from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from datetime import datetime
import json
import os

app = FastAPI()
LOG_DIR = "request_logs"
os.makedirs(LOG_DIR, exist_ok=True)

def format_markdown_log(headers, body, response):
    timestamp = datetime.now().isoformat()

    # Extract messages
    messages = body.get("messages", [])
    messages_text = "\n".join(
        f"{m.get('role', 'unknown')}: {m.get('content', '')}" for m in messages
    )

    log = f"""## 📥 Request - {timestamp}

**Timestamp:** {timestamp}

### Headers
\```json
{json.dumps(headers, indent=4)}
\```

### Message Contents
\```text
{messages_text or "No messages"}
\```

### Full Body
\```json
{json.dumps(body, indent=4)}
\```

### 📤 Response
\```json
{json.dumps(response, indent=4)}
\```

---
"""
    return log

@app.post("/v1/chat/completions")
async def chat_completions(request: Request):
    headers = dict(request.headers)
    body = await request.json()

    dummy_response = {
        "id": "chatcmpl-mock123",
        "object": "chat.completion",
        "created": int(datetime.now().timestamp()),
        "model": body.get("model", "gpt-4"),
        "choices": [
            {
                "index": 0,
                "message": {
                    "role": "assistant",
                    "content": "This is a mock response for testing purposes."
                },
                "finish_reason": "stop"
            }
        ],
        "usage": {
            "prompt_tokens": 10,
            "completion_tokens": 12,
            "total_tokens": 22
        }
    }

    markdown_log = format_markdown_log(headers, body, dummy_response)
    timestamp_str = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
    log_file = os.path.join(LOG_DIR, f"request_{timestamp_str}.md")
    with open(log_file, "w", encoding="utf-8") as f:
        f.write(markdown_log)

    return JSONResponse(content=dummy_response)