Python: Fixed Anthropic and GitHub Copilot samples (#4025)

* Fixed Anthropic advanced example

* Small improvement

* Simplified skills sample

* Fixed custom agent sample

* Added service_session_id parameter

* Added tests

* Resolved comments

python/packages/anthropic/agent_framework_anthropic/_chat_client.py

@@ -324,8 +324,9 @@ class AnthropicClient(
         self.anthropic_client = anthropic_client
         self.additional_beta_flags = additional_beta_flags or []
         self.model_id = anthropic_settings["chat_model_id"]
-        # streaming requires tracking the last function call ID and name
+        # streaming requires tracking the last function call ID, name, and content type
         self._last_call_id_name: tuple[str, str] | None = None
+        self._last_call_content_type: str | None = None
 
     # region Static factory methods for hosted tools
 
@@ -333,11 +334,13 @@ class AnthropicClient(
     def get_code_interpreter_tool(
         *,
         type_name: str | None = None,
+        name: str = "code_execution",
     ) -> dict[str, Any]:
         """Create a code interpreter tool configuration for Anthropic.
 
         Keyword Args:
             type_name: Override the tool type name. Defaults to "code_execution_20250825".
+            name: The name for this tool. Defaults to "code_execution".
 
         Returns:
             A dict-based tool configuration ready to pass to ChatAgent.
@@ -350,17 +353,19 @@ class AnthropicClient(
                 tool = AnthropicClient.get_code_interpreter_tool()
                 agent = AnthropicClient().as_agent(tools=[tool])
         """
-        return {"type": type_name or "code_execution_20250825"}
+        return {"type": type_name or "code_execution_20250825", "name": name}
 
     @staticmethod
     def get_web_search_tool(
         *,
         type_name: str | None = None,
+        name: str = "web_search",
     ) -> dict[str, Any]:
         """Create a web search tool configuration for Anthropic.
 
         Keyword Args:
             type_name: Override the tool type name. Defaults to "web_search_20250305".
+            name: The name for this tool. Defaults to "web_search".
 
         Returns:
             A dict-based tool configuration ready to pass to ChatAgent.
@@ -373,7 +378,7 @@ class AnthropicClient(
                 tool = AnthropicClient.get_web_search_tool()
                 agent = AnthropicClient().as_agent(tools=[tool])
         """
-        return {"type": type_name or "web_search_20250305"}
+        return {"type": type_name or "web_search_20250305", "name": name}
 
     @staticmethod
     def get_mcp_tool(
@@ -661,8 +666,27 @@ class AnthropicClient(
                         "content": content.result if content.result is not None else "",
                         "is_error": content.exception is not None,
                     })
+                case "mcp_server_tool_call":
+                    mcp_call: dict[str, Any] = {
+                        "type": "mcp_tool_use",
+                        "id": content.call_id,
+                        "name": content.tool_name,
+                        "server_name": content.server_name or "",
+                        "input": content.parse_arguments() or {},
+                    }
+                    a_content.append(mcp_call)
+                case "mcp_server_tool_result":
+                    mcp_result: dict[str, Any] = {
+                        "type": "mcp_tool_result",
+                        "tool_use_id": content.call_id,
+                        "content": content.output if content.output is not None else "",
+                    }
+                    a_content.append(mcp_result)
                 case "text_reasoning":
-                    a_content.append({"type": "thinking", "thinking": content.text})
+                    thinking_block: dict[str, Any] = {"type": "thinking", "thinking": content.text}
+                    if content.protected_data:
+                        thinking_block["signature"] = content.protected_data
+                    a_content.append(thinking_block)
                 case _:
                     logger.debug(f"Ignoring unsupported content type: {content.type} for now")
 
