Create main.py

main.py

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+import os
+os.environ["POSTHOG_DISABLED"] = "true"  # Disable PostHog telemetry
+import requests
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from dotenv import load_dotenv
+#from kb_embed import search_knowledge_base
+import logging
+
+logging.basicConfig(level=logging.INFO)
+
+# Load environment variables from the .env file
+load_dotenv()
+
+# --- 1. Initialize FastAPI ---
+app = FastAPI()
+
+# --- 2. Configure CORS ---
+#origins = [
+#    "http://localhost:5173",
+#    "http://localhost:3000",
+#]
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["https://jaita-chatbot-fastapi-backend.hf.space/chat","https://jaita-chatbot-react-frontend-v1.hf.space"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# --- 3. Define the Request Data Structure ---
+class ChatInput(BaseModel):
+    user_message: str
+
+# --- 4. Gemini API Setup ---
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+GEMINI_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent?key={GEMINI_API_KEY}"
+
+# --- 5. Endpoints ---
+@app.get("/")
+async def health_check():
+    return {"status": "ok"}
+
+
+@app.post("/chat")
+async def chat_with_ai(input_data: ChatInput):
+    """Handle chat interactions using Google Generative AI via requests."""
+    try:
+        # Gemini expects contents array with role and parts
+        payload = {
+            "contents": [
+                {
+                    "role": "user",
+                    "parts": [{"text": input_data.user_message}],
+                }
+            ],
+            #"generationConfig": {
+            #    "temperature": 0.7,
+            #    "maxOutputTokens": 512
+            #}
+        }
+
+        # Make POST request to Gemini API
+        response = requests.post(GEMINI_URL, json=payload,verify=False)
+        response.raise_for_status()
+        data = response.json()
+
+        # Extract text from response
+        bot_response = ""
+        if "candidates" in data and data["candidates"]:
+            parts = data["candidates"][0].get("content", {}).get("parts", [])
+            for part in parts:
+                if "text" in part:
+                    bot_response += part["text"]
+
+        return {"bot_response": bot_response or "No response text."}
+
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))