diff --git a/Dockerfile b/Dockerfile index 724e1222..9e47413e 100644 --- a/Dockerfile +++ b/Dockerfile @@ -23,7 +23,7 @@ RUN poetry build && pip install dist/*.whl # Install server dependencies WORKDIR /app/server -RUN poetry install --no-interaction --no-ansi --no-dev +RUN poetry install --no-interaction --no-ansi --only main --no-root FROM python:3.12-slim diff --git a/graphiti_core/helpers.py b/graphiti_core/helpers.py index 0d46a2a0..48dc07a0 100644 --- a/graphiti_core/helpers.py +++ b/graphiti_core/helpers.py @@ -73,12 +73,12 @@ def lucene_sanitize(query: str) -> str: return sanitized -def normalize_l2(embedding: list[float]) -> list[float]: +def normalize_l2(embedding: list[float]): embedding_array = np.array(embedding) if embedding_array.ndim == 1: norm = np.linalg.norm(embedding_array) if norm == 0: - return embedding_array.tolist() + return [0.0] * len(embedding) return (embedding_array / norm).tolist() else: norm = np.linalg.norm(embedding_array, 2, axis=1, keepdims=True) diff --git a/graphiti_core/llm_client/anthropic_client.py b/graphiti_core/llm_client/anthropic_client.py index df99fb91..def6fe55 100644 --- a/graphiti_core/llm_client/anthropic_client.py +++ b/graphiti_core/llm_client/anthropic_client.py @@ -48,7 +48,10 @@ def __init__(self, config: LLMConfig | None = None, cache: bool = False): ) async def _generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: system_message = messages[0] user_messages = [{'role': m.role, 'content': m.content} for m in messages[1:]] + [ @@ -59,7 +62,7 @@ async def _generate_response( result = await self.client.messages.create( system='Only include JSON in the response. Do not include any additional text or explanation of the content.\n' + system_message.content, - max_tokens=self.max_tokens, + max_tokens=max_tokens or self.max_tokens, temperature=self.temperature, messages=user_messages, # type: ignore model=self.model or DEFAULT_MODEL, diff --git a/graphiti_core/llm_client/client.py b/graphiti_core/llm_client/client.py index 0c28e895..561defcc 100644 --- a/graphiti_core/llm_client/client.py +++ b/graphiti_core/llm_client/client.py @@ -26,7 +26,7 @@ from tenacity import retry, retry_if_exception, stop_after_attempt, wait_random_exponential from ..prompts.models import Message -from .config import LLMConfig +from .config import DEFAULT_MAX_TOKENS, LLMConfig from .errors import RateLimitError DEFAULT_TEMPERATURE = 0 @@ -90,16 +90,22 @@ def _clean_input(self, input: str) -> str: reraise=True, ) async def _generate_response_with_retry( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: try: - return await self._generate_response(messages, response_model) + return await self._generate_response(messages, response_model, max_tokens) except (httpx.HTTPStatusError, RateLimitError) as e: raise e @abstractmethod async def _generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: pass @@ -110,7 +116,10 @@ def _get_cache_key(self, messages: list[Message]) -> str: return hashlib.md5(key_str.encode()).hexdigest() async def generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: if response_model is not None: serialized_model = json.dumps(response_model.model_json_schema()) @@ -131,7 +140,7 @@ async def generate_response( for message in messages: message.content = self._clean_input(message.content) - response = await self._generate_response_with_retry(messages, response_model) + response = await self._generate_response_with_retry(messages, response_model, max_tokens) if self.cache_enabled: self.cache_dir.set(cache_key, response) diff --git a/graphiti_core/llm_client/config.py b/graphiti_core/llm_client/config.py index 5e346367..63257d21 100644 --- a/graphiti_core/llm_client/config.py +++ b/graphiti_core/llm_client/config.py @@ -14,7 +14,7 @@ limitations under the License. """ -DEFAULT_MAX_TOKENS = 16384 +DEFAULT_MAX_TOKENS = 1024 DEFAULT_TEMPERATURE = 0 diff --git a/graphiti_core/llm_client/groq_client.py b/graphiti_core/llm_client/groq_client.py index 45ccc3cb..56b7fb28 100644 --- a/graphiti_core/llm_client/groq_client.py +++ b/graphiti_core/llm_client/groq_client.py @@ -45,7 +45,10 @@ def __init__(self, config: LLMConfig | None = None, cache: bool = False): self.client = AsyncGroq(api_key=config.api_key) async def _generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: msgs: list[ChatCompletionMessageParam] = [] for m in messages: @@ -58,7 +61,7 @@ async def _generate_response( model=self.model or DEFAULT_MODEL, messages=msgs, temperature=self.temperature, - max_tokens=self.max_tokens, + max_tokens=max_tokens or self.max_tokens, response_format={'type': 'json_object'}, ) result = response.choices[0].message.content or '' diff --git a/graphiti_core/llm_client/openai_client.py b/graphiti_core/llm_client/openai_client.py index 7804e06f..45b89a0f 100644 --- a/graphiti_core/llm_client/openai_client.py +++ b/graphiti_core/llm_client/openai_client.py @@ -25,7 +25,7 @@ from ..prompts.models import Message from .client import LLMClient -from .config import LLMConfig +from .config import DEFAULT_MAX_TOKENS, LLMConfig from .errors import RateLimitError, RefusalError logger = logging.getLogger(__name__) @@ -58,7 +58,11 @@ class OpenAIClient(LLMClient): MAX_RETRIES: ClassVar[int] = 2 def __init__( - self, config: LLMConfig | None = None, cache: bool = False, client: typing.Any = None + self, + config: LLMConfig | None = None, + cache: bool = False, + client: typing.Any = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ): """ Initialize the OpenAIClient with the provided configuration, cache setting, and client. @@ -84,7 +88,10 @@ def __init__( self.client = client async def _generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: openai_messages: list[ChatCompletionMessageParam] = [] for m in messages: @@ -98,7 +105,7 @@ async def _generate_response( model=self.model or DEFAULT_MODEL, messages=openai_messages, temperature=self.temperature, - max_tokens=self.max_tokens, + max_tokens=max_tokens or self.max_tokens, response_format=response_model, # type: ignore ) @@ -119,14 +126,17 @@ async def _generate_response( raise async def generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: retry_count = 0 last_error = None while retry_count <= self.MAX_RETRIES: try: - response = await self._generate_response(messages, response_model) + response = await self._generate_response(messages, response_model, max_tokens) return response except (RateLimitError, RefusalError): # These errors should not trigger retries diff --git a/graphiti_core/llm_client/openai_generic_client.py b/graphiti_core/llm_client/openai_generic_client.py index 50c7bc50..b64ca67b 100644 --- a/graphiti_core/llm_client/openai_generic_client.py +++ b/graphiti_core/llm_client/openai_generic_client.py @@ -26,7 +26,7 @@ from ..prompts.models import Message from .client import LLMClient -from .config import LLMConfig +from .config import DEFAULT_MAX_TOKENS, LLMConfig from .errors import RateLimitError, RefusalError logger = logging.getLogger(__name__) @@ -85,7 +85,10 @@ def __init__( self.client = client async def _generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: openai_messages: list[ChatCompletionMessageParam] = [] for m in messages: @@ -111,7 +114,10 @@ async def _generate_response( raise async def generate_response( - self, messages: list[Message], response_model: type[BaseModel] | None = None + self, + messages: list[Message], + response_model: type[BaseModel] | None = None, + max_tokens: int = DEFAULT_MAX_TOKENS, ) -> dict[str, typing.Any]: retry_count = 0 last_error = None @@ -126,7 +132,9 @@ async def generate_response( while retry_count <= self.MAX_RETRIES: try: - response = await self._generate_response(messages, response_model) + response = await self._generate_response( + messages, response_model, max_tokens=max_tokens + ) return response except (RateLimitError, RefusalError): # These errors should not trigger retries diff --git a/graphiti_core/utils/maintenance/edge_operations.py b/graphiti_core/utils/maintenance/edge_operations.py 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