Bump dependencies (#966)

Author: Kludex

examples/pydantic_ai_examples/flight_booking.py

@@ -105,9 +105,7 @@ class Failed(BaseModel):
 
 
 # This agent is responsible for extracting the user's seat selection
-seat_preference_agent = Agent[
-    None, SeatPreference | Failed
-](
+seat_preference_agent = Agent[None, SeatPreference | Failed](
     'openai:gpt-4o',
     result_type=SeatPreference | Failed,  # type: ignore
     system_prompt=(

examples/pydantic_ai_examples/rag.py

@@ -67,9 +67,9 @@ async def retrieve(context: RunContext[Deps], search_query: str) -> str:
             model='text-embedding-3-small',
         )
 
-    assert (
-        len(embedding.data) == 1
-    ), f'Expected 1 embedding, got {len(embedding.data)}, doc query: {search_query!r}'
+    assert len(embedding.data) == 1, (
+        f'Expected 1 embedding, got {len(embedding.data)}, doc query: {search_query!r}'
+    )
     embedding = embedding.data[0].embedding
     embedding_json = pydantic_core.to_json(embedding).decode()
     rows = await context.deps.pool.fetch(
@@ -149,9 +149,9 @@ async def insert_doc_section(
                 input=section.embedding_content(),
                 model='text-embedding-3-small',
             )
-        assert (
-            len(embedding.data) == 1
-        ), f'Expected 1 embedding, got {len(embedding.data)}, doc section: {section}'
+        assert len(embedding.data) == 1, (
+            f'Expected 1 embedding, got {len(embedding.data)}, doc section: {section}'
+        )
         embedding = embedding.data[0].embedding
         embedding_json = pydantic_core.to_json(embedding).decode()
         await pool.execute(

pydantic_ai_slim/pydantic_ai/models/__init__.py

@@ -364,7 +364,6 @@ def infer_model(model: Model | KnownModelName) -> Model:
         raise UserError(f'Unknown model: {model}')
 
 
-@cache
 def cached_async_http_client(timeout: int = 600, connect: int = 5) -> httpx.AsyncClient:
     """Cached HTTPX async client so multiple agents and calls can share the same client.
 
@@ -375,6 +374,16 @@ def cached_async_http_client(timeout: int = 600, connect: int = 5) -> httpx.Asyn
     The default timeouts match those of OpenAI,
     see <https://github.com/openai/openai-python/blob/v1.54.4/src/openai/_constants.py#L9>.
     """
+    client = _cached_async_http_client(timeout=timeout, connect=connect)
+    if client.is_closed:
+        # This happens if the context manager is used, so we need to create a new client.
+        _cached_async_http_client.cache_clear()
+        client = _cached_async_http_client(timeout=timeout, connect=connect)
+    return client
+
+
+@cache
+def _cached_async_http_client(timeout: int = 600, connect: int = 5) -> httpx.AsyncClient:
     return httpx.AsyncClient(
         timeout=httpx.Timeout(timeout=timeout, connect=connect),
         headers={'User-Agent': get_user_agent()},

pydantic_ai_slim/pydantic_ai/models/cohere.py

@@ -124,7 +124,7 @@ def __init__(
             assert api_key is None, 'Cannot provide both `cohere_client` and `api_key`'
             self.client = cohere_client
         else:
-            self.client = AsyncClientV2(api_key=api_key, httpx_client=http_client)  # type: ignore
+            self.client = AsyncClientV2(api_key=api_key, httpx_client=http_client)
 
     async def request(
         self,

pydantic_ai_slim/pydantic_ai/models/function.py

@@ -109,9 +109,9 @@ async def request_stream(
             model_settings,
         )
 
