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| import os | |
| from langchain_huggingface import HuggingFaceEndpoint | |
| import streamlit as st | |
| from langchain_core.prompts import PromptTemplate | |
| from langchain_core.output_parsers import StrOutputParser | |
| import requests | |
| from config import NASA_API_KEY # Import the NASA API key from the configuration file | |
| model_id = "mistralai/Mistral-7B-Instruct-v0.3" | |
| def get_llm_hf_inference(model_id=model_id, max_new_tokens=128, temperature=0.1): | |
| llm = HuggingFaceEndpoint( | |
| repo_id=model_id, | |
| max_new_tokens=max_new_tokens, | |
| temperature=temperature, | |
| token=os.getenv("HF_TOKEN") # Hugging Face token from environment variable | |
| ) | |
| return llm | |
| def get_nasa_apod(): | |
| """ | |
| Fetch the Astronomy Picture of the Day (APOD) from the NASA API. | |
| """ | |
| url = f"https://api.nasa.gov/planetary/apod?api_key={NASA_API_KEY}" | |
| response = requests.get(url) | |
| if response.status_code == 200: | |
| data = response.json() | |
| return f"Title: {data['title']}\nExplanation: {data['explanation']}\nURL: {data['url']}" | |
| else: | |
| return "I couldn't fetch data from NASA right now. Please try again later." | |
| def get_response(system_message, chat_history, user_text, | |
| eos_token_id=['User'], max_new_tokens=256, get_llm_hf_kws={}): | |
| if "NASA" in user_text or "space" in user_text: | |
| nasa_response = get_nasa_apod() | |
| chat_history.append({'role': 'user', 'content': user_text}) | |
| chat_history.append({'role': 'assistant', 'content': nasa_response}) | |
| return nasa_response, chat_history | |
| hf = get_llm_hf_inference(max_new_tokens=max_new_tokens, temperature=0.1) | |
| prompt = PromptTemplate.from_template( | |
| ( | |
| "[INST] {system_message}" | |
| "\nCurrent Conversation:\n{chat_history}\n\n" | |
| "\nUser: {user_text}.\n [/INST]" | |
| "\nAI:" | |
| ) | |
| ) | |
| chat = prompt | hf.bind(skip_prompt=True) | StrOutputParser(output_key='content') | |
| response = chat.invoke(input=dict(system_message=system_message, user_text=user_text, chat_history=chat_history)) | |
| response = response.split("AI:")[-1] | |
| chat_history.append({'role': 'user', 'content': user_text}) | |
| chat_history.append({'role': 'assistant', 'content': response}) | |
| return response, chat_history | |
| # Streamlit setup | |
| st.set_page_config(page_title="HuggingFace ChatBot", page_icon="🤗") | |
| st.title("NASA Personal Assistant") | |
| st.markdown(f"*This chatbot uses {model_id} and NASA's APIs to provide information and responses.*") | |
| # Initialize session state | |
| if "chat_history" not in st.session_state: | |
| st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}] | |
| # Sidebar for settings | |
| if st.sidebar.button("Reset Chat"): | |
| st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}] | |
| # Main chat interface | |
| user_input = st.chat_input(placeholder="Type your message here...") | |
| if user_input: | |
| response, st.session_state.chat_history = get_response( | |
| system_message="You are a helpful AI assistant.", | |
| user_text=user_input, | |
| chat_history=st.session_state.chat_history, | |
| max_new_tokens=128 | |
| ) | |
| # Display messages | |
| for message in st.session_state.chat_history: | |
| st.chat_message(message["role"]).write(message["content"]) | |