Merge branch 'getzep:main' into main

graphiti_core/graphiti.py

@@ -123,6 +123,7 @@ class Graphiti:
         store_raw_episode_content: bool = True,
         graph_driver: GraphDriver | None = None,
         max_coroutines: int | None = None,
+        ensure_ascii: bool = False,
     ):
         """
         Initialize a Graphiti instance.
@@ -155,6 +156,10 @@ class Graphiti:
         max_coroutines : int | None, optional
             The maximum number of concurrent operations allowed. Overrides SEMAPHORE_LIMIT set in the environment.
             If not set, the Graphiti default is used.
+        ensure_ascii : bool, optional
+            Whether to escape non-ASCII characters in JSON serialization for prompts. Defaults to False.
+            Set to False to preserve non-ASCII characters (e.g., Korean, Japanese, Chinese) in their
+            original form, making them readable in LLM logs and improving model understanding.
 
         Returns
         -------
@@ -184,6 +189,7 @@ class Graphiti:
 
         self.store_raw_episode_content = store_raw_episode_content
         self.max_coroutines = max_coroutines
+        self.ensure_ascii = ensure_ascii
         if llm_client:
             self.llm_client = llm_client
         else:
@@ -202,6 +208,7 @@ class Graphiti:
             llm_client=self.llm_client,
             embedder=self.embedder,
             cross_encoder=self.cross_encoder,
+            ensure_ascii=self.ensure_ascii,
         )
 
         # Capture telemetry event
@@ -541,7 +548,9 @@ class Graphiti:
             if update_communities:
                 communities, community_edges = await semaphore_gather(
                     *[
-                        update_community(self.driver, self.llm_client, self.embedder, node)
+                        update_community(
+                            self.driver, self.llm_client, self.embedder, node, self.ensure_ascii
+                        )
                         for node in nodes
                     ],
                     max_coroutines=self.max_coroutines,
@@ -1021,6 +1030,8 @@ class Graphiti:
                 entity_edges=[],
                 group_id=edge.group_id,
             ),
+            None,
+            self.ensure_ascii,
         )
 
         edges: list[EntityEdge] = [resolved_edge] + invalidated_edges

graphiti_core/graphiti_types.py

@@ -27,5 +27,6 @@ class GraphitiClients(BaseModel):
     llm_client: LLMClient
     embedder: EmbedderClient
     cross_encoder: CrossEncoderClient
+    ensure_ascii: bool = False
 
     model_config = ConfigDict(arbitrary_types_allowed=True)

graphiti_core/nodes.py

@@ -118,7 +118,7 @@ class Node(BaseModel, ABC):
         return False
 
     @classmethod
-    async def delete_by_group_id(cls, driver: GraphDriver, group_id: str):
+    async def delete_by_group_id(cls, driver: GraphDriver, group_id: str, batch_size: int = 100):
         if driver.provider == GraphProvider.FALKORDB:
             for label in ['Entity', 'Episodic', 'Community']:
                 await driver.execute_query(
@@ -129,13 +129,18 @@ class Node(BaseModel, ABC):
                     group_id=group_id,
                 )
         else:
-            await driver.execute_query(
+            async with driver.session() as session:
-                """
+                await session.run(
-                MATCH (n:Entity|Episodic|Community {group_id: $group_id})
+                    """
-                DETACH DELETE n
+                    MATCH (n:Entity|Episodic|Community {group_id: $group_id})
-                """,
+                    CALL {
-                group_id=group_id,
+                        WITH n
-            )
+                        DETACH DELETE n
+                    } IN TRANSACTIONS OF $batch_size ROWS
+                    """,
+                    group_id=group_id,
+                    batch_size=batch_size,
+                )
 
     @classmethod
     async def get_by_uuid(cls, driver: GraphDriver, uuid: str): ...

graphiti_core/prompts/dedupe_edges.py

@@ -14,12 +14,12 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-import json
 from typing import Any, Protocol, TypedDict
 
 from pydantic import BaseModel, Field
 
 from .models import Message, PromptFunction, PromptVersion
+from .prompt_helpers import to_prompt_json
 
 
 class EdgeDuplicate(BaseModel):
@@ -67,11 +67,11 @@ def edge(context: dict[str, Any]) -> list[Message]:
         Given the following context, determine whether the New Edge represents any of the edges in the list of Existing Edges.
 
