rule)
-                new_lines.append(f"{key}={secret}\n")
-                print(f"  + Secret generated for {key} ({rule})")
-            elif key in settings_keys_upper:
-                value = settings_keys_upper[key]
-                new_lines.append(f"{key}={value}\n")
-                print(f"  + Setting added: {key}={value}")
-            elif key == "PYTHON_VERSION":
-                new_lines.append(f"{key}={python_version_full}\n")
-                print(f"  + Python version: {python_version_full}")
-            elif key == "PYTHON_VERSION_SHORT":
-                new_lines.append(f"{key}={python_version_short}\n")
-                print(f"  + Python version (short): {python_version_short}")
-            elif key == "ALFRED_VERSION":
-                new_lines.append(f"{key}={alfred_version}\n")
-                print(f"  + Alfred version: {alfred_version}")
-            else:
-                new_lines.append(raw_line)
-        else:
-            # Keep comments and empty lines
-            new_lines.append(raw_line)
-
-    # Compute database URIs from the generated values
-    final_env = {}
-    for line in new_lines:
-        if "=" in line and not line.strip().startswith("#"):
-            key, value = line.split("=", 1)
-            final_env[key.strip()] = value.strip()
-
-    # Compute MONGO_URI
-    if "MONGO_USER" in final_env and "MONGO_PASSWORD" in final_env:
-        mongo_uri = (
-            f"mongodb://{final_env.get('MONGO_USER', 'alfred')}:"
-            f"{final_env.get('MONGO_PASSWORD', '')}@"
-            f"{final_env.get('MONGO_HOST', 'mongodb')}:"
-            f"{final_env.get('MONGO_PORT', '27017')}/"
-            f"{final_env.get('MONGO_DB_NAME', 'alfred')}?authSource=admin"
-        )
-        # Update MONGO_URI in new_lines
-        for i, line in enumerate(new_lines):
-            if line.startswith("MONGO_URI="):
-                new_lines[i] = f"MONGO_URI={mongo_uri}\n"
-                print("  ✓ Computed MONGO_URI")
-                break
-
-    # Compute POSTGRES_URI
-    if "POSTGRES_USER" in final_env and "POSTGRES_PASSWORD" in final_env:
-        postgres_uri = (
-            f"postgresql://{final_env.get('POSTGRES_USER', 'alfred')}:"
-            f"{final_env.get('POSTGRES_PASSWORD', '')}@"
-            f"{final_env.get('POSTGRES_HOST', 'vectordb')}:"
-            f"{final_env.get('POSTGRES_PORT', '5432')}/"
-            f"{final_env.get('POSTGRES_DB_NAME', 'alfred')}"
-        )
-        # Update POSTGRES_URI in new_lines
-        for i, line in enumerate(new_lines):
-            if line.startswith("POSTGRES_URI="):
-                new_lines[i] = f"POSTGRES_URI={postgres_uri}\n"
-                print("  ✓ Computed POSTGRES_URI")
-                break
-
-    # Write .env file
-    with open(env_path, "w", encoding="utf-8") as f:
-        f.writelines(new_lines)
-    print(f"\n✅ {env_path.name} generated successfully.")
-
-    # Generate .env.make for Makefile using shared config loader
-    config = load_build_config(base_dir)
-    write_env_make(config, base_dir)
-    print("✅ .env.make generated for Makefile.")
-    print("\n⚠️  Reminder: Please manually add your API keys to the .env file.")
+    print("\n✅ Bootstrap complete!")
+    return 0
 
 
 if __name__ == "__main__":
-    bootstrap()
+    sys.exit(main())

scripts/config_loader.py

@@ -1,4 +1,4 @@
-"""Shared configuration loader for bootstrap and CI."""
+"""Shared configuration loader — reads build config from pyproject.toml."""
 
 import re
 from pathlib import Path
@@ -13,31 +13,25 @@ class BuildConfig(NamedTuple):
     alfred_version: str
     python_version: str
     python_version_short: str
-    runner: str
     image_name: str
     service_name: str
     librechat_version: str
     rag_version: str
+    uv_version: str
 
 
 def extract_python_version(version_string: str) -> tuple[str, str]:
     """
-    Extract Python version from poetry dependency string.
+    Extract Python version from uv dependency string.
     Examples:
         "==3.14.2" -> ("3.14.2", "3.14")
-        "^3.14.2" -> ("3.14.2", "3.14")
-        "~3.14.2" -> ("3.14.2", "3.14")
-        "3.14.2" -> ("3.14.2", "3.14")
+        "^3.14.2"  -> ("3.14.2", "3.14")
     """
-    clean_version = re.sub(r"^[=^~><]+", "", version_string.strip())
-    parts = clean_version.split(".")
-
+    clean = re.sub(r"^[=^~><]+", "", version_string.strip())
+    parts = clean.split(".")
     if len(parts) >= 2:
-        full_version = clean_version
-        short_version = f"{parts[0]}.{parts[1]}"
-        return full_version, short_version
-    else:
-        raise ValueError(f"Invalid Python version format: {version_string}")
+        return clean, f"{parts[0]}.{parts[1]}"
+    raise ValueError(f"Invalid Python version format: {version_string}")
 
 
 def load_build_config(base_dir: Path | None = None) -> BuildConfig:
@@ -51,23 +45,21 @@ def load_build_config(base_dir: Path | None = None) -> BuildConfig:
 
     with open(toml_path, "rb") as f:
         data = tomllib.load(f)
-        settings_keys = data["tool"]["alfred"]["settings"]
-        dependencies = data["tool"]["poetry"]["dependencies"]
-        alfred_version = data["tool"]["poetry"]["version"]
 
-    python_version_full, python_version_short = extract_python_version(
-        dependencies["python"]
-    )
+    project = data["project"]
+    alfred = data["tool"]["alfred"]
+
+    python_full, python_short = extract_python_version(project["requires-python"])
 
     return BuildConfig(
-        alfred_version=alfred_version,
-        python_version=python_version_full,
-        python_version_short=python_version_short,
-        runner=settings_keys["runner"],
-        image_name=settings_keys["image_name"],
-        service_name=settings_keys["service_name"],
-        librechat_version=settings_keys["librechat_version"],
-        rag_version=settings_keys["rag_version"],
+        alfred_version=project["version"],
+        python_version=python_full,
+        python_version_short=python_short,
+        image_name=alfred["image_name"],
+        service_name=alfred["service_name"],
+        librechat_version=alfred["librechat_version"],
+        rag_version=alfred["rag_version"],
+        uv_version=alfred["uv_version"],
     )
 
 
@@ -76,14 +68,16 @@ def write_env_make(config: BuildConfig, base_dir: Path | None = None) -> None:
     if base_dir is None:
         base_dir = Path(__file__).resolve().parent.parent
 
+    lines = [
+        "# Auto-generated from pyproject.toml — do not edit manually",
+        f"export ALFRED_VERSION={config.alfred_version}",
+        f"export PYTHON_VERSION={config.python_version}",
+        f"export IMAGE_NAME={config.image_name}",
+        f"export SERVICE_NAME={config.service_name}",
+        f"export LIBRECHAT_VERSION={config.librechat_version}",
+        f"export RAG_VERSION={config.rag_version}",
+        f"export UV_VERSION={config.uv_version}",
+    ]
+
     env_make_path = base_dir / ".env.make"
-    with open(env_make_path, "w", encoding="utf-8") as f:
-        f.write("# Auto-generated from pyproject.toml\n")
-        f.write(f"export ALFRED_VERSION={config.alfred_version}\n")
-        f.write(f"export PYTHON_VERSION={config.python_version}\n")
-        f.write(f"export PYTHON_VERSION_SHORT={config.python_version_short}\n")
-        f.write(f"export RUNNER={config.runner}\n")
-        f.write(f"export IMAGE_NAME={config.image_name}\n")
-        f.write(f"export SERVICE_NAME={config.service_name}\n")
-        f.write(f"export LIBRECHAT_VERSION={config.librechat_version}\n")
-        f.write(f"export RAG_VERSION={config.rag_version}\n")
+    env_make_path.write_text("\n".join(lines) + "\n")

scripts/generate_build_vars.py

@@ -1,22 +0,0 @@
-#!/usr/bin/env python3
-"""Generate .env.make for CI/CD without generating secrets."""
-
-import sys
-
-from config_loader import load_build_config, write_env_make
-
-
-def main():
-    """Generate .env.make from pyproject.toml."""
-    try:
-        config = load_build_config()
-        write_env_make(config)
-        print("✅ .env.make generated successfully.")
-        return 0
-    except Exception as e:
-        print(f"❌ Failed to generate .env.make: {e}")
-        return 1
-
-
-if __name__ == "__main__":
-    sys.exit(main())