@@ -866,12 +890,13 @@ class AnthropicClient(
                     )
                 case "tool_use" | "mcp_tool_use" | "server_tool_use":
                     self._last_call_id_name = (content_block.id, content_block.name)
+                    self._last_call_content_type = content_block.type
                     if content_block.type == "mcp_tool_use":
                         contents.append(
                             Content.from_mcp_server_tool_call(
                                 call_id=content_block.id,
                                 tool_name=content_block.name,
-                                server_name=None,
+                                server_name=getattr(content_block, "server_name", None),
                                 arguments=content_block.input,
                                 raw_representation=content_block,
                             )
@@ -1129,24 +1154,32 @@ class AnthropicClient(
                         )
                     )
                 case "input_json_delta":
-                    # For streaming argument deltas, only pass call_id and arguments.
-                    # Pass empty string for name - it causes ag-ui to emit duplicate ToolCallStartEvents
-                    # since it triggers on `if content.name:`. The initial tool_use event already
-                    # provides the name, so deltas should only carry incremental arguments.
-                    # This matches OpenAI's behavior where streaming chunks have name="".
-                    call_id, _name = self._last_call_id_name if self._last_call_id_name else ("", "")
-                    contents.append(
-                        Content.from_function_call(
-                            call_id=call_id,
-                            name="",
-                            arguments=content_block.partial_json,
-                            raw_representation=content_block,
+                    # Skip argument deltas for MCP tools — execution is handled server-side.
+                    if self._last_call_content_type == "mcp_tool_use":
+                        pass
+                    else:
+                        call_id = self._last_call_id_name[0] if self._last_call_id_name else ""
+                        contents.append(
+                            Content.from_function_call(
+                                call_id=call_id,
+                                name="",
+                                arguments=content_block.partial_json,
+                                raw_representation=content_block,
+                            )
                         )
-                    )
                 case "thinking" | "thinking_delta":
                     contents.append(
                         Content.from_text_reasoning(
                             text=content_block.thinking,
+                            protected_data=getattr(content_block, "signature", None),
+                            raw_representation=content_block,
+                        )
+                    )
+                case "signature_delta":
+                    contents.append(
+                        Content.from_text_reasoning(
+                            text=None,
+                            protected_data=content_block.signature,
                             raw_representation=content_block,
                         )
                     )

