lints (#8987)

Author: chenmoneygithub

dspy/adapters/types/base_type.py

@@ -88,7 +88,6 @@ def parse_stream_chunk(cls, chunk: ModelResponseStream) -> Optional["Type"]:
         """
         return None
 
-
     @classmethod
     def parse_lm_response(cls, response: str | dict[str, Any]) -> Optional["Type"]:
         """Parse a LM response into the custom type.
@@ -101,6 +100,7 @@ def parse_lm_response(cls, response: str | dict[str, Any]) -> Optional["Type"]:
         """
         return None
 
+
 def split_message_content_for_custom_types(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
     """Split user message content into a list of content blocks.
 

dspy/adapters/types/citation.py

@@ -54,6 +54,7 @@ class AnswerWithSources(Signature):
 
     class Citation(Type):
         """Individual citation with character location information."""
+
         type: str = "char_location"
         cited_text: str
         document_index: int
@@ -73,7 +74,7 @@ def format(self) -> dict[str, Any]:
                 "cited_text": self.cited_text,
                 "document_index": self.document_index,
                 "start_char_index": self.start_char_index,
-                "end_char_index": self.end_char_index
+                "end_char_index": self.end_char_index,
             }
 
             if self.document_title:
@@ -134,9 +135,7 @@ def validate_input(cls, data: Any):
             return data
 
         # Handle case where data is a list of dicts with citation info
-        if isinstance(data, list) and all(
-            isinstance(item, dict) and "cited_text" in item for item in data
-        ):
+        if isinstance(data, list) and all(isinstance(item, dict) and "cited_text" in item for item in data):
             return {"citations": [cls.Citation(**item) for item in data]}
 
         # Handle case where data is a dict
@@ -147,8 +146,7 @@ def validate_input(cls, data: Any):
                 if isinstance(citations_data, list):
                     return {
                         "citations": [
-                            cls.Citation(**item) if isinstance(item, dict) else item
-                            for item in citations_data
+                            cls.Citation(**item) if isinstance(item, dict) else item for item in citations_data
                         ]
                     }
             elif "cited_text" in data:
@@ -197,7 +195,6 @@ def parse_stream_chunk(cls, chunk) -> Optional["Citations"]:
             pass
         return None
 
-
     @classmethod
     def parse_lm_response(cls, response: str | dict[str, Any]) -> Optional["Citations"]:
         """Parse a LM response into Citations.

dspy/clients/lm.py

@@ -88,7 +88,6 @@ def __init__(
         model_pattern = re.match(r"^(?:o[1345]|gpt-5)(?:-(?:mini|nano))?", model_family)
 
         if model_pattern:
-
             if (temperature and temperature != 1.0) or (max_tokens and max_tokens < 16000):
                 raise ValueError(
                     "OpenAI's reasoning models require passing temperature=1.0 or None and max_tokens >= 16000 or None to "
@@ -228,9 +227,7 @@ def thread_function_wrapper():
 
         return job
 
-    def reinforce(
-        self, train_kwargs
-    ) -> ReinforceJob:
+    def reinforce(self, train_kwargs) -> ReinforceJob:
         # TODO(GRPO Team): Should we return an initialized job here?
         from dspy import settings as settings
 
@@ -482,6 +479,7 @@ def _convert_chat_request_to_responses_request(request: dict[str, Any]):
 
     return request
 
+
 def _get_headers(headers: dict[str, Any] | None = None):
     headers = headers or {}
     return {

dspy/streaming/streaming_listener.py

@@ -287,8 +287,9 @@ def _output_type(self) -> type | None:
             return None
 
 
-
-def find_predictor_for_stream_listeners(program: "Module", stream_listeners: list[StreamListener]) -> dict[int, list[StreamListener]]:
+def find_predictor_for_stream_listeners(
+    program: "Module", stream_listeners: list[StreamListener]
+) -> dict[int, list[StreamListener]]:
     """Find the predictor for each stream listener.
 
     This is a utility function to automatically find the predictor for each stream listener. It is used when some
@@ -337,6 +338,7 @@ def find_predictor_for_stream_listeners(program: "Module", stream_listeners: lis
         predict_id_to_listener[id(listener.predict)].append(listener)
     return predict_id_to_listener
 
+
 def _is_streamable(field_type: type | None) -> bool:
     if field_type is None:
         return False

tests/adapters/test_json_adapter.py

@@ -334,8 +334,16 @@ class MySignature(dspy.Signature):
     adapter = dspy.JSONAdapter()
     messages = adapter.format(MySignature, [], {"document": document_wrapper})
 
-    expected_doc1_content = {"type": "document", "source": {"type": "text", "media_type": "text/plain", "data": "Hello, world!"}, "citations": {"enabled": True}}
-    expected_doc2_content = {"type": "document", "source": {"type": "text", "media_type": "text/plain", "data": "Hello, world 2!"}, "citations": {"enabled": True}}
+    expected_doc1_content = {
+        "type": "document",
+        "source": {"type": "text", "media_type": "text/plain", "data": "Hello, world!"},
+        "citations": {"enabled": True},
+    }
+    expected_doc2_content = {
+        "type": "document",
+        "source": {"type": "text", "media_type": "text/plain", "data": "Hello, world 2!"},
+        "citations": {"enabled": True},
+    }
 
     assert expected_doc1_content in messages[1]["content"]
     assert expected_doc2_content in messages[1]["content"]
@@ -643,6 +651,7 @@ class TestSignature(dspy.Signature):
         _, second_call_kwargs = mock_completion.call_args_list[1]
         assert second_call_kwargs.get("response_format") == {"type": "json_object"}
 
