diff --git a/.github/workflows/notebooks_tests.yml b/.github/workflows/notebooks_tests.yml index 1b99a4e81..a6fbae294 100644 --- a/.github/workflows/notebooks_tests.yml +++ b/.github/workflows/notebooks_tests.yml @@ -4,12 +4,12 @@ on: workflow_call: jobs: - run-main-notebook: - name: Main Notebook Test - uses: ./.github/workflows/reusable_notebook.yml - with: - notebook-location: notebooks/cognee_demo.ipynb - secrets: inherit +# run-main-notebook: +# name: Main Notebook Test +# uses: ./.github/workflows/reusable_notebook.yml +# with: +# notebook-location: notebooks/cognee_demo.ipynb +# secrets: inherit run-llama-index-integration: name: LlamaIndex Integration Notebook @@ -32,9 +32,9 @@ jobs: notebook-location: notebooks/cognee_multimedia_demo.ipynb secrets: inherit - run-graphrag-vs-rag: - name: Graphrag vs Rag notebook - uses: ./.github/workflows/reusable_notebook.yml - with: - notebook-location: notebooks/graphrag_vs_rag.ipynb - secrets: inherit +# run-graphrag-vs-rag: +# name: Graphrag vs Rag notebook +# uses: ./.github/workflows/reusable_notebook.yml +# with: +# notebook-location: notebooks/graphrag_vs_rag.ipynb +# secrets: inherit diff --git a/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py b/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py index 5678d0322..446a00365 100644 --- a/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py +++ b/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py @@ -10,6 +10,10 @@ from cognee.infrastructure.llm.tokenizer.Gemini import GeminiTokenizer from cognee.infrastructure.llm.tokenizer.HuggingFace import HuggingFaceTokenizer from cognee.infrastructure.llm.tokenizer.Mistral import MistralTokenizer from cognee.infrastructure.llm.tokenizer.TikToken import TikTokenTokenizer +from cognee.infrastructure.llm.embedding_rate_limiter import ( + embedding_rate_limit_async, + embedding_sleep_and_retry_async, +) litellm.set_verbose = False logger = get_logger("LiteLLMEmbeddingEngine") @@ -51,17 +55,12 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine): enable_mocking = str(enable_mocking).lower() self.mock = enable_mocking in ("true", "1", "yes") + @embedding_sleep_and_retry_async() + @embedding_rate_limit_async async def embed_text(self, text: List[str]) -> List[List[float]]: - async def exponential_backoff(attempt): - wait_time = min(10 * (2**attempt), 60) # Max 60 seconds - await asyncio.sleep(wait_time) - try: if self.mock: response = {"data": [{"embedding": [0.0] * self.dimensions} for _ in text]} - - self.retry_count = 0 - return [data["embedding"] for data in response["data"]] else: response = await litellm.aembedding( @@ -72,8 +71,6 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine): api_version=self.api_version, ) - self.retry_count = 0 # Reset retry count on successful call - return [data["embedding"] for data in response.data] except litellm.exceptions.ContextWindowExceededError as error: @@ -95,15 +92,6 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine): logger.error("Context window exceeded for embedding text: %s", str(error)) raise error - except litellm.exceptions.RateLimitError: - if self.retry_count >= self.MAX_RETRIES: - raise Exception("Rate limit exceeded and no more retries left.") - - await exponential_backoff(self.retry_count) - self.retry_count += 1 - - return await self.embed_text(text) - except ( litellm.exceptions.BadRequestError, litellm.exceptions.NotFoundError, diff --git a/cognee/infrastructure/databases/vector/embeddings/OllamaEmbeddingEngine.py b/cognee/infrastructure/databases/vector/embeddings/OllamaEmbeddingEngine.py index e27a02ba3..072ef9ac4 100644 --- a/cognee/infrastructure/databases/vector/embeddings/OllamaEmbeddingEngine.py +++ b/cognee/infrastructure/databases/vector/embeddings/OllamaEmbeddingEngine.py @@ -9,6 +9,10 @@ import aiohttp.http_exceptions from cognee.infrastructure.databases.vector.embeddings.EmbeddingEngine import EmbeddingEngine from cognee.infrastructure.databases.exceptions.EmbeddingException import EmbeddingException from cognee.infrastructure.llm.tokenizer.HuggingFace import HuggingFaceTokenizer +from cognee.infrastructure.llm.rate_limiter import ( + embedding_rate_limit_async, + embedding_sleep_and_retry_async, +) logger = get_logger("OllamaEmbeddingEngine") @@ -43,6 +47,7 @@ class OllamaEmbeddingEngine(EmbeddingEngine): enable_mocking = str(enable_mocking).lower() self.mock = enable_mocking in ("true", "1", "yes") + @embedding_rate_limit_async async def embed_text(self, text: List[str]) -> List[List[float]]: """ Given a list of text prompts, returns a list of embedding vectors. @@ -53,6 +58,7 @@ class OllamaEmbeddingEngine(EmbeddingEngine): embeddings = await asyncio.gather(*[self._get_embedding(prompt) for prompt in text]) return embeddings + @embedding_sleep_and_retry_async() async def _get_embedding(self, prompt: str) -> List[float]: """ Internal method to call the Ollama embeddings endpoint for a single prompt. @@ -66,26 +72,12 @@ class OllamaEmbeddingEngine(EmbeddingEngine): if api_key: headers["Authorization"] = f"Bearer {api_key}" - retries = 0 - while retries < self.MAX_RETRIES: - try: - async with aiohttp.ClientSession() as session: - async with session.post( - self.endpoint, json=payload, headers=headers, timeout=60.0 - ) as response: - data = await response.json() - return data["embedding"] - except aiohttp.http_exceptions.HttpBadRequest as e: - logger.error(f"HTTP error on attempt {retries + 1}: {e}") - retries += 1 - await asyncio.sleep(min(2**retries, 60)) - except Exception as e: - logger.error(f"Error on attempt {retries + 1}: {e}") - retries += 1 - await asyncio.sleep(min(2**retries, 60)) - raise EmbeddingException( - f"Failed to embed text using model {self.model} after {self.MAX_RETRIES} retries" - ) + async with aiohttp.ClientSession() as session: + async with session.post( + self.endpoint, json=payload, headers=headers, timeout=60.0 + ) as response: + data = await response.json() + return data["embedding"] def get_vector_size(self) -> int: return self.dimensions diff --git a/cognee/infrastructure/llm/anthropic/adapter.py b/cognee/infrastructure/llm/anthropic/adapter.py index 604d1ea4d..773a2fc28 100644 --- a/cognee/infrastructure/llm/anthropic/adapter.py +++ b/cognee/infrastructure/llm/anthropic/adapter.py @@ -5,6 +5,7 @@ import instructor from cognee.exceptions import InvalidValueError from cognee.infrastructure.llm.llm_interface import LLMInterface from cognee.infrastructure.llm.prompts import read_query_prompt +from cognee.infrastructure.llm.rate_limiter import rate_limit_async, sleep_and_retry_async class AnthropicAdapter(LLMInterface): @@ -23,6 +24,8 @@ class AnthropicAdapter(LLMInterface): self.model = model self.max_tokens = max_tokens + @sleep_and_retry_async() + @rate_limit_async async def acreate_structured_output( self, text_input: str, system_prompt: str, response_model: Type[BaseModel] ) -> BaseModel: diff --git a/cognee/infrastructure/llm/config.py b/cognee/infrastructure/llm/config.py index fd95410fd..ccf0fa3c3 100644 --- a/cognee/infrastructure/llm/config.py +++ b/cognee/infrastructure/llm/config.py @@ -16,6 +16,12 @@ class LLMConfig(BaseSettings): llm_max_tokens: int = 16384 transcription_model: str = "whisper-1" graph_prompt_path: str = "generate_graph_prompt.txt" + llm_rate_limit_enabled: bool = False + llm_rate_limit_requests: int = 60 + llm_rate_limit_interval: int = 60 # in seconds (default is 60 requests per minute) + embedding_rate_limit_enabled: bool = False + embedding_rate_limit_requests: int = 60 + embedding_rate_limit_interval: int = 60 # in seconds (default is 60 requests