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Update app.py
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app.py
CHANGED
@@ -1,6 +1,5 @@
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import os
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import re
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import random
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import requests
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import streamlit as st
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from langchain_huggingface import HuggingFaceEndpoint
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@@ -21,9 +20,7 @@ if NASA_API_KEY is None:
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# β
Set Up Streamlit
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st.set_page_config(page_title="HAL - NASA ChatBot", page_icon="π")
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# β
Ensure Session State Variables
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if "chat_history" not in st.session_state:
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st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
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if "response_ready" not in st.session_state:
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@@ -35,7 +32,7 @@ if "follow_up" not in st.session_state:
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model_id = "mistralai/Mistral-7B-Instruct-v0.3"
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# β
Initialize Hugging Face Model
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def get_llm_hf_inference(model_id=model_id, max_new_tokens=
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return HuggingFaceEndpoint(
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repo_id=model_id,
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max_new_tokens=max_new_tokens,
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@@ -65,28 +62,11 @@ def analyze_sentiment(user_text):
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# β
Intent Detection
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def predict_action(user_text):
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if "NASA" in user_text or "space" in user_text:
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return "nasa_info"
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return "general_query"
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# β
Follow-Up Question Generation
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def generate_follow_up(user_text):
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prompt_text = f"Based on: '{user_text}', generate a concise, friendly follow-up."
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hf = get_llm_hf_inference(max_new_tokens=80, temperature=0.9)
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output = hf.invoke(input=prompt_text).strip()
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return output if output else "Would you like to explore this topic further?"
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# β
Ensure English Responses
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def ensure_english(text):
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try:
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detected_lang = detect(text)
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if detected_lang != "en":
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return "β οΈ Sorry, I only respond in English. Can you rephrase your question?"
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except:
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return "β οΈ Language detection failed. Please ask your question again."
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return text
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# β
Ensure Every Response Has a Follow-Up Question
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def generate_follow_up(user_text):
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"""Generates a clean follow-up question to guide the user toward related topics or next steps."""
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prompt_text = (
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@@ -98,13 +78,22 @@ def generate_follow_up(user_text):
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hf = get_llm_hf_inference(max_new_tokens=40, temperature=0.8)
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output = hf.invoke(input=prompt_text).strip()
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# β
Remove unnecessary characters (like backticks and misplaced formatting)
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cleaned_output = re.sub(r"```|''|\"", "", output).strip()
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# β
Fallback in case the response is empty or invalid
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return cleaned_output if cleaned_output else "Would you like to explore another related topic or ask about something else?"
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# β
Main Response Function
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def get_response(system_message, chat_history, user_text, max_new_tokens=512):
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@@ -155,70 +144,27 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=512):
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return response, follow_up, chat_history, None
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# β
Ensure response is displayed
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if response:
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st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
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# β
Save and display follow-up question separately
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if follow_up: # π Here is the `if follow_up:` section
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st.session_state.chat_history.append({'role': 'assistant', 'content': follow_up})
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st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {follow_up}</div>", unsafe_allow_html=True)
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# β
Streamlit UI
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st.title("π HAL - NASA AI Assistant")
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# β
Justify all chatbot responses
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st.markdown("""
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<style>
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.user-msg {
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background-color: #696969;
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color: white;
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padding: 10px;
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border-radius: 10px;
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margin-bottom: 5px;
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width: fit-content;
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max-width: 80%;
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text-align: justify; /* β
Justify text */
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}
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.assistant-msg {
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background-color: #333333;
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color: white;
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padding: 10px;
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border-radius: 10px;
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margin-bottom: 5px;
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width: fit-content;
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max-width: 80%;
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text-align: justify; /* β
Justify text */
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}
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.container {
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display: flex;
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flex-direction: column;
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align-items: flex-start;
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}
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@media (max-width: 600px) {
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.user-msg, .assistant-msg { font-size: 16px; max-width: 100%; }
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}
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</style>
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""", unsafe_allow_html=True)
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# β
Reset Chat Button
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if st.sidebar.button("Reset Chat"):
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st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
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st.session_state.response_ready = False
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st.session_state.follow_up = ""
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if user_input:
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# β
Ensure get_response()
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response, follow_up, st.session_state.chat_history, image_url = get_response(
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system_message="You are a helpful AI assistant.",
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user_text=user_input,
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chat_history=st.session_state.chat_history
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)
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# β
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if not response:
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response = "I'm sorry, but I couldn't generate a response."