+
 def test_json_adapter_json_mode_no_structured_outputs():
     class TestSignature(dspy.Signature):
         question: str = dspy.InputField()
@@ -651,11 +660,15 @@ class TestSignature(dspy.Signature):
     dspy.configure(lm=dspy.LM(model="openai/gpt-4o", cache=False), adapter=dspy.JSONAdapter())
     program = dspy.Predict(TestSignature)
 
-    with mock.patch("litellm.completion") as mock_completion, \
-        mock.patch("litellm.get_supported_openai_params") as mock_get_supported_openai_params, \
-        mock.patch("litellm.supports_response_schema") as mock_supports_response_schema:
+    with (
+        mock.patch("litellm.completion") as mock_completion,
+        mock.patch("litellm.get_supported_openai_params") as mock_get_supported_openai_params,
+        mock.patch("litellm.supports_response_schema") as mock_supports_response_schema,
+    ):
         # Call a model that allows json but not structured outputs
-        mock_completion.return_value = ModelResponse(choices=[Choices(message=Message(content="{'answer': 'Test output'}"))])
+        mock_completion.return_value = ModelResponse(
+            choices=[Choices(message=Message(content="{'answer': 'Test output'}"))]
+        )
         mock_get_supported_openai_params.return_value = ["response_format"]
         mock_supports_response_schema.return_value = False
 
@@ -676,11 +689,15 @@ class TestSignature(dspy.Signature):
 
     program = dspy.Predict(TestSignature)
 
-    with mock.patch("litellm.acompletion") as mock_acompletion, \
-        mock.patch("litellm.get_supported_openai_params") as mock_get_supported_openai_params, \
-        mock.patch("litellm.supports_response_schema") as mock_supports_response_schema:
+    with (
+        mock.patch("litellm.acompletion") as mock_acompletion,
+        mock.patch("litellm.get_supported_openai_params") as mock_get_supported_openai_params,
+        mock.patch("litellm.supports_response_schema") as mock_supports_response_schema,
+    ):
         # Call a model that allows json but not structured outputs
-        mock_acompletion.return_value = ModelResponse(choices=[Choices(message=Message(content="{'answer': 'Test output'}"))])
+        mock_acompletion.return_value = ModelResponse(
+            choices=[Choices(message=Message(content="{'answer': 'Test output'}"))]
+        )
         mock_get_supported_openai_params.return_value = ["response_format"]
         mock_supports_response_schema.return_value = False
 
@@ -890,9 +907,7 @@ class TestSignature(dspy.Signature):
                     "type": "message",
                     "role": "assistant",
                     "status": "completed",
-                    "content": [
-                        {"type": "output_text", "text": '{"answer": "Washington, D.C."}', "annotations": []}
-                    ],
+                    "content": [{"type": "output_text", "text": '{"answer": "Washington, D.C."}', "annotations": []}],
                 },
             ),
         ],

tests/clients/test_lm.py

@@ -30,7 +30,7 @@ def make_response(output_blocks):
         model="openai/dspy-test-model",
         object="response",
         output=output_blocks,
-        metadata = {},
+        metadata={},
         parallel_tool_calls=False,
         temperature=1.0,
         tool_choice="auto",
@@ -107,9 +107,11 @@ def test_disabled_cache_skips_cache_key(monkeypatch):
     cache = dspy.cache
 
     try:
-        with mock.patch.object(cache, "cache_key", wraps=cache.cache_key) as cache_key_spy, \
-             mock.patch.object(cache, "get", wraps=cache.get) as cache_get_spy, \
-             mock.patch.object(cache, "put", wraps=cache.put) as cache_put_spy:
+        with (
+            mock.patch.object(cache, "cache_key", wraps=cache.cache_key) as cache_key_spy,
+            mock.patch.object(cache, "get", wraps=cache.get) as cache_get_spy,
+            mock.patch.object(cache, "put", wraps=cache.put) as cache_put_spy,
+        ):
 
             def fake_completion(*, cache, num_retries, retry_strategy, **request):
                 return ModelResponse(
@@ -315,6 +317,7 @@ def test_reasoning_model_token_parameter():
             assert "max_tokens" in lm.kwargs
             assert lm.kwargs["max_tokens"] == 1000
 
+
 @pytest.mark.parametrize("model_name", ["openai/o1", "openai/gpt-5-nano"])
 def test_reasoning_model_requirements(model_name):
     # Should raise assertion error if temperature or max_tokens requirements not met
@@ -516,6 +519,7 @@ def test_disable_history():
                 model="openai/gpt-4o-mini",
             )
 
+
 def test_responses_api():
     api_response = make_response(
         output_blocks=[
@@ -562,20 +566,15 @@ def test_responses_api():
 
 
 def test_lm_replaces_system_with_developer_role():
-    with mock.patch(
-        "dspy.clients.lm.litellm_responses_completion", return_value={"choices": []}
-    ) as mock_completion:
+    with mock.patch("dspy.clients.lm.litellm_responses_completion", return_value={"choices": []}) as mock_completion:
         lm = dspy.LM(
             "openai/gpt-4o-mini",
             cache=False,
             model_type="responses",
             use_developer_role=True,
         )
         lm.forward(messages=[{"role": "system", "content": "hi"}])
-        assert (
-            mock_completion.call_args.kwargs["request"]["messages"][0]["role"]
-            == "developer"
-        )
+        assert mock_completion.call_args.kwargs["request"]["messages"][0]["role"] == "developer"
 
 
 def test_responses_api_tool_calls(litellm_test_server):