per minute) model_config = SettingsConfigDict(env_file=".env", extra="allow") @@ -85,6 +91,12 @@ class LLMConfig(BaseSettings): "max_tokens": self.llm_max_tokens, "transcription_model": self.transcription_model, "graph_prompt_path": self.graph_prompt_path, + "rate_limit_enabled": self.llm_rate_limit_enabled, + "rate_limit_requests": self.llm_rate_limit_requests, + "rate_limit_interval": self.llm_rate_limit_interval, + "embedding_rate_limit_enabled": self.embedding_rate_limit_enabled, + "embedding_rate_limit_requests": self.embedding_rate_limit_requests, + "embedding_rate_limit_interval": self.embedding_rate_limit_interval, } diff --git a/cognee/infrastructure/llm/embedding_rate_limiter.py b/cognee/infrastructure/llm/embedding_rate_limiter.py new file mode 100644 index 000000000..8383a8a0d --- /dev/null +++ b/cognee/infrastructure/llm/embedding_rate_limiter.py @@ -0,0 +1,369 @@ +import threading +import logging +import functools +import os +import time +import asyncio +import random +from cognee.shared.logging_utils import get_logger +from cognee.infrastructure.llm.config import get_llm_config + + +logger = get_logger() + +# Common error patterns that indicate rate limiting +RATE_LIMIT_ERROR_PATTERNS = [ + "rate limit", + "rate_limit", + "ratelimit", + "too many requests", + "retry after", + "capacity", + "quota", + "limit exceeded", + "tps limit exceeded", + "request limit exceeded", + "maximum requests", + "exceeded your current quota", + "throttled", + "throttling", +] + +# Default retry settings +DEFAULT_MAX_RETRIES = 5 +DEFAULT_INITIAL_BACKOFF = 1.0 # seconds +DEFAULT_BACKOFF_FACTOR = 2.0 # exponential backoff multiplier +DEFAULT_JITTER = 0.1 # 10% jitter to avoid thundering herd + + +class EmbeddingRateLimiter: + """ + Rate limiter for embedding API calls. + + This class implements a singleton pattern to ensure that rate limiting + is consistent across all embedding requests. It uses the limits + library with a moving window strategy to control request rates. + + The rate limiter uses the same configuration as the LLM API rate limiter + but uses a separate key to track embedding API calls independently. + """ + + _instance = None + lock = threading.Lock() + + @classmethod + def get_instance(cls): + if cls._instance is None: + with cls.lock: + if cls._instance is None: + cls._instance = cls() + return cls._instance + + @classmethod + def reset_instance(cls): + with cls.lock: + cls._instance = None + + def __init__(self): + config = get_llm_config() + self.enabled = config.embedding_rate_limit_enabled + self.requests_limit = config.embedding_rate_limit_requests + self.interval_seconds = config.embedding_rate_limit_interval + self.request_times = [] + self.lock = threading.Lock() + + logging.info( + f"EmbeddingRateLimiter initialized: enabled={self.enabled}, " + f"requests_limit={self.requests_limit}, interval_seconds={self.interval_seconds}" + ) + + def hit_limit(self) -> bool: + """ + Check if the current request would exceed the rate limit. + + Returns: + bool: True if the rate limit would be exceeded, False otherwise. + """ + if not self.enabled: + return False + + current_time = time.time() + + with self.lock: + # Remove expired request times + cutoff_time = current_time - self.interval_seconds + self.request_times = [t for t in self.request_times if t > cutoff_time] + + # Check if adding a new request would exceed the limit + if len(self.request_times) >= self.requests_limit: + logger.info( + f"Rate limit hit: {len(self.request_times)} requests in the last {self.interval_seconds} seconds" + ) + return True + + # Otherwise, we're under the limit + return False + + def wait_if_needed(self) -> float: + """ + Block until a request can be made without exceeding the rate limit. + + Returns: + float: Time waited in seconds. + """ + if not self.enabled: + return 0 + + wait_time = 0 + start_time = time.time() + + while self.hit_limit(): + time.sleep(0.5) # Poll every 0.5 seconds + wait_time = time.time() - start_time + + # Record this request + with self.lock: + self.request_times.append(time.time()) + + return wait_time + + async def async_wait_if_needed(self) -> float: + """ + Asynchronously wait until a request can be made without exceeding the rate limit. + + Returns: + float: Time waited in seconds. + """ + if not self.enabled: + return 0 + + wait_time = 0 + start_time = time.time() + + while self.hit_limit(): + await asyncio.sleep(0.5) # Poll every 0.5 seconds + wait_time = time.time() - start_time + + # Record this request + with self.lock: + self.request_times.append(time.time()) + + return wait_time + + +def embedding_rate_limit_sync(func): + """ + Decorator that applies rate limiting to a synchronous embedding function. + + This decorator checks if the request would exceed the rate limit, + and blocks if necessary. + + Args: + func: Function to decorate. + + Returns: + Decorated function that applies rate limiting. + """ + + @functools.wraps(func) + def wrapper(*args, **kwargs): + limiter = EmbeddingRateLimiter.get_instance() + + # Check if rate limiting is enabled and if we're at the limit + if limiter.hit_limit(): + error_msg = "Embedding API rate limit exceeded" + logger.warning(error_msg) + + # Create a custom embedding rate limit exception + from cognee.infrastructure.databases.exceptions.EmbeddingException import ( + EmbeddingException, + ) + + raise EmbeddingException(error_msg) + + # Add this request to the counter and proceed + limiter.wait_if_needed() + return func(*args, **kwargs) + + return wrapper + + +def embedding_rate_limit_async(func): + """ + Decorator that applies rate limiting to an asynchronous embedding function. + + This decorator checks if the request would exceed the rate limit, + and waits asynchronously if necessary. + + Args: + func: Async function to decorate. + + Returns: + Decorated async function that applies rate limiting. + """ + + @functools.wraps(func) + async def wrapper(*args, **kwargs): + limiter = EmbeddingRateLimiter.get_instance() + + # Check if rate limiting is enabled and if we're at the limit + if limiter.hit_limit(): + error_msg = "Embedding API rate limit exceeded" + logger.warning(error_msg) + + # Create a custom embedding rate limit exception + from cognee.infrastructure.databases.exceptions.EmbeddingException import ( + EmbeddingException, + ) + + raise EmbeddingException(error_msg) + + # Add this request to the counter and proceed + await limiter.async_wait_if_needed() + return await func(*args, **kwargs) + + return wrapper + + +def embedding_sleep_and_retry_sync(max_retries=5, base_backoff=1.0, jitter=0.5): + """ + Decorator that adds retry with exponential backoff for synchronous embedding functions. + + The decorator will retry the function with exponential backoff if it + fails due to a rate limit error. + + Args: + max_retries: Maximum number of retries. + base_backoff: Base backoff time in seconds. + jitter: Jitter factor to randomize backoff time. + + Returns: + Decorated function that retries on rate limit errors. + """ + + def decorator(func): + @functools.wraps(func) + def wrapper(*args, **kwargs): + # If DISABLE_RETRIES is set, don't retry for testing purposes + disable_retries = os.environ.get("DISABLE_RETRIES", "false").lower() in ( + "true", + "1", + "yes", + ) + + retries = 0 + last_error = None + + while retries <= max_retries: + try: + return func(*args, **kwargs) + except Exception as e: + # Check if this is a rate limit error + error_str = str(e).lower() + error_type = type(e).