         <EXISTING EDGES>
-        {json.dumps(context['related_edges'], indent=2)}
+        {to_prompt_json(context['related_edges'], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
         </EXISTING EDGES>
 
         <NEW EDGE>
-        {json.dumps(context['extracted_edges'], indent=2)}
+        {to_prompt_json(context['extracted_edges'], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
         </NEW EDGE>
         
         Task:
@@ -98,7 +98,7 @@ def edge_list(context: dict[str, Any]) -> list[Message]:
         Given the following context, find all of the duplicates in a list of facts:
 
         Facts:
-        {json.dumps(context['edges'], indent=2)}
+        {to_prompt_json(context['edges'], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
 
         Task:
         If any facts in Facts is a duplicate of another fact, return a new fact with one of their uuid's.

graphiti_core/prompts/dedupe_nodes.py

@@ -14,12 +14,12 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-import json
 from typing import Any, Protocol, TypedDict
 
 from pydantic import BaseModel, Field
 
 from .models import Message, PromptFunction, PromptVersion
+from .prompt_helpers import to_prompt_json
 
 
 class NodeDuplicate(BaseModel):
@@ -64,20 +64,20 @@ def node(context: dict[str, Any]) -> list[Message]:
             role='user',
             content=f"""
         <PREVIOUS MESSAGES>
-        {json.dumps([ep for ep in context['previous_episodes']], indent=2)}
+        {to_prompt_json([ep for ep in context['previous_episodes']], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
         </PREVIOUS MESSAGES>
         <CURRENT MESSAGE>
         {context['episode_content']}
         </CURRENT MESSAGE>
         <NEW ENTITY>
-        {json.dumps(context['extracted_node'], indent=2)}
+        {to_prompt_json(context['extracted_node'], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
         </NEW ENTITY>
         <ENTITY TYPE DESCRIPTION>
-        {json.dumps(context['entity_type_description'], indent=2)}
+        {to_prompt_json(context['entity_type_description'], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
         </ENTITY TYPE DESCRIPTION>
 
         <EXISTING ENTITIES>
-        {json.dumps(context['existing_nodes'], indent=2)}
+        {to_prompt_json(context['existing_nodes'], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
         </EXISTING ENTITIES>
         
         Given the above EXISTING ENTITIES and their attributes, MESSAGE, and PREVIOUS MESSAGES; Determine if the NEW ENTITY extracted from the conversation
@@ -114,7 +114,7 @@ def nodes(context: dict[str, Any]) -> list[Message]:
             role='user',
             content=f"""
         <PREVIOUS MESSAGES>
-        {json.dumps([ep for ep in context['previous_episodes']], indent=2)}
+        {to_prompt_json([ep for ep in context['previous_episodes']], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         </PREVIOUS MESSAGES>
         <CURRENT MESSAGE>
         {context['episode_content']}
@@ -139,11 +139,11 @@ def nodes(context: dict[str, Any]) -> list[Message]:
         }}
         
         <ENTITIES>
-        {json.dumps(context['extracted_nodes'], indent=2)}
+        {to_prompt_json(context['extracted_nodes'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         </ENTITIES>
         
         <EXISTING ENTITIES>
-        {json.dumps(context['existing_nodes'], indent=2)}
+        {to_prompt_json(context['existing_nodes'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         </EXISTING ENTITIES>
 
         For each of the above ENTITIES, determine if the entity is a duplicate of any of the EXISTING ENTITIES.
@@ -180,7 +180,7 @@ def node_list(context: dict[str, Any]) -> list[Message]:
         Given the following context, deduplicate a list of nodes:
 
