Basic tool calling works.

client/anthropic_bridge.py

@@ -192,9 +192,10 @@ class AnthropicBridge(LLMBridge):
             model=self.model,
             max_tokens=4096,
             system='You are a helpful tool-using assistant.',
-            messages=[
-                {'role': 'user', 'content': query}
-            ],
+            # messages=[
+            #     {'role': 'user', 'content': query}
+            # ],
+            messages=query,
             tools=formatted_tools
         )
 

rss_client.py

@@ -1,11 +1,13 @@
 '''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
 from client.mcp_client import MCPClientWrapper
 from client.anthropic_bridge import AnthropicBridge
 
@@ -39,14 +41,63 @@ async def submit_input(message: str, chat_history: list) -> str:
 
     function_logger = logging.getLogger(__name__ + '.submit_input')
 
-    result = await bridge.process_query(message)
-    function_logger.info(result)
     chat_history.append({"role": "user", "content": message})
-    chat_history.append({"role": "assistant", "content": result['llm_response'].content[0].text})
+    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
+        })
+
 
     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(