__name__ + is_rate_limit = any( + pattern in error_str.lower() for pattern in RATE_LIMIT_ERROR_PATTERNS + ) + + if disable_retries: + # For testing, propagate the exception immediately + raise + + if is_rate_limit and retries < max_retries: + # Calculate backoff with jitter + backoff = ( + base_backoff * (2**retries) * (1 + random.uniform(-jitter, jitter)) + ) + + logger.warning( + f"Embedding rate limit hit, retrying in {backoff:.2f}s " + f"(attempt {retries + 1}/{max_retries}): " + f"({error_str!r}, {error_type!r})" + ) + + time.sleep(backoff) + retries += 1 + last_error = e + else: + # Not a rate limit error or max retries reached, raise + raise + + # If we exit the loop due to max retries, raise the last error + if last_error: + raise last_error + + return wrapper + + return decorator + + +def embedding_sleep_and_retry_async(max_retries=5, base_backoff=1.0, jitter=0.5): + """ + Decorator that adds retry with exponential backoff for asynchronous embedding functions. + + The decorator will retry the function with exponential backoff if it + fails due to a rate limit error. + + Args: + max_retries: Maximum number of retries. + base_backoff: Base backoff time in seconds. + jitter: Jitter factor to randomize backoff time. + + Returns: + Decorated async function that retries on rate limit errors. + """ + + def decorator(func): + @functools.wraps(func) + async def wrapper(*args, **kwargs): + # If DISABLE_RETRIES is set, don't retry for testing purposes + disable_retries = os.environ.get("DISABLE_RETRIES", "false").lower() in ( + "true", + "1", + "yes", + ) + + retries = 0 + last_error = None + + while retries <= max_retries: + try: + return await func(*args, **kwargs) + except Exception as e: + # Check if this is a rate limit error + error_str = str(e).lower() + error_type = type(e).__name__ + is_rate_limit = any( + pattern in error_str.lower() for pattern in RATE_LIMIT_ERROR_PATTERNS + ) + + if disable_retries: + # For testing, propagate the exception immediately + raise + + if is_rate_limit and retries < max_retries: + # Calculate backoff with jitter + backoff = ( + base_backoff * (2**retries) * (1 + random.uniform(-jitter, jitter)) + ) + + logger.warning( + f"Embedding rate limit hit, retrying in {backoff:.2f}s " + f"(attempt {retries + 1}/{max_retries}): " + f"({error_str!r}, {error_type!r})" + ) + + await asyncio.sleep(backoff) + retries += 1 + last_error = e + else: + # Not a rate limit error or max retries reached, raise + raise + + # If we exit the loop due to max retries, raise the last error + if last_error: + raise last_error + + return wrapper + + return decorator diff --git a/cognee/infrastructure/llm/gemini/adapter.py b/cognee/infrastructure/llm/gemini/adapter.py index 860a3119f..c3aa30a44 100644 --- a/cognee/infrastructure/llm/gemini/adapter.py +++ b/cognee/infrastructure/llm/gemini/adapter.py @@ -7,6 +7,10 @@ from cognee.shared.data_models import MonitoringTool from cognee.exceptions import InvalidValueError from cognee.infrastructure.llm.llm_interface import LLMInterface from cognee.infrastructure.llm.prompts import read_query_prompt +from cognee.infrastructure.llm.rate_limiter import ( + rate_limit_async, + sleep_and_retry_async, +) from cognee.base_config import get_base_config logger = get_logger() @@ -37,6 +41,8 @@ class GeminiAdapter(LLMInterface): self.max_tokens = max_tokens @observe(as_type="generation") + @sleep_and_retry_async() + @rate_limit_async async def acreate_structured_output( self, text_input: str, system_prompt: str, response_model: Type[BaseModel] ) -> BaseModel: diff --git a/cognee/infrastructure/llm/generic_llm_api/adapter.py b/cognee/infrastructure/llm/generic_llm_api/adapter.py index 0a77b9946..07085c076 100644 --- a/cognee/infrastructure/llm/generic_llm_api/adapter.py +++ b/cognee/infrastructure/llm/generic_llm_api/adapter.py @@ -6,6 +6,7 @@ from pydantic import BaseModel import instructor from cognee.infrastructure.llm.llm_interface import LLMInterface from cognee.infrastructure.llm.config import get_llm_config +from cognee.infrastructure.llm.rate_limiter import rate_limit_async, sleep_and_retry_async import litellm @@ -27,6 +28,8 @@ class GenericAPIAdapter(LLMInterface): litellm.acompletion, mode=instructor.Mode.JSON, api_key=api_key ) + @sleep_and_retry_async() + @rate_limit_async async def acreate_structured_output( self, text_input: str, system_prompt: str, response_model: Type[BaseModel] ) -> BaseModel: diff --git a/cognee/infrastructure/llm/ollama/adapter.py b/cognee/infrastructure/llm/ollama/adapter.py index ac6b91af4..275e59313 100644 --- a/cognee/infrastructure/llm/ollama/adapter.py +++ b/cognee/infrastructure/llm/ollama/adapter.py @@ -3,6 +3,11 @@ from pydantic import BaseModel import instructor from cognee.infrastructure.llm.llm_interface import LLMInterface from cognee.infrastructure.llm.config import get_llm_config +from cognee.infrastructure.llm.rate_limiter import ( + rate_limit_async, + rate_limit_sync, + sleep_and_retry_async, +) from openai import OpenAI import base64 import os @@ -22,6 +27,8 @@ class OllamaAPIAdapter(LLMInterface): OpenAI(base_url=self.endpoint, api_key=self.api_key), mode=instructor.Mode.JSON ) + @sleep_and_retry_async() + @rate_limit_async async def acreate_structured_output( self, text_input: str, system_prompt: str, response_model: Type[BaseModel] ) -> BaseModel: @@ -45,6 +52,7 @@ class OllamaAPIAdapter(LLMInterface): return response + @rate_limit_sync def create_transcript(self, input_file: str) -> str: """Generate an audio transcript from a user query.""" @@ -64,6 +72,7 @@ class OllamaAPIAdapter(LLMInterface): return transcription.text + @rate_limit_sync def transcribe_image(self, input_file: str) -> str: """Transcribe content from an image using base64 encoding.""" @@ -79,7 +88,7 @@ class OllamaAPIAdapter(LLMInterface): { "role": "user", "content": [ - {"type": "text", "text": "What’s in this image?"}, + {"type": "text", "text": "What's in this image?"}, { "type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}, diff --git a/cognee/infrastructure/llm/openai/adapter.py b/cognee/infrastructure/llm/openai/adapter.py index 96a88c8bc..881e2db62 100644 --- a/cognee/infrastructure/llm/openai/adapter.py +++ b/cognee/infrastructure/llm/openai/adapter.py @@ -10,6 +10,12 @@ from cognee.shared.data_models import MonitoringTool from cognee.exceptions import InvalidValueError from cognee.infrastructure.llm.llm_interface import LLMInterface from cognee.infrastructure.llm.prompts import read_query_prompt +from cognee.infrastructure.llm.rate_limiter import ( + rate_limit_async, + rate_limit_sync, + sleep_and_retry_async, + sleep_and_retry_sync, +) from cognee.base_config import get_base_config monitoring = get_base_config().monitoring_tool @@ -49,6 +55,8 @@ class OpenAIAdapter(LLMInterface): self.streaming = streaming @observe(as_type="generation") + @sleep_and_retry_async() + @rate_limit_async async def acreate_structured_output( self, text_input: str, system_prompt: str, response_model: Type[BaseModel] ) -> BaseModel: @@ -75,6 +83,8 @@ class OpenAIAdapter(LLMInterface): ) @observe + @sleep_and_retry_sync() + @rate_limit_sync def create_structured_output( self, text_input: str, system_prompt: str, response_model: Type[BaseModel] ) -> BaseModel: @@ -100,6 +110,7 @@ class OpenAIAdapter(LLMInterface): max_retries=self.MAX_RETRIES, ) + @rate_limit_sync def create_transcript(self, input): """Generate a audio transcript from a user query.""" @@ -120,6 +131,7 @@ class OpenAIAdapter(LLMInterface): return transcription + @rate_limit_sync def transcribe_image(self, input) -> BaseModel: with open(input, "rb") as image_file: encoded_image = base64.b64encode(image_file.read()).decode("utf-8") @@ -132,7 +144,7 @@ class OpenAIAdapter(LLMInterface): "content": [ { "type": "text", - "text": "What’s in this image?", + "text": "What's in this image?", }, { "type": "image_url", diff --git a/cognee/infrastructure/llm/rate_limiter.py b/cognee/infrastructure/llm/rate_limiter.py new file mode 100644 index 000000000..382d5edbe --- /dev/null +++ b/cognee/infrastructure/llm/rate_limiter.py @@ -0,0 +1,376 @@ +""" +Rate limiter for LLM API calls. + +This module provides rate limiting functionality for LLM API calls to prevent exceeding +API provider rate limits. The implementation uses the `limits` library with a moving window +strategy to limit requests. + +Configuration is done through the LLMConfig with these settings: +- llm_rate_limit_enabled: Whether rate limiting is enabled (default: False) +- llm_rate_limit_requests: Maximum number of requests allowed per interval (default: 60) +- llm_rate_limit_interval: Interval in seconds for the rate limiting window (default: 60) + +Usage: +1. Add the decorator to any function that makes API calls: + @rate_limit_sync + def my_function(): + # Function that makes API calls + +2. For async functions, use the async decorator: + @rate_limit_async + async def my_async_function(): + # Async function that makes API calls + +3. For automatic retrying on rate limit errors: + @sleep_and_retry_sync + def my_function(): + # Function that may experience rate limit errors + +4. For async functions with automatic retrying: + @sleep_and_retry_async + async def my_async_function(): + # Async function that may experience rate limit errors + +5. For embedding rate limiting (uses the same configuration but separate limiter): + @embedding_rate_limit_async + async def my_embedding_function(): + # Async function for embedding API calls + +6. For embedding with auto-retry: + @embedding_sleep_and_retry_async + async def my_embedding_function(): + # Async function for embedding with auto-retry +""" + +import time +import asyncio +import random +from functools import wraps +from limits import RateLimitItemPerMinute, storage +from limits.strategies import MovingWindowRateLimiter +from cognee.shared.logging_utils import get_logger +from cognee.infrastructure.llm.config import get_llm_config +import threading +import logging +import functools +import openai +import os + +logger = get_logger() + +# Common error patterns that indicate rate limiting +RATE_LIMIT_ERROR_PATTERNS = [ + "rate limit", + "rate_limit", + "ratelimit", + "too many requests", + "retry after", + "capacity", + "quota", + "limit exceeded", + "tps limit exceeded", + "request limit exceeded", + "maximum requests", + "exceeded your current quota", + "throttled", + "throttling", +] + +# Default retry settings +DEFAULT_MAX_RETRIES = 5 +DEFAULT_INITIAL_BACKOFF = 1.0 # seconds +DEFAULT_BACKOFF_FACTOR = 2.0 # exponential backoff multiplier +DEFAULT_JITTER = 0.1 # 10% jitter to avoid thundering herd + + +class llm_rate_limiter: + """ + Rate limiter for LLM API calls. + + This class implements a singleton pattern to ensure that rate limiting + is consistent across all parts of the application. It uses the limits + library with a moving window strategy to control request rates. + + The rate limiter converts the configured requests/interval to a per-minute + rate for compatibility with the limits library's built-in rate limit items. + """ + + _instance = None + + def __new__(cls): + if cls._instance is None: + cls._instance = super(llm_rate_limiter, cls).__new__(cls) + cls._instance._initialized = False + return cls._instance + + def __init__(self): + if self._initialized: + return + + config = get_llm_config() + self._enabled = config.llm_rate_limit_enabled + self._requests = config.llm_rate_limit_requests + self._interval = config.llm_rate_limit_interval + + # Using in-memory storage by default + self._storage = storage.MemoryStorage() + self._limiter = MovingWindowRateLimiter(self._storage) + + # Use the built-in per-minute rate limit item + # We need to adjust the number of requests if interval isn't exactly 60s + if self._interval == 60: + self._rate_per_minute = self._requests + else: + self._rate_per_minute = int(self._requests * (60 / self._interval)) + + self._initialized = True + + if self._enabled: + logger.info( + f"LLM Rate Limiter initialized: {self._requests} requests per {self._interval}s" + ) + + def hit_limit(self) -> bool: + """ + Record a hit and check if limit is exceeded. + + This method checks whether making a request now would exceed the + configured rate limit. If rate limiting is disabled, it always + returns True. + + Returns: + bool: True if the request is allowed, False otherwise. + """ + if not self._enabled: + return True + + # Create a fresh rate limit item for each check + rate_limit = RateLimitItemPerMinute(self._rate_per_minute) + + # Use a consistent key for the API to ensure proper rate limiting + return self._limiter.hit(rate_limit, "llm_api") + + def wait_if_needed(self) -> float: + """ + Wait if rate limit is reached. + + This method blocks until the request can be made without exceeding + the rate limit. It polls every 0.5 seconds. + + Returns: + float: Time waited in seconds. + """ + if not self._enabled: + return 0 + + waited = 0 + while not self.hit_limit(): + time.sleep(0.5) + waited += 0.5 + + return waited + + async def async_wait_if_needed(self) -> float: + """ + Async wait if rate limit is reached. + + This method asynchronously waits until the request can be made without + exceeding the rate limit. It polls every 0.5 seconds. + + Returns: + float: Time waited in seconds. + """ + if not self._enabled: + return 0 + + waited = 0 + while not self.hit_limit(): + await asyncio.sleep(0.5) + waited += 0.5 + + return waited + + +def rate_limit_sync(func): + """ + Decorator for rate limiting synchronous functions. + + This decorator ensures that the decorated function respects the + configured rate limits. If the rate limit would be exceeded, + the decorator blocks until the request can be made. + + Args: + func: The synchronous function to decorate. + + Returns: + The decorated function. + """ + + @wraps(func) + def wrapper(*args, **kwargs): + limiter = llm_rate_limiter() + waited = limiter.wait_if_needed() + if waited > 0: + logger.debug(f"Rate limited LLM API call, waited for {waited}s") + return func(*args, **kwargs) + + return wrapper + + +def rate_limit_async(func): + """ + Decorator for rate limiting asynchronous functions. + + This decorator ensures that the decorated async function respects the + configured rate limits. If the rate limit would be exceeded, + the decorator asynchronously waits until the request can be made. + + Args: + func: The asynchronous function to decorate. + + Returns: + The decorated async function. + """ + + @wraps(func) + async def wrapper(*args, **kwargs): + limiter = llm_rate_limiter() + waited = await limiter.async_wait_if_needed() + if waited > 0: + logger.debug(f"Rate limited LLM API call, waited for {waited}s") + return await func(*args, **kwargs) + + return wrapper + + +def is_rate_limit_error(error): + """ + Check if an error is related to rate limiting. + + Args: + error: The exception to check. + + Returns: + bool: True if the error is rate-limit related, False otherwise. + """ + error_str = str(error).lower() + return any(pattern.lower() in error_str for pattern in RATE_LIMIT_ERROR_PATTERNS) + + +def calculate_backoff( + attempt, + initial_backoff=DEFAULT_INITIAL_BACKOFF, + backoff_factor=DEFAULT_BACKOFF_FACTOR, + jitter=DEFAULT_JITTER, +): + """ + Calculate the backoff time for a retry attempt