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import os
import streamlit as st
import faiss
import pickle
from groq import Groq
from datasets import load_dataset
from transformers import pipeline
# Initialize Groq API
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
# Load datasets
healthcare_ds = load_dataset("harishnair04/mtsamples")
education_ds = load_dataset("ehovy/race", "all")
finance_ds = load_dataset("warwickai/financial_phrasebank_mirror")
# FAISS Index Setup
index = faiss.IndexFlatL2(768)
chat_history = []
# Streamlit UI Setup
st.set_page_config(page_title="AI Chatbot", layout="wide")
st.title("🤖 AI Chatbot (Healthcare, Education & Finance)")
# Sidebar for chat history
st.sidebar.title("📜 Chat History")
if st.sidebar.button("Download Chat History"):
with open("chat_history.txt", "w") as file:
file.write("\n".join(chat_history))
st.sidebar.success("Chat history saved!")
# Chat Interface
user_input = st.text_input("💬 Ask me anything:", placeholder="Type your query here...")
if st.button("Send"):
if user_input:
# Determine dataset based on user query (Basic CAG Implementation)
dataset = healthcare_ds if "health" in user_input.lower() else \
education_ds if "education" in user_input.lower() else \
finance_ds
# RAG: Retrieve relevant data
retrieved_data = dataset['train'][0] # Simplified retrieval
# Generate response using Llama via Groq API
chat_completion = client.chat.completions.create(
messages=[{"role": "user", "content": f"{user_input} {retrieved_data}"}],
model="llama-3.3-70b-versatile"
)
response = chat_completion.choices[0].message.content
# Save chat to FAISS and display
chat_history.append(f"User: {user_input}\nBot: {response}")
st.text_area("🤖 AI Response:", value=response, height=200)
# Display past chats
st.sidebar.write("\n".join(chat_history))
# Save chat history using pickle for persistence
def save_chat_history():
with open("chat_history.pkl", "wb") as file:
pickle.dump(chat_history, file)
def load_chat_history():
global chat_history
if os.path.exists("chat_history.pkl"):
with open("chat_history.pkl", "rb") as file:
chat_history = pickle.load(file)
load_chat_history()
if st.sidebar.button("Save Chat History"):
save_chat_history()
st.sidebar.success("Chat history saved permanently!")
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