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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("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"])
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