testing/subtitles/scan_subtitles.py

@@ -0,0 +1,528 @@
+#!/usr/bin/env python3
+"""
+scan_subtitles.py — CLI pour tester le pipeline de scan de sous-titres Alfred.
+
+Usage:
+    uv run testing/subtitles/scan_subtitles.py <season_folder> [options]
+
+Options:
+    --release-group RARBG     Groupe de release (optionnel — active les known patterns)
+    --pattern adjacent        Forcer un pattern (adjacent|flat|episode_subfolder|embedded)
+    --video FILE              Fichier vidéo de référence (défaut: premier .mkv/.mp4 trouvé)
+    --verbose                 Détails sur chaque token analysé
+    --no-color                Désactive la colorisation
+
+Exemples:
+    uv run scripts/scan_subtitles.py "/media/tv/The X-Files/Season 01"
+    uv run scripts/scan_subtitles.py "/media/tv/The X-Files/Season 01" --release-group RARBG
+    uv run scripts/scan_subtitles.py "/media/tv/The X-Files/Season 01" --pattern episode_subfolder --verbose
+"""
+
+import argparse
+import sys
+import textwrap
+from pathlib import Path
+
+# Ajoute la racine du projet au path (testing/subtitles/ → ../../)
+_PROJECT_ROOT = Path(__file__).resolve().parents[2]
+if str(_PROJECT_ROOT) not in sys.path:
+    sys.path.insert(0, str(_PROJECT_ROOT))
+
+# ---------------------------------------------------------------------------
+# Colorisation simple (pas de dépendance externe)
+# ---------------------------------------------------------------------------
+
+USE_COLOR = True
+
+RESET  = "\033[0m"
+BOLD   = "\033[1m"
+DIM    = "\033[2m"
+GREEN  = "\033[32m"
+YELLOW = "\033[33m"
+RED    = "\033[31m"
+CYAN   = "\033[36m"
+BLUE   = "\033[34m"
+MAGENTA = "\033[35m"
+
+
+def c(text: str, *codes: str) -> str:
+    if not USE_COLOR:
+        return text
+    return "".join(codes) + text + RESET
+
+
+def section(title: str) -> None:
+    width = 70
+    print()
+    print(c("─" * width, DIM))
+    print(c(f"  {title}", BOLD, CYAN))
+    print(c("─" * width, DIM))
+
+
+def ok(msg: str) -> None:
+    print(c("  ✓ ", GREEN, BOLD) + msg)
+
+
+def warn(msg: str) -> None:
+    print(c("  ⚠ ", YELLOW, BOLD) + msg)
+
+
+def err(msg: str) -> None:
+    print(c("  ✗ ", RED, BOLD) + msg)
+
+
+def info(msg: str, indent: int = 2) -> None:
+    print(" " * indent + msg)
+
+
+def kv(key: str, value: str, indent: int = 4) -> None:
+    print(" " * indent + c(f"{key}: ", BOLD) + value)
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+VIDEO_EXTS = {".mkv", ".mp4", ".avi", ".mov", ".ts", ".m2ts"}
+
+
+def find_videos(folder: Path) -> list[Path]:
+    return sorted(
+        p for p in folder.iterdir()
+        if p.is_file() and p.suffix.lower() in VIDEO_EXTS
+    )
+
+
+def confidence_bar(conf: float, width: int = 20) -> str:
+    filled = int(conf * width)
+    bar = "█" * filled + "░" * (width - filled)
+    if conf >= 0.8:
+        color = GREEN
+    elif conf >= 0.5:
+        color = YELLOW
+    else:
+        color = RED
+    return c(bar, color) + c(f" {conf:.0%}", BOLD)
+
+
+def track_summary(track, verbose: bool = False) -> None:
+    lang = track.language.code if track.language else c("?", RED)
+    fmt  = track.format.id if track.format else c("?", RED)
+    typ  = track.subtitle_type.value
+    src  = "embedded" if track.is_embedded else (track.file_path.name if track.file_path else "?")
+
+    # Couleur du type
+    type_colors = {
+        "standard": GREEN,
+        "sdh": YELLOW,
+        "forced": BLUE,
+        "unknown": RED,
+    }
+    typ_str = c(typ, type_colors.get(typ, RESET))
+
+    unresolved = not track.is_embedded and track.language is None
+    clarif = c(" [langue inconnue]", RED, BOLD) if unresolved else ""
+
+    print(f"    {c(src, BOLD)}")
+    print(f"      lang={c(lang, CYAN)}  type={typ_str}  format={fmt}")
+    conf_str = c("n/a (embedded)", DIM) if track.is_embedded else confidence_bar(track.confidence)
+    print(f"      confidence={conf_str}{clarif}")
+
+    if track.entry_count is not None:
+        print(f"      entries={track.entry_count}  size={track.file_size_kb:.1f} KB" if track.file_size_kb else f"      entries={track.entry_count}")
+
+    if verbose and track.raw_tokens:
+        print(f"      tokens={track.raw_tokens}")
+
+    if track.is_resolved() and track.language and track.format:
+        try:
+            dest = track.destination_name
+            print(f"      → {c(dest, GREEN, BOLD)}")
+        except ValueError:
+            pass
+
+
+# ---------------------------------------------------------------------------
+# Étapes du pipeline
+# ---------------------------------------------------------------------------
+
+def step_load_kb() -> "SubtitleKnowledgeBase":
+    from alfred.domain.subtitles.knowledge.base import SubtitleKnowledgeBase
+    from alfred.domain.subtitles.knowledge.loader import KnowledgeLoader
+
+    section("ÉTAPE 1 — Chargement de la base de connaissances")
+    kb = SubtitleKnowledgeBase(KnowledgeLoader())
+
+    fmts = kb.formats()
+    langs = kb.languages()
+    patterns = kb.patterns()
+
+    ok(f"{len(fmts)} format(s) connu(s): {', '.join(fmts.keys())}")
+    ok(f"{len(langs)} langue(s) connue(s): {', '.join(langs.keys())}")
+    ok(f"{len(patterns)} pattern(s) connu(s): {', '.join(patterns.keys())}")
+
+    total_tokens = sum(len(l.tokens) for l in langs.values())
+    info(c(f"→ {total_tokens} tokens de langue au total", DIM), indent=4)
+
+    return kb
+
+
+def step_detect_pattern(
+    kb: "SubtitleKnowledgeBase",
+    season_folder: Path,
+    sample_video: Path,
+    release_group: str | None,
+    forced_pattern: str | None,
+) -> "SubtitlePattern":
+    from alfred.domain.subtitles.services.pattern_detector import PatternDetector
+
+    section("ÉTAPE 2 — Détection du pattern de release")
+
+    # Priorité: forced > known patterns from release_group > auto-detect
+    if forced_pattern:
+        pattern = kb.pattern(forced_pattern)
+        if not pattern:
+            err(f"Pattern inconnu: '{forced_pattern}'")
+            print(f"  Patterns disponibles: {', '.join(kb.patterns().keys())}")
+            sys.exit(1)
+        ok(f"Pattern forcé: {c(forced_pattern, CYAN, BOLD)}")
+        return pattern
+
+    if release_group:
+        known = kb.patterns_for_group(release_group)
+        if known:
+            kv("Release group", release_group)
+            ok(f"Pattern(s) connu(s) pour {release_group}: {', '.join(p.id for p in known)}")
+            pattern = known[0]
+            kv("Pattern sélectionné", c(pattern.id, CYAN, BOLD))
+            return pattern
+        else:
+            warn(f"Groupe '{release_group}' inconnu — lancement de la détection auto")
+
+    # Auto-detect
+    kv("Dossier analysé", str(season_folder))
+    kv("Vidéo de référence", sample_video.name)
+
+    detector = PatternDetector(kb)
+    result = detector.detect(season_folder, sample_video)
+
+    findings = result.get("raw_findings", {})
+    info(c("Observations:", BOLD), indent=4)
+    for key, val in findings.items():
+        if val not in (False, None, 0):
+            info(f"  {key}: {c(str(val), CYAN)}", indent=4)
+
+    detected = result.get("detected")
+    confidence = result.get("confidence", 0.0)
+    description = result.get("description", "")
+
+    print()
+    info(c(f'Description: "{description}"', DIM), indent=4)
+    print(f"    Confiance: {confidence_bar(confidence)}")
+
+    if detected:
+        ok(f"Pattern détecté: {c(detected.id, CYAN, BOLD)}")
+        kv("Stratégie de scan", detected.scan_strategy.value)
+        kv("Détection de type", detected.type_detection.value)
+        if detected.root_folder:
+            kv("Dossier racine", detected.root_folder)
+        return detected
+    else:
+        warn("Aucun pattern détecté avec confiance suffisante — fallback: adjacent")
+        fallback = kb.pattern("adjacent")
+        if not fallback:
+            err("Pattern 'adjacent' introuvable dans la KB !")
+            sys.exit(1)
+        return fallback
+
+
+def step_identify_tracks(
+    kb: "SubtitleKnowledgeBase",
+    sample_video: Path,
+    pattern: "SubtitlePattern",
+    release_group: str | None,
+    verbose: bool,
+) -> "MediaSubtitleMetadata":
+    from alfred.domain.subtitles.services.identifier import SubtitleIdentifier
+
+    section("ÉTAPE 3 — Identification des pistes")
+
+    kv("Vidéo", sample_video.name)
+    kv("Pattern", pattern.id)
+
+    identifier = SubtitleIdentifier(kb)
+    metadata = identifier.identify(
+        video_path=sample_video,
+        pattern=pattern,
+        media_id=None,
+        media_type="tv_show",
+        release_group=release_group,
+    )
+
+    n_emb = len(metadata.embedded_tracks)
+    n_ext = len(metadata.external_tracks)
+    n_unresolved = len(metadata.unresolved_tracks)
+
+    print()
+    ok(f"{n_ext} piste(s) externe(s) trouvée(s)")
+    if n_emb:
+        ok(f"{n_emb} piste(s) embarquée(s) (ffprobe)")
+    if n_unresolved:
+        warn(f"{n_unresolved} piste(s) externe(s) sans langue reconnue")
+
+    if metadata.external_tracks:
