bump version (#1219)

Author: prasmussen15

graphiti_core/llm_client/gemini_client.py

@@ -147,11 +147,9 @@ def _check_safety_blocks(self, response) -> None:
                     safety_info.append(f'{category}: {probability}')
 
         safety_details = (
-            ', '.join(
-                safety_info) if safety_info else 'Content blocked for safety reasons'
+            ', '.join(safety_info) if safety_info else 'Content blocked for safety reasons'
         )
-        raise Exception(
-            f'Response blocked by Gemini safety filters: {safety_details}')
+        raise Exception(f'Response blocked by Gemini safety filters: {safety_details}')
 
     def _check_prompt_blocks(self, response) -> None:
         """Check if prompt was blocked and raise appropriate exceptions."""
@@ -282,8 +280,7 @@ async def _generate_response(
             for m in messages:
                 m.content = self._clean_input(m.content)
                 gemini_messages.append(
-                    types.Content(role=m.role, parts=[
-                                  types.Part.from_text(text=m.content)])
+                    types.Content(role=m.role, parts=[types.Part.from_text(text=m.content)])
                 )
 
             # Get the appropriate model for the requested size
@@ -322,8 +319,7 @@ async def _generate_response(
                     if not raw_output:
                         raise ValueError('No response text')
 
-                    validated_model = response_model.model_validate(
-                        json.loads(raw_output))
+                    validated_model = response_model.model_validate(json.loads(raw_output))
 
                     # Return as a dictionary for API consistency
                     return validated_model.model_dump()
@@ -332,16 +328,13 @@ async def _generate_response(
                         logger.error(
                             '🦀 LLM generation failed parsing as JSON, will try to salvage.'
                         )
-                        logger.error(self._get_failed_generation_log(
-                            gemini_messages, raw_output))
+                        logger.error(self._get_failed_generation_log(gemini_messages, raw_output))
                         # Try to salvage
                         salvaged = self.salvage_json(raw_output)
                         if salvaged is not None:
-                            logger.warning(
-                                'Salvaged partial JSON from truncated/malformed output.')
+                            logger.warning('Salvaged partial JSON from truncated/malformed output.')
                             return salvaged
-                    raise Exception(
-                        f'Failed to parse structured response: {e}') from e
+                    raise Exception(f'Failed to parse structured response: {e}') from e
 
             # Otherwise, return the response text as a dictionary
             return {'content': raw_output}
@@ -424,14 +417,11 @@ async def generate_response(
                     last_error = e
 
                     # Check if this is a safety block - these typically shouldn't be retried
-                    error_text = str(e) or (
-                        str(e.__cause__) if e.__cause__ else '')
+                    error_text = str(e) or (str(e.__cause__) if e.__cause__ else '')
                     if 'safety' in error_text.lower() or 'blocked' in error_text.lower():
-                        logger.warning(
-                            f'Content blocked by safety filters: {e}')
+                        logger.warning(f'Content blocked by safety filters: {e}')
                         span.set_status('error', str(e))
-                        raise Exception(
-                            f'Content blocked by safety filters: {e}') from e
+                        raise Exception(f'Content blocked by safety filters: {e}') from e
 
                     retry_count += 1
 
@@ -452,10 +442,8 @@ async def generate_response(
 
             # If we exit the loop without returning, all retries are exhausted
             logger.error('🦀 LLM generation failed and retries are exhausted.')
-            logger.error(self._get_failed_generation_log(
-                messages, last_output))
-            logger.error(
-                f'Max retries ({self.MAX_RETRIES}) exceeded. Last error: {last_error}')
+            logger.error(self._get_failed_generation_log(messages, last_output))
+            logger.error(f'Max retries ({self.MAX_RETRIES}) exceeded. Last error: {last_error}')
             span.set_status('error', str(last_error))
             span.record_exception(last_error) if last_error else None
             raise last_error or Exception('Max retries exceeded')

graphiti_core/prompts/dedupe_edges.py

@@ -45,7 +45,7 @@ def resolve_edge(context: dict[str, Any]) -> list[Message]:
         Message(
             role='system',
             content='You are a helpful assistant that de-duplicates facts from fact lists and determines which existing '
-                    'facts are contradicted by the new fact.',
+            'facts are contradicted by the new fact.',
         ),
         Message(
             role='user',

graphiti_core/prompts/extract_edges.py

@@ -74,8 +74,8 @@ def edge(context: dict[str, Any]) -> list[Message]:
         Message(
             role='system',
             content='You are an expert fact extractor that extracts fact triples from text. '
-                    '1. Extracted fact triples should also be extracted with relevant date information.'
-                    '2. Treat the CURRENT TIME as the time the CURRENT MESSAGE was sent. All temporal information should be extracted relative to this time.',
+            '1. Extracted fact triples should also be extracted with relevant date information.'
+            '2. Treat the CURRENT TIME as the time the CURRENT MESSAGE was sent. All temporal information should be extracted relative to this time.',
         ),
         Message(
             role='user',

graphiti_core/prompts/extract_nodes.py

@@ -29,7 +29,7 @@ class ExtractedEntity(BaseModel):
     name: str = Field(..., description='Name of the extracted entity')
     entity_type_id: int = Field(
         description='ID of the classified entity type. '
-                    'Must be one of the provided entity_type_id integers.',
+        'Must be one of the provided entity_type_id integers.',
     )
 
 

graphiti_core/utils/maintenance/edge_operations.py

@@ -160,10 +160,7 @@ async def extract_edges_for_chunk(
         # Prepare context for LLM
         context = {
             'episode_content': episode.content,
-            'nodes': [
-                {'name': node.name, 'entity_types': node.labels}
-                for node in chunk
-            ],
+            'nodes': [{'name': node.name, 'entity_types': node.labels} for node in chunk],
             'previous_episodes': [ep.content for ep in previous_episodes],
             'reference_time': episode.valid_at,
             'edge_types': edge_types_context,

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "graphiti-core"
 description = "A temporal graph building library"
-version = "0.27.0pre2"
+version = "0.27.0"
 authors = [
     { name = "Paul Paliychuk", email = "paul@getzep.com" },
     { name = "Preston Rasmussen", email = "preston@getzep.com" },

tests/utils/maintenance/test_edge_operations.py

@@ -501,9 +501,7 @@ def test_edge_type_signatures_map_preserves_multiple_signatures():
     edge_types_context = [
         {
             'fact_type_name': type_name,
-            'fact_type_signatures': edge_type_signatures_map.get(
-                type_name, [('Entity', 'Entity')]
-            ),
+            'fact_type_signatures': edge_type_signatures_map.get(type_name, [('Entity', 'Entity')]),
             'fact_type_description': type_model.__doc__,
         }
         for type_name, type_model in edge_types.items()
@@ -547,9 +545,7 @@ def test_edge_type_signatures_map_single_signature_still_works():
     edge_types_context = [
         {
             'fact_type_name': type_name,
-            'fact_type_signatures': edge_type_signatures_map.get(
-                type_name, [('Entity', 'Entity')]
-            ),
+            'fact_type_signatures': edge_type_signatures_map.get(type_name, [('Entity', 'Entity')]),
             'fact_type_description': type_model.__doc__,
         }
         for type_name, type_model in edge_types.items()