The New Archon (Beta) - The Operating System for AI Coding Assistants!

original_archon/streamlit_pages/chat.py

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+from langgraph.types import Command
+import streamlit as st
+import uuid
+import sys
+import os
+
+# Add the current directory to Python path
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+from archon.archon_graph import agentic_flow
+
+@st.cache_resource
+def get_thread_id():
+    return str(uuid.uuid4())
+
+thread_id = get_thread_id()
+
+async def run_agent_with_streaming(user_input: str):
+    """
+    Run the agent with streaming text for the user_input prompt,
+    while maintaining the entire conversation in `st.session_state.messages`.
+    """
+    config = {
+        "configurable": {
+            "thread_id": thread_id
+        }
+    }
+
+    # First message from user
+    if len(st.session_state.messages) == 1:
+        async for msg in agentic_flow.astream(
+                {"latest_user_message": user_input}, config, stream_mode="custom"
+            ):
+                yield msg
+    # Continue the conversation
+    else:
+        async for msg in agentic_flow.astream(
+            Command(resume=user_input), config, stream_mode="custom"
+        ):
+            yield msg
+
+async def chat_tab():
+    """Display the chat interface for talking to Archon"""
+    st.write("Describe to me an AI agent you want to build and I'll code it for you with Pydantic AI.")
+    st.write("Example: Build me an AI agent that can search the web with the Brave API.")
+
+    # Initialize chat history in session state if not present
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+    
+    # Add a clear conversation button
+    if st.button("Clear Conversation"):
+        st.session_state.messages = []
+        st.rerun()
+
+    # Display chat messages from history on app rerun
+    for message in st.session_state.messages:
+        message_type = message["type"]
+        if message_type in ["human", "ai", "system"]:
+            with st.chat_message(message_type):
+                st.markdown(message["content"])    
+
+    # Chat input for the user
+    user_input = st.chat_input("What do you want to build today?")
+
+    if user_input:
+        # We append a new request to the conversation explicitly
+        st.session_state.messages.append({"type": "human", "content": user_input})
+        
+        # Display user prompt in the UI
+        with st.chat_message("user"):
+            st.markdown(user_input)
+
+        # Display assistant response in chat message container
+        response_content = ""
+        with st.chat_message("assistant"):
+            message_placeholder = st.empty()  # Placeholder for updating the message
+            
+            # Add a spinner while loading
+            with st.spinner("Archon is thinking..."):
+                # Run the async generator to fetch responses
+                async for chunk in run_agent_with_streaming(user_input):
+                    response_content += chunk
+                    # Update the placeholder with the current response content
+                    message_placeholder.markdown(response_content)
+        
+        st.session_state.messages.append({"type": "ai", "content": response_content})