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| import streamlit as st | |
| import requests | |
| # ----------------------------------- | |
| # 1. Hugging Face API Configuration | |
| # ----------------------------------- | |
| API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B" | |
| def query(payload): | |
| """ | |
| Query the Hugging Face Inference API with the given payload. | |
| Keeps the original approach: payload = {"inputs": user_input}. | |
| """ | |
| headers = {"Authorization": f"Bearer {st.secrets['HF_TOKEN']}"} | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| # ----------------------------------- | |
| # 2. Streamlit Page Settings | |
| # ----------------------------------- | |
| st.set_page_config( | |
| page_title="DeepSeek Chatbot - ruslanmv.com", | |
| page_icon="🤖", | |
| layout="centered" | |
| ) | |
| # ----------------------------------- | |
| # 3. Session State Initialization | |
| # ----------------------------------- | |
| # We'll keep a chat history in st.session_state | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| # ----------------------------------- | |
| # 4. Sidebar Configuration | |
| # ----------------------------------- | |
| with st.sidebar: | |
| st.header("Configuration") | |
| st.markdown("[Get your HuggingFace Token](https://huggingface.co/settings/tokens)") | |
| # Although these parameters are shown on the sidebar, we won't actually | |
| # pass them to the payload in `query()`, to strictly preserve the "original" approach. | |
| st.write("**NOTE:** These sliders do not affect the inference in this demo.") | |
| system_message = st.text_area( | |
| "System Message (display only)", | |
| value="You are a friendly Chatbot created by ruslanmv.com", | |
| height=100 | |
| ) | |
| max_tokens = st.slider("Max Tokens (not used here)", 1, 4000, 512) | |
| temperature = st.slider("Temperature (not used here)", 0.1, 4.0, 0.7) | |
| top_p = st.slider("Top-p (not used here)", 0.1, 1.0, 0.9) | |
| # ----------------------------------- | |
| # 5. Main Chat Interface | |
| # ----------------------------------- | |
| st.title("🤖 DeepSeek Chatbot") | |
| st.caption("Powered by Hugging Face Inference API - Original Inference Approach") | |
| # Display the chat history, message by message | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| # ----------------------------------- | |
| # 6. Capture User Input | |
| # ----------------------------------- | |
| if user_input := st.chat_input("Type your message..."): | |
| # 6.1 Append user message to chat history | |
| st.session_state.messages.append({"role": "user", "content": user_input}) | |
| # Display user's message | |
| with st.chat_message("user"): | |
| st.markdown(user_input) | |
| # ----------------------------------- | |
| # 7. Query the Model | |
| # ----------------------------------- | |
| try: | |
| with st.spinner("Generating response..."): | |
| # Prepare payload with the original approach | |
| payload = {"inputs": user_input} | |
| output = query(payload) | |
| # Check if the output is valid | |
| if ( | |
| isinstance(output, list) | |
| and len(output) > 0 | |
| and "generated_text" in output[0] | |
| ): | |
| assistant_response = output[0]["generated_text"] | |
| else: | |
| assistant_response = ( | |
| "Error: Unable to generate a response. Please try again." | |
| ) | |
| # Display the assistant's response | |
| with st.chat_message("assistant"): | |
| st.markdown(assistant_response) | |
| # Store assistant's response in chat history | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": assistant_response} | |
| ) | |
| except Exception as e: | |
| st.error(f"Application Error: {str(e)}") | |