+        print()
+        info(c("Pistes externes:", BOLD))
+        for track in metadata.external_tracks:
+            track_summary(track, verbose)
+
+    if metadata.embedded_tracks:
+        print()
+        info(c("Pistes embarquées:", BOLD))
+        for track in metadata.embedded_tracks:
+            track_summary(track, verbose)
+
+    return metadata
+
+
+def step_apply_rules(
+    metadata: "MediaSubtitleMetadata",
+    release_group: str | None,
+) -> tuple["SubtitleMatchingRules | None", list, list]:
+    from alfred.domain.subtitles.aggregates import DEFAULT_RULES
+    from alfred.domain.subtitles.services.matcher import SubtitleMatcher
+    from alfred.domain.subtitles.services.utils import available_subtitles
+    from alfred.domain.subtitles.value_objects import ScanStrategy
+
+    section("ÉTAPE 4 — Application des règles")
+
+    # Cas embedded : pas de matcher, on liste directement les pistes disponibles
+    if metadata.detected_pattern_id == ScanStrategy.EMBEDDED.value:
+        info(c("Pattern embedded — le matcher est court-circuité", DIM), indent=4)
+        tracks = available_subtitles(metadata.embedded_tracks)
+        ok(f"{len(tracks)} piste(s) disponible(s)")
+        return None, tracks, []
+
+    rules = DEFAULT_RULES()
+    kv("Langues préférées", str(rules.preferred_languages))
+    kv("Formats préférés", str(rules.preferred_formats))
+    kv("Types autorisés", str(rules.allowed_types))
+    kv("Confiance min", str(rules.min_confidence))
+    info(c("(règles globales par défaut — pas de .alfred/ en mode scan)", DIM), indent=4)
+
+    matcher = SubtitleMatcher()
+    matched, unresolved = matcher.match(metadata.external_tracks, rules)
+
+    print()
+    ok(f"{len(matched)} piste(s) retenue(s)")
+    if unresolved:
+        warn(f"{len(unresolved)} piste(s) écartée(s) ou non résolue(s)")
+
+    return rules, matched, unresolved
+
+
+def step_show_results(
+    matched: list,
+    unresolved: list,
+    is_embedded: bool,
+    verbose: bool,
+) -> None:
+    section("RÉSULTAT FINAL")
+
+    if matched:
+        label = "piste(s) disponible(s)" if is_embedded else "piste(s) qui seraient placées"
+        ok(f"{len(matched)} {label}:")
+        for track in matched:
+            lang = track.language.code if track.language else "?"
+            typ = track.subtitle_type.value
+            if is_embedded:
+                print(f"    {c(lang, CYAN)}  {c(typ, GREEN)}")
+            else:
+                try:
+                    dest = track.destination_name
+                    src = track.file_path.name if track.file_path else "?"
+                    print(f"    {c(src, DIM)} → {c(dest, GREEN, BOLD)}")
+                except ValueError:
+                    warn(f"  Piste incomplète (lang ou format manquant): {track}")
+    else:
+        warn("Aucune piste retenue.")
+
+    if unresolved:
+        print()
+        warn(f"{len(unresolved)} piste(s) écartées ou à clarifier:")
+        for track in unresolved:
+            src = track.file_path.name if track.file_path else "?"
+            reason = "langue inconnue" if track.language is None else "confiance insuffisante"
+            line = f"    {c(src, DIM)}  ({reason})"
+            if verbose and track.raw_tokens:
+                line += c(f"  tokens: {track.raw_tokens}", YELLOW)
+            print(line)
+
+    print()
+
+
+# ---------------------------------------------------------------------------
+# Scan multi-épisodes (résumé)
+# ---------------------------------------------------------------------------
+
+def scan_season(
+    kb: "SubtitleKnowledgeBase",
+    pattern: "SubtitlePattern",
+    season_folder: Path,
+    release_group: str | None,
+    verbose: bool,
+) -> None:
+    from alfred.domain.subtitles.aggregates import DEFAULT_RULES
+    from alfred.domain.subtitles.services.identifier import SubtitleIdentifier
+    from alfred.domain.subtitles.services.matcher import SubtitleMatcher
+
+    videos = find_videos(season_folder)
+
+    section(f"SCAN COMPLET DE LA SAISON ({len(videos)} épisode(s))")
+
+    if not videos:
+        warn("Aucun fichier vidéo trouvé dans ce dossier.")
+        return
+
+    identifier = SubtitleIdentifier(kb)
+    matcher = SubtitleMatcher()
+    rules = DEFAULT_RULES()
+
+    col_w = max(len(v.name) for v in videos) + 2
+
+    for video in videos:
+        metadata = identifier.identify(
+            video_path=video,
+            pattern=pattern,
+            media_id=None,
+            media_type="tv_show",
+            release_group=release_group,
+        )
+        matched, unresolved = matcher.match(metadata.external_tracks, rules)
+
+        placed_names = []
+        for t in matched:
+            try:
+                placed_names.append(t.destination_name)
+            except ValueError:
+                pass
+
+        status_icon = c("✓", GREEN, BOLD) if placed_names else c("✗", RED, BOLD)
+        warn_icon = c(f" [{len(unresolved)} non-résolue(s)]", YELLOW) if unresolved else ""
+
+        print(f"  {status_icon} {video.name:{col_w}} {c(', '.join(placed_names) or '—', GREEN if placed_names else DIM)}{warn_icon}")
+
+
+# ---------------------------------------------------------------------------
+# Main
+# ---------------------------------------------------------------------------
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description="Scanner de sous-titres Alfred — pipeline de diagnostic",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=textwrap.dedent(__doc__ or ""),
+    )
+    parser.add_argument("season_folder", help="Dossier de la saison (ou du film)")
+    parser.add_argument("--release-group", "-g", metavar="GROUP",
+                        help="Groupe de release (ex: RARBG, KONSTRAST)")
+    parser.add_argument("--pattern", "-p", metavar="PATTERN",
+                        help="Forcer un pattern (adjacent|flat|episode_subfolder|embedded)")
+    parser.add_argument("--video", "-v", metavar="FILE",
+                        help="Fichier vidéo de référence (défaut: premier trouvé)")
+    parser.add_argument("--verbose", action="store_true",
+                        help="Affiche les tokens bruts par piste")
+    parser.add_argument("--no-color", action="store_true",
+                        help="Désactive la colorisation ANSI")
+    parser.add_argument("--season-scan", action="store_true",
+                        help="Après le diagnostic, scanner tous les épisodes de la saison")
+    return parser.parse_args()
+
+
+def main() -> None:
+    global USE_COLOR
+
+    args = parse_args()
+
+    if args.no_color or not sys.stdout.isatty():
+        USE_COLOR = False
+
+    season_folder = Path(args.season_folder).expanduser().resolve()
+    if not season_folder.is_dir():
+        print(f"Erreur: '{season_folder}' n'est pas un dossier.", file=sys.stderr)
+        sys.exit(1)
+
+    print()
+    print(c("━" * 70, BOLD))
+    print(c("  Alfred — Subtitle Scanner", BOLD, MAGENTA))
+    print(c("━" * 70, BOLD))
+    kv("Dossier", str(season_folder), indent=2)
+
+    # Trouver la vidéo de référence
+    if args.video:
+        sample_video = Path(args.video).expanduser().resolve()
+        if not sample_video.exists():
+            print(f"Erreur: '{sample_video}' introuvable.", file=sys.stderr)
+            sys.exit(1)
+    else:
+        videos = find_videos(season_folder)
+        if not videos:
+            # Chercher un niveau plus bas (structure release root)
+            for sub in season_folder.iterdir():
+                if sub.is_dir():
+                    videos = find_videos(sub)
+                    if videos:
+                        break
+        if not videos:
+            print("Erreur: aucun fichier vidéo trouvé dans ce dossier.", file=sys.stderr)
+            sys.exit(1)
+        sample_video = videos[0]
+
+    kv("Vidéo de référence", sample_video.name, indent=2)
+
+    # ---- Pipeline ----
+    kb = step_load_kb()
+
+    pattern = step_detect_pattern(
+        kb=kb,
+        season_folder=season_folder,
+        sample_video=sample_video,
+        release_group=args.release_group,
+        forced_pattern=args.pattern,
+    )
+
+    metadata = step_identify_tracks(
+        kb=kb,
+        sample_video=sample_video,
+        pattern=pattern,
+        release_group=args.release_group,
+        verbose=args.verbose,
+    )
+
+    rules, matched, unresolved = step_apply_rules(
+        metadata=metadata,
+        release_group=args.release_group,
+    )
+
+    step_show_results(
+        matched=matched,
+        unresolved=unresolved,
+        is_embedded=rules is None,
+        verbose=args.verbose,
+    )
+
+    if args.season_scan:
+        scan_season(
+            kb=kb,
+            pattern=pattern,
+            season_folder=season_folder,
+            release_group=args.release_group,
+            verbose=args.verbose,
+        )
+
+    print(c("━" * 70, BOLD))
+    print()
+
+
+if __name__ == "__main__":
+    main()