-        assert (
-            self.stream_function is not None
-        ), 'FunctionModel must receive a `stream_function` to support streamed requests'
+        assert self.stream_function is not None, (
+            'FunctionModel must receive a `stream_function` to support streamed requests'
+        )
 
         response_stream = PeekableAsyncStream(self.stream_function(messages, agent_info))
 

pydantic_ai_slim/pydantic_ai/models/test.py

@@ -130,15 +130,15 @@ def _get_tool_calls(self, model_request_parameters: ModelRequestParameters) -> l
 
     def _get_result(self, model_request_parameters: ModelRequestParameters) -> _TextResult | _FunctionToolResult:
         if self.custom_result_text is not None:
-            assert (
-                model_request_parameters.allow_text_result
-            ), 'Plain response not allowed, but `custom_result_text` is set.'
+            assert model_request_parameters.allow_text_result, (
+                'Plain response not allowed, but `custom_result_text` is set.'
+            )
             assert self.custom_result_args is None, 'Cannot set both `custom_result_text` and `custom_result_args`.'
             return _TextResult(self.custom_result_text)
         elif self.custom_result_args is not None:
-            assert (
-                model_request_parameters.result_tools is not None
-            ), 'No result tools provided, but `custom_result_args` is set.'
+            assert model_request_parameters.result_tools is not None, (
+                'No result tools provided, but `custom_result_args` is set.'
+            )
             result_tool = model_request_parameters.result_tools[0]
 
             if k := result_tool.outer_typed_dict_key:

pyproject.toml

@@ -57,7 +57,7 @@ members = ["pydantic_ai_slim", "pydantic_graph", "examples"]
 # dev dependencies are defined in `pydantic-ai-slim/pyproject.toml` to allow for minimal testing
 lint = [
     "mypy>=1.11.2",
-    "pyright>=1.1.388",
+    "pyright>=1.1.388,<1.1.390",
     "ruff>=0.6.9",
 ]
 docs = [

tests/models/test_gemini.py

@@ -365,7 +365,7 @@ class FormattedStringFields(BaseModel):
         _GeminiTools(
             function_declarations=[
                 _GeminiFunction(
-                    description='This is the tool for the final ' 'Result',
+                    description='This is the tool for the final Result',
                     name='result',
                     parameters={
                         'properties': {

tests/test_agent.py

@@ -848,15 +848,14 @@ def test_run_sync_multiple():
 
     @agent.tool_plain
     async def make_request() -> str:
-        # raised a `RuntimeError: Event loop is closed` on repeat runs when we used `asyncio.run()`
-        client = cached_async_http_client()
-        # use this as I suspect it's about the fastest globally available endpoint
-        try:
-            response = await client.get('https://cloudflare.com/cdn-cgi/trace')
-        except httpx.ConnectError:
-            pytest.skip('offline')
-        else:
-            return str(response.status_code)
+        async with cached_async_http_client() as client:
+            # use this as I suspect it's about the fastest globally available endpoint
+            try:
+                response = await client.get('https://cloudflare.com/cdn-cgi/trace')
+            except httpx.ConnectError:  # pragma: no cover
+                pytest.skip('offline')
+            else:
+                return str(response.status_code)
 
     for _ in range(2):
         result = agent.run_sync('Hello')

tests/test_streaming.py

@@ -590,7 +590,7 @@ def another_tool(y: int) -> int:  # pragma: no cover
             ModelRequest(
                 parts=[
                     UserPromptPart(
-                        content='test early strategy with final ' 'result in middle',
+                        content='test early strategy with final result in middle',
                         timestamp=IsNow(tz=datetime.timezone.utc),
                         part_kind='user-prompt',
                     )
@@ -632,7 +632,7 @@ def another_tool(y: int) -> int:  # pragma: no cover
                 parts=[
                     ToolReturnPart(
                         tool_name='regular_tool',
-                        content='Tool not executed - a final ' 'result was already processed.',
+                        content='Tool not executed - a final result was already processed.',
                         tool_call_id=None,
                         timestamp=IsNow(tz=datetime.timezone.utc),
                         part_kind='tool-return',
@@ -646,7 +646,7 @@ def another_tool(y: int) -> int:  # pragma: no cover
                     ),
                     ToolReturnPart(
                         tool_name='another_tool',
-                        content='Tool not executed - a final ' 'result was already processed.',
+                        content='Tool not executed - a final result was already processed.',
                         tool_call_id=None,
                         timestamp=IsNow(tz=datetime.timezone.utc),
                         part_kind='tool-return',