python/packages/anthropic/tests/test_anthropic_client.py

@@ -220,6 +220,119 @@ def test_prepare_message_for_anthropic_text_reasoning(mock_anthropic_client: Mag
     assert len(result["content"]) == 1
     assert result["content"][0]["type"] == "thinking"
     assert result["content"][0]["thinking"] == "Let me think about this..."
+    assert "signature" not in result["content"][0]
+
+
+def test_prepare_message_for_anthropic_text_reasoning_with_signature(mock_anthropic_client: MagicMock) -> None:
+    """Test converting text reasoning message with signature to Anthropic format."""
+    client = create_test_anthropic_client(mock_anthropic_client)
+    message = Message(
+        role="assistant",
+        contents=[Content.from_text_reasoning(text="Let me think about this...", protected_data="sig_abc123")],
+    )
+
+    result = client._prepare_message_for_anthropic(message)
+
+    assert result["role"] == "assistant"
+    assert len(result["content"]) == 1
+    assert result["content"][0]["type"] == "thinking"
+    assert result["content"][0]["thinking"] == "Let me think about this..."
+    assert result["content"][0]["signature"] == "sig_abc123"
+
+
+def test_prepare_message_for_anthropic_mcp_server_tool_call(mock_anthropic_client: MagicMock) -> None:
+    """Test converting MCP server tool call message to Anthropic format."""
+    client = create_test_anthropic_client(mock_anthropic_client)
+    message = Message(
+        role="assistant",
+        contents=[
+            Content.from_mcp_server_tool_call(
+                call_id="mcp_call_123",
+                tool_name="search_docs",
+                server_name="microsoft-learn",
+                arguments={"query": "Azure Functions"},
+            )
+        ],
+    )
+
+    result = client._prepare_message_for_anthropic(message)
+
+    assert result["role"] == "assistant"
+    assert len(result["content"]) == 1
+    assert result["content"][0]["type"] == "mcp_tool_use"
+    assert result["content"][0]["id"] == "mcp_call_123"
+    assert result["content"][0]["name"] == "search_docs"
+    assert result["content"][0]["server_name"] == "microsoft-learn"
+    assert result["content"][0]["input"] == {"query": "Azure Functions"}
+
+
+def test_prepare_message_for_anthropic_mcp_server_tool_call_no_server_name(mock_anthropic_client: MagicMock) -> None:
+    """Test converting MCP server tool call with no server name defaults to empty string."""
+    client = create_test_anthropic_client(mock_anthropic_client)
+    message = Message(
+        role="assistant",
+        contents=[
+            Content.from_mcp_server_tool_call(
+                call_id="mcp_call_456",
+                tool_name="list_files",
+                arguments=None,
+            )
+        ],
+    )
+
+    result = client._prepare_message_for_anthropic(message)
+
+    assert result["role"] == "assistant"
+    assert len(result["content"]) == 1
+    assert result["content"][0]["type"] == "mcp_tool_use"
+    assert result["content"][0]["id"] == "mcp_call_456"
+    assert result["content"][0]["name"] == "list_files"
+    assert result["content"][0]["server_name"] == ""
+    assert result["content"][0]["input"] == {}
+
+
+def test_prepare_message_for_anthropic_mcp_server_tool_result(mock_anthropic_client: MagicMock) -> None:
+    """Test converting MCP server tool result message to Anthropic format."""
+    client = create_test_anthropic_client(mock_anthropic_client)
+    message = Message(
+        role="tool",
+        contents=[
+            Content.from_mcp_server_tool_result(
+                call_id="mcp_call_123",
+                output="Found 3 results for Azure Functions.",
+            )
+        ],
+    )
+
+    result = client._prepare_message_for_anthropic(message)
+
+    assert result["role"] == "user"
+    assert len(result["content"]) == 1
+    assert result["content"][0]["type"] == "mcp_tool_result"
+    assert result["content"][0]["tool_use_id"] == "mcp_call_123"
+    assert result["content"][0]["content"] == "Found 3 results for Azure Functions."
+
+
+def test_prepare_message_for_anthropic_mcp_server_tool_result_none_output(mock_anthropic_client: MagicMock) -> None:
+    """Test converting MCP server tool result with None output defaults to empty string."""
+    client = create_test_anthropic_client(mock_anthropic_client)
+    message = Message(
+        role="tool",
+        contents=[
+            Content.from_mcp_server_tool_result(
+                call_id="mcp_call_789",
+                output=None,
+            )
+        ],
+    )
+
+    result = client._prepare_message_for_anthropic(message)
+
+    assert result["role"] == "user"
+    assert len(result["content"]) == 1
+    assert result["content"][0]["type"] == "mcp_tool_result"
+    assert result["content"][0]["tool_use_id"] == "mcp_call_789"
+    assert result["content"][0]["content"] == ""
 
 
 def test_prepare_messages_for_anthropic_with_system(mock_anthropic_client: MagicMock) -> None:
@@ -287,6 +400,7 @@ def test_prepare_tools_for_anthropic_web_search(mock_anthropic_client: MagicMock
     assert "tools" in result
     assert len(result["tools"]) == 1
     assert result["tools"][0]["type"] == "web_search_20250305"
+    assert result["tools"][0]["name"] == "web_search"
 
 
 def test_prepare_tools_for_anthropic_code_interpreter(mock_anthropic_client: MagicMock) -> None:
@@ -300,6 +414,7 @@ def test_prepare_tools_for_anthropic_code_interpreter(mock_anthropic_client: Mag
     assert "tools" in result
     assert len(result["tools"]) == 1
     assert result["tools"][0]["type"] == "code_execution_20250825"
+    assert result["tools"][0]["name"] == "code_execution"
 
