ruslanmv/DeepSeek-R1-Chatbot

1import streamlit as st2import requests3import logging4 5# Configure logging6logging.basicConfig(level=logging.INFO)7logger = logging.getLogger(__name__)8 9# Page configuration10st.set_page_config(11    page_title="DeepSeek Chatbot - ruslanmv.com",12    page_icon="🤖",13    layout="centered"14)15 16# Initialize session state for chat history17if "messages" not in st.session_state:18    st.session_state.messages = []19 20# Sidebar configuration21with st.sidebar:22    st.header("Model Configuration")23    st.markdown("[Get HuggingFace Token](https://huggingface.co/settings/tokens)")24 25    # Dropdown to select model26    model_options = [27        "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",28    ]29    selected_model = st.selectbox("Select Model", model_options, index=0)30 31    system_message = st.text_area(32        "System Message",33        value="You are a friendly chatbot created by ruslanmv.com. Provide clear, accurate, and brief answers. Keep responses polite, engaging, and to the point. If unsure, politely suggest alternatives.",34        height=10035    )36 37    max_tokens = st.slider(38        "Max Tokens",39        10, 4000, 10040    )41 42    temperature = st.slider(43        "Temperature",44        0.1, 4.0, 0.345    )46 47    top_p = st.slider(48        "Top-p",49        0.1, 1.0, 0.650    )51 52# Function to query the Hugging Face API53def query(payload, api_url):54    headers = {"Authorization": f"Bearer {st.secrets['HF_TOKEN']}"}55    logger.info(f"Sending request to {api_url} with payload: {payload}")56    response = requests.post(api_url, headers=headers, json=payload)57    logger.info(f"Received response: {response.status_code}, {response.text}")58    try:59        return response.json()60    except requests.exceptions.JSONDecodeError:61        logger.error(f"Failed to decode JSON response: {response.text}")62        return None63 64# Chat interface65st.title("🤖 DeepSeek Chatbot")66st.caption("Powered by Hugging Face Inference API - Configure in sidebar")67 68# Display chat history69for message in st.session_state.messages:70    with st.chat_message(message["role"]):71        st.markdown(message["content"])72 73# Handle input74if prompt := st.chat_input("Type your message..."):75    st.session_state.messages.append({"role": "user", "content": prompt})76 77    with st.chat_message("user"):78        st.markdown(prompt)79 80    try:81        with st.spinner("Generating response..."):82            # Prepare the payload for the API83            # Combine system message and user input into a single prompt84            full_prompt = f"{system_message}\n\nUser: {prompt}\nAssistant:"85            payload = {86                "inputs": full_prompt,87                "parameters": {88                    "max_new_tokens": max_tokens,89                    "temperature": temperature,90                    "top_p": top_p,91                    "return_full_text": False92                }93            }94 95            # Dynamically construct the API URL based on the selected model96            api_url = f"https://api-inference.huggingface.co/models/{selected_model}"97            logger.info(f"Selected model: {selected_model}, API URL: {api_url}")98 99            # Query the Hugging Face API using the selected model100            output = query(payload, api_url)101 102            # Handle API response103            if output is not None and isinstance(output, list) and len(output) > 0:104                if 'generated_text' in output[0]:105                    # Extract the assistant's response106                    assistant_response = output[0]['generated_text'].strip()107 108                    # Check for and remove duplicate responses109                    responses = assistant_response.split("\n</think>\n")110                    unique_response = responses[0].strip()111 112                    logger.info(f"Generated response: {unique_response}")113 114                    # Append response to chat only once115                    with st.chat_message("assistant"):116                        st.markdown(unique_response)117 118                    st.session_state.messages.append({"role": "assistant", "content": unique_response})119                else:120                    logger.error(f"Unexpected API response structure: {output}")121                    st.error("Error: Unexpected response from the model. Please try again.")122            else:123                logger.error(f"Empty or invalid API response: {output}")124                st.error("Error: Unable to generate a response. Please check the model and try again.")125 126    except Exception as e:127        logger.error(f"Application Error: {str(e)}", exc_info=True)128        st.error(f"Application Error: {str(e)}")129