Update app.py

app.py

@@ -1,44 +1,39 @@
 import gradio as gr
-import requests
-from fastapi import FastAPI
-from pydantic import BaseModel
 from huggingface_hub import InferenceClient
 
-# FastAPI app for Telegram bot
-app = FastAPI()
+# Initialize Hugging Face model client
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-# Hugging Face Model Client
-client = InferenceClient("RahulGanapathy/MisInfo-ChatBot")
+# System message setting the chatbot's behavior
+SYSTEM_MESSAGE = (
+    "You are a helpful Assistant. You let the user know if the information they share with you is true or false. "
+    "You return the actual facts behind the information given, after stating the state of Truth or False."
+)
 
-# Define request schema for API
-class RequestData(BaseModel):
-    text: str
-    chat_id: int
-
-
-@app.post("/predict")
-def predict(data: RequestData):
-    """
-    API endpoint to process requests from the Telegram bot.
-    Takes user text input and returns model response.
-    """
-    try:
-        response = client.text_generation(prompt=data.text, max_new_tokens=100)
-        return {"response": response}
-    except Exception as e:
-        return {"response": f"Error: {str(e)}"}
-
-# Function for Gradio UI interaction
+# Function to handle chatbot responses
 def respond(message, history):
-    """
-    Handles chat interaction in Gradio UI.
-    """
-    messages = [{}"role":"system","content":"You are a helpful Assistant. You let the user to know if the information they share with you is true or false. You return the actual facts behind the information given, after stating the state of Truth or False.",{"role": "user", "content": message}]
-    response = client.text_generation(prompt=message, max_new_tokens=100)
-    return response
-
-# Gradio UI Setup
-demo = gr.ChatInterface(respond)
-
+    messages = [{"role": "system", "content": SYSTEM_MESSAGE}]
+    
+    for user_msg, bot_reply in history:
+        if user_msg:
+            messages.append({"role": "user", "content": user_msg})
+        if bot_reply:
+            messages.append({"role": "assistant", "content": bot_reply})
+
+    messages.append({"role": "user", "content": message})
+
+    response = client.chat_completion(messages, max_tokens=200, temperature=0.7)
+    bot_reply = response.choices[0].message.content
+    return bot_reply
+
+# Create Gradio chatbot UI
+demo = gr.ChatInterface(
+    respond, 
+    chatbot=gr.Chatbot(type="messages"), 
+    title="Misinformation Detection Chatbot",
+    description="Ask anything, and the chatbot will verify whether it's true or false.",
+)
+
+# Launch Gradio UI
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()