update prompts and support thinking models (#846)

* update prompts and support thinking models

* update

* type ignore

examples/podcast/podcast_runner.py

@@ -77,7 +77,11 @@ class IsPresidentOf(BaseModel):
 
 async def main(use_bulk: bool = False):
     setup_logging()
-    client = Graphiti(neo4j_uri, neo4j_user, neo4j_password)
+    client = Graphiti(
+        neo4j_uri,
+        neo4j_user,
+        neo4j_password,
+    )
     await clear_data(client.driver)
     await client.build_indices_and_constraints()
     messages = parse_podcast_messages()

graphiti_core/llm_client/openai_base_client.py

@@ -107,10 +107,10 @@ class BaseOpenAIClient(LLMClient):
 
     def _handle_structured_response(self, response: Any) -> dict[str, Any]:
         """Handle structured response parsing and validation."""
-        response_object = response.choices[0].message
+        response_object = response.output_text
 
-        if response_object.parsed:
-            return response_object.parsed.model_dump()
+        if response_object:
+            return json.loads(response_object)
         elif response_object.refusal:
             raise RefusalError(response_object.refusal)
         else:

graphiti_core/llm_client/openai_client.py

@@ -69,14 +69,16 @@ class OpenAIClient(BaseOpenAIClient):
         response_model: type[BaseModel],
     ):
         """Create a structured completion using OpenAI's beta parse API."""
-        return await self.client.beta.chat.completions.parse(
+        response = await self.client.responses.parse(
             model=model,
-            messages=messages,
+            input=messages,  # type: ignore
             temperature=temperature,
-            max_tokens=max_tokens,
-            response_format=response_model,  # type: ignore
+            max_output_tokens=max_tokens,
+            text_format=response_model,  # type: ignore
         )
 
+        return response
+
     async def _create_completion(
         self,
         model: str,

graphiti_core/prompts/extract_edges.py

@@ -94,6 +94,7 @@ Only extract facts that:
 - involve two DISTINCT ENTITIES from the ENTITIES list,
 - are clearly stated or unambiguously implied in the CURRENT MESSAGE,
     and can be represented as edges in a knowledge graph.
+- Facts should include entity names rather than pronouns whenever possible.
 - The FACT TYPES provide a list of the most important types of facts, make sure to extract facts of these types
 - The FACT TYPES are not an exhaustive list, extract all facts from the message even if they do not fit into one
     of the FACT TYPES

graphiti_core/prompts/extract_nodes.py

@@ -100,7 +100,7 @@ Instructions:
 
 You are given a conversation context and a CURRENT MESSAGE. Your task is to extract **entity nodes** mentioned **explicitly or implicitly** in the CURRENT MESSAGE.
 Pronoun references such as he/she/they or this/that/those should be disambiguated to the names of the 
-reference entities.
+reference entities. Only extract distinct entities from the CURRENT MESSAGE. Don't extract pronouns like you, me, he/she/they, we/us as entities.
 
 1. **Speaker Extraction**: Always extract the speaker (the part before the colon `:` in each dialogue line) as the first entity node.
    - If the speaker is mentioned again in the message, treat both mentions as a **single entity**.

graphiti_core/utils/maintenance/node_operations.py

@@ -152,9 +152,13 @@ async def extract_nodes(
     # Convert the extracted data into EntityNode objects
     extracted_nodes = []
     for extracted_entity in filtered_extracted_entities:
-        entity_type_name = entity_types_context[extracted_entity.entity_type_id].get(
-            'entity_type_name'
-        )
+        type_id = extracted_entity.entity_type_id
+        if 0 <= type_id < len(entity_types_context):
+            entity_type_name = entity_types_context[extracted_entity.entity_type_id].get(
+                'entity_type_name'
+            )
+        else:
+            entity_type_name = 'Entity'
 
         # Check if this entity type should be excluded
         if excluded_entity_types and entity_type_name in excluded_entity_types:

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "graphiti-core"
 description = "A temporal graph building library"
-version = "0.18.8"
+version = "0.18.9"
 authors = [
     { name = "Paul Paliychuk", email = "paul@getzep.com" },
     { name = "Preston Rasmussen", email = "preston@getzep.com" },

uv.lock

@@ -746,7 +746,7 @@ wheels = [
 
 [[package]]
 name = "graphiti-core"
-version = "0.18.7"
+version = "0.18.9"
 source = { editable = "." }
 dependencies = [
     { name = "diskcache" },