Refactor chatbot interface.

client/interface.py

@@ -0,0 +1,62 @@
+'''Functions for controlling chat flow between Gradio and Anthropic/MCP'''
+
+import json
+import logging
+from gradio.components.chatbot import ChatMessage
+from client.anthropic_bridge import AnthropicBridge
+
+async def agent_input(bridge: AnthropicBridge, chat_history: list) -> list:
+    '''Handles model interactions.'''
+
+    function_logger = logging.getLogger(__name__ + '.agent_input')
+
+    input_messages = format_chat_history(chat_history)
+    result = await bridge.process_query(input_messages)
+    function_logger.info(result)
+
+    try:
+        chat_history.append({
+            "role": "assistant",
+            "content": result['llm_response'].content[0].text
+        })
+
+    except AttributeError:
+        function_logger.info('Model called the tool, but did not talk about it')
+
+    if result['tool_result']:
+        articles = json.loads(result['tool_result'].content)['text']
+        function_logger.info(articles)
+        tmp_chat_history = chat_history.copy()
+        tmp_chat_history.append({
+            "role": "assistant",
+            "content": ('Here are the three most recent entries from the RSS ' +
+                f'feed in JSON format. Tell the user what you have found: {json.dumps(articles)}')
+        })
+
+        tmp_input_messages = format_chat_history(tmp_chat_history)
+        function_logger.info(tmp_input_messages)
+        result = await bridge.process_query(tmp_input_messages)
+
+        chat_history.append({
+            "role": "assistant",
+            "content": result['llm_response'].content[0].text
+        })
+
+    return chat_history
+
+
+def format_chat_history(history) -> list[dict]:
+    '''Formats gradio chat history for submission to anthropic.'''
+
+    messages = []
+
+    for chat_message in history:
+        if isinstance(chat_message, ChatMessage):
+            role, content = chat_message.role, chat_message.content
+        else:
+            role, content = chat_message.get("role"), chat_message.get("content")
+
+        if role in ["user", "assistant", "system"]:
+            messages.append({"role": role, "content": content})
+
+    return messages

rss_client.py

@@ -1,13 +1,12 @@
 '''RSS MCP server demonstration client app.'''
 
 import os
-import json
 import logging
 from pathlib import Path
 from logging.handlers import RotatingFileHandler
 
 import gradio as gr
-from gradio.components.chatbot import ChatMessage
+import client.interface as interface
 from client.mcp_client import MCPClientWrapper
 from client.anthropic_bridge import AnthropicBridge
 
@@ -30,74 +29,27 @@ logging.basicConfig(
 
 logger = logging.getLogger(__name__)
 
-client = MCPClientWrapper('https://agents-mcp-hackathon-rss-mcp-server.hf.space/gradio_api/mcp/sse')
-bridge = AnthropicBridge(
-    client,
+RSS_CLIENT = MCPClientWrapper(
+    'https://agents-mcp-hackathon-rss-mcp-server.hf.space/gradio_api/mcp/sse'
+)
+
+BRIDGE = AnthropicBridge(
+    RSS_CLIENT,
     api_key=os.environ['ANTHROPIC_API_KEY']
 )
 
-async def submit_input(message: str, chat_history: list) -> str:
+async def send_message(message: str, chat_history: list) -> str:
     '''Submits user message to agent'''
 
     function_logger = logging.getLogger(__name__ + '.submit_input')
+    function_logger.info('Submitting user message: %s', message)
 
     chat_history.append({"role": "user", "content": message})
-    input_messages = format_chat_history(chat_history)
-    function_logger.info(input_messages)
-
-    result = await bridge.process_query(input_messages)
-    function_logger.info(result)
-    function_logger.info(result.keys())
-
-    try:
-        chat_history.append({
-            "role": "assistant",
-            "content": result['llm_response'].content[0].text
-        })
-
-    except AttributeError:
-        function_logger.info('Model called the tool, but did not talk about it')
-
-    if result['tool_result']:
-        articles = json.loads(result['tool_result'].content)['text']
-        function_logger.info(articles)
-        tmp_chat_history = chat_history.copy()
-        tmp_chat_history.append({
-            "role": "assistant",
-            "content": ('Here are the three most recent entries from the RSS ' +
-                f'feed in JSON format. Tell the user what you have found: {json.dumps(articles)}')
-        })
-
-        tmp_input_messages = format_chat_history(tmp_chat_history)
-        function_logger.info(tmp_input_messages)
-        result = await bridge.process_query(tmp_input_messages)
-
-        chat_history.append({
-            "role": "assistant",
-            "content": result['llm_response'].content[0].text
-        })
-
+    chat_history = await interface.agent_input(BRIDGE, chat_history)
 
     return '', chat_history
 
 
-def format_chat_history(history) -> list[dict]:
-    '''Formats gradio chat history for submission to anthropic.'''
-
-    messages = []
-
-    for chat_message in history:
-        if isinstance(msg, ChatMessage):
-            role, content = chat_message.role, chat_message.content
-        else:
-            role, content = chat_message.get("role"), chat_message.get("content")
-
-        if role in ["user", "assistant", "system"]:
-            messages.append({"role": role, "content": content})
-
-    return messages
-
-
 with gr.Blocks(title='MCP RSS client') as demo:
     gr.Markdown('# MCP RSS reader')
     gr.Markdown(
@@ -122,8 +74,8 @@ with gr.Blocks(title='MCP RSS client') as demo:
         scale=4
     )
 
-    connect_btn.click(client.list_tools, outputs=status) # pylint: disable=no-member
-    msg.submit(submit_input, [msg, chatbot], [msg, chatbot]) # pylint: disable=no-member
+    connect_btn.click(RSS_CLIENT.list_tools, outputs=status) # pylint: disable=no-member
+    msg.submit(send_message, [msg, chatbot], [msg, chatbot]) # pylint: disable=no-member
 
 if __name__ == '__main__':