"""Prompt builder for the agent system."""
from typing import Dict, List, Any
import json

from .registry import Tool
from infrastructure.persistence import get_memory


class PromptBuilder:
    """Builds system prompts for the agent with memory context."""

    def __init__(self, tools: Dict[str, Tool]):
        self.tools = tools

    def build_tools_spec(self) -> List[Dict[str, Any]]:
        """Build the tool specification for the LLM API."""
        tool_specs = []
        for tool in self.tools.values():
            spec = {
                "type": "function",
                "function": {
                    "name": tool.name,
                    "description": tool.description,
                    "parameters": tool.parameters,
                },
            }
            tool_specs.append(spec)
        return tool_specs

    def _format_tools_description(self) -> str:
        """Format tools with their descriptions and parameters."""
        if not self.tools:
            return ""
        return "\n".join(
            f"- {tool.name}: {tool.description}\n"
            f"  Parameters: {json.dumps(tool.parameters, ensure_ascii=False)}"
            for tool in self.tools.values()
        )

    def _format_episodic_context(self) -> str:
        """Format episodic memory context for the prompt."""
        memory = get_memory()
        lines = []

        if memory.episodic.last_search_results:
            results = memory.episodic.last_search_results
            result_list = results.get('results', [])
            lines.append(f"\nLAST SEARCH: '{results.get('query')}' ({len(result_list)} results)")
            # Show first 5 results
            for i, result in enumerate(result_list[:5]):
                name = result.get('name', 'Unknown')
                lines.append(f"  {i+1}. {name}")
            if len(result_list) > 5:
                lines.append(f"  ... and {len(result_list) - 5} more")

        if memory.episodic.pending_question:
            question = memory.episodic.pending_question
            lines.append(f"\nPENDING QUESTION: {question.get('question')}")
            lines.append(f"  Type: {question.get('type')}")
            if question.get('options'):
                lines.append(f"  Options: {len(question.get('options'))}")

        if memory.episodic.active_downloads:
            lines.append(f"\nACTIVE DOWNLOADS: {len(memory.episodic.active_downloads)}")
            for dl in memory.episodic.active_downloads[:3]:
                lines.append(f"  - {dl.get('name')}: {dl.get('progress', 0)}%")

        if memory.episodic.recent_errors:
            lines.append("\nRECENT ERRORS (up to 3):")
            for error in memory.episodic.recent_errors[-3:]:
                lines.append(f"  - Action '{error.get('action')}' failed: {error.get('error')}")

        # Unread events
        unread = [e for e in memory.episodic.background_events if not e.get('read')]
        if unread:
            lines.append(f"\nUNREAD EVENTS: {len(unread)}")
            for event in unread[:3]:
                lines.append(f"  - {event.get('type')}: {event.get('data')}")

        return "\n".join(lines)

    def _format_stm_context(self) -> str:
        """Format short-term memory context for the prompt."""
        memory = get_memory()
        lines = []

        if memory.stm.current_workflow:
            workflow = memory.stm.current_workflow
            lines.append(f"CURRENT WORKFLOW: {workflow.get('type')} (stage: {workflow.get('stage')})")
            if workflow.get('target'):
                lines.append(f"  Target: {workflow.get('target')}")

        if memory.stm.current_topic:
            lines.append(f"CURRENT TOPIC: {memory.stm.current_topic}")

        if memory.stm.extracted_entities:
            lines.append("EXTRACTED ENTITIES:")
            for key, value in memory.stm.extracted_entities.items():
                lines.append(f"  - {key}: {value}")
        
        if memory.stm.language:
            lines.append(f"CONVERSATION LANGUAGE: {memory.stm.language}")

        return "\n".join(lines)

    def _format_config_context(self) -> str:
        """Format configuration context."""
        memory = get_memory()
        
        lines = ["CURRENT CONFIGURATION:"]
        if memory.ltm.config:
            for key, value in memory.ltm.config.items():
                lines.append(f"  - {key}: {value}")
        else:
            lines.append("  (no configuration set)")
        return "\n".join(lines)

    def build_system_prompt(self) -> str:
        """Build the complete system prompt."""
        memory = get_memory()
        
        # Base instruction
        base = "You are a helpful AI assistant for managing a media library."
        
        # Language instruction
        language_instruction = (
            "Your first task is to determine the user's language from their message "
            "and use the `set_language` tool if it's different from the current one. "
            "After that, proceed to help the user."
        )

        # Available tools
        tools_desc = self._format_tools_description()
        tools_section = f"\nAVAILABLE TOOLS:\n{tools_desc}" if tools_desc else ""

        # Configuration
        config_section = self._format_config_context()
        if config_section:
            config_section = f"\n{config_section}"

        # STM context
        stm_context = self._format_stm_context()
        if stm_context:
            stm_context = f"\n{stm_context}"

        # Episodic context
        episodic_context = self._format_episodic_context()

        # Important rules
        rules = """
IMPORTANT RULES:
- Use tools to accomplish tasks
- When search results are available, reference them by index (e.g., "add_torrent_by_index")
- Always confirm actions with the user before executing destructive operations
- Provide clear, concise responses
"""

        # Examples
        examples = """
EXAMPLES:
- User: "Find Inception" → Use find_media_imdb_id, then find_torrent
- User: "download the 3rd one" → Use add_torrent_by_index with index=3
- User: "List my downloads" → Use list_folder with folder_type="download"
"""

        return f"""{base}

{language_instruction}
{tools_section}
{config_section}
{stm_context}
{episodic_context}
{rules}
{examples}
"""