testing/workflows/run_workflow.py

@@ -0,0 +1,479 @@
+#!/usr/bin/env python3
+"""
+run_workflow.py — Simulate an Alfred workflow step by step (dry-run or live).
+
+Usage:
+    uv run testing/workflows/run_workflow.py organize_media [options]
+
+Options:
+    --dry-run             Print what each step would do without executing tools (default).
+    --live                Actually execute the tools (uses real filesystem + memory).
+    --source PATH         Source video file (download folder).
+    --dest PATH           Destination video file (library path).
+    --download-folder P   Original download folder (for create_seed_links).
+    --imdb-id ID          IMDb ID for identify_media step (tt1234567).
+    --seed                Answer "yes" to the seeding question.
+    --no-color            Disable ANSI colours.
+
+Examples:
+    uv run testing/workflows/run_workflow.py organize_media --dry-run \\
+        --source "/downloads/Breaking.Bad.S01E01.mkv" \\
+        --dest "/tv/Breaking Bad/Season 01/Breaking Bad.S01E01.mkv"
+
+    uv run testing/workflows/run_workflow.py organize_media --live \\
+        --source "/downloads/BB/Breaking.Bad.S01E01.mkv" \\
+        --dest "/tv/Breaking Bad/Season 01/Breaking Bad.S01E01.mkv" \\
+        --download-folder "/downloads/BB" --seed
+"""
+
+import argparse
+import sys
+import textwrap
+from pathlib import Path
+from typing import Any
+
+# Project root on sys.path
+_PROJECT_ROOT = Path(__file__).resolve().parents[2]
+if str(_PROJECT_ROOT) not in sys.path:
+    sys.path.insert(0, str(_PROJECT_ROOT))
+
+# ---------------------------------------------------------------------------
+# Colours
+# ---------------------------------------------------------------------------
+
+USE_COLOR = True
+
+RESET   = "\033[0m"
+BOLD    = "\033[1m"
+DIM     = "\033[2m"
+GREEN   = "\033[32m"
+YELLOW  = "\033[33m"
+RED     = "\033[31m"
+CYAN    = "\033[36m"
+BLUE    = "\033[34m"
+MAGENTA = "\033[35m"
+
+
+def c(text: str, *codes: str) -> str:
+    if not USE_COLOR:
+        return text
+    return "".join(codes) + str(text) + RESET
+
+
+def section(title: str) -> None:
+    print()
+    print(c("─" * 70, DIM))
+    print(c(f"  {title}", BOLD, CYAN))
+    print(c("─" * 70, DIM))
+
+
+def ok(msg: str)   -> None: print(c("  ✓ ", GREEN,  BOLD) + msg)
+def warn(msg: str) -> None: print(c("  ⚠ ", YELLOW, BOLD) + msg)
+def err(msg: str)  -> None: print(c("  ✗ ", RED,    BOLD) + msg)
+def info(msg: str) -> None: print(f"    {msg}")
+def kv(key: str, val: str) -> None:
+    print(f"    {c(key + ':', BOLD)} {val}")
+
+
+# ---------------------------------------------------------------------------
+# Dry-run tool stubs
+# ---------------------------------------------------------------------------
+
+def _dry_list_folder(folder_type: str, path: str = ".") -> dict[str, Any]:
+    return {
+        "status": "ok",
+        "folder_type": folder_type,
+        "path": path,
+        "entries": ["[dry-run — no real listing]"],
+        "count": 1,
+    }
+
+
+def _dry_find_media_imdb_id(**kwargs) -> dict[str, Any]:
+    return {
+        "status": "ok",
+        "imdb_id": kwargs.get("imdb_id") or "tt0000000",
+        "title": "Dry Run Show",
+        "type": "tv_show",
+        "year": 2024,
+    }
+
+
+def _dry_resolve_destination(
+    release_name: str,
+    source_file: str,
+    tmdb_title: str,
+    tmdb_year: int,
+    tmdb_episode_title: str | None = None,
+    confirmed_folder: str | None = None,
+) -> dict[str, Any]:
+    from alfred.domain.media.release_parser import parse_release
+    parsed = parse_release(release_name)
+    ext = Path(source_file).suffix
+    if parsed.is_movie:
+        folder = parsed.movie_folder_name(tmdb_title, tmdb_year)
+        fname = parsed.movie_filename(tmdb_title, tmdb_year, ext)
+        return {
+            "status": "ok",
+            "library_file": f"/movies/{folder}/{fname}",
+            "series_folder": f"/movies/{folder}",
+            "series_folder_name": folder,
+            "season_folder": None,
+            "season_folder_name": None,
+            "filename": fname,
+            "is_new_series_folder": True,
+        }
+    season_folder = parsed.season_folder_name()
+    show_folder = confirmed_folder or parsed.show_folder_name(tmdb_title, tmdb_year)
+    fname = parsed.episode_filename(tmdb_episode_title, ext) if not parsed.is_season_pack else season_folder + ext
+    return {
+        "status": "ok",
+        "library_file": f"/tv/{show_folder}/{season_folder}/{fname}",
+        "series_folder": f"/tv/{show_folder}",
+        "season_folder": f"/tv/{show_folder}/{season_folder}",
+        "series_folder_name": show_folder,
+        "season_folder_name": season_folder,
+        "filename": fname,
+        "is_new_series_folder": confirmed_folder is None,
+    }
+
+
+def _dry_move_media(source: str, destination: str) -> dict[str, Any]:
+    return {
+        "status": "ok",
+        "source": source,
+        "destination": destination,
+        "filename": Path(destination).name,
+        "size": 0,
+    }
+
+
+def _dry_manage_subtitles(source_video: str, destination_video: str) -> dict[str, Any]:
+    return {
+        "status": "ok",
+        "video_path": destination_video,
+        "placed": [],
+        "placed_count": 0,
+        "skipped_count": 0,
+    }
+
+
+def _dry_create_seed_links(library_file: str, original_download_folder: str) -> dict[str, Any]:
+    return {
+        "status": "ok",
+        "torrent_subfolder": f"/torrents/{Path(original_download_folder).name}",
+        "linked_file": f"/torrents/{Path(original_download_folder).name}/{Path(library_file).name}",
+        "copied_files": ["[dry-run — no real copy]"],
+        "copied_count": 1,
+        "skipped": [],
+    }
+
+
+DRY_RUN_TOOLS: dict[str, Any] = {
+    "list_folder":        _dry_list_folder,
+    "find_media_imdb_id": _dry_find_media_imdb_id,
+    "resolve_destination": _dry_resolve_destination,
+    "move_media":         _dry_move_media,
+    "manage_subtitles":   _dry_manage_subtitles,
+    "create_seed_links":  _dry_create_seed_links,
+}
+
+
+# ---------------------------------------------------------------------------
+# Live tools
+# ---------------------------------------------------------------------------
+
+def _load_live_tools() -> dict[str, Any]:
+    from alfred.agent.tools.filesystem import (
+        create_seed_links,
+        list_folder,
+        manage_subtitles,
+        move_media,
+    )
+    # find_media_imdb_id lives in the api tools
+    try:
+        from alfred.agent.tools.api import find_media_imdb_id
+    except ImportError:
+        def find_media_imdb_id(**kwargs):  # type: ignore[misc]
+            return {"status": "error", "error": "not_available", "message": "api tools not loaded"}
+
+    return {
+        "list_folder":        list_folder,
+        "find_media_imdb_id": find_media_imdb_id,
+        "move_media":         move_media,
+        "manage_subtitles":   manage_subtitles,
+        "create_seed_links":  create_seed_links,
+    }
+
+
+# ---------------------------------------------------------------------------
+# Workflow runner
+# ---------------------------------------------------------------------------
+
+class WorkflowRunner:
+    def __init__(self, workflow: dict, tools: dict[str, Any], live: bool, args: argparse.Namespace):
+        self.workflow = workflow
+        self.tools = tools
+        self.live = live
+        self.args = args
+        self.context: dict[str, Any] = {}   # step results accumulate here
+        self.step_results: list[dict] = []
+
+    def run(self) -> None:
+        name = self.workflow.get("name", "?")
+        desc = self.workflow.get("description", "").strip()
+        mode = c("LIVE", RED, BOLD) if self.live else c("DRY-RUN", YELLOW, BOLD)
+
+        print()
+        print(c("━" * 70, BOLD))
+        print(c(f"  Alfred — Workflow Simulator [{mode}]", BOLD, MAGENTA))
+        print(c("━" * 70, BOLD))
+        kv("Workflow", c(name, CYAN, BOLD))
+        kv("Description", desc)
+        kv("Tools allowed", ", ".join(self.workflow.get("tools", [])))
+
+        steps = self.workflow.get("steps", [])
+        for step in steps:
+            self._run_step(step)
+
+        section("SIMULATION TERMINÉE")
+        ok(f"{len(self.step_results)} step(s) exécuté(s)")
+        errors = [r for r in self.step_results if r.get("result", {}).get("status") == "error"]
+        if errors:
+            warn(f"{len(errors)} step(s) en erreur")
+            for r in errors:
+                err(f"  {r['id']}: {r['result'].get('error')} — {r['result'].get('message')}")
+        print()
+        print(c("━" * 70, BOLD))
+        print()
+
+    def _run_step(self, step: dict) -> None:
+        step_id = step.get("id", "?")
+
+        # --- ask_user step ---
+        if "ask_user" in step:
+            section(f"STEP [{step_id}] — ask_user")
+            q = step["ask_user"].get("question", "")
+            answers = step["ask_user"].get("answers", {})
+            info(c(f'Question: "{q}"', BOLD))