 
 def test_prepare_tools_for_anthropic_mcp_tool(mock_anthropic_client: MagicMock) -> None:
@@ -1764,11 +1879,13 @@ def test_parse_thinking_block(mock_anthropic_client: MagicMock) -> None:
     mock_block = MagicMock()
     mock_block.type = "thinking"
     mock_block.thinking = "Let me think about this..."
+    mock_block.signature = "sig_abc123"
 
     result = client._parse_contents_from_anthropic([mock_block])
 
     assert len(result) == 1
     assert result[0].type == "text_reasoning"
+    assert result[0].protected_data == "sig_abc123"
 
 
 def test_parse_thinking_delta_block(mock_anthropic_client: MagicMock) -> None:
@@ -1786,6 +1903,23 @@ def test_parse_thinking_delta_block(mock_anthropic_client: MagicMock) -> None:
     assert result[0].type == "text_reasoning"
 
 
+def test_parse_signature_delta_block(mock_anthropic_client: MagicMock) -> None:
+    """Test parsing signature delta content block."""
+    client = create_test_anthropic_client(mock_anthropic_client)
+
+    # Create mock signature delta block
+    mock_block = MagicMock()
+    mock_block.type = "signature_delta"
+    mock_block.signature = "sig_xyz789"
+
+    result = client._parse_contents_from_anthropic([mock_block])
+
+    assert len(result) == 1
+    assert result[0].type == "text_reasoning"
+    assert result[0].text is None
+    assert result[0].protected_data == "sig_xyz789"
+
+
 # Citation Tests
 
 

python/samples/02-agents/providers/anthropic/anthropic_advanced.py

@@ -44,7 +44,7 @@ async def main() -> None:
     print("Agent: ", end="", flush=True)
     async for chunk in agent.run(query, stream=True):
         for content in chunk.contents:
-            if content.type == "text_reasoning":
+            if content.type == "text_reasoning" and content.text:
                 print(f"\033[32m{content.text}\033[0m", end="", flush=True)
             if content.type == "usage":
                 print(f"\n\033[34m[Usage so far: {content.usage_details}]\033[0m\n", end="", flush=True)

python/samples/02-agents/providers/anthropic/anthropic_claude_with_session.py

@@ -123,8 +123,8 @@ async def example_with_existing_session_id() -> None:
         )
 
         async with agent2:
-            # Create session with existing session ID
-            session = agent2.create_session(service_session_id=existing_session_id)
+            # Get session with existing session ID
+            session = agent2.get_session(service_session_id=existing_session_id)
 
             query2 = "What was the last city I asked about?"
             print(f"User: {query2}")

python/samples/02-agents/providers/anthropic/anthropic_claude_with_shell.py

@@ -47,7 +47,7 @@ async def main() -> None:
     )
 
     async with agent:
-        query = "List the first 3 Python files in the current directory"
+        query = "List the first 3 markdown (.md) files in the current directory"
         print(f"User: {query}")
         result = await agent.run(query)
         print(f"Agent: {result.text}\n")

