save

app.py

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+import os
+
+import openai
+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, enable_streaming=False):
+        """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-3.3-70b-instruct",
+                temperature=0.5,  # Adjust temperature for creativity
+                top_p=1,
+                max_tokens=1024,
+                messages=messages,
+                stream=enable_streaming
+            )
+
+            # Update conversation history in the session state object
+            st.session_state.conversation_manager.conversation_history.append({
+                "role": "assistant",
+                "content": completion.choices[0].message.content
+            })
+
+            if enable_streaming:
+                response_container = st.empty()
+                model_response = ""
+                for chunk in completion:
+                    if chunk.choices[0].delta.content is not None:
+                        model_response += chunk.choices[0].delta.content
+                        response_container.markdown(model_response)
+                    elif 'error' in chunk:
+                        st.error(f"Error occurred: {chunk['error']}")
+                        break
+                return model_response
+            else:
+                return completion.choices[0].message.content
+
+        except Exception as e:
+            print(f"Error: {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("Generating code..."):
+                # 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()

requirements.txt

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+streamlit
+openai
+streamlit-chat
+python-dotenv