app.py

from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from pydantic import BaseModel
import gradio as gr
import os
import requests
import nest_asyncio
import uvicorn
import re
import json

# ✅ API config
API_KEY = os.environ.get("OPENROUTER_API_KEY")
MODEL = "deepseek/deepseek-chat-v3-0324:free"

app = FastAPI()

# ✅ Chat Function
def chat_fn(message, history):
    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }

    messages = [
        {
            "role": "system",
            "content": (
                "You are a coding assistant with a focus on programming tasks. You should provide clear, friendly, "
                "and concise responses to coding questions or tasks. If you're unsure, say: 'I’m not sure about that. Could you rephrase?'"
            )
        }
    ]

    for user, assistant in history:
        messages.append({"role": "user", "content": user})
        messages.append({"role": "assistant", "content": assistant})

    messages.append({"role": "user", "content": message + "\n\nReply in a natural tone."})

    payload = {
        "model": MODEL,
        "messages": messages,
        "max_tokens": 16384,
        "temperature": 0.7,
        "top_p": 0.9
    }

    try:
        response = requests.post(
            "https://openrouter.ai/api/v1/chat/completions",
            headers=headers,
            json=payload,
            timeout=300
        )
        response.raise_for_status()
        reply = response.json()["choices"][0]["message"]["content"]
    except Exception as e:
        reply = f"⚠️ API error: {str(e)[:200]}"

    return reply.strip()

# ✅ /chat API endpoint
@app.post("/chat")
async def chat_api(request: Request):
    body = await request.json()
    message = body.get("message", "").strip()
    history = body.get("history", [])

    if not message:
        return JSONResponse(content={"response": "⚠️ Please enter a valid message."})

    response = chat_fn(message, history)
    return JSONResponse(content={"response": response})


# ✅ New: /code-check endpoint for Monaco Editor integration
class CodePayload(BaseModel):
    code: str

@app.post("/code-check")
async def code_check(payload: CodePayload):
    code = payload.code

    if not code.strip():
        return JSONResponse(content={"suggestions": []})

    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }

    prompt = (
        "Analyze the following code. Identify syntax issues or improvements.\n"
        "Return a JSON array of suggestions with these keys:\n"
        "- message\n"
        "- severity ('error' or 'hint')\n"
        "- fix (string to replace)\n"
        "- line (1-based)\n"
        "- startColumn, endColumn\n\n"
        f"Code:\n{code}\n\n"
        "Respond ONLY with the JSON array."
    )

    api_payload = {
        "model": MODEL,
        "messages": [
            {"role": "system", "content": "You are a code analysis tool."},
            {"role": "user", "content": prompt}
        ],
        "temperature": 0.3,
        "top_p": 0.9,
        "max_tokens": 2048
    }

    try:
        response = requests.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=api_payload)
        response.raise_for_status()
        raw = response.json()["choices"][0]["message"]["content"]

        # Try to extract JSON array from output
        match = re.search(r"\[\s*{.*?}\s*\]", raw, re.DOTALL)
        suggestions = json.loads(match.group(0)) if match else []

        return JSONResponse(content={"suggestions": suggestions})

    except Exception as e:
        return JSONResponse(content={"suggestions": [], "error": str(e)}, status_code=500)


# ✅ Gradio interface
demo = gr.ChatInterface(
    fn=chat_fn,
    title="\ud83d\udcac CODEX MIRXA KAMRAN",
    description="Ask coding or general programming questions! Short, natural, and helpful responses.",
    theme="soft"
)

# ✅ Mount Gradio on FastAPI
app = gr.mount_gradio_app(app, demo, path="/")

# ✅ Local debug (won't run on HF Spaces, but okay locally)
if __name__ == "__main__":
    nest_asyncio.apply()
    uvicorn.run(app, host="0.0.0.0", port=7860)