         Nodes:
-        {json.dumps(context['nodes'], indent=2)}
+        {to_prompt_json(context['nodes'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
 
         Task:
         1. Group nodes together such that all duplicate nodes are in the same list of uuids

graphiti_core/prompts/eval.py

@@ -14,12 +14,12 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-import json
 from typing import Any, Protocol, TypedDict
 
 from pydantic import BaseModel, Field
 
 from .models import Message, PromptFunction, PromptVersion
+from .prompt_helpers import to_prompt_json
 
 
 class QueryExpansion(BaseModel):
@@ -68,7 +68,7 @@ def query_expansion(context: dict[str, Any]) -> list[Message]:
     Bob is asking Alice a question, are you able to rephrase the question into a simpler one about Alice in the third person
     that maintains the relevant context?
     <QUESTION>
-    {json.dumps(context['query'])}
+    {to_prompt_json(context['query'], ensure_ascii=context.get('ensure_ascii', False))}
     </QUESTION>
     """
     return [
@@ -84,10 +84,10 @@ def qa_prompt(context: dict[str, Any]) -> list[Message]:
     Your task is to briefly answer the question in the way that you think Alice would answer the question.
     You are given the following entity summaries and facts to help you determine the answer to your question.
     <ENTITY_SUMMARIES>
-    {json.dumps(context['entity_summaries'])}
+    {to_prompt_json(context['entity_summaries'], ensure_ascii=context.get('ensure_ascii', False))}
     </ENTITY_SUMMARIES>
     <FACTS>
-    {json.dumps(context['facts'])}
+    {to_prompt_json(context['facts'], ensure_ascii=context.get('ensure_ascii', False))}
     </FACTS>
     <QUESTION>
     {context['query']}

graphiti_core/prompts/extract_edges.py

@@ -14,12 +14,12 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-import json
 from typing import Any, Protocol, TypedDict
 
 from pydantic import BaseModel, Field
 
 from .models import Message, PromptFunction, PromptVersion
+from .prompt_helpers import to_prompt_json
 
 
 class Edge(BaseModel):
@@ -73,7 +73,7 @@ def edge(context: dict[str, Any]) -> list[Message]:
 </FACT TYPES>
 
 <PREVIOUS_MESSAGES>
-{json.dumps([ep for ep in context['previous_episodes']], indent=2)}
+{to_prompt_json([ep for ep in context['previous_episodes']], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
 </PREVIOUS_MESSAGES>
 
 <CURRENT_MESSAGE>
@@ -132,7 +132,7 @@ def reflexion(context: dict[str, Any]) -> list[Message]:
 
     user_prompt = f"""
 <PREVIOUS MESSAGES>
-{json.dumps([ep for ep in context['previous_episodes']], indent=2)}
+{to_prompt_json([ep for ep in context['previous_episodes']], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
 </PREVIOUS MESSAGES>
 <CURRENT MESSAGE>
 {context['episode_content']}
@@ -166,7 +166,7 @@ def extract_attributes(context: dict[str, Any]) -> list[Message]:
             content=f"""
 
         <MESSAGE>
-        {json.dumps(context['episode_content'], indent=2)}
+        {to_prompt_json(context['episode_content'], ensure_ascii=context.get('ensure_ascii', False), indent=2)}
         </MESSAGE>
         <REFERENCE TIME>
         {context['reference_time']}

graphiti_core/prompts/extract_nodes.py

@@ -14,12 +14,12 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-import json
 from typing import Any, Protocol, TypedDict
 
 from pydantic import BaseModel, Field
 
 from .models import Message, PromptFunction, PromptVersion
+from .prompt_helpers import to_prompt_json
 
 
 class ExtractedEntity(BaseModel):
@@ -89,7 +89,7 @@ def extract_message(context: dict[str, Any]) -> list[Message]:
 </ENTITY TYPES>
 