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@@ -227,14 +173,11 @@ if user_input:
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# β
Handle follow-up question
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if follow_up:
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st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {follow_up}</div>", unsafe_allow_html=True)
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# β
Display NASA image if available
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if image_url:
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st.image(image_url, caption="NASA Image of the Day")
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# β
Check before displaying follow-up message
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if st.session_state.response_ready and st.session_state.follow_up:
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st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {st.session_state.follow_up}</div>", unsafe_allow_html=True)
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st.session_state.response_ready = False
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import os
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import re
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import requests
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import streamlit as st
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from langchain_huggingface import HuggingFaceEndpoint
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# β
Set Up Streamlit
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st.set_page_config(page_title="HAL - NASA ChatBot", page_icon="π")
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# β
Initialize Session State Variables
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if "chat_history" not in st.session_state:
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st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
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if "response_ready" not in st.session_state:
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model_id = "mistralai/Mistral-7B-Instruct-v0.3"
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# β
Initialize Hugging Face Model
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def get_llm_hf_inference(model_id=model_id, max_new_tokens=512, temperature=0.7):
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return HuggingFaceEndpoint(
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repo_id=model_id,
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max_new_tokens=max_new_tokens,
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# β
Intent Detection
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def predict_action(user_text):
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if "NASA" in user_text.lower() or "space" in user_text.lower():
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return "nasa_info"
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return "general_query"
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# β
Follow-Up Question Generation
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def generate_follow_up(user_text):
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"""Generates a clean follow-up question to guide the user toward related topics or next steps."""
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prompt_text = (
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hf = get_llm_hf_inference(max_new_tokens=40, temperature=0.8)
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output = hf.invoke(input=prompt_text).strip()
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# β
Remove unnecessary characters (like backticks and misplaced formatting)
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cleaned_output = re.sub(r"```|''|\"", "", output).strip()
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# β
Fallback in case the response is empty or invalid
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return cleaned_output if cleaned_output else "Would you like to explore another related topic or ask about something else?"
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# β
Ensure English Responses
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def ensure_english(text):
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try:
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detected_lang = detect(text)
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if detected_lang != "en":
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return "β οΈ Sorry, I only respond in English. Can you rephrase your question?"
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except:
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return "β οΈ Language detection failed. Please ask your question again."
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return text
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# β
Main Response Function
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def get_response(system_message, chat_history, user_text, max_new_tokens=512):
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return response, follow_up, chat_history, None
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# β
Streamlit UI
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st.title("π HAL - NASA AI Assistant")
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# β
Reset Chat Button
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if st.sidebar.button("Reset Chat"):
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st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
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st.session_state.response_ready = False
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st.session_state.follow_up = ""
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# β
Chat UI
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user_input = st.chat_input("Type your message here...")
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if user_input:
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# β
Ensure `get_response()` is executed BEFORE using `response`
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response, follow_up, st.session_state.chat_history, image_url = get_response(
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system_message="You are a helpful AI assistant.",
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user_text=user_input,
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chat_history=st.session_state.chat_history
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)
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# β
Ensure `response` is not None before using it
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if not response:
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response = "I'm sorry, but I couldn't generate a response."
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# β
Handle follow-up question
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if follow_up:
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st.session_state.chat_history.append({'role': 'assistant', 'content': follow_up})
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st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {follow_up}</div>", unsafe_allow_html=True)
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# β
Display NASA image if available
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if image_url:
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st.image(image_url, caption="NASA Image of the Day")
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st.session_state.response_ready = True
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