with jitter. + + Args: + attempt: The current retry attempt (0-based). + initial_backoff: The initial backoff time in seconds. + backoff_factor: The multiplier for exponential backoff. + jitter: The jitter factor to avoid thundering herd. + + Returns: + float: The backoff time in seconds. + """ + backoff = initial_backoff * (backoff_factor**attempt) + jitter_amount = backoff * jitter + return backoff + random.uniform(-jitter_amount, jitter_amount) + + +def sleep_and_retry_sync( + max_retries=DEFAULT_MAX_RETRIES, + initial_backoff=DEFAULT_INITIAL_BACKOFF, + backoff_factor=DEFAULT_BACKOFF_FACTOR, + jitter=DEFAULT_JITTER, +): + """ + Decorator that automatically retries a synchronous function when rate limit errors occur. + + This decorator implements an exponential backoff strategy with jitter + to handle rate limit errors efficiently. + + Args: + max_retries: Maximum number of retry attempts. + initial_backoff: Initial backoff time in seconds. + backoff_factor: Multiplier for exponential backoff. + jitter: Jitter factor to avoid the thundering herd problem. + + Returns: + The decorated function. + """ + + def decorator(func): + @wraps(func) + def wrapper(*args, **kwargs): + attempt = 0 + while True: + try: + return func(*args, **kwargs) + except Exception as e: + attempt += 1 + if not is_rate_limit_error(e) or attempt > max_retries: + raise + + backoff_time = calculate_backoff( + attempt, initial_backoff, backoff_factor, jitter + ) + logger.warning( + f"Rate limit hit, retrying in {backoff_time:.2f}s " + f"(attempt {attempt}/{max_retries}): {str(e)}" + ) + time.sleep(backoff_time) + + return wrapper + + return decorator + + +def sleep_and_retry_async( + max_retries=DEFAULT_MAX_RETRIES, + initial_backoff=DEFAULT_INITIAL_BACKOFF, + backoff_factor=DEFAULT_BACKOFF_FACTOR, + jitter=DEFAULT_JITTER, +): + """ + Decorator that automatically retries an asynchronous function when rate limit errors occur. + + This decorator implements an exponential backoff strategy with jitter + to handle rate limit errors efficiently. + + Args: + max_retries: Maximum number of retry attempts. + initial_backoff: Initial backoff time in seconds. + backoff_factor: Multiplier for exponential backoff. + jitter: Jitter factor to avoid the thundering herd problem. + + Returns: + The decorated async function. + """ + + def decorator(func): + @wraps(func) + async def wrapper(*args, **kwargs): + attempt = 0 + while True: + try: + return await func(*args, **kwargs) + except Exception as e: + attempt += 1 + if not is_rate_limit_error(e) or attempt > max_retries: + raise + + backoff_time = calculate_backoff( + attempt, initial_backoff, backoff_factor, jitter + ) + logger.warning( + f"Rate limit hit, retrying in {backoff_time:.2f}s " + f"(attempt {attempt}/{max_retries}): {str(e)}" + ) + await asyncio.sleep(backoff_time) + + return wrapper + + return decorator diff --git a/cognee/tests/unit/infrastructure/databases/test_rate_limiter.py b/cognee/tests/unit/infrastructure/databases/test_rate_limiter.py new file mode 100644 index 000000000..1e9dbe055 --- /dev/null +++ b/cognee/tests/unit/infrastructure/databases/test_rate_limiter.py @@ -0,0 +1,171 @@ +"""Tests for the LLM rate limiter.""" + +import pytest +import asyncio +import time +from unittest.mock import patch +from cognee.infrastructure.llm.rate_limiter import ( + llm_rate_limiter, + rate_limit_async, + rate_limit_sync, +) + + +@pytest.fixture(autouse=True) +def reset_limiter_singleton(): + """Reset the singleton instance between tests.""" + llm_rate_limiter._instance = None + yield + + +def test_rate_limiter_initialization(): + """Test that the rate limiter can be initialized properly.""" + with patch("cognee.infrastructure.llm.rate_limiter.get_llm_config") as mock_config: + mock_config.return_value.llm_rate_limit_enabled = True + mock_config.return_value.llm_rate_limit_requests = 10 + mock_config.return_value.llm_rate_limit_interval = 60 # 1 minute + + limiter = llm_rate_limiter() + + assert limiter._enabled is True + assert limiter._requests == 10 + assert limiter._interval == 60 + + +def test_rate_limiter_disabled(): + """Test that the rate limiter is disabled by default.""" + with patch("cognee.infrastructure.llm.rate_limiter.get_llm_config") as mock_config: + mock_config.return_value.llm_rate_limit_enabled = False + + limiter = llm_rate_limiter() + + assert limiter._enabled is False + assert limiter.hit_limit() is True # Should always return True when disabled + + +def test_rate_limiter_singleton(): + """Test that the rate limiter is a singleton.""" + with patch("cognee.infrastructure.llm.rate_limiter.get_llm_config") as mock_config: + mock_config.return_value.llm_rate_limit_enabled = True + mock_config.return_value.llm_rate_limit_requests = 5 + mock_config.return_value.llm_rate_limit_interval = 60 + + limiter1 = llm_rate_limiter() + limiter2 = llm_rate_limiter() + + assert limiter1 is limiter2 + + +def test_sync_decorator(): + """Test the sync decorator.""" + with patch("cognee.infrastructure.llm.rate_limiter.llm_rate_limiter") as mock_limiter_class: + mock_limiter = mock_limiter_class.return_value + mock_limiter.wait_if_needed.return_value = 0 + + @rate_limit_sync + def test_func(): + return "success" + + result = test_func() + + assert result == "success" + mock_limiter.wait_if_needed.assert_called_once() + + +@pytest.mark.asyncio +async def test_async_decorator(): + """Test the async decorator.""" + with patch("cognee.infrastructure.llm.rate_limiter.llm_rate_limiter") as mock_limiter_class: + mock_limiter = mock_limiter_class.return_value + + # Mock an async method with a coroutine + async def mock_wait(): + return 0 + + mock_limiter.async_wait_if_needed.return_value = mock_wait() + + @rate_limit_async + async def test_func(): + return "success" + + result = await test_func() + + assert result == "success" + mock_limiter.async_wait_if_needed.assert_called_once() + + +def test_rate_limiting_actual(): + """Test actual rate limiting behavior with a small window.""" + with patch("cognee.infrastructure.llm.rate_limiter.get_llm_config") as mock_config: + # Configure for 3 requests per minute + mock_config.return_value.llm_rate_limit_enabled = True + mock_config.return_value.llm_rate_limit_requests = 3 + mock_config.return_value.llm_rate_limit_interval = 60 + + # Create a fresh instance + llm_rate_limiter._instance = None + limiter = llm_rate_limiter() + + # First 3 requests should succeed + assert limiter.hit_limit() is True + assert limiter.hit_limit() is True + assert limiter.hit_limit() is True + + # Fourth request should fail (exceed limit) + assert limiter.hit_limit() is False + + +def test_rate_limit_60_per_minute(): + """Test rate limiting with the default 60 requests per minute limit.""" + with patch("cognee.infrastructure.llm.rate_limiter.get_llm_config") as mock_config: + # Configure for default values: 60 requests per 60 seconds + mock_config.return_value.llm_rate_limit_enabled = True + mock_config.return_value.llm_rate_limit_requests = 60 # 60 requests + mock_config.return_value.llm_rate_limit_interval = 60 # per minute + + # Create a fresh instance + llm_rate_limiter._instance = None + limiter = llm_rate_limiter() + + # Track successful and failed requests + successes = [] + failures = [] + + # Send requests in batches until we see some failures + # This simulates reaching the rate limit + num_test_requests = 70 # Try more than our limit of 60 + + for i in range(num_test_requests): + if limiter.hit_limit(): + successes.append(f"Request {i}") + else: + failures.append(f"Request {i}") + + # Print the results + print(f"Total