 <PREVIOUS MESSAGES>
-{json.dumps([ep for ep in context['previous_episodes']], indent=2)}
+{to_prompt_json([ep for ep in context['previous_episodes']], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
 </PREVIOUS MESSAGES>
 
 <CURRENT MESSAGE>
@@ -196,7 +196,7 @@ def reflexion(context: dict[str, Any]) -> list[Message]:
 
     user_prompt = f"""
 <PREVIOUS MESSAGES>
-{json.dumps([ep for ep in context['previous_episodes']], indent=2)}
+{to_prompt_json([ep for ep in context['previous_episodes']], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
 </PREVIOUS MESSAGES>
 <CURRENT MESSAGE>
 {context['episode_content']}
@@ -220,7 +220,7 @@ def classify_nodes(context: dict[str, Any]) -> list[Message]:
 
     user_prompt = f"""
     <PREVIOUS MESSAGES>
-    {json.dumps([ep for ep in context['previous_episodes']], indent=2)}
+    {to_prompt_json([ep for ep in context['previous_episodes']], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
     </PREVIOUS MESSAGES>
     <CURRENT MESSAGE>
     {context['episode_content']}
@@ -258,8 +258,8 @@ def extract_attributes(context: dict[str, Any]) -> list[Message]:
             content=f"""
 
         <MESSAGES>
-        {json.dumps(context['previous_episodes'], indent=2)}
+        {to_prompt_json(context['previous_episodes'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
-        {json.dumps(context['episode_content'], indent=2)}
+        {to_prompt_json(context['episode_content'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         </MESSAGES>
 
         Given the above MESSAGES and the following ENTITY, update any of its attributes based on the information provided
@@ -288,8 +288,8 @@ def extract_summary(context: dict[str, Any]) -> list[Message]:
             content=f"""
 
         <MESSAGES>
-        {json.dumps(context['previous_episodes'], indent=2)}
+        {to_prompt_json(context['previous_episodes'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
-        {json.dumps(context['episode_content'], indent=2)}
+        {to_prompt_json(context['episode_content'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         </MESSAGES>
 
         Given the above MESSAGES and the following ENTITY, update the summary that combines relevant information about the entity

graphiti_core/prompts/prompt_helpers.py

@@ -1 +1,24 @@
+import json
+from typing import Any
+
 DO_NOT_ESCAPE_UNICODE = '\nDo not escape unicode characters.\n'
+
+
+def to_prompt_json(data: Any, ensure_ascii: bool = True, indent: int = 2) -> str:
+    """
+    Serialize data to JSON for use in prompts.
+
+    Args:
+        data: The data to serialize
+        ensure_ascii: If True, escape non-ASCII characters. If False, preserve them.
+        indent: Number of spaces for indentation
+
+    Returns:
+        JSON string representation of the data
+
+    Notes:
+        When ensure_ascii=False, non-ASCII characters (e.g., Korean, Japanese, Chinese)
+        are preserved in their original form in the prompt, making them readable
+        in LLM logs and improving model understanding.
+    """
+    return json.dumps(data, ensure_ascii=ensure_ascii, indent=indent)

graphiti_core/prompts/summarize_nodes.py

@@ -14,12 +14,12 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-import json
 from typing import Any, Protocol, TypedDict
 
 from pydantic import BaseModel, Field
 
 from .models import Message, PromptFunction, PromptVersion
+from .prompt_helpers import to_prompt_json
 
 
 class Summary(BaseModel):
@@ -59,7 +59,7 @@ def summarize_pair(context: dict[str, Any]) -> list[Message]:
         Summaries must be under 250 words.
 
