Add chat_input version Streamlit

Gradio_UI.py

@@ -239,7 +239,7 @@ class GradioUI:
             if not os.path.exists(file_upload_folder):
                 os.mkdir(file_upload_folder)
 
-    def interact_with_agent(self, prompt, messages):
+    def interact_with_agent(self, prompt: str, messages: list):
         import gradio as gr
 
         messages.append(gr.ChatMessage(role="user", content=prompt))
@@ -301,7 +301,7 @@ class GradioUI:
             f"File uploaded: {file_path}", visible=True
         ), file_uploads_log + [file_path]
 
-    def log_user_message(self, text_input, file_uploads_log):
+    def log_user_message(self, text_input: str, file_uploads_log):
         return (
             text_input
             + (

README.md

@@ -22,10 +22,13 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
 - [First Agent Template - a Hugging Face Space by daviddwlee84](https://huggingface.co/spaces/daviddwlee84/First_Agent)
 
 ```bash
+# https://www.gradio.app/guides/quickstart#building-your-first-demo
 # Gradio (TODO: somehow buggy)
 python app.py
-# Streamlit (TODO: use `chat_input` and able to clear message history)
+# Streamlit (TODO: able to clear message history)
 streamlit run streamlit_app.py
+# Streamlit chat_input (TODO: move ReAct process to `st.expander`)
+streamlit run streamlit_app_chat.py
 # Chainlit (TODO: move the ReAct process from agent message to "step")
 chainlit run chainlit_app.py
 ```

streamlit_app_chat.py

@@ -0,0 +1,36 @@
+import streamlit as st
+
+from app import agent  # your CodeAgent instance
+from Gradio_UI import stream_to_gradio  # generator yielding gr.ChatMessage objects
+
+st.set_page_config(page_title="CodeAgent Chat", layout="wide")
+st.title("CodeAgent Chat (Streamlit)")
+
+# Initialize session state for chat history.
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+
+# Reset Chat button.
+if st.button("Reset Chat"):
+    st.session_state.chat_history = []
+    st.rerun()  # Rerun the script to update the UI immediately.
+
+# Display chat history using Streamlit's chat message container.
+for chat in st.session_state.chat_history:
+    st.chat_message(chat["role"]).write(chat["content"])
+
+# Use st.chat_input for user message entry.
+user_input = st.chat_input("Type your message here")
+if user_input:
+    # Append and display the user's message.
+    st.session_state.chat_history.append({"role": "user", "content": user_input})
+    st.chat_message("user").write(user_input)
+
+    # Stream the agent responses.
+    # The generator yields gr.ChatMessage objects that have 'role' and 'content' attributes.
+    for msg in stream_to_gradio(agent, user_input, reset_agent_memory=False):
+        role = msg.role
+        # Convert non-string content to a string as needed.
+        content = msg.content if isinstance(msg.content, str) else str(msg.content)
+        st.session_state.chat_history.append({"role": role, "content": content})
+        st.chat_message(role).write(content)