Update app.py

app.py

@@ -1,28 +1,34 @@
+from fastapi import FastAPI, Request
+from fastapi.responses import JSONResponse
 import gradio as gr
-import requests
 import os
+import json
 import faiss
 import numpy as np
-import json
-from fastapi import FastAPI
-from pydantic import BaseModel
 from sentence_transformers import SentenceTransformer
+import requests
 
-# Load data
+# ✅ Load RAG-related files
 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")
 
+# ✅ Use your OpenRouter API key from environment
 API_KEY = os.environ.get("OPENROUTER_API_KEY")
 MODEL = "qwen/qwen-2.5-coder-32b-instruct:free"
 
+# ✅ FastAPI app
+app = FastAPI()
+
+# ✅ Context Retriever
 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]])
 
+# ✅ Chat Function
 def chat_fn(message, history):
     headers = {
         "Authorization": f"Bearer {API_KEY}",
@@ -30,7 +36,10 @@ def chat_fn(message, history):
     }
 
     context = get_context(message)
-    messages = [{"role": "system", "content": f"You are CODEX Assistant. Use this:\n{context}"}]
+
+    messages = [
+        {"role": "system", "content": "You are a helpful assistant. Use the following context to answer: " + context}
+    ]
 
     for user, assistant in history:
         messages.append({"role": "user", "content": user})
@@ -49,25 +58,24 @@ def chat_fn(message, history):
 
     return reply
 
-# ✅ Gradio Interface
-gradio_ui = gr.ChatInterface(
+# ✅ FastAPI POST endpoint
+@app.post("/chat")
+async def chat_api(request: Request):
+    body = await request.json()
+    message = body.get("message")
+    history = body.get("history", [])
+    response = chat_fn(message, history)
+    return JSONResponse(content={"response": response})
+
+# ✅ Gradio Chat Interface
+demo = gr.ChatInterface(
     fn=chat_fn,
-    title="💻 CODEX Assistant",
-    description="Ask me coding or technical questions!",
+    title="CODEX MIRXA KAMRAN",
+    description="Chat with AI MODEL trained by Mirxa Kamran",
     theme="soft"
 )
 
-# ✅ FastAPI App
-app = FastAPI()
-
-# ✅ Mount Gradio at `/`
-app = gr.mount_gradio_app(app, gradio_ui, path="/")
-
-# ✅ FastAPI API Endpoint
-class ChatRequest(BaseModel):
-    message: str
-    history: list = []
-
-@app.post("/chat")
-def api_chat(req: ChatRequest):
-    return {"response": chat_fn(req.message, req.history)}
+# ✅ Mount Gradio in FastAPI
+@app.get("/")
+def gradio_app():
+    return gr.mount_gradio_app(app, demo, path="/")