         Summaries:
-        {json.dumps(context['node_summaries'], indent=2)}
+        {to_prompt_json(context['node_summaries'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         """,
         ),
     ]
@@ -76,8 +76,8 @@ def summarize_context(context: dict[str, Any]) -> list[Message]:
             content=f"""
             
         <MESSAGES>
-        {json.dumps(context['previous_episodes'], indent=2)}
+        {to_prompt_json(context['previous_episodes'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
-        {json.dumps(context['episode_content'], indent=2)}
+        {to_prompt_json(context['episode_content'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         </MESSAGES>
         
         Given the above MESSAGES and the following ENTITY name, create a summary for the ENTITY. Your summary must only use
@@ -100,7 +100,7 @@ def summarize_context(context: dict[str, Any]) -> list[Message]:
         </ENTITY CONTEXT>
         
         <ATTRIBUTES>
-        {json.dumps(context['attributes'], indent=2)}
+        {to_prompt_json(context['attributes'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         </ATTRIBUTES>
         """,
         ),
@@ -120,7 +120,7 @@ def summary_description(context: dict[str, Any]) -> list[Message]:
         Summaries must be under 250 words.
 
         Summary:
-        {json.dumps(context['summary'], indent=2)}
+        {to_prompt_json(context['summary'], ensure_ascii=context.get('ensure_ascii', True), indent=2)}
         """,
         ),
     ]

graphiti_core/search/search_filters.py

@@ -31,7 +31,7 @@ class ComparisonOperator(Enum):
 
 
 class DateFilter(BaseModel):
-    date: datetime = Field(description='A datetime to filter on')
+    date: datetime | None = Field(description='A datetime to filter on')
     comparison_operator: ComparisonOperator = Field(
         description='Comparison operator for date filter'
     )

graphiti_core/search/search_helpers.py

@@ -14,9 +14,8 @@ See the License for the specific language governing permissions and
 limitations under the License.
 """
 
-import json
-
 from graphiti_core.edges import EntityEdge
+from graphiti_core.prompts.prompt_helpers import to_prompt_json
 from graphiti_core.search.search_config import SearchResults
 
 
@@ -25,7 +24,9 @@ def format_edge_date_range(edge: EntityEdge) -> str:
     return f'{edge.valid_at if edge.valid_at else "date unknown"} - {(edge.invalid_at if edge.invalid_at else "present")}'
 
 
-def search_results_to_context_string(search_results: SearchResults) -> str:
+def search_results_to_context_string(
+    search_results: SearchResults, ensure_ascii: bool = False
+) -> str:
     """Reformats a set of SearchResults into a single string to pass directly to an LLM as context"""
     fact_json = [
         {
@@ -57,16 +58,16 @@ def search_results_to_context_string(search_results: SearchResults) -> str:
     These are the most relevant facts and their valid and invalid dates. Facts are considered valid
     between their valid_at and invalid_at dates. Facts with an invalid_at date of "Present" are considered valid.
     <FACTS>
-    {json.dumps(fact_json, indent=12)}
+            {to_prompt_json(fact_json, ensure_ascii=ensure_ascii, indent=12)}
     </FACTS>
     <ENTITIES>
-    {json.dumps(entity_json, indent=12)}
+            {to_prompt_json(entity_json, ensure_ascii=ensure_ascii, indent=12)}
     </ENTITIES>
     <EPISODES>
-    {json.dumps(episode_json, indent=12)}
+            {to_prompt_json(episode_json, ensure_ascii=ensure_ascii, indent=12)}
     </EPISODES>
     <COMMUNITIES>
-    {json.dumps(community_json, indent=12)}
+            {to_prompt_json(community_json, ensure_ascii=ensure_ascii, indent=12)}
     </COMMUNITIES>
 """
 

graphiti_core/utils/bulk_utils.py

@@ -343,7 +343,13 @@ async def dedupe_edges_bulk(
     ] = await semaphore_gather(
         *[
             resolve_extracted_edge(
-                clients.llm_client, edge, candidates, candidates, episode, edge_types
+                clients.llm_client,
+                edge,
+                candidates,
+                candidates,
+                episode,
+                edge_types,
+                clients.ensure_ascii,
             )
             for episode, edge, candidates in dedupe_tuples
         ]

graphiti_core/utils/maintenance/community_operations.py

@@ -122,9 +122,14 @@ def label_propagation(projection: dict[str, list[Neighbor]]) -> list[list[str]]:
     return clusters
 
