Merge branch 'main' into qian/dbos-agent

Author: qianl15

docs/builtin-tools.md

@@ -1,10 +1,10 @@
 # Builtin Tools
 
-Builtin tools are native tools provided by LLM providers that can be used to enhance your agent's capabilities. Unlike [common tools](common-tools.md), which are custom implementations that PydanticAI executes, builtin tools are executed directly by the model provider.
+Builtin tools are native tools provided by LLM providers that can be used to enhance your agent's capabilities. Unlike [common tools](common-tools.md), which are custom implementations that Pydantic AI executes, builtin tools are executed directly by the model provider.
 
 ## Overview
 
-PydanticAI supports the following builtin tools:
+Pydantic AI supports the following builtin tools:
 
 - **[`WebSearchTool`][pydantic_ai.builtin_tools.WebSearchTool]**: Allows agents to search the web
 - **[`CodeExecutionTool`][pydantic_ai.builtin_tools.CodeExecutionTool]**: Enables agents to execute code in a secure environment
@@ -13,7 +13,9 @@ PydanticAI supports the following builtin tools:
 These tools are passed to the agent via the `builtin_tools` parameter and are executed by the model provider's infrastructure.
 
 !!! warning "Provider Support"
-    Not all model providers support builtin tools. If you use a builtin tool with an unsupported provider, PydanticAI will raise a [`UserError`][pydantic_ai.exceptions.UserError] when you try to run the agent.
+    Not all model providers support builtin tools. If you use a builtin tool with an unsupported provider, Pydantic AI will raise a [`UserError`][pydantic_ai.exceptions.UserError] when you try to run the agent.
+
+    If a provider supports a built-in tool that is not currently supported by Pydantic AI, please file an issue.
 
 ## Web Search Tool
 
@@ -26,16 +28,13 @@ making it ideal for queries that require up-to-date data.
 |----------|-----------|-------|
 | OpenAI | ✅ | Full feature support |
 | Anthropic | ✅ | Full feature support |
-| Groq | ✅ | Limited parameter support |
-| Google | ✅ | No parameter support |
+| Groq | ✅ | Limited parameter support. To use web search capabilities with Groq, you need to use the [compound models](https://console.groq.com/docs/compound). |
+| Google | ✅ | No parameter support. Google does not support using built-in tools and user tools (including [output tools](output.md#tool-output)) at the same time. To use structured output, use [`PromptedOutput`](output.md#prompted-output) instead. |
 | Bedrock | ❌ | Not supported |
 | Mistral | ❌ | Not supported |
 | Cohere | ❌ | Not supported |
 | HuggingFace | ❌ | Not supported |
 
