chatgskd.py

import streamlit as st
import requests
import os

# Load API Key from Hugging Face Secrets
HF_API_KEY = os.getenv("KEY")

# API URL
HF_MISTRAL_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.3"

# Function to call Hugging Face API
def chat_with_mistral_hf(prompt):
    if not HF_API_KEY:
        return "Error: API key not found. Please set it in Hugging Face Secrets."
    
    headers = {"Authorization": f"Bearer {HF_API_KEY}"}
    payload = {"inputs": prompt, "parameters": {"max_length": 200, "temperature": 0.7}}
    
    response = requests.post(HF_MISTRAL_URL, json=payload, headers=headers)
    
    if response.status_code == 200:
        return response.json()[0]["generated_text"]
    else:
        return f"Error: {response.json()}"

# Streamlit UI
st.set_page_config(page_title="ChatGSKD", layout="wide")

# Sidebar: Chat title rename option
st.sidebar.header("Chat Settings")
chat_title = st.sidebar.text_input("Rename Chat:", "Temporary Chat")

# Initialize chat history if not present
if "chat_history" not in st.session_state:
    st.session_state.chat_history = []

# Display Chat Title
st.title(chat_title)

# Show chat history
for chat in st.session_state.chat_history:
    with st.chat_message(chat["role"]):
        st.write(chat["content"])

# Input box at the bottom
user_input = st.text_area("Ask AI:", height=100, key="query", label_visibility="collapsed")

# Generate response when user submits a prompt
if st.button("Generate Response"):
    if user_input.strip():
        with st.spinner("Generating response..."):
            response = chat_with_mistral_hf(user_input)
            
            # Store user query & response in chat history
            st.session_state.chat_history.append({"role": "user", "content": user_input})
            st.session_state.chat_history.append({"role": "assistant", "content": response})

            # Refresh the page to show new messages
            st.rerun()
    else:
        st.warning("Please enter a prompt before clicking Generate Response.")