Add group_id parameter to get_extraction_language_instruction

Enable consumers to provide group-specific language extraction
instructions by passing group_id through the call chain.

Changes:
- Add optional group_id parameter to get_extraction_language_instruction()
- Add group_id parameter to all LLMClient.generate_response() methods
- Pass group_id through to language instruction function
- Maintain backward compatibility with default None value

Users can now customize extraction per group:
```python
def custom_instruction(group_id: str | None = None) -> str:
    if group_id == 'spanish-users':
        return '\n\nExtract in Spanish.'
    return '\n\nExtract in original language.'

client.get_extraction_language_instruction = custom_instruction
```

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

graphiti_core/llm_client/client.py

@@ -33,12 +33,16 @@ DEFAULT_TEMPERATURE = 0
 DEFAULT_CACHE_DIR = './llm_cache'
 
 
-def get_extraction_language_instruction() -> str:
+def get_extraction_language_instruction(group_id: str | None = None) -> str:
     """Returns instruction for language extraction behavior.
 
     Override this function to customize language extraction:
     - Return empty string to disable multilingual instructions
     - Return custom instructions for specific language requirements
+    - Use group_id to provide different instructions per group/partition
+
+    Args:
+        group_id: Optional partition identifier for the graph
 
     Returns:
         str: Language instruction to append to system messages
@@ -142,6 +146,7 @@ class LLMClient(ABC):
         response_model: type[BaseModel] | None = None,
         max_tokens: int | None = None,
         model_size: ModelSize = ModelSize.medium,
+        group_id: str | None = None,
     ) -> dict[str, typing.Any]:
         if max_tokens is None:
             max_tokens = self.max_tokens
@@ -155,7 +160,7 @@ class LLMClient(ABC):
             )
 
         # Add multilingual extraction instructions
-        messages[0].content += get_extraction_language_instruction()
+        messages[0].content += get_extraction_language_instruction(group_id)
 
         if self.cache_enabled and self.cache_dir is not None:
             cache_key = self._get_cache_key(messages)

graphiti_core/llm_client/gemini_client.py

@@ -357,6 +357,7 @@ class GeminiClient(LLMClient):
         response_model: type[BaseModel] | None = None,
         max_tokens: int | None = None,
         model_size: ModelSize = ModelSize.medium,
+        group_id: str | None = None,
     ) -> dict[str, typing.Any]:
         """
         Generate a response from the Gemini language model with retry logic and error handling.
@@ -367,6 +368,7 @@ class GeminiClient(LLMClient):
             response_model (type[BaseModel] | None): An optional Pydantic model to parse the response into.
             max_tokens (int | None): The maximum number of tokens to generate in the response.
             model_size (ModelSize): The size of the model to use (small or medium).
+            group_id (str | None): Optional partition identifier for the graph.
 
         Returns:
             dict[str, typing.Any]: The response from the language model.
@@ -376,7 +378,7 @@ class GeminiClient(LLMClient):
         last_output = None
 
         # Add multilingual extraction instructions
-        messages[0].content += get_extraction_language_instruction()
+        messages[0].content += get_extraction_language_instruction(group_id)
 
         while retry_count < self.MAX_RETRIES:
             try:

graphiti_core/llm_client/openai_base_client.py

@@ -175,6 +175,7 @@ class BaseOpenAIClient(LLMClient):
         response_model: type[BaseModel] | None = None,
         max_tokens: int | None = None,
         model_size: ModelSize = ModelSize.medium,
+        group_id: str | None = None,
     ) -> dict[str, typing.Any]:
         """Generate a response with retry logic and error handling."""
         if max_tokens is None:
@@ -184,7 +185,7 @@ class BaseOpenAIClient(LLMClient):
         last_error = None
 
         # Add multilingual extraction instructions
-        messages[0].content += get_extraction_language_instruction()
+        messages[0].content += get_extraction_language_instruction(group_id)
 
         while retry_count <= self.MAX_RETRIES:
             try:

graphiti_core/llm_client/openai_generic_client.py

@@ -120,6 +120,7 @@ class OpenAIGenericClient(LLMClient):
         response_model: type[BaseModel] | None = None,
         max_tokens: int | None = None,
         model_size: ModelSize = ModelSize.medium,
+        group_id: str | None = None,
     ) -> dict[str, typing.Any]:
         if max_tokens is None:
             max_tokens = self.max_tokens
@@ -136,7 +137,7 @@ class OpenAIGenericClient(LLMClient):
             )
 
         # Add multilingual extraction instructions
-        messages[0].content += get_extraction_language_instruction()
+        messages[0].content += get_extraction_language_instruction(group_id)
 
         while retry_count <= self.MAX_RETRIES:
             try:

uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.10, <4"
 resolution-markers = [
     "python_full_version >= '3.14'",