-!!! note "Groq Support"
-    To use web search capabilities with Groq, you need to use the [compound models](https://console.groq.com/docs/compound).
-
 ### Usage
 
 ```py title="web_search_basic.py"
@@ -97,16 +96,16 @@ in a secure environment, making it perfect for computational tasks, data analysi
 
 ### Provider Support
 
-| Provider | Supported |
-|----------|-----------|
-| OpenAI | ✅ |
-| Anthropic | ✅ |
-| Google | ✅ |
-| Groq | ❌ |
-| Bedrock | ❌ |
-| Mistral | ❌ |
-| Cohere | ❌ |
-| HuggingFace | ❌ |
+| Provider | Supported | Notes |
+|----------|-----------|-------|
+| OpenAI | ✅ | |
+| Anthropic | ✅ | Google does not support using built-in tools and user tools (including [output tools](output.md#tool-output)) at the same time. To use structured output, use [`PromptedOutput`](output.md#prompted-output) instead. |
+| Google | ✅ | |
+| Groq | ❌ | |
+| Bedrock | ❌ | |
+| Mistral | ❌ | |
+| Cohere | ❌ | |
+| HuggingFace | ❌ | |
 
 ### Usage
 
@@ -126,16 +125,16 @@ allowing it to pull up-to-date information from the web.
 
 ### Provider Support
 
-| Provider | Supported |
-|----------|-----------|
-| Google | ✅ |
-| OpenAI | ❌ |
-| Anthropic | ❌ |
-| Groq | ❌ |
-| Bedrock | ❌ |
-| Mistral | ❌ |
-| Cohere | ❌ |
-| HuggingFace | ❌ |
+| Provider | Supported | Notes |
+|----------|-----------|-------|
+| Google | ✅ | Google does not support using built-in tools and user tools (including [output tools](output.md#tool-output)) at the same time. To use structured output, use [`PromptedOutput`](output.md#prompted-output) instead. |
+| OpenAI | ❌ | |
+| Anthropic | ❌ | |
+| Groq | ❌ | |
+| Bedrock | ❌ | |
+| Mistral | ❌ | |
+| Cohere | ❌ | |
+| HuggingFace | ❌ | |
 
 ### Usage
 

pydantic_ai_slim/pydantic_ai/_parts_manager.py

@@ -154,6 +154,7 @@ def handle_thinking_delta(
         *,
         vendor_part_id: Hashable | None,
         content: str | None = None,
+        id: str | None = None,
         signature: str | None = None,
     ) -> ModelResponseStreamEvent:
         """Handle incoming thinking content, creating or updating a ThinkingPart in the manager as appropriate.
@@ -167,6 +168,7 @@ def handle_thinking_delta(
                 of thinking. If None, a new part will be created unless the latest part is already
                 a ThinkingPart.
             content: The thinking content to append to the appropriate ThinkingPart.
+            id: An optional id for the thinking part.
             signature: An optional signature for the thinking content.
 
         Returns:
@@ -197,7 +199,7 @@ def handle_thinking_delta(
             if content is not None:
                 # There is no existing thinking part that should be updated, so create a new one
                 new_part_index = len(self._parts)
-                part = ThinkingPart(content=content, signature=signature)
+                part = ThinkingPart(content=content, id=id, signature=signature)
                 if vendor_part_id is not None:  # pragma: no branch
                     self._vendor_id_to_part_index[vendor_part_id] = new_part_index
                 self._parts.append(part)

pydantic_ai_slim/pydantic_ai/models/anthropic.py

@@ -536,20 +536,15 @@ def _map_tool_definition(f: ToolDefinition) -> BetaToolParam:
         }
 
 
-def _map_usage(message: BetaMessage | BetaRawMessageStreamEvent) -> usage.RequestUsage:
+def _map_usage(message: BetaMessage | BetaRawMessageStartEvent | BetaRawMessageDeltaEvent) -> usage.RequestUsage:
     if isinstance(message, BetaMessage):
         response_usage = message.usage
     elif isinstance(message, BetaRawMessageStartEvent):
         response_usage = message.message.usage
     elif isinstance(message, BetaRawMessageDeltaEvent):
         response_usage = message.usage
     else:
-        # No usage information provided in:
-        # - RawMessageStopEvent
-        # - RawContentBlockStartEvent
-        # - RawContentBlockDeltaEvent
-        # - RawContentBlockStopEvent
-        return usage.RequestUsage()
+        assert_never(message)
 
     # Store all integer-typed usage values in the details, except 'output_tokens' which is represented exactly by
     # `response_tokens`
@@ -586,10 +581,8 @@ async def _get_event_iterator(self) -> AsyncIterator[ModelResponseStreamEvent]:
         current_block: BetaContentBlock | None = None
 
         async for event in self._response:
-            self._usage += _map_usage(event)
-
             if isinstance(event, BetaRawMessageStartEvent):
-                pass
+                self._usage = _map_usage(event)
 
             elif isinstance(event, BetaRawContentBlockStartEvent):
                 current_block = event.content_block
@@ -652,7 +645,7 @@ async def _get_event_iterator(self) -> AsyncIterator[ModelResponseStreamEvent]:
                     pass
 
             elif isinstance(event, BetaRawMessageDeltaEvent):
-                pass
+                self._usage = _map_usage(event)
 
             elif isinstance(event, BetaRawContentBlockStopEvent | BetaRawMessageStopEvent):  # pragma: no branch
                 current_block = None

pydantic_ai_slim/pydantic_ai/models/gemini.py

@@ -211,7 +211,9 @@ async def _make_request(
         generation_config = _settings_to_generation_config(model_settings)
         if model_request_parameters.output_mode == 'native':
             if tools:
-                raise UserError('Gemini does not support structured output and tools at the same time.')
+                raise UserError(
+                    'Gemini does not support `NativeOutput` and tools at the same time. Use `output_type=ToolOutput(...)` instead.'
+                )
 
             generation_config['response_mime_type'] = 'application/json'
 

pydantic_ai_slim/pydantic_ai/models/google.py

@@ -264,6 +264,14 @@ async def request_stream(
         yield await self._process_streamed_response(response, model_request_parameters)  # type: ignore
 
     def _get_tools(self, model_request_parameters: ModelRequestParameters) -> list[ToolDict] | None:
+        if model_request_parameters.builtin_tools:
+            if model_request_parameters.output_tools:
+                raise UserError(
+                    'Gemini does not support output tools and built-in tools at the same time. Use `output_type=PromptedOutput(...)` instead.'
+                )
+            if model_request_parameters.function_tools:
+                raise UserError('Gemini does not support user tools and built-in tools at the same time.')
+
         tools: list[ToolDict] = [
             ToolDict(function_declarations=[_function_declaration_from_tool(t)])
             for t in model_request_parameters.tool_defs.values()
@@ -334,7 +342,9 @@ async def _build_content_and_config(
         response_schema = None
         if model_request_parameters.output_mode == 'native':
             if tools:
-                raise UserError('Gemini does not support structured output and tools at the same time.')
+                raise UserError(
+                    'Gemini does not support `NativeOutput` and tools at the same time. Use `output_type=ToolOutput(...)` instead.'
+                )
             response_mime_type = 'application/json'
             output_object = model_request_parameters.output_object
             assert output_object is not None