 
-async def summarize_pair(llm_client: LLMClient, summary_pair: tuple[str, str]) -> str:
+async def summarize_pair(
+    llm_client: LLMClient, summary_pair: tuple[str, str], ensure_ascii: bool = True
+) -> str:
     # Prepare context for LLM
-    context = {'node_summaries': [{'summary': summary} for summary in summary_pair]}
+    context = {
+        'node_summaries': [{'summary': summary} for summary in summary_pair],
+        'ensure_ascii': ensure_ascii,
+    }
 
     llm_response = await llm_client.generate_response(
         prompt_library.summarize_nodes.summarize_pair(context), response_model=Summary
@@ -135,8 +140,13 @@ async def summarize_pair(llm_client: LLMClient, summary_pair: tuple[str, str]) -
     return pair_summary
 
 
-async def generate_summary_description(llm_client: LLMClient, summary: str) -> str:
+async def generate_summary_description(
-    context = {'summary': summary}
+    llm_client: LLMClient, summary: str, ensure_ascii: bool = True
+) -> str:
+    context = {
+        'summary': summary,
+        'ensure_ascii': ensure_ascii,
+    }
 
     llm_response = await llm_client.generate_response(
         prompt_library.summarize_nodes.summary_description(context),
@@ -149,7 +159,7 @@ async def generate_summary_description(llm_client: LLMClient, summary: str) -> s
 
 
 async def build_community(
-    llm_client: LLMClient, community_cluster: list[EntityNode]
+    llm_client: LLMClient, community_cluster: list[EntityNode], ensure_ascii: bool = True
 ) -> tuple[CommunityNode, list[CommunityEdge]]:
     summaries = [entity.summary for entity in community_cluster]
     length = len(summaries)
@@ -161,7 +171,9 @@ async def build_community(
         new_summaries: list[str] = list(
             await semaphore_gather(
                 *[
-                    summarize_pair(llm_client, (str(left_summary), str(right_summary)))
+                    summarize_pair(
+                        llm_client, (str(left_summary), str(right_summary)), ensure_ascii
+                    )
                     for left_summary, right_summary in zip(
                         summaries[: int(length / 2)], summaries[int(length / 2) :], strict=False
                     )
@@ -174,7 +186,7 @@ async def build_community(
         length = len(summaries)
 
     summary = summaries[0]
-    name = await generate_summary_description(llm_client, summary)
+    name = await generate_summary_description(llm_client, summary, ensure_ascii)
     now = utc_now()
     community_node = CommunityNode(
         name=name,
@@ -191,7 +203,10 @@ async def build_community(
 
 
 async def build_communities(
-    driver: GraphDriver, llm_client: LLMClient, group_ids: list[str] | None
+    driver: GraphDriver,
+    llm_client: LLMClient,
+    group_ids: list[str] | None,
+    ensure_ascii: bool = True,
 ) -> tuple[list[CommunityNode], list[CommunityEdge]]:
     community_clusters = await get_community_clusters(driver, group_ids)
 
@@ -199,7 +214,7 @@ async def build_communities(
 
     async def limited_build_community(cluster):
         async with semaphore:
-            return await build_community(llm_client, cluster)
+            return await build_community(llm_client, cluster, ensure_ascii)
 
     communities: list[tuple[CommunityNode, list[CommunityEdge]]] = list(
         await semaphore_gather(
@@ -285,15 +300,21 @@ async def determine_entity_community(
 
 
 async def update_community(
-    driver: GraphDriver, llm_client: LLMClient, embedder: EmbedderClient, entity: EntityNode
+    driver: GraphDriver,
+    llm_client: LLMClient,
+    embedder: EmbedderClient,
+    entity: EntityNode,
+    ensure_ascii: bool = True,
 ) -> tuple[list[CommunityNode], list[CommunityEdge]]:
     community, is_new = await determine_entity_community(driver, entity)
 
     if community is None:
         return [], []
 