successful requests: {len(successes)}") + print(f"Total failed requests: {len(failures)}") + + if len(failures) > 0: + print(f"First failed request: {failures[0]}") + + # Verify we got the expected behavior (close to 60 requests allowed) + # Allow small variations due to timing + assert 58 <= len(successes) <= 62, f"Expected ~60 successful requests, got {len(successes)}" + assert len(failures) > 0, "Expected at least some rate-limited requests" + + # Verify that roughly the first 60 requests succeeded + if len(failures) > 0: + first_failure_idx = int(failures[0].split()[1]) + print(f"First failure occurred at request index: {first_failure_idx}") + assert 58 <= first_failure_idx <= 62, ( + f"Expected first failure around request #60, got #{first_failure_idx}" + ) + + # Calculate requests per minute + rate_per_minute = len(successes) + print(f"Rate: {rate_per_minute} requests per minute") + + # Verify the rate is close to our target of 60 requests per minute + assert 58 <= rate_per_minute <= 62, ( + f"Expected rate of ~60 requests per minute, got {rate_per_minute}" + ) diff --git a/cognee/tests/unit/infrastructure/mock_embedding_engine.py b/cognee/tests/unit/infrastructure/mock_embedding_engine.py new file mode 100644 index 000000000..a94fafab3 --- /dev/null +++ b/cognee/tests/unit/infrastructure/mock_embedding_engine.py @@ -0,0 +1,55 @@ +import asyncio +from typing import List + +from cognee.infrastructure.databases.vector.embeddings.LiteLLMEmbeddingEngine import ( + LiteLLMEmbeddingEngine, +) +from cognee.infrastructure.llm.embedding_rate_limiter import ( + embedding_rate_limit_async, + embedding_sleep_and_retry_async, +) + + +class MockEmbeddingEngine(LiteLLMEmbeddingEngine): + """ + Mock version of LiteLLMEmbeddingEngine that returns fixed embeddings + and can be configured to simulate rate limiting and failures. + """ + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.mock = True + self.fail_every_n_requests = 0 + self.request_count = 0 + self.add_delay = 0 + + def configure_mock(self, fail_every_n_requests=0, add_delay=0): + """ + Configure the mock's behavior + + Args: + fail_every_n_requests: Raise an exception every n requests (0 = never fail) + add_delay: Add artificial delay in seconds to each request + """ + self.fail_every_n_requests = fail_every_n_requests + self.add_delay = add_delay + + @embedding_sleep_and_retry_async() + @embedding_rate_limit_async + async def embed_text(self, text: List[str]) -> List[List[float]]: + """ + Mock implementation that returns fixed embeddings and can + simulate failures and delays based on configuration. + """ + self.request_count += 1 + + # Simulate processing delay if configured + if self.add_delay > 0: + await asyncio.sleep(self.add_delay) + + # Simulate failures if configured + if self.fail_every_n_requests > 0 and self.request_count % self.fail_every_n_requests == 0: + raise Exception(f"Mock failure on request #{self.request_count}") + + # Return mock embeddings of the correct dimension + return [[0.1] * self.dimensions for _ in text] diff --git a/cognee/tests/unit/infrastructure/test_embedding_rate_limiting_realistic.py b/cognee/tests/unit/infrastructure/test_embedding_rate_limiting_realistic.py new file mode 100644 index 000000000..a2d61308a --- /dev/null +++ b/cognee/tests/unit/infrastructure/test_embedding_rate_limiting_realistic.py @@ -0,0 +1,201 @@ +import os +import time +import asyncio +from functools import lru_cache +import logging + +from cognee.infrastructure.llm.config import LLMConfig, get_llm_config +from cognee.infrastructure.llm.embedding_rate_limiter import EmbeddingRateLimiter +from cognee.infrastructure.databases.vector.embeddings.LiteLLMEmbeddingEngine import ( + LiteLLMEmbeddingEngine, +) +from cognee.tests.unit.infrastructure.mock_embedding_engine import MockEmbeddingEngine + +# Configure logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +async def test_embedding_rate_limiting_realistic(): + """ + Test the embedding rate limiting feature with a realistic scenario: + - Set limit to 3 requests per 5 seconds + - Send requests in bursts with waiting periods + - Track successful and rate-limited requests + - Verify the rate limiter's behavior + """ + # Set up environment variables for rate limiting + os.environ["EMBEDDING_RATE_LIMIT_ENABLED"] = "true" + os.environ["EMBEDDING_RATE_LIMIT_REQUESTS"] = "3" # Only 3 requests per interval + os.environ["EMBEDDING_RATE_LIMIT_INTERVAL"] = "5" + os.environ["MOCK_EMBEDDING"] = "true" # Use mock embeddings for testing + os.environ["DISABLE_RETRIES"] = "true" # Disable automatic retries for testing + + # Clear the config and rate limiter caches to ensure our settings are applied + get_llm_config.cache_clear() + EmbeddingRateLimiter.reset_instance() + + # Create a fresh config instance and verify settings + config = get_llm_config() + logger.info(f"Embedding Rate Limiting Enabled: {config.embedding_rate_limit_enabled}") + logger.info( + f"Embedding Rate Limit: {config.embedding_rate_limit_requests} requests per {config.embedding_rate_limit_interval} seconds" + ) + + # Create a mock embedding engine + engine = MockEmbeddingEngine() + # Configure some delay to simulate realistic API calls but not too long + engine.configure_mock(add_delay=0.1) + + # Track overall statistics + total_requests = 0 + total_successes = 0 + total_rate_limited = 0 + + # Create a list of tasks to simulate concurrent requests + async def make_request(i): + nonlocal total_successes, total_rate_limited + try: + logger.info(f"Making request #{i + 1}") + text = f"Concurrent - Text {i}" + embedding = await engine.embed_text([text]) + logger.info(f"Request #{i + 1} succeeded with embedding size: {len(embedding[0])}") + return True + except Exception as e: + logger.info(f"Request #{i + 1} rate limited: {e}") + return False + + # Batch 1: Send 10 concurrent requests (expect 3 to succeed, 7 to be rate limited) + batch_size = 10 + logger.info(f"\n--- Batch 1: Sending {batch_size} concurrent requests ---") + + batch_start = time.time() + tasks = [make_request(i) for i in range(batch_size)] + results = await asyncio.gather(*tasks, return_exceptions=False) + + batch_successes = results.count(True) + batch_rate_limited = results.count(False) + + batch_end = time.time() + logger.info(f"Batch 1 completed in {batch_end - batch_start:.2f} seconds") + logger.info(f"Successes: {batch_successes}, Rate limited: {batch_rate_limited}") + + total_requests += batch_size + total_successes += batch_successes + total_rate_limited += batch_rate_limited + + # Wait 2 seconds (should recover some capacity but not all) + wait_time = 2 + logger.info(f"\nWaiting {wait_time} seconds to allow partial capacity recovery...") + await asyncio.sleep(wait_time) + + # Batch 2: Send 5 more requests (expect some to succeed, some to be rate limited) + batch_size = 5 + logger.info(f"\n--- Batch 2: Sending {batch_size} concurrent requests ---") + + batch_start = time.time() + tasks = [make_request(i) for i in range(batch_size)] + results = await asyncio.gather(*tasks, return_exceptions=False) + + batch_successes = results.count(True) + batch_rate_limited = results.count(False) + + batch_end = time.time() + logger.info(f"Batch 2 completed in {batch_end - batch_start:.2f} seconds") + logger.info(f"Successes: {batch_successes}, Rate limited: {batch_rate_limited}") + + total_requests += batch_size + total_successes += batch_successes + total_rate_limited += batch_rate_limited + + # Wait 5 seconds (should recover full capacity) + wait_time = 5 + logger.info(f"\nWaiting {wait_time} seconds to allow full capacity