python/samples/02-agents/providers/anthropic/anthropic_skills.py

@@ -36,8 +36,8 @@ async def main() -> None:
         instructions="You are a helpful agent for creating powerpoint presentations.",
         tools=client.get_code_interpreter_tool(),
         default_options={
-            "max_tokens": 20000,
-            "thinking": {"type": "enabled", "budget_tokens": 10000},
+            "max_tokens": 4096,
+            "thinking": {"type": "enabled", "budget_tokens": 2000},
             "container": {"skills": [{"type": "anthropic", "skill_id": "pptx", "version": "latest"}]},
         },
     )
@@ -49,7 +49,7 @@ async def main() -> None:
         "\033[32mAgent Reasoning: (green)\033[0m\n"
         "\033[34mUsage: (blue)\033[0m\n"
     )
-    query = "Create a presentation about renewable energy with 5 slides"
+    query = "Create a simple presentation with 2 slides about Python programming"
     print(f"User: {query}")
     print("Agent: ", end="", flush=True)
     files: list[Content] = []
@@ -79,9 +79,9 @@ async def main() -> None:
             file_content = await client.anthropic_client.beta.files.download(
                 file_id=file.file_id, betas=["files-api-2025-04-14"]
             )
-            with open(Path(__file__).parent / f"renewable_energy-{idx}.pptx", "wb") as f:
+            with open(Path(__file__).parent / f"python_programming-{idx}.pptx", "wb") as f:
                 await file_content.write_to_file(f.name)
-            print(f"File {idx}: renewable_energy-{idx}.pptx saved to disk.")
+            print(f"File {idx}: python_programming-{idx}.pptx saved to disk.")
 
 
 if __name__ == "__main__":

python/samples/02-agents/providers/custom/custom_agent.py

@@ -12,7 +12,6 @@ from agent_framework import (
     Content,
     InMemoryHistoryProvider,
     Message,
-    Role,
     normalize_messages,
 )
 
@@ -93,7 +92,7 @@ class EchoAgent(BaseAgent):
 
         if not normalized_messages:
             response_message = Message(
-                role=Role.ASSISTANT,
+                role="assistant",
                 contents=[
                     Content.from_text(text="Hello! I'm a custom echo agent. Send me a message and I'll echo it back.")
                 ],
@@ -106,11 +105,11 @@ class EchoAgent(BaseAgent):
             else:
                 echo_text = f"{self.echo_prefix}[Non-text message received]"
 
-            response_message = Message(role=Role.ASSISTANT, contents=[Content.from_text(text=echo_text)])
+            response_message = Message(role="assistant", contents=[Content.from_text(text=echo_text)])
 
         # Store messages in session state if provided
         if session is not None:
-            stored = session.state.setdefault("memory", {}).setdefault("messages", [])
+            stored = session.state.setdefault(InMemoryHistoryProvider.DEFAULT_SOURCE_ID, {}).setdefault("messages", [])
             stored.extend(normalized_messages)
             stored.append(response_message)
 
@@ -145,7 +144,7 @@ class EchoAgent(BaseAgent):
 
             yield AgentResponseUpdate(
                 contents=[Content.from_text(text=chunk_text)],
-                role=Role.ASSISTANT,
+                role="assistant",
             )
 
             # Small delay to simulate streaming
@@ -153,8 +152,8 @@ class EchoAgent(BaseAgent):
 
         # Store messages in session state if provided
         if session is not None:
-            complete_response = Message(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)])
-            stored = session.state.setdefault("memory", {}).setdefault("messages", [])
+            complete_response = Message(role="assistant", contents=[Content.from_text(text=response_text)])
+            stored = session.state.setdefault(InMemoryHistoryProvider.DEFAULT_SOURCE_ID, {}).setdefault("messages", [])
             stored.extend(normalized_messages)
             stored.append(complete_response)
 

python/samples/02-agents/providers/github_copilot/github_copilot_with_session.py

@@ -118,8 +118,8 @@ async def example_with_existing_session_id() -> None:
         )
 
         async with agent2:
-            # Create session with existing session ID
-            session = agent2.create_session(service_session_id=existing_session_id)
+            # Get session with existing session ID
+            session = agent2.get_session(service_session_id=existing_session_id)
 
             query2 = "What was the last city I asked about?"
             print(f"User: {query2}")

python/samples/04-hosting/azure_functions/12_workflow_hitl/function_app.py

@@ -32,8 +32,8 @@ from typing import Any
 from agent_framework import (
     AgentExecutorRequest,
     AgentExecutorResponse,
-    Message,
     Executor,
+    Message,
     Workflow,
     WorkflowBuilder,
     WorkflowContext,