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import gradio as gr
import requests
import os
import faiss
import numpy as np
import json
from fastapi import FastAPI, Request
from pydantic import BaseModel
from sentence_transformers import SentenceTransformer
# ✅ Load vector data
with open("texts.json", "r", encoding="utf-8") as f:
texts = json.load(f)
index = faiss.read_index("faiss_index.bin")
embed_model = SentenceTransformer("all-MiniLM-L6-v2")
API_KEY = os.environ.get("OPENROUTER_API_KEY")
MODEL = "qwen/qwen-2.5-coder-32b-instruct:free"
# ✅ Semantic search
def get_context(query, top_k=5):
query_vec = embed_model.encode([query])
D, I = index.search(np.array(query_vec), top_k)
return "\n".join([texts[i] for i in I[0]])
# ✅ Chatbot response
def chat_fn(message, history):
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
}
context = get_context(message)
messages = [{"role": "system", "content": f"You are CODEX Assistant by Mirxa Kamran. Use this context:\n{context}"}]
for user, assistant in history:
messages.append({"role": "user", "content": user})
messages.append({"role": "assistant", "content": assistant})
messages.append({"role": "user", "content": message})
payload = {"model": MODEL, "messages": messages}
try:
response = requests.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=payload)
response.raise_for_status()
reply = response.json()["choices"][0]["message"]["content"]
except Exception as e:
reply = f"❌ Error: {e}"
return reply
# ✅ Gradio UI
demo = gr.ChatInterface(
fn=chat_fn,
title="💻 CODEX Assistant by Mirxa Kamran",
description="Chat with a context-aware AI code assistant.",
theme="soft"
)
# ✅ FastAPI app
app = FastAPI()
# ✅ Mount Gradio on root path
app = gr.mount_gradio_app(app, demo, path="/")
# ✅ FastAPI POST API endpoint
class ChatRequest(BaseModel):
message: str
history: list = []
@app.post("/chat")
def api_chat(req: ChatRequest):
reply = chat_fn(req.message, req.history)
return {"response": reply}
# ✅ Run manually in local dev or on Spaces
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)
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