-    new_summary = await summarize_pair(llm_client, (entity.summary, community.summary))
+    new_summary = await summarize_pair(
-    new_name = await generate_summary_description(llm_client, new_summary)
+        llm_client, (entity.summary, community.summary), ensure_ascii
+    )
+    new_name = await generate_summary_description(llm_client, new_summary, ensure_ascii)
 
     community.summary = new_summary
     community.name = new_name

graphiti_core/utils/maintenance/edge_operations.py

@@ -151,6 +151,7 @@ async def extract_edges(
         'reference_time': episode.valid_at,
         'edge_types': edge_types_context,
         'custom_prompt': '',
+        'ensure_ascii': clients.ensure_ascii,
     }
 
     facts_missed = True
@@ -311,6 +312,7 @@ async def resolve_extracted_edges(
                     existing_edges,
                     episode,
                     extracted_edge_types,
+                    clients.ensure_ascii,
                 )
                 for extracted_edge, related_edges, existing_edges, extracted_edge_types in zip(
                     extracted_edges,
@@ -382,6 +384,7 @@ async def resolve_extracted_edge(
     existing_edges: list[EntityEdge],
     episode: EpisodicNode,
     edge_types: dict[str, type[BaseModel]] | None = None,
+    ensure_ascii: bool = True,
 ) -> tuple[EntityEdge, list[EntityEdge], list[EntityEdge]]:
     if len(related_edges) == 0 and len(existing_edges) == 0:
         return extracted_edge, [], []
@@ -415,6 +418,7 @@ async def resolve_extracted_edge(
         'new_edge': extracted_edge.fact,
         'edge_invalidation_candidates': invalidation_edge_candidates_context,
         'edge_types': edge_types_context,
+        'ensure_ascii': ensure_ascii,
     }
 
     llm_response = await llm_client.generate_response(
@@ -449,6 +453,7 @@ async def resolve_extracted_edge(
             'episode_content': episode.content,
             'reference_time': episode.valid_at,
             'fact': resolved_edge.fact,
+            'ensure_ascii': ensure_ascii,
         }
 
         edge_model = edge_types.get(fact_type)

graphiti_core/utils/maintenance/node_operations.py

@@ -48,12 +48,14 @@ async def extract_nodes_reflexion(
     episode: EpisodicNode,
     previous_episodes: list[EpisodicNode],
     node_names: list[str],
+    ensure_ascii: bool = False,
 ) -> list[str]:
     # Prepare context for LLM
     context = {
         'episode_content': episode.content,
         'previous_episodes': [ep.content for ep in previous_episodes],
         'extracted_entities': node_names,
+        'ensure_ascii': ensure_ascii,
     }
 
     llm_response = await llm_client.generate_response(
@@ -106,6 +108,7 @@ async def extract_nodes(
         'custom_prompt': custom_prompt,
         'entity_types': entity_types_context,
         'source_description': episode.source_description,
+        'ensure_ascii': clients.ensure_ascii,
     }
 
     while entities_missed and reflexion_iterations <= MAX_REFLEXION_ITERATIONS:
@@ -134,6 +137,7 @@ async def extract_nodes(
                 episode,
                 previous_episodes,
                 [entity.name for entity in extracted_entities],
+                clients.ensure_ascii,
             )
 
             entities_missed = len(missing_entities) != 0
@@ -244,6 +248,7 @@ async def resolve_extracted_nodes(
         'previous_episodes': [ep.content for ep in previous_episodes]
         if previous_episodes is not None
         else [],
+        'ensure_ascii': clients.ensure_ascii,
     }
 