+            info(f"Réponses possibles: {', '.join(str(k) for k in answers.keys())}")
+
+            answer = "yes" if self.args.seed else "no"
+            # PyYAML parses bare yes/no as booleans — normalise keys to str
+            answers_str = {str(k): v for k, v in answers.items()}
+            next_step = answers_str.get(answer, {}).get("next_step", "update_library")
+            ok(f"Réponse simulée: {c(answer, CYAN)} → next: {c(next_step, CYAN)}")
+            self.context["seeding"] = (answer == "yes")
+            self.context["ask_seeding_answer"] = answer
+            self.context["next_after_ask"] = next_step
+
+            # If "no", skip create_seed_links
+            if answer == "no":
+                self.context["skip_create_seed_links"] = True
+            return
+
+        # --- memory_write step ---
+        if "memory_write" in step:
+            section(f"STEP [{step_id}] — memory_write ({step['memory_write']})")
+            if self.live:
+                warn("memory_write: pas encore implémenté dans le simulator live")
+            else:
+                ok("(dry-run) Library entry would be written to LTM")
+            self.step_results.append({"id": step_id, "result": {"status": "ok"}})
+            return
+
+        # --- tool step ---
+        tool_name = step.get("tool")
+        if not tool_name:
+            warn(f"Step '{step_id}' has no tool or ask_user — skipped")
+            return
+
+        # Skip create_seed_links if user said no to seeding
+        if tool_name == "create_seed_links" and self.context.get("skip_create_seed_links"):
+            section(f"STEP [{step_id}] — {tool_name}")
+            warn("Skipped (user chose not to seed)")
+            return
+
+        section(f"STEP [{step_id}] — {c(tool_name, CYAN, BOLD)}")
+
+        desc = step.get("description", "").strip()
+        if desc:
+            info(c(desc, DIM))
+
+        kwargs = self._build_kwargs(tool_name, step)
+        for k, v in kwargs.items():
+            kv(k, str(v))
+
+        if tool_name not in self.tools:
+            err(f"Tool '{tool_name}' not found in tool registry")
+            self.step_results.append({"id": step_id, "result": {"status": "error", "error": "unknown_tool"}})
+            return
+
+        try:
+            result = self.tools[tool_name](**kwargs)
+        except Exception as e:
+            err(f"Tool raised an exception: {e}")
+            self.step_results.append({"id": step_id, "result": {"status": "error", "error": str(e)}})
+            return
+
+        self._print_result(result)
+        self.context[step_id] = result
+        self.step_results.append({"id": step_id, "result": result})
+
+    def _build_kwargs(self, tool_name: str, step: dict) -> dict[str, Any]:
+        """Build tool kwargs from step params + CLI args + previous context."""
+        # Start from step-level params (static defaults from YAML)
+        kwargs: dict[str, Any] = dict(step.get("params") or {})
+
+        a = self.args
+
+        if tool_name == "list_folder":
+            kwargs.setdefault("folder_type", "download")
+
+        elif tool_name == "find_media_imdb_id":
+            if a.imdb_id:
+                kwargs["imdb_id"] = a.imdb_id
+
+        elif tool_name == "resolve_destination":
+            if a.release:
+                kwargs["release_name"] = a.release
+            elif a.source:
+                kwargs.setdefault("release_name", Path(a.source).parent.name)
+            if a.source:
+                kwargs["source_file"] = a.source
+            if a.tmdb_title:
+                kwargs["tmdb_title"] = a.tmdb_title
+            if a.tmdb_year:
+                kwargs["tmdb_year"] = a.tmdb_year
+            if a.episode_title:
+                kwargs["tmdb_episode_title"] = a.episode_title
+
+        elif tool_name == "move_media":
+            # If resolve_destination ran, use its library_file as destination
+            resolved = self.context.get("resolve_destination", {})
+            if a.source:
+                kwargs["source"] = a.source
+            dest = a.dest or resolved.get("library_file")
+            if dest:
+                kwargs["destination"] = dest
+
+        elif tool_name == "manage_subtitles":
+            resolved = self.context.get("resolve_destination", {})
+            if a.source:
+                kwargs["source_video"] = a.source
+            dest = a.dest or resolved.get("library_file")
+            if dest:
+                kwargs["destination_video"] = dest
+
+        elif tool_name == "create_seed_links":
+            resolved = self.context.get("resolve_destination", {})
+            library_file = a.dest or resolved.get("library_file")
+            if library_file:
+                kwargs["library_file"] = library_file
+            if a.download_folder:
+                kwargs["original_download_folder"] = a.download_folder
+            elif a.source:
+                kwargs.setdefault("original_download_folder", str(Path(a.source).parent))
+
+        return kwargs
+
+    def _print_result(self, result: dict) -> None:
+        status = result.get("status", "?")
+        if status == "ok":
+            ok(f"status={c('ok', GREEN)}")
+        elif status == "needs_clarification":
+            warn(f"status={c('needs_clarification', YELLOW)}")
+        else:
+            err(f"status={c(status, RED)}  error={result.get('error')}  msg={result.get('message')}")
+            return
+
+        # Pretty-print notable fields
+        skip = {"status", "error", "message"}
+        for k, v in result.items():
+            if k in skip:
+                continue
+            if isinstance(v, list):
+                if v:
+                    info(c(f"{k}:", BOLD))
+                    for item in v[:10]:
+                        info(f"  • {item}")
+                    if len(v) > 10:
+                        info(c(f"  … and {len(v) - 10} more", DIM))
+                else:
+                    info(f"{c(k + ':', BOLD)} (empty)")
+            else:
+                kv(k, str(v))
+
+
+# ---------------------------------------------------------------------------
+# CLI
+# ---------------------------------------------------------------------------
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description="Alfred workflow simulator",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=textwrap.dedent(__doc__ or ""),
+    )
+    parser.add_argument("workflow", help="Workflow name (e.g. organize_media)")
+    parser.add_argument("--dry-run", dest="dry_run", action="store_true", default=True,
+                        help="Simulate steps without executing tools (default)")
+    parser.add_argument("--live", action="store_true",
+                        help="Actually execute tools against the real filesystem")
+    parser.add_argument("--source", metavar="PATH",
+                        help="Source video file (in download folder)")
+    parser.add_argument("--dest", metavar="PATH",
+                        help="Destination video file (in library, overrides resolve_destination)")
+    parser.add_argument("--download-folder", metavar="PATH",
+                        help="Original download folder (for create_seed_links)")
+    parser.add_argument("--imdb-id", metavar="ID",
+                        help="IMDb ID for identify_media (tt1234567)")
+    parser.add_argument("--release", metavar="NAME",
+                        help="Release name (e.g. Oz.S03.1080p.WEBRip.x265-KONTRAST)")
+    parser.add_argument("--tmdb-title", metavar="TITLE",
+                        help="Canonical title from TMDB (e.g. 'Oz')")
+    parser.add_argument("--tmdb-year", metavar="YEAR", type=int,
+                        help="Start/release year from TMDB (e.g. 1997)")
+    parser.add_argument("--episode-title", metavar="TITLE",
+                        help="Episode title from TMDB for single-episode releases")
+    parser.add_argument("--seed", action="store_true",
+                        help='Answer "yes" to the seeding question')
+    parser.add_argument("--no-color", action="store_true")
+    return parser.parse_args()
+
+
+def main() -> None:
+    global USE_COLOR
+    args = parse_args()
+
+    if args.no_color or not sys.stdout.isatty():
+        USE_COLOR = False
+
+    if args.live:
+        args.dry_run = False
+
+    # Load workflow
+    from alfred.agent.workflows.loader import WorkflowLoader
+    loader = WorkflowLoader()
+    workflow = loader.get(args.workflow)
+    if not workflow:
+        print(f"Erreur: workflow '{args.workflow}' introuvable.", file=sys.stderr)
+        print(f"Disponibles: {', '.join(loader.names())}", file=sys.stderr)
+        sys.exit(1)
+
+    # Load tools
+    if args.live:
+        try:
+            tools = _load_live_tools()
+        except Exception as e:
+            print(f"Erreur chargement des tools live: {e}", file=sys.stderr)
+            sys.exit(1)
+    else:
+        tools = DRY_RUN_TOOLS
+
+    runner = WorkflowRunner(workflow, tools, live=args.live, args=args)
+    runner.run()
+
+
+if __name__ == "__main__":
+    main()

