format

Change-Id: Iab48a9400d53f3cbdc5ca49c73df4f6a186a867b

Author: MarkDaoust

google/generativeai/types/content_types.py

@@ -692,7 +692,6 @@ def _make_google_search_retrieval(gsr: GoogleSearchRetrievalType):
             f"However, received an object of type: {type(gsr)}.\n"
             f"Object Value: {gsr}"
         )
-    
 
 
 class Tool:

google/generativeai/types/generation_types.py

@@ -346,11 +346,10 @@ def _join_prompt_feedbacks(
 
 def _join_chunks(chunks: Iterable[protos.GenerateContentResponse]):
     chunks = tuple(chunks)
-    if 'usage_metadata' in chunks[-1]:
+    if "usage_metadata" in chunks[-1]:
         usage_metadata = chunks[-1].usage_metadata
     else:
-        usage_metadata=None
-
+        usage_metadata = None
 
     return protos.GenerateContentResponse(
         candidates=_join_candidate_lists(c.candidates for c in chunks),

google/generativeai/types/model_types.py

@@ -143,7 +143,9 @@ def idecode_time(parent: dict["str", Any], name: str):
 
 def decode_tuned_model(tuned_model: protos.TunedModel | dict["str", Any]) -> TunedModel:
     if isinstance(tuned_model, protos.TunedModel):
-        tuned_model = type(tuned_model).to_dict(tuned_model, including_default_value_fields=False)  # pytype: disable=attribute-error
+        tuned_model = type(tuned_model).to_dict(
+            tuned_model, including_default_value_fields=False
+        )  # pytype: disable=attribute-error
     tuned_model["state"] = to_tuned_model_state(tuned_model.pop("state", None))
 
     base_model = tuned_model.pop("base_model", None)

tests/test_generation.py

@@ -39,6 +39,7 @@ class Person(TypedDict):
 
 class UnitTests(parameterized.TestCase):
     maxDiff = None
+
     @parameterized.named_parameters(
         [
             "protos.GenerationConfig",
@@ -473,7 +474,10 @@ def test_join_prompt_feedbacks(self):
     def test_join_candidates(self):
         candidate_lists = [[protos.Candidate(c) for c in cl] for cl in self.CANDIDATE_LISTS]
         result = generation_types._join_candidate_lists(candidate_lists)
-        self.assertEqual(self.MERGED_CANDIDATES, [type(r).to_dict(r, including_default_value_fields=False) for r in result])
+        self.assertEqual(
+            self.MERGED_CANDIDATES,
+            [type(r).to_dict(r, including_default_value_fields=False) for r in result],
+        )
 
     def test_join_chunks(self):
         chunks = [protos.GenerateContentResponse(candidates=cl) for cl in self.CANDIDATE_LISTS]
@@ -485,7 +489,9 @@ def test_join_chunks(self):
             ],
         )
 
-        chunks[-1].usage_metadata = protos.GenerateContentResponse.UsageMetadata(prompt_token_count=5)
+        chunks[-1].usage_metadata = protos.GenerateContentResponse.UsageMetadata(
+            prompt_token_count=5
+        )
 
         result = generation_types._join_chunks(chunks)
 
@@ -502,15 +508,16 @@ def test_join_chunks(self):
                         }
                     ],
                 },
-                "usage_metadata": {
-                         "prompt_token_count": 5
-                }
-
+                "usage_metadata": {"prompt_token_count": 5},
             },
         )
 
-        expected = json.dumps(type(expected).to_dict(expected, including_default_value_fields=False), indent=4)
-        result = json.dumps(type(result).to_dict(result, including_default_value_fields=False), indent=4)
+        expected = json.dumps(
+            type(expected).to_dict(expected, including_default_value_fields=False), indent=4
+        )
+        result = json.dumps(
+            type(result).to_dict(result, including_default_value_fields=False), indent=4
+        )
 
         self.assertEqual(expected, result)