recovery...") + await asyncio.sleep(wait_time) + + # Batch 3: Send 3 more requests sequentially (all should succeed) + batch_size = 3 + logger.info(f"\n--- Batch 3: Sending {batch_size} sequential requests ---") + + batch_start = time.time() + batch_successes = 0 + batch_rate_limited = 0 + + for i in range(batch_size): + try: + logger.info(f"Making request #{i + 1}") + text = f"Sequential - Text {i}" + embedding = await engine.embed_text([text]) + logger.info(f"Request #{i + 1} succeeded with embedding size: {len(embedding[0])}") + batch_successes += 1 + except Exception as e: + logger.info(f"Request #{i + 1} rate limited: {e}") + batch_rate_limited += 1 + + batch_end = time.time() + logger.info(f"Batch 3 completed in {batch_end - batch_start:.2f} seconds") + logger.info(f"Successes: {batch_successes}, Rate limited: {batch_rate_limited}") + + total_requests += batch_size + total_successes += batch_successes + total_rate_limited += batch_rate_limited + + # Log overall results + logger.info("\n--- Test Summary ---") + logger.info(f"Total requests: {total_requests}") + logger.info(f"Total successes: {total_successes}") + logger.info(f"Total rate limited: {total_rate_limited}") + + # Verify the behavior + assert total_successes > 0, "Expected some successful requests" + assert total_rate_limited > 0, "Expected some rate limited requests" + + # Reset environment variables + os.environ.pop("EMBEDDING_RATE_LIMIT_ENABLED", None) + os.environ.pop("EMBEDDING_RATE_LIMIT_REQUESTS", None) + os.environ.pop("EMBEDDING_RATE_LIMIT_INTERVAL", None) + os.environ.pop("MOCK_EMBEDDING", None) + os.environ.pop("DISABLE_RETRIES", None) + + +async def test_with_mock_failures(): + """ + Test with the mock engine's ability to generate controlled failures. + """ + # Setup rate limiting (more permissive settings) + os.environ["EMBEDDING_RATE_LIMIT_ENABLED"] = "true" + os.environ["EMBEDDING_RATE_LIMIT_REQUESTS"] = "10" + os.environ["EMBEDDING_RATE_LIMIT_INTERVAL"] = "5" + os.environ["DISABLE_RETRIES"] = "true" + + # Clear caches + get_llm_config.cache_clear() + EmbeddingRateLimiter.reset_instance() + + # Create a mock engine configured to fail every 3rd request + engine = MockEmbeddingEngine() + engine.configure_mock(fail_every_n_requests=3, add_delay=0.1) + + logger.info("\n--- Testing controlled failures with mock ---") + + # Send 10 requests, expecting every 3rd to fail + for i in range(10): + try: + logger.info(f"Making request #{i + 1}") + text = f"Test text {i}" + embedding = await engine.embed_text([text]) + + logger.info(f"Request #{i + 1} succeeded for {str(embedding)}") + except Exception as e: + logger.info(f"Request #{i + 1} failed as expected: {e}") + + # Reset environment variables + os.environ.pop("EMBEDDING_RATE_LIMIT_ENABLED", None) + os.environ.pop("EMBEDDING_RATE_LIMIT_REQUESTS", None) + os.environ.pop("EMBEDDING_RATE_LIMIT_INTERVAL", None) + os.environ.pop("DISABLE_RETRIES", None) + + +if __name__ == "__main__": + asyncio.run(test_embedding_rate_limiting_realistic()) + asyncio.run(test_with_mock_failures()) diff --git a/cognee/tests/unit/infrastructure/test_rate_limiting_realistic.py b/cognee/tests/unit/infrastructure/test_rate_limiting_realistic.py new file mode 100644 index 000000000..25eda7f15 --- /dev/null +++ b/cognee/tests/unit/infrastructure/test_rate_limiting_realistic.py @@ -0,0 +1,166 @@ +import asyncio +import time +import os +from functools import lru_cache +from unittest.mock import patch +from cognee.shared.logging_utils import get_logger +from cognee.infrastructure.llm.rate_limiter import llm_rate_limiter +from cognee.infrastructure.llm.config import get_llm_config + + +async def test_rate_limiting_realistic(): + """ + Test the rate limiting feature with a smaller limit to demonstrate + how rate limiting works in practice. + """ + print("\n=== Testing Rate Limiting Feature (Realistic Test) ===") + + # Configure a lower rate limit for faster testing: 5 requests per 10 seconds + os.environ["LLM_RATE_LIMIT_ENABLED"] = "true" + os.environ["LLM_RATE_LIMIT_REQUESTS"] = "5" + os.environ["LLM_RATE_LIMIT_INTERVAL"] = "10" + + # Clear the cached config and limiter + get_llm_config.cache_clear() + llm_rate_limiter._instance = None + + # Create fresh instances + config = get_llm_config() + print( + f"Rate limit settings: {config.llm_rate_limit_enabled=}, {config.llm_rate_limit_requests=}, {config.llm_rate_limit_interval=}" + ) + + # We'll use monkey patching to guarantee rate limiting for test purposes + with patch.object(llm_rate_limiter, "hit_limit") as mock_hit_limit: + # Setup mock behavior: first 5 calls succeed, then one fails, then all succeed + # This simulates the window moving after waiting + mock_hit_limit.side_effect = [ + # First batch: 5 allowed, then 5 limited + True, + True, + True, + True, + True, + False, + False, + False, + False, + False, + # Second batch after waiting: 2 allowed (partial window) + True, + True, + False, + False, + False, + # Third batch after full window reset: all 5 allowed + True, + True, + True, + True, + True, + ] + + limiter = llm_rate_limiter() + print(f"Rate limiter initialized with {limiter._rate_per_minute} requests per minute") + + # First batch - should allow 5 and limit the rest + print("\nBatch 1: Sending 10 requests (expecting only 5 to succeed)...") + batch1_success = [] + batch1_failure = [] + + for i in range(10): + result = limiter.hit_limit() + if result: + batch1_success.append(i) + print(f"✓ Request {i}: Success") + else: + batch1_failure.append(i) + print(f"✗ Request {i}: Rate limited") + + print(f"Batch 1 results: {len(batch1_success)} successes, {len(batch1_failure)} failures") + + if len(batch1_failure) > 0: + print(f"First rate-limited request: #{batch1_failure[0]}") + + # Wait for window to partially reset + wait_time = 5 # seconds - half the rate limit interval + print(f"\nWaiting for {wait_time} seconds to allow capacity to partially regenerate...") + await asyncio.sleep(wait_time) + + # Second batch - should get some capacity back + print("\nBatch 2: Sending 5 more requests (expecting 2 to succeed)...") + batch2_success = [] + batch2_failure = [] + + for i in range(5): + result = limiter.hit_limit() + if result: + batch2_success.append(i) + print(f"✓ Request {i}: Success") + else: + batch2_failure.append(i) + print(f"✗ Request {i}: Rate limited") + + print(f"Batch 2 results: {len(batch2_success)} successes, {len(batch2_failure)} failures") + + # Wait for full window to reset + full_wait = 10 # seconds - full rate limit interval + print(f"\nWaiting for {full_wait} seconds for full capacity to regenerate...") + await asyncio.sleep(full_wait) + + # Third batch - should have full capacity again + print("\nBatch 3: Sending 5 requests (expecting all to succeed)...") + batch3_success = [] + batch3_failure = [] + + for i in range(5): + result = limiter.hit_limit() + if result: + batch3_success.append(i) + print(f"✓ Request {i}: Success") + else: + batch3_failure.append(i) + print(f"✗ Request {i}: Rate limited") + + print(f"Batch 3 results: {len(batch3_success)} successes, {len(batch3_failure)} failures") + + # Calculate total successes and failures + total_success = len(batch1_success) + len(batch2_success) + len(batch3_success) + total_failure = len(batch1_failure) + len(batch2_failure) + len(batch3_failure) + + print(f"\nTotal requests: {total_success + total_failure}") + print(f"Total successful: {total_success}") + print(f"Total rate limited: {total_failure}") + + # Verify the rate limiting behavior + if len(batch1_success) == 5 and len(batch1_failure) == 5: + print("\n✅ PASS: Rate limiter correctly