tests/agent/test_registry.py

@@ -0,0 +1,208 @@
+"""
+Tests for alfred.agent.registry — tool registration and JSON schema generation.
+"""
+
+import pytest
+
+from alfred.agent.registry import Tool, _create_tool_from_function, make_tools
+from alfred.settings import settings
+
+
+# ---------------------------------------------------------------------------
+# _create_tool_from_function
+# ---------------------------------------------------------------------------
+
+class TestCreateToolFromFunction:
+
+    def test_name_from_function(self):
+        def my_tool(x: str) -> dict:
+            """Does something."""
+            return {}
+        tool = _create_tool_from_function(my_tool)
+        assert tool.name == "my_tool"
+
+    def test_description_from_docstring_first_line(self):
+        def my_tool(x: str) -> dict:
+            """First line description.
+
+            More details here.
+            """
+            return {}
+        tool = _create_tool_from_function(my_tool)
+        assert tool.description == "First line description."
+
+    def test_description_fallback_to_name(self):
+        def no_doc(x: str) -> dict:
+            return {}
+        tool = _create_tool_from_function(no_doc)
+        assert tool.description == "no_doc"
+
+    def test_required_params_without_default(self):
+        def tool(a: str, b: int) -> dict:
+            """Tool."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert "a" in t.parameters["required"]
+        assert "b" in t.parameters["required"]
+
+    def test_optional_params_not_required(self):
+        def tool(a: str, b: str = "default") -> dict:
+            """Tool."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert "a" in t.parameters["required"]
+        assert "b" not in t.parameters["required"]
+
+    def test_none_default_not_required(self):
+        def tool(a: str, b: str | None = None) -> dict:
+            """Tool."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert "b" not in t.parameters["required"]
+
+    def test_type_mapping_str(self):
+        def tool(x: str) -> dict:
+            """T."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert t.parameters["properties"]["x"]["type"] == "string"
+
+    def test_type_mapping_int(self):
+        def tool(x: int) -> dict:
+            """T."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert t.parameters["properties"]["x"]["type"] == "integer"
+
+    def test_type_mapping_float(self):
+        def tool(x: float) -> dict:
+            """T."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert t.parameters["properties"]["x"]["type"] == "number"
+
+    def test_type_mapping_bool(self):
+        def tool(x: bool) -> dict:
+            """T."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert t.parameters["properties"]["x"]["type"] == "boolean"
+
+    def test_unknown_type_defaults_to_string(self):
+        def tool(x: list) -> dict:
+            """T."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert t.parameters["properties"]["x"]["type"] == "string"
+
+    def test_no_annotation_defaults_to_string(self):
+        def tool(x) -> dict:
+            """T."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert t.parameters["properties"]["x"]["type"] == "string"
+
+    def test_self_param_excluded(self):
+        class MyClass:
+            def tool(self, x: str) -> dict:
+                """T."""
+                return {}
+        t = _create_tool_from_function(MyClass().tool)
+        assert "self" not in t.parameters["properties"]
+
+    def test_parameters_schema_structure(self):
+        def tool(a: str, b: int = 0) -> dict:
+            """T."""
+            return {}
+        t = _create_tool_from_function(tool)
+        assert t.parameters["type"] == "object"
+        assert "properties" in t.parameters
+        assert "required" in t.parameters
+
+    def test_func_stored_on_tool(self):
+        def tool(x: str) -> dict:
+            """T."""
+            return {"x": x}
+        t = _create_tool_from_function(tool)
+        assert t.func("hello") == {"x": "hello"}
+
+
+# ---------------------------------------------------------------------------
+# make_tools
+# ---------------------------------------------------------------------------
+
+class TestMakeTools:
+
+    def test_returns_dict(self):
+        tools = make_tools(settings)
+        assert isinstance(tools, dict)
+
+    def test_all_expected_tools_present(self):
+        tools = make_tools(settings)
+        expected = {
+            "set_path_for_folder",
+            "list_folder",
+            "resolve_destination",
+            "move_media",
+            "manage_subtitles",
+            "create_seed_links",
+            "learn",
+            "find_media_imdb_id",
+            "find_torrent",
+            "add_torrent_by_index",
+            "add_torrent_to_qbittorrent",
+            "get_torrent_by_index",
+            "set_language",
+        }
+        assert expected.issubset(tools.keys())
+
+    def test_each_tool_is_tool_instance(self):
+        tools = make_tools(settings)
+        for name, tool in tools.items():
+            assert isinstance(tool, Tool), f"{name} is not a Tool instance"
+
+    def test_each_tool_has_callable_func(self):
+        tools = make_tools(settings)
+        for name, tool in tools.items():
+            assert callable(tool.func), f"{name}.func is not callable"
+
+    def test_tool_name_matches_key(self):
+        tools = make_tools(settings)
+        for key, tool in tools.items():
+            assert tool.name == key
+
+    def test_resolve_destination_schema(self):
+        tools = make_tools(settings)
+        t = tools["resolve_destination"]
+        props = t.parameters["properties"]
+        required = t.parameters["required"]
+        # Required args
+        assert "release_name" in required
+        assert "source_file" in required
+        assert "tmdb_title" in required
+        assert "tmdb_year" in required
+        # Optional args not required
+        assert "tmdb_episode_title" not in required
+        assert "confirmed_folder" not in required
+        # tmdb_year is int
+        assert props["tmdb_year"]["type"] == "integer"
+
+    def test_move_media_schema(self):
+        tools = make_tools(settings)
+        t = tools["move_media"]
+        required = t.parameters["required"]
+        assert "source" in required
+        assert "destination" in required
+
+    def test_create_seed_links_schema(self):
+        tools = make_tools(settings)
+        t = tools["create_seed_links"]
+        required = t.parameters["required"]
+        assert "library_file" in required
+        assert "original_download_folder" in required
+
+    def test_no_duplicate_tools(self):
+        tools = make_tools(settings)
+        # dict keys are unique by definition, but verify no name conflicts
+        names = [t.name for t in tools.values()]
+        assert len(names) == len(set(names))

tests/application/conftest.py

@@ -0,0 +1,41 @@
+"""Fixtures for application-layer tests."""
+
+import shutil
+import tempfile
+from pathlib import Path
+
+import pytest
+
+from alfred.infrastructure.persistence import Memory, set_memory
+
+
+@pytest.fixture
+def app_temp(tmp_path):
+    """Real folder structure: downloads, movies, tv_shows, torrents."""
+    (tmp_path / "downloads").mkdir()
+    (tmp_path / "movies").mkdir()
+    (tmp_path / "tv_shows").mkdir()
+    (tmp_path / "torrents").mkdir()
+    return tmp_path
+
+
+@pytest.fixture
+def memory_configured(app_temp, tmp_path):
+    """
+    Fresh Memory with library_paths and workspace configured using the real API.
+    Replaces the broken memory_with_config from root conftest for these tests.
+    """
+    import tempfile, os
+    storage = tempfile.mkdtemp()
+    mem = Memory(storage_dir=storage)
+    set_memory(mem)
+
+    mem.ltm.workspace.download = str(app_temp / "downloads")
+    mem.ltm.workspace.torrent = str(app_temp / "torrents")
+    mem.ltm.library_paths.set("movie", str(app_temp / "movies"))
+    mem.ltm.library_paths.set("tv_show", str(app_temp / "tv_shows"))
+    mem.save()
+
+    yield mem
+
+    shutil.rmtree(storage, ignore_errors=True)

tests/application/test_create_seed_links.py

@@ -0,0 +1,117 @@
+"""
+Tests for alfred.application.filesystem.create_seed_links.CreateSeedLinksUseCase
+"""
+
+import os
+from pathlib import Path
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from alfred.application.filesystem.create_seed_links import CreateSeedLinksUseCase
+from alfred.infrastructure.filesystem.file_manager import FileManager
+
+
+@pytest.fixture
+def fm():
+    return FileManager()
+
+
+@pytest.fixture
+def use_case(fm):
+    return CreateSeedLinksUseCase(fm)
+
+
+@pytest.fixture
+def seed_env(tmp_path_factory):
+    """
+    Realistic post-move environment (uses its own tmp dir, independent of app_temp):
+      - library video file (hard-linked from original)
+      - original download folder with remaining files
+      - torrents root folder
+    """
+    d = tmp_path_factory.mktemp("seed_env")
+
+    lib_dir = d / "tv" / "Oz.1997.1080p.WEBRip.x265-KONTRAST" / "Oz.S01.1080p.WEBRip.x265-KONTRAST"
+    lib_dir.mkdir(parents=True)
+    lib_video = lib_dir / "Oz.S01E01.1080p.WEBRip.x265-KONTRAST.mp4"
+    lib_video.write_bytes(b"video")
+
+    dl = d / "downloads" / "Oz.S01.1080p.WEBRip.x265-KONTRAST"
+    dl.mkdir(parents=True)
+    (dl / "KONTRAST.txt").write_text("release notes")
+    (dl / "[TGx]info.txt").write_text("tgx")
+    subs = dl / "Subs" / "Oz.S01E01.1080p.WEBRip.x265-KONTRAST"
+    subs.mkdir(parents=True)
+    (subs / "2_eng,English [CC][SDH].srt").write_text("1\n00:00:01 --> 00:00:02\nHello\n")
+
+    torrents = d / "torrents"
+    torrents.mkdir()
+
+    return lib_video, dl, torrents
+
+
+# ---------------------------------------------------------------------------
+# Happy path
+# ---------------------------------------------------------------------------
+
+class TestCreateSeedLinksHappyPath:
+
+    def test_ok_when_torrent_folder_configured(self, use_case, seed_env, memory_configured):
+        from alfred.infrastructure.persistence import get_memory
+        mem = get_memory()
+        lib_video, dl, torrents = seed_env
+        mem.ltm.workspace.torrent = str(torrents)
+        mem.save()
+
+        result = use_case.execute(str(lib_video), str(dl))
+
+        assert result.status == "ok"
+        assert result.torrent_subfolder is not None
+        assert result.linked_file is not None
+        assert result.copied_count > 0
+
+    def test_to_dict_ok(self, use_case, seed_env, memory_configured):
+        from alfred.infrastructure.persistence import get_memory
+        mem = get_memory()
+        lib_video, dl, torrents = seed_env
+        mem.ltm.workspace.torrent = str(torrents)
+        mem.save()
+
+        d = use_case.execute(str(lib_video), str(dl)).to_dict()
+        assert d["status"] == "ok"
+        assert "torrent_subfolder" in d
+        assert "copied_files" in d
+        assert isinstance(d["copied_files"], list)
+
+
+# ---------------------------------------------------------------------------
+# Error: torrent folder not configured
+# ---------------------------------------------------------------------------
+
+class TestCreateSeedLinksErrors:
+
+    def test_error_when_torrent_not_configured(self, use_case, seed_env, memory):
+        lib_video, dl, _ = seed_env
+        result = use_case.execute(str(lib_video), str(dl))
+
+        assert result.status == "error"
+        assert result.error == "torrent_folder_not_set"
+        assert result.message is not None
+
+    def test_to_dict_error(self, use_case, seed_env, memory):
+        lib_video, dl, _ = seed_env
+        d = use_case.execute(str(lib_video), str(dl)).to_dict()
+        assert d["status"] == "error"
+        assert "error" in d
+        assert "message" in d
+
+    def test_error_delegates_to_file_manager(self, memory_configured):
+        """FileManager errors are propagated correctly."""
+        from alfred.infrastructure.persistence import get_memory
+        mem = get_memory()
+        # torrent already configured by memory_configured fixture
+        # library_file does not exist → should propagate error from FileManager
+        uc = CreateSeedLinksUseCase(FileManager())
+        result = uc.execute("/nonexistent/lib.mkv", "/nonexistent/dl")
+        assert result.status == "error"