     llm_response = await llm_client.generate_response(
@@ -309,6 +314,7 @@ async def extract_attributes_from_nodes(
                 entity_types.get(next((item for item in node.labels if item != 'Entity'), ''))
                 if entity_types is not None
                 else None,
+                clients.ensure_ascii,
             )
             for node in nodes
         ]
@@ -325,6 +331,7 @@ async def extract_attributes_from_node(
     episode: EpisodicNode | None = None,
     previous_episodes: list[EpisodicNode] | None = None,
     entity_type: type[BaseModel] | None = None,
+    ensure_ascii: bool = False,
 ) -> EntityNode:
     node_context: dict[str, Any] = {
         'name': node.name,
@@ -339,6 +346,7 @@ async def extract_attributes_from_node(
         'previous_episodes': [ep.content for ep in previous_episodes]
         if previous_episodes is not None
         else [],
+        'ensure_ascii': ensure_ascii,
     }
 
     summary_context: dict[str, Any] = {
@@ -347,6 +355,7 @@ async def extract_attributes_from_node(
         'previous_episodes': [ep.content for ep in previous_episodes]
         if previous_episodes is not None
         else [],
+        'ensure_ascii': ensure_ascii,
     }
 
     llm_response = (

graphiti_core/utils/maintenance/temporal_operations.py

@@ -35,12 +35,14 @@ async def extract_edge_dates(
     edge: EntityEdge,
     current_episode: EpisodicNode,
     previous_episodes: list[EpisodicNode],
+    ensure_ascii: bool = False,
 ) -> tuple[datetime | None, datetime | None]:
     context = {
         'edge_fact': edge.fact,
         'current_episode': current_episode.content,
         'previous_episodes': [ep.content for ep in previous_episodes],
         'reference_timestamp': current_episode.valid_at.isoformat(),
+        'ensure_ascii': ensure_ascii,
     }
     llm_response = await llm_client.generate_response(
         prompt_library.extract_edge_dates.v1(context), response_model=EdgeDates
@@ -70,7 +72,10 @@ async def extract_edge_dates(
 
 
 async def get_edge_contradictions(
-    llm_client: LLMClient, new_edge: EntityEdge, existing_edges: list[EntityEdge]
+    llm_client: LLMClient,
+    new_edge: EntityEdge,
+    existing_edges: list[EntityEdge],
+    ensure_ascii: bool = False,
 ) -> list[EntityEdge]:
     start = time()
 
@@ -79,7 +84,11 @@ async def get_edge_contradictions(
         {'id': i, 'fact': existing_edge.fact} for i, existing_edge in enumerate(existing_edges)
     ]
 
-    context = {'new_edge': new_edge_context, 'existing_edges': existing_edge_context}
+    context = {
+        'new_edge': new_edge_context,
+        'existing_edges': existing_edge_context,
+        'ensure_ascii': ensure_ascii,
+    }
 
     llm_response = await llm_client.generate_response(
         prompt_library.invalidate_edges.v2(context),

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "graphiti-core"
 description = "A temporal graph building library"
-version = "0.18.3"
+version = "0.18.5"
 authors = [
     { name = "Paul Paliychuk", email = "paul@getzep.com" },
     { name = "Preston Rasmussen", email = "preston@getzep.com" },

signatures/version1/cla.json

@@ -287,6 +287,22 @@
       "created_at": "2025-08-07T02:23:09Z",
       "repoId": 840056306,
       "pullRequestNo": 812
+    },
+    {
+      "name": "vjeeva",
+      "id": 13189349,
+      "comment_id": 3165600173,
+      "created_at": "2025-08-07T20:24:08Z",
+      "repoId": 840056306,
+      "pullRequestNo": 814
+    },
+    {
+      "name": "liebertar",
+      "id": 99405438,
+      "comment_id": 3166905812,
+      "created_at": "2025-08-08T07:52:27Z",
+      "repoId": 840056306,
+      "pullRequestNo": 816
     }
   ]
 }

uv.lock

@@ -746,7 +746,7 @@ wheels = [
 
 [[package]]
 name = "graphiti-core"
-version = "0.18.3"
+version = "0.18.4"
 source = { editable = "." }
 dependencies = [
     { name = "diskcache" },