app.py

import streamlit as st
import requests
import json

def query_api(message, system_prompt):
    url = "https://cc15-115-112-111-186.ngrok-free.app/v1/chat/completions"
    headers = {"Content-Type": "application/json"}
    payload = {
        "model": "deepseek-r1-distill-llama-70b",
        "messages": [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": message}
        ],
        "temperature": 0.7,
        "max_tokens": 300,
        "stream": False
    }
    
    response = requests.post(url, headers=headers, json=payload)
    return response.json()

# Streamlit UI Setup
st.set_page_config(page_title="AI Chatbot", layout="centered")
st.title("🤖 AI Chatbot")
st.write("Talk to an AI coding assistant!")

# Sidebar for system prompt
st.sidebar.header("Settings")
system_prompt = st.sidebar.text_area("System Prompt", "You are a helpful coding assistant.")

if "chat_history" not in st.session_state:
    st.session_state.chat_history = []

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

# User input field
user_input = st.chat_input("Type your message here...")

if user_input:
    st.session_state.chat_history.append({"role": "user", "content": user_input})
    with st.chat_message("user"):
        st.markdown(user_input)
    
    with st.chat_message("assistant"):
        response_data = query_api(user_input, system_prompt)
        response_text = response_data["choices"][0]["message"]["content"]
        st.markdown(response_text)
        
        st.session_state.chat_history.append({"role": "assistant", "content": response_text})