tests/application/test_list_folder_move_media.py

@@ -0,0 +1,179 @@
+"""Tests for ListFolderUseCase and MoveMediaUseCase."""
+
+import pytest
+from unittest.mock import MagicMock
+
+from alfred.application.filesystem.list_folder import ListFolderUseCase
+from alfred.application.filesystem.move_media import MoveMediaUseCase
+
+
+# ---------------------------------------------------------------------------
+# ListFolderUseCase
+# ---------------------------------------------------------------------------
+
+class TestListFolderUseCase:
+
+    def _use_case(self, fm_result):
+        fm = MagicMock()
+        fm.list_folder.return_value = fm_result
+        return ListFolderUseCase(fm)
+
+    def test_success_returns_response(self):
+        uc = self._use_case({
+            "status": "ok",
+            "folder_type": "download",
+            "path": ".",
+            "entries": ["movie.mkv", "show/"],
+            "count": 2,
+        })
+        resp = uc.execute("download")
+        assert resp.status == "ok"
+        assert resp.folder_type == "download"
+        assert resp.path == "."
+        assert resp.entries == ["movie.mkv", "show/"]
+        assert resp.count == 2
+
+    def test_error_propagates(self):
+        uc = self._use_case({
+            "status": "error",
+            "error": "folder_not_set",
+            "message": "Download folder not configured.",
+        })
+        resp = uc.execute("download")
+        assert resp.status == "error"
+        assert resp.error == "folder_not_set"
+        assert resp.message == "Download folder not configured."
+
+    def test_delegates_folder_type_and_path(self):
+        fm = MagicMock()
+        fm.list_folder.return_value = {
+            "status": "ok",
+            "folder_type": "tv_show",
+            "path": "Breaking Bad",
+            "entries": [],
+            "count": 0,
+        }
+        uc = ListFolderUseCase(fm)
+        uc.execute("tv_show", "Breaking Bad")
+        fm.list_folder.assert_called_once_with("tv_show", "Breaking Bad")
+
+    def test_default_path_is_dot(self):
+        fm = MagicMock()
+        fm.list_folder.return_value = {
+            "status": "ok", "folder_type": "download",
+            "path": ".", "entries": [], "count": 0,
+        }
+        uc = ListFolderUseCase(fm)
+        uc.execute("download")
+        fm.list_folder.assert_called_once_with("download", ".")
+
+    def test_success_response_has_no_error(self):
+        uc = self._use_case({
+            "status": "ok",
+            "folder_type": "movie",
+            "path": ".",
+            "entries": [],
+            "count": 0,
+        })
+        resp = uc.execute("movie")
+        assert resp.error is None
+
+    def test_error_response_has_no_entries(self):
+        uc = self._use_case({
+            "status": "error",
+            "error": "not_found",
+            "message": "Path does not exist",
+        })
+        resp = uc.execute("download", "some/path")
+        assert resp.entries is None
+        assert resp.count is None
+
+
+# ---------------------------------------------------------------------------
+# MoveMediaUseCase
+# ---------------------------------------------------------------------------
+
+class TestMoveMediaUseCase:
+
+    def _use_case(self, fm_result):
+        fm = MagicMock()
+        fm.move_file.return_value = fm_result
+        return MoveMediaUseCase(fm)
+
+    def test_success_returns_response(self, tmp_path):
+        src = str(tmp_path / "src.mkv")
+        dst = str(tmp_path / "dst.mkv")
+        uc = self._use_case({
+            "status": "ok",
+            "source": src,
+            "destination": dst,
+            "filename": "dst.mkv",
+            "size": 1024,
+        })
+        resp = uc.execute(src, dst)
+        assert resp.status == "ok"
+        assert resp.source == src
+        assert resp.destination == dst
+        assert resp.filename == "dst.mkv"
+        assert resp.size == 1024
+
+    def test_error_propagates(self, tmp_path):
+        uc = self._use_case({
+            "status": "error",
+            "error": "source_not_found",
+            "message": "Source does not exist: /ghost.mkv",
+        })
+        resp = uc.execute("/ghost.mkv", str(tmp_path / "dst.mkv"))
+        assert resp.status == "error"
+        assert resp.error == "source_not_found"
+
+    def test_delegates_to_file_manager(self, tmp_path):
+        src = "/downloads/movie.mkv"
+        dst = "/movies/Movie.2024/movie.mkv"
+        fm = MagicMock()
+        fm.move_file.return_value = {
+            "status": "ok", "source": src, "destination": dst,
+            "filename": "movie.mkv", "size": 1,
+        }
+        uc = MoveMediaUseCase(fm)
+        uc.execute(src, dst)
+        fm.move_file.assert_called_once_with(src, dst)
+
+    def test_error_response_has_no_paths(self):
+        uc = self._use_case({
+            "status": "error",
+            "error": "destination_exists",
+            "message": "File already exists",
+        })
+        resp = uc.execute("/src.mkv", "/dst.mkv")
+        assert resp.source is None
+        assert resp.destination is None
+        assert resp.filename is None
+
+    def test_to_dict_success(self, tmp_path):
+        src = "/downloads/movie.mkv"
+        dst = "/movies/movie.mkv"
+        uc = self._use_case({
+            "status": "ok",
+            "source": src,
+            "destination": dst,
+            "filename": "movie.mkv",
+            "size": 2048,
+        })
+        resp = uc.execute(src, dst)
+        d = resp.to_dict()
+        assert d["status"] == "ok"
+        assert d["filename"] == "movie.mkv"
+        assert d["size"] == 2048
+
+    def test_to_dict_error(self):
+        uc = self._use_case({
+            "status": "error",
+            "error": "link_failed",
+            "message": "Cross-device link not permitted",
+        })
+        resp = uc.execute("/src.mkv", "/dst.mkv")
+        d = resp.to_dict()
+        assert d["status"] == "error"
+        assert "error" in d
+        assert "message" in d

