Prompt for root directory and list it

app.py

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+# app.py
+import time
+import uuid
+import json
+from typing import Any, Dict
+
+from fastapi import FastAPI, Request
+from fastapi.responses import JSONResponse, StreamingResponse
+
+from agent.llm import DeepSeekClient
+from agent.memory import Memory
+from agent.agent import Agent
+from agent.commands import CommandRegistry
+
+app = FastAPI(
+    title="LibreChat Agent Backend",
+    version="0.1.0",
+)
+
+llm = DeepSeekClient()
+memory = Memory()
+agent = Agent(llm=llm, memory=memory)
+commands_registry = CommandRegistry(memory=memory)
+
+
+def extract_last_user_content(messages: list[Dict[str, Any]]) -> str:
+    last = ""
+    for m in reversed(messages):
+        if m.get("role") == "user":
+            last = m.get("content") or ""
+            break
+    return last
+
+
+@app.post("/v1/chat/completions")
+async def chat_completions(request: Request):
+    body = await request.json()
+    model = body.get("model", "local-deepseek-agent")
+    messages = body.get("messages", [])
+    stream = body.get("stream", False)
+
+    user_input = extract_last_user_content(messages)
+    print("Received chat completion request, stream =", stream, "input:", user_input)
+
+    # 🔹 1) Si c'est une commande, on ne fait PAS intervenir le LLM
+    if user_input.strip().startswith("/"):
+        answer = commands_registry.handle(user_input)
+    else:
+        # 🔹 2) Sinon, logique agent + LLM comme avant
+        answer = agent.step(user_input)
+
+    # Ensuite = même logique de réponse (non-stream ou stream)
+    created_ts = int(time.time())
+    completion_id = f"chatcmpl-{uuid.uuid4().hex}"
+
+    if not stream:
+        resp = {
+            "id": completion_id,
+            "object": "chat.completion",
+            "created": created_ts,
+            "model": model,
+            "choices": [
+                {
+                    "index": 0,
+                    "finish_reason": "stop",
+                    "message": {
+                        "role": "assistant",
+                        "content": answer or "",
+                    },
+                }
+            ],
+            "usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
+        }
+        return JSONResponse(resp)
+
+    async def event_generator():
+        chunk = {
+            "id": completion_id,
+            "object": "chat.completion.chunk",
+            "created": created_ts,
+            "model": model,
+            "choices": [
+                {
+                    "index": 0,
+                    "delta": {
+                        "role": "assistant",
+                        "content": answer or "",
+                    },
+                    "finish_reason": "stop",
+                }
+            ],
+        }
+        yield f"data: {json.dumps(chunk, ensure_ascii=False)}\n\n"
+        yield "data: [DONE]\n\n"
+
+    return StreamingResponse(event_generator(), media_type="text/event-stream")