import os from openai import OpenAI import streamlit as st api_key = os.getenv("NVIDIA_API_KEY") # Check if the API key is found if api_key is None: st.error("NVIDIA_API_KEY environment variable not found.") else: # Initialize the OpenAI client client = OpenAI( base_url="https://integrate.api.nvidia.com/v1", api_key=api_key ) class ConversationManager: def __init__(self): # (No need to initialize history here, it will be handled in main()) pass def generate_ai_response(self, prompt): """Generates a response from an AI model Args: prompt: The prompt to send to the AI model. Returns: response from the AI model. """ try: # Access conversation_history from session state messages = [ { "role": "system", "content": "You are a programming assistant focused on providing \ accurate, clear, and concise answers to technical questions. \ Your goal is to help users solve programming problems efficiently, \ explain concepts clearly, and provide examples when appropriate. \ Use a professional yet approachable tone. Use explicit markdown \ format for code for all codes in the output." } ] for message in st.session_state.conversation_manager.conversation_history: messages.append(message) messages.append({ "role": "user", "content": prompt }) completion = client.chat.completions.create( model="meta/llama-3.1-405b-instruct", temperature=0.5, # Adjust temperature for creativity top_p=1, max_tokens=1024, messages=messages, stream=False ) model_response = completion.choices[0].message.content st.session_state.conversation_manager.conversation_history.append({ "role": "assistant", "content": model_response }) st.session_state.conversation_manager.conversation_history.append({ "role": "assistant", "content": completion.choices[0].message.content }) return model_response except Exception as e: st.error(f"Error handling AI response: {e}") return None def main(): # Initialize ConversationManager in session state if not already present if "conversation_manager" not in st.session_state: st.session_state.conversation_manager = ConversationManager() st.session_state.conversation_manager.conversation_history = [] st.title("AI-Assisted Code Generator") tab1, tab2, tab3 = st.tabs(["About", "Code Generation", "Conversation History"]) with tab1: st.header("About this App") st.write("This app demonstrates how to use AI to assist in code generation.") with tab2: st.header("Generate Code") framework = st.selectbox("Select a framework", ["Streamlit", "Gradio"]) app_details = st.text_area("Describe the app you want to create", value="Create a complete app that ") if st.button("Generate Prompt"): user_prompt = f"Using {framework}, {app_details}" st.write("**Generated Prompt:**", user_prompt) with st.spinner("Thinking..."): # Add the user message to the history FIRST st.session_state.conversation_manager.conversation_history.append({"role": "user", "content": user_prompt}) ai_response = st.session_state.conversation_manager.generate_ai_response(user_prompt) if ai_response: st.session_state.conversation_manager.conversation_history.append({"role": "assistant", "content": ai_response}) st.markdown(f"**User:** {user_prompt}") st.markdown(f"**AI:** {ai_response}") else: st.write("**Error:** Failed to generate AI response.") with tab3: st.header("Conversation History") if st.session_state.conversation_manager.conversation_history: for msg in st.session_state.conversation_manager.conversation_history: if msg['role'] == 'user': st.markdown(f"**User:** {msg['content']}") else: st.markdown(f"**AI:** {msg['content']}") else: st.write("No conversation history yet.") if __name__ == "__main__": main()