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| import os | |
| import requests | |
| import streamlit as st | |
| from langchain_huggingface import HuggingFaceEndpoint | |
| from langchain_core.prompts import PromptTemplate | |
| from langchain_core.output_parsers import StrOutputParser | |
| from transformers import pipeline | |
| from config import NASA_API_KEY # Import the NASA API key | |
| model_id = "mistralai/Mistral-7B-Instruct-v0.3" | |
| # Initialize sentiment analysis pipeline | |
| sentiment_analyzer = pipeline("sentiment-analysis") | |
| 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 NASA Astronomy Picture of the Day (APOD). | |
| """ | |
| 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 data.get("url", ""), data.get("title", ""), data.get("explanation", "") | |
| else: | |
| return "", "NASA Data Unavailable", "I couldn't fetch data from NASA right now. Please try again later." | |
| def analyze_sentiment(user_text): | |
| """ | |
| Analyze sentiment of user input. | |
| """ | |
| result = sentiment_analyzer(user_text)[0] | |
| return result['label'] | |
| def predict_action(user_text): | |
| """ | |
| Predicts user's intent based on input. | |
| """ | |
| if "NASA" in user_text or "space" in user_text: | |
| return "nasa_info" | |
| return "general_query" | |
| def generate_follow_up(user_text): | |
| """ | |
| Generates a follow-up question to continue the conversation. | |
| """ | |
| prompt_text = ( | |
| f"Based on the user's message: '{user_text}', suggest a natural follow-up question " | |
| "to keep the conversation engaging." | |
| ) | |
| hf = get_llm_hf_inference(max_new_tokens=64, temperature=0.7) | |
| chat = hf.invoke(input=prompt_text) | |
| return chat.strip() | |
| def get_response(system_message, chat_history, user_text, max_new_tokens=256): | |
| sentiment = analyze_sentiment(user_text) | |
| action = predict_action(user_text) | |
| if action == "nasa_info": | |
| nasa_url, nasa_title, nasa_explanation = get_nasa_apod() | |
| response = f"**{nasa_title}**\n\n{nasa_explanation}" | |
| chat_history.append({'role': 'user', 'content': user_text}) | |
| chat_history.append({'role': 'assistant', 'content': response}) | |
| follow_up = generate_follow_up(user_text) | |
| chat_history.append({'role': 'assistant', 'content': follow_up}) | |
| return response, follow_up, chat_history, nasa_url | |
| hf = get_llm_hf_inference(max_new_tokens=max_new_tokens, temperature=0.1) | |
| prompt = PromptTemplate.from_template( | |
| "[INST] {system_message}\n\nCurrent Conversation:\n{chat_history}\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}) | |
| if sentiment == "NEGATIVE": | |
| response += "\n😞 I'm sorry to hear that. How can I assist you further?" | |
| follow_up = generate_follow_up(user_text) | |
| chat_history.append({'role': 'assistant', 'content': follow_up}) | |
| return response, follow_up, chat_history, None | |
| # Streamlit UI Setup | |
| st.set_page_config(page_title="NASA ChatBot", page_icon="🚀") | |
| st.title("🚀 HAL") | |
| # Chat Display with Updated Styling | |
| st.markdown("<div class='container'>", unsafe_allow_html=True) | |
| for message in st.session_state.chat_history: | |
| if message["role"] == "user": | |
| st.markdown(f"<div class='user-msg'><strong>You:</strong> {message['content']}</div>", unsafe_allow_html=True) | |
| else: | |
| st.markdown(f"<div class='assistant-msg'><strong>Bot:</strong> {message['content']}</div>", unsafe_allow_html=True) | |
| st.markdown("</div>", unsafe_allow_html=True) | |
| # Custom CSS for chat styling | |
| st.markdown(""" | |
| <style> | |
| /* Style for chat messages */ | |
| .user-msg { | |
| background-color: #0078D7; /* Dark Blue */ | |
| color: white; /* White text for contrast */ | |
| padding: 10px; | |
| border-radius: 10px; | |
| margin-bottom: 5px; | |
| width: fit-content; | |
| max-width: 80%; | |
| } | |
| .assistant-msg { | |
| background-color: #333333; /* Dark Gray */ | |
| color: white; /* White text for contrast */ | |
| padding: 10px; | |
| border-radius: 10px; | |
| margin-bottom: 5px; | |
| width: fit-content; | |
| max-width: 80%; | |
| } | |
| /* Center messages for better appearance */ | |
| .container { | |
| display: flex; | |
| flex-direction: column; | |
| align-items: flex-start; | |
| } | |
| /* Adjust messages on mobile */ | |
| @media (max-width: 600px) { | |
| .user-msg, .assistant-msg { | |
| font-size: 16px; | |
| max-width: 100%; | |
| } | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| # Initialize chat history | |
| # Initialize chat history in 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?"}] | |
| # Chat Display | |
| st.markdown("<div class='container'>", unsafe_allow_html=True) | |
| for message in st.session_state.chat_history: | |
| if message["role"] == "user": | |
| st.markdown(f"<div class='user-msg'><strong>You:</strong> {message['content']}</div>", unsafe_allow_html=True) | |
| else: | |
| st.markdown(f"<div class='assistant-msg'><strong>Bot:</strong> {message['content']}</div>", unsafe_allow_html=True) | |
| st.markdown("</div>", unsafe_allow_html=True) | |
| # Sidebar for chat reset | |
| if st.sidebar.button("Reset Chat"): | |
| st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}] | |
| st.experimental_rerun() | |
| # Chat display | |
| for message in st.session_state.chat_history: | |
| if message["role"] == "user": | |
| st.markdown(f"<div class='user-msg'><strong>You:</strong> {message['content']}</div>", unsafe_allow_html=True) | |
| else: | |
| st.markdown(f"<div class='assistant-msg'><strong>Bot:</strong> {message['content']}</div>", unsafe_allow_html=True) | |
| # User input | |
| user_input = st.text_area("Type your message:", height=100) | |
| if st.button("Send"): | |
| if user_input: | |
| response, follow_up, st.session_state.chat_history, image_url = get_response( | |
| system_message="You are a helpful AI assistant.", | |
| user_text=user_input, | |
| chat_history=st.session_state.chat_history | |
| ) | |
| # Display response | |
| st.markdown(f"<div class='assistant-msg'><strong>Bot:</strong> {response}</div>", unsafe_allow_html=True) | |
| # Display NASA image if available | |
| if image_url: | |
| st.image(image_url, caption="NASA Image of the Day") | |
| # Follow-up options | |
| follow_up_options = [follow_up, "Explain differently", "Give me an example"] | |
| selected_option = st.radio("What would you like to do next?", follow_up_options) | |
| if st.button("Continue"): | |
| if selected_option: | |
| response, _, st.session_state.chat_history, _ = get_response( | |
| system_message="You are a helpful AI assistant.", | |
| user_text=selected_option, | |
| chat_history=st.session_state.chat_history | |
| ) | |
| st.markdown(f"<div class='assistant-msg'><strong>Bot:</strong> {response}</div>", unsafe_allow_html=True) | |