Update app.py

app.py

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+from fastapi import FastAPI, Request, HTTPException
+from fastapi.responses import JSONResponse
+from starlette.middleware.cors import CORSMiddleware
+import rasa.core.interpreter
+from rasa.core.agent import Agent
+import asyncio
+import json
+import os
+from dotenv import load_dotenv
+import streamlit as st
+import requests
+
+load_dotenv()
+
+app = FastAPI()
+
+# CORS setup to allow Streamlit frontend to communicate with FastAPI backend
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Allows all origins (for development, restrict in production)
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Rasa model directory and paths - adjust if needed, or use environment variables
+RASA_MODEL_PATH = os.getenv("RASA_MODEL_PATH", "./models")
+DOMAIN_PATH = os.getenv("DOMAIN_PATH", "./domain.yml")
+NLU_MODEL_PATH = os.getenv("NLU_MODEL_PATH", None) # NLU model path is optional
+
+# Load Rasa agent
+async def load_rasa_agent():
+    interpreter = None
+    if NLU_MODEL_PATH:
+        interpreter = await rasa.core.interpreter.create_interpreter(NLU_MODEL_PATH)
+
+    agent = Agent.load(RASA_MODEL_PATH,
+                       interpreter=interpreter,
+                       domain=DOMAIN_PATH)
+    return agent
+
+loop = asyncio.get_event_loop()
+rasa_agent = loop.run_until_complete(load_rasa_agent())
+
+# FastAPI endpoint for chat
+@app.post("/chat")
+async def chat_endpoint(message_data: dict):
+    """Rasa chatbot endpoint that takes message in JSON and returns bot response."""
+    user_message = message_data.get('message')
+
+    if not user_message:
+        raise HTTPException(status_code=400, detail="Message text not found")
+
+    response = await rasa_agent.handle_text(user_message)
+
+    bot_responses = []
+    for message in response:
+        if "text" in message:
+            bot_responses.append(message["text"])
+
+    return JSONResponse({"responses": bot_responses})
+
+
+@app.get("/health")
+async def health_check():
+    """Health check endpoint for monitoring."""
+    return JSONResponse({"status": "ok"})
+
+# Streamlit UI
+def main():
+    st.title("HealthVoice Bot")
+    st.write("Talk to the bot about your symptoms.")
+
+    user_input = st.text_input("Your message:", "")
+
+    if user_input:
+        api_url = "http://localhost:8000/chat"  # FastAPI endpoint URL
+        message_payload = {"message": user_input}
+
+        try:
+            response = requests.post(api_url, json=message_payload)
+            response.raise_for_status()  # Raise HTTPError for bad responses (4xx or 5xx)
+            bot_response_json = response.json()
+            bot_messages = bot_response_json.get("responses", [])
+            for bot_message in bot_messages:
+                st.text_area("Bot Response:", value=bot_message, height=len(bot_message.split('\n')) * 25) # Adjust height dynamically
+
+        except requests.exceptions.RequestException as e:
+            st.error(f"Error communicating with the chatbot backend: {e}")
+
+
+if __name__ == "__main__":
+    import uvicorn
+    import threading
+
+    # Start FastAPI app in a separate thread
+    def run_fastapi():
+        uvicorn.run(app, host="0.0.0.0", port=8000)
+
+    fastapi_thread = threading.Thread(target=run_fastapi)
+    fastapi_thread.daemon = True # Daemon threads are abruptly stopped at exit
+    fastapi_thread.start()
+
+    main() # Run Streamlit app in the main thread