tests/application/test_resolve_destination.py

@@ -0,0 +1,315 @@
+"""
+Tests for alfred.application.filesystem.resolve_destination
+
+Uses a real temp filesystem + a real Memory instance (via conftest fixtures).
+No network calls — TMDB data is passed in directly.
+"""
+
+from pathlib import Path
+
+import pytest
+
+from alfred.application.filesystem.resolve_destination import (
+    ResolveDestinationUseCase,
+    _find_existing_series_folders,
+)
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+def _use_case():
+    return ResolveDestinationUseCase()
+
+
+# ---------------------------------------------------------------------------
+# Movies
+# ---------------------------------------------------------------------------
+
+class TestResolveMovie:
+
+    def test_basic_movie(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Another.Round.2020.1080p.BluRay.x264-YTS",
+            source_file="/downloads/Another.Round.2020.1080p.BluRay.x264-YTS/Another.Round.2020.1080p.BluRay.x264-YTS.mp4",
+            tmdb_title="Another Round",
+            tmdb_year=2020,
+        )
+        assert result.status == "ok"
+        assert "Another.Round.2020" in result.series_folder_name
+        assert "1080p.BluRay.x264-YTS" in result.series_folder_name
+        assert result.filename.endswith(".mp4")
+        assert result.season_folder is None
+
+    def test_movie_library_file_path_is_inside_series_folder(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Revolver.2005.1080p.BluRay.x265-RARBG",
+            source_file="/downloads/Revolver.2005.1080p.BluRay.x265-RARBG.mkv",
+            tmdb_title="Revolver",
+            tmdb_year=2005,
+        )
+        assert result.status == "ok"
+        assert result.library_file.startswith(result.series_folder)
+
+    def test_movie_library_not_set(self, memory):
+        # memory has no library paths configured
+        result = _use_case().execute(
+            release_name="Revolver.2005.1080p.BluRay.x265-RARBG",
+            source_file="/downloads/Revolver.2005.1080p.BluRay.x265-RARBG.mkv",
+            tmdb_title="Revolver",
+            tmdb_year=2005,
+        )
+        assert result.status == "error"
+        assert result.error == "library_not_set"
+
+    def test_movie_folder_marked_new(self, memory_configured):
+        # No existing folder → is_new_series_folder = True
+        result = _use_case().execute(
+            release_name="Godzilla.Minus.One.2023.1080p.BluRay.x265-YTS",
+            source_file="/downloads/Godzilla.Minus.One.2023.1080p.BluRay.x265-YTS.mp4",
+            tmdb_title="Godzilla Minus One",
+            tmdb_year=2023,
+        )
+        assert result.status == "ok"
+        assert result.is_new_series_folder is True
+
+    def test_movie_sanitises_forbidden_chars_in_title(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Alien.Earth.2024.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Alien.Earth.2024.1080p.WEBRip.x265-KONTRAST.mkv",
+            tmdb_title="Alien: Earth",
+            tmdb_year=2024,
+        )
+        assert result.status == "ok"
+        assert ":" not in result.series_folder_name
+
+    def test_to_dict_ok(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Revolver.2005.1080p.BluRay.x265-RARBG",
+            source_file="/downloads/Revolver.mkv",
+            tmdb_title="Revolver",
+            tmdb_year=2005,
+        )
+        d = result.to_dict()
+        assert d["status"] == "ok"
+        assert "library_file" in d
+        assert "series_folder_name" in d
+
+
+# ---------------------------------------------------------------------------
+# TV shows — no existing folder
+# ---------------------------------------------------------------------------
+
+class TestResolveTVShowNewFolder:
+
+    def test_oz_s01_creates_new_folder(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Oz.S01.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Oz.S01.1080p.WEBRip.x265-KONTRAST/Oz.S01E01.1080p.WEBRip.x265-KONTRAST.mp4",
+            tmdb_title="Oz",
+            tmdb_year=1997,
+        )
+        assert result.status == "ok"
+        assert result.is_new_series_folder is True
+        assert result.series_folder_name == "Oz.1997.1080p.WEBRip.x265-KONTRAST"
+        assert result.season_folder_name == "Oz.S01.1080p.WEBRip.x265-KONTRAST"
+
+    def test_tv_library_not_set(self, memory):
+        result = _use_case().execute(
+            release_name="Oz.S01.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Oz.S01E01.mp4",
+            tmdb_title="Oz",
+            tmdb_year=1997,
+        )
+        assert result.status == "error"
+        assert result.error == "library_not_set"
+
+    def test_single_episode_filename(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Fallout.2024.S02E01.1080p.x265-ELiTE",
+            source_file="/downloads/Fallout.2024.S02E01.1080p.x265-ELiTE.mkv",
+            tmdb_title="Fallout",
+            tmdb_year=2024,
+            tmdb_episode_title="The Beginning",
+        )
+        assert result.status == "ok"
+        assert "S02E01" in result.filename
+        assert "The.Beginning" in result.filename
+        assert result.filename.endswith(".mkv")
+
+    def test_season_pack_filename_is_folder_name_plus_ext(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Oz.S01.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Oz.S01.1080p.WEBRip.x265-KONTRAST/Oz.S01E01.mp4",
+            tmdb_title="Oz",
+            tmdb_year=1997,
+        )
+        assert result.status == "ok"
+        # Season pack: filename = season_folder_name + ext
+        assert result.filename == result.season_folder_name + ".mp4"
+
+    def test_library_file_is_inside_season_folder(self, memory_configured):
+        result = _use_case().execute(
+            release_name="Oz.S01.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Oz.S01E01.mp4",
+            tmdb_title="Oz",
+            tmdb_year=1997,
+        )
+        assert result.library_file.startswith(result.season_folder)
+        assert result.season_folder.startswith(result.series_folder)
+
+
+# ---------------------------------------------------------------------------
+# TV shows — existing folder matching
+# ---------------------------------------------------------------------------
+
+class TestResolveTVShowExistingFolder:
+
+    def _make_series_folder(self, tv_root, name):
+        """Create a series folder in the tv library."""
+        import os
+        path = tv_root / name
+        path.mkdir(parents=True, exist_ok=True)
+        return path
+
+    def test_uses_existing_single_folder(self, memory_configured, app_temp):
+        """When exactly one folder matches title+year, use it regardless of group."""
+        from alfred.infrastructure.persistence import get_memory
+        mem = get_memory()
+        tv_root = Path(mem.ltm.library_paths.get("tv_show"))
+
+        existing = tv_root / "Oz.1997.1080p.WEBRip.x265-RARBG"
+        existing.mkdir(parents=True, exist_ok=True)
+
+        result = _use_case().execute(
+            release_name="Oz.S02.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Oz.S02E01.mp4",
+            tmdb_title="Oz",
+            tmdb_year=1997,
+        )
+        assert result.status == "ok"
+        assert result.series_folder_name == "Oz.1997.1080p.WEBRip.x265-RARBG"
+        assert result.is_new_series_folder is False
+
+    def test_needs_clarification_on_multiple_folders(self, memory_configured, app_temp):
+        """When multiple folders match, return needs_clarification with options."""
+        from alfred.infrastructure.persistence import get_memory
+        mem = get_memory()
+        tv_root = Path(mem.ltm.library_paths.get("tv_show"))
+
+        (tv_root / "Slow.Horses.2022.1080p.WEBRip.x265-RARBG").mkdir(parents=True, exist_ok=True)
+        (tv_root / "Slow.Horses.2022.1080p.WEBRip.x265-KONTRAST").mkdir(parents=True, exist_ok=True)
+
+        result = _use_case().execute(
+            release_name="Slow.Horses.S05.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Slow.Horses.S05E01.mkv",
+            tmdb_title="Slow Horses",
+            tmdb_year=2022,
+        )
+        assert result.status == "needs_clarification"
+        assert result.question is not None
+        assert len(result.options) == 2
+        assert "Slow.Horses.2022.1080p.WEBRip.x265-RARBG" in result.options
+        assert "Slow.Horses.2022.1080p.WEBRip.x265-KONTRAST" in result.options
+
+    def test_confirmed_folder_bypasses_detection(self, memory_configured, app_temp):
+        """confirmed_folder skips the folder search."""
+        from alfred.infrastructure.persistence import get_memory
+        mem = get_memory()
+        tv_root = Path(mem.ltm.library_paths.get("tv_show"))
+        chosen = "Slow.Horses.2022.1080p.WEBRip.x265-RARBG"
+        (tv_root / chosen).mkdir(parents=True, exist_ok=True)
+
+        result = _use_case().execute(
+            release_name="Slow.Horses.S05.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Slow.Horses.S05E01.mkv",
+            tmdb_title="Slow Horses",
+            tmdb_year=2022,
+            confirmed_folder=chosen,
+        )
+        assert result.status == "ok"
+        assert result.series_folder_name == chosen
+
+    def test_to_dict_needs_clarification(self, memory_configured, app_temp):
+        from alfred.infrastructure.persistence import get_memory
+        mem = get_memory()
+        tv_root = Path(mem.ltm.library_paths.get("tv_show"))
+        (tv_root / "Oz.1997.1080p.WEBRip.x265-RARBG").mkdir(parents=True, exist_ok=True)
+        (tv_root / "Oz.1997.1080p.WEBRip.x265-KONTRAST").mkdir(parents=True, exist_ok=True)
+
+        result = _use_case().execute(
+            release_name="Oz.S03.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Oz.S03E01.mp4",
+            tmdb_title="Oz",
+            tmdb_year=1997,
+        )
+        d = result.to_dict()
+        assert d["status"] == "needs_clarification"
+        assert "question" in d
+        assert isinstance(d["options"], list)
+
+    def test_to_dict_error(self, memory):
+        result = _use_case().execute(
+            release_name="Oz.S01.1080p.WEBRip.x265-KONTRAST",
+            source_file="/downloads/Oz.S01E01.mp4",
+            tmdb_title="Oz",
+            tmdb_year=1997,
+        )
+        d = result.to_dict()
+        assert d["status"] == "error"
+        assert "error" in d
+        assert "message" in d
+
+
+# ---------------------------------------------------------------------------
+# _find_existing_series_folders
+# ---------------------------------------------------------------------------
+
+class TestFindExistingSeriesFolders:
+
+    def test_empty_library(self, tmp_path):
+        assert _find_existing_series_folders(tmp_path, "Oz", 1997) == []
+
+    def test_nonexistent_root(self, tmp_path):
+        assert _find_existing_series_folders(tmp_path / "nope", "Oz", 1997) == []
+
+    def test_single_match(self, tmp_path):
+        (tmp_path / "Oz.1997.1080p.WEBRip.x265-KONTRAST").mkdir()
+        result = _find_existing_series_folders(tmp_path, "Oz", 1997)
+        assert result == ["Oz.1997.1080p.WEBRip.x265-KONTRAST"]
+
+    def test_multiple_matches(self, tmp_path):
+        (tmp_path / "Oz.1997.1080p.WEBRip.x265-KONTRAST").mkdir()
+        (tmp_path / "Oz.1997.1080p.WEBRip.x265-RARBG").mkdir()
+        result = _find_existing_series_folders(tmp_path, "Oz", 1997)
+        assert len(result) == 2
+        assert sorted(result) == result   # sorted
+
+    def test_no_match_different_year(self, tmp_path):
+        (tmp_path / "Oz.1997.1080p.WEBRip.x265-KONTRAST").mkdir()
+        result = _find_existing_series_folders(tmp_path, "Oz", 2000)
+        assert result == []
+
+    def test_no_match_different_title(self, tmp_path):
+        (tmp_path / "Oz.1997.1080p.WEBRip.x265-KONTRAST").mkdir()
+        result = _find_existing_series_folders(tmp_path, "Breaking Bad", 2008)
+        assert result == []
+
+    def test_ignores_files_not_dirs(self, tmp_path):
+        (tmp_path / "Oz.1997.1080p.WEBRip.x265-KONTRAST").mkdir()
+        (tmp_path / "Oz.1997.some.file.txt").touch()
+        result = _find_existing_series_folders(tmp_path, "Oz", 1997)
+        assert len(result) == 1
+
+    def test_case_insensitive_prefix(self, tmp_path):
+        # Folder stored with mixed case
+        (tmp_path / "OZ.1997.1080p.WEBRip.x265-KONTRAST").mkdir()
+        result = _find_existing_series_folders(tmp_path, "Oz", 1997)
+        assert len(result) == 1
+
+    def test_title_with_special_chars_sanitised(self, tmp_path):
+        # "Star Wars: Andor" → sanitised (colon removed) + spaces→dots → "Star.Wars.Andor.2022"
+        (tmp_path / "Star.Wars.Andor.2022.1080p.WEBRip.x265-GROUP").mkdir()
+        result = _find_existing_series_folders(tmp_path, "Star Wars: Andor", 2022)
+        assert len(result) == 1