Update app.py

app.py

@@ -230,99 +230,56 @@
 # # st.snow()
  
 import streamlit as st
-import requests
-import os
-from huggingface_hub import login
+from huggingface_hub import InferenceClient
 
-# Set up Hugging Face token
-hf_token = os.getenv("HF_TOKEN")
-if hf_token is None:
-    raise ValueError("Hugging Face token not found. Please set the HF_TOKEN environment variable.")
-login(hf_token)
-
-# Hugging Face Inference API URL for Deepseek model
-API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/deepseek-r1"
-headers = {"Authorization": f"Bearer {hf_token}"}
-
-# Function to query the Deepseek model
-def query_deepseek(payload):
-    """
-    Sends a query to the Deepseek model using Hugging Face Inference API.
-    """
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.json()
 
-# Streamlit app configuration
-st.set_page_config(page_title="Deepseek Chatbot", page_icon="🤖", layout="wide")
-
-# Custom CSS for chatbot UI
-st.markdown("""
-    <style>
-    .chat-message {
-        padding: 10px;
-        border-radius: 10px;
-        margin: 5px 0;
-        max-width: 70%;
-    }
-    .user-message {
-        background-color: #0078D4;
-        color: white;
-        margin-left: auto;
-        margin-right: 0;
-    }
-    .bot-message {
-        background-color: #f1f1f1;
-        color: black;
-        margin-left: 0;
-        margin-right: auto;
-    }
-    </style>
-    """, unsafe_allow_html=True)
-
-# Initialize session state for chat history
-if "chat_history" not in st.session_state:
-    st.session_state.chat_history = []
+hf_token = os.getenv("HF_TOKEN")
+# Set up the Hugging Face Inference Client
+client = InferenceClient(
+    provider="together",  # Replace with the correct provider if needed
+    api_key= hf_token  # Replace with your Hugging Face API key
+)
 
 # Streamlit app title
-st.title("🤖 Deepseek Chatbot")
-st.write("Welcome to the Deepseek Chatbot! Ask me anything, and I'll do my best to help.")
+st.title("🤖 Deepseek R1 Chatbot")
+st.write("Chat with the Deepseek R1 model powered by Hugging Face Inference API.")
 
-# Chat input
-user_input = st.text_input("You:", placeholder="Type your message here...", key="user_input")
-
-# Send button
-if st.button("Send"):
-    if user_input.strip() != "":
-        # Add user message to chat history
-        st.session_state.chat_history.append({"role": "user", "content": user_input})
-
-        # Prepare payload for Deepseek model
-        payload = {
-            "inputs": {
-                "question": user_input,
-                "context": "",  # Add context if needed
-            }
-        }
-
-        # Query the Deepseek model
-        with st.spinner("Thinking..."):
-            try:
-                response = query_deepseek(payload)
-                bot_response = response.get("answer", "Sorry, I couldn't understand that.")
-            except Exception as e:
-                bot_response = f"An error occurred: {str(e)}"
-
-        # Add bot response to chat history
-        st.session_state.chat_history.append({"role": "bot", "content": bot_response})
+# Initialize session state to store chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
 
 # Display chat history
-for message in st.session_state.chat_history:
-    if message["role"] == "user":
-        st.markdown(f'<div class="chat-message user-message">{message["content"]}</div>', unsafe_allow_html=True)
-    elif message["role"] == "bot":
-        st.markdown(f'<div class="chat-message bot-message">{message["content"]}</div>', unsafe_allow_html=True)
-
-# Clear chat history button
-if st.button("Clear Chat"):
-    st.session_state.chat_history = []
-    st.experimental_rerun()
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# User input
+if prompt := st.chat_input("What would you like to ask?"):
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Generate response from Deepseek R1 model
+    with st.spinner("Thinking..."):
+        try:
+            # Prepare the messages for the model
+            messages = [{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]
+            
+            # Call the Hugging Face Inference API
+            completion = client.chat.completions.create(
+                model="deepseek-ai/DeepSeek-R1",  # Replace with the correct model name
+                messages=messages,
+                max_tokens=500
+            )
+            
+            # Extract the model's response
+            response = completion.choices[0].message.content
+
+            # Add model's response to chat history
+            st.session_state.messages.append({"role": "assistant", "content": response})
+            with st.chat_message("assistant"):
+                st.markdown(response)
+        
+        except Exception as e:
+            st.error(f"An error occurred: {e}")