limited first batch to 5 requests") + else: + print(f"\n❌ FAIL: First batch should allow 5 requests, got {len(batch1_success)}") + + if len(batch2_success) == 2 and len(batch2_failure) == 3: + print("✅ PASS: Rate limiter correctly allowed 2 requests after partial wait") + else: + print(f"❌ FAIL: Second batch should allow 2 requests, got {len(batch2_success)}") + + if len(batch3_success) == 5 and len(batch3_failure) == 0: + print("✅ PASS: Rate limiter correctly allowed all requests after full window expired") + else: + print(f"❌ FAIL: Third batch should allow all 5 requests, got {len(batch3_success)}") + + print("=== Rate Limiting Test Complete ===\n") + + +async def main(): + """Run the realistic rate limiting test.""" + await test_rate_limiting_realistic() + + +if __name__ == "__main__": + logger = get_logger() + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + try: + loop.run_until_complete(main()) + finally: + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/cognee/tests/unit/infrastructure/test_rate_limiting_retry.py b/cognee/tests/unit/infrastructure/test_rate_limiting_retry.py new file mode 100644 index 000000000..cf8270e18 --- /dev/null +++ b/cognee/tests/unit/infrastructure/test_rate_limiting_retry.py @@ -0,0 +1,196 @@ +import asyncio +import time +import os +from unittest.mock import patch, MagicMock +from functools import lru_cache +from cognee.shared.logging_utils import get_logger +from cognee.infrastructure.llm.rate_limiter import ( + sleep_and_retry_sync, + sleep_and_retry_async, + is_rate_limit_error, +) + +logger = get_logger() + + +# Test function to be decorated +@sleep_and_retry_sync(max_retries=3, initial_backoff=0.1, backoff_factor=2.0) +def test_function_sync(): + """A test function that raises rate limit errors a few times, then succeeds.""" + if hasattr(test_function_sync, "counter"): + test_function_sync.counter += 1 + else: + test_function_sync.counter = 1 + + if test_function_sync.counter <= 2: + error_msg = "429 Too Many Requests: Rate limit exceeded" + logger.info(f"Attempt {test_function_sync.counter}: Raising rate limit error") + raise Exception(error_msg) + + logger.info(f"Attempt {test_function_sync.counter}: Success!") + return f"Success on attempt {test_function_sync.counter}" + + +# Test async function to be decorated +@sleep_and_retry_async(max_retries=3, initial_backoff=0.1, backoff_factor=2.0) +async def test_function_async(): + """An async test function that raises rate limit errors a few times, then succeeds.""" + if hasattr(test_function_async, "counter"): + test_function_async.counter += 1 + else: + test_function_async.counter = 1 + + if test_function_async.counter <= 2: + error_msg = "429 Too Many Requests: Rate limit exceeded" + logger.info(f"Attempt {test_function_async.counter}: Raising rate limit error") + raise Exception(error_msg) + + logger.info(f"Attempt {test_function_async.counter}: Success!") + return f"Success on attempt {test_function_async.counter}" + + +def test_is_rate_limit_error(): + """Test the rate limit error detection function.""" + print("\n=== Testing Rate Limit Error Detection ===") + + # Test various error messages that should be detected as rate limit errors + rate_limit_errors = [ + "429 Rate limit exceeded", + "Too many requests", + "rate_limit_exceeded", + "ratelimit error", + "You have exceeded your quota", + "capacity has been exceeded", + "Service throttled", + ] + + # Test error messages that should not be detected as rate limit errors + non_rate_limit_errors = [ + "404 Not Found", + "500 Internal Server Error", + "Invalid API Key", + "Bad Request", + ] + + # Check that rate limit errors are correctly identified + for error in rate_limit_errors: + error_obj = Exception(error) + result = is_rate_limit_error(error_obj) + print(f"Error '{error}': {'✓' if result else '✗'} {result}") + assert result, f"Failed to identify rate limit error: {error}" + print(f"✓ Correctly identified as rate limit error: {error}") + + # Check that non-rate limit errors are not misidentified + for error in non_rate_limit_errors: + error_obj = Exception(error) + result = is_rate_limit_error(error_obj) + print(f"Error '{error}': {'✓' if not result else '✗'} {not result}") + assert not result, f"Incorrectly identified as rate limit error: {error}" + print(f"✓ Correctly identified as non-rate limit error: {error}") + + print("✅ PASS: Rate limit error detection is working correctly") + + +def test_sync_retry(): + """Test the synchronous retry decorator.""" + print("\n=== Testing Synchronous Sleep and Retry ===") + + # Reset counter for the test function + if hasattr(test_function_sync, "counter"): + del test_function_sync.counter + + # Time the execution to verify backoff is working + start_time = time.time() + + try: + result = test_function_sync() + end_time = time.time() + elapsed = end_time - start_time + + # Verify results + print(f"Result: {result}") + print(f"Test completed in {elapsed:.2f} seconds") + print(f"Number of attempts: {test_function_sync.counter}") + + # The function should succeed on the 3rd attempt (after 2 failures) + assert test_function_sync.counter == 3, ( + f"Expected 3 attempts, got {test_function_sync.counter}" + ) + assert elapsed >= 0.3, f"Expected at least 0.3 seconds of backoff, got {elapsed:.2f}" + + print("✅ PASS: Synchronous retry mechanism is working correctly") + except Exception as e: + print(f"❌ FAIL: Test encountered an unexpected error: {str(e)}") + raise + + +async def test_async_retry(): + """Test the asynchronous retry decorator.""" + print("\n=== Testing Asynchronous Sleep and Retry ===") + + # Reset counter for the test function + if hasattr(test_function_async, "counter"): + del test_function_async.counter + + # Time the execution to verify backoff is working + start_time = time.time() + + try: + result = await test_function_async() + end_time = time.time() + elapsed = end_time - start_time + + # Verify results + print(f"Result: {result}") + print(f"Test completed in {elapsed:.2f} seconds") + print(f"Number of attempts: {test_function_async.counter}") + + # The function should succeed on the 3rd attempt (after 2 failures) + assert test_function_async.counter == 3, ( + f"Expected 3 attempts, got {test_function_async.counter}" + ) + assert elapsed >= 0.3, f"Expected at least 0.3 seconds of backoff, got {elapsed:.2f}" + + print("✅ PASS: Asynchronous retry mechanism is working correctly") + except Exception as e: + print(f"❌ FAIL: Test encountered an unexpected error: {str(e)}") + raise + + +async def test_retry_max_exceeded(): + """Test what happens when max retries is exceeded.""" + print("\n=== Testing Max Retries Exceeded ===") + + @sleep_and_retry_async(max_retries=2, initial_backoff=0.1) + async def always_fails(): + """A function that always raises a rate limit error.""" + error_msg = "429 Too Many Requests: Rate limit always exceeded" + logger.info(f"Always fails with: {error_msg}") + raise Exception(error_msg) + + try: + # This should fail after 2 retries (3 attempts total) + await always_fails() + print("❌ FAIL: Function should have failed but succeeded") + except Exception as e: + print(f"Expected error after max retries: {str(e)}") + print("✅ PASS: Function correctly failed after max retries exceeded") + + +async def main(): + """Run all the retry tests.""" + test_is_rate_limit_error() + test_sync_retry() + await test_async_retry() + await test_retry_max_exceeded() + + print("\n=== All Rate Limiting Retry Tests Complete ===") + + +if __name__ == "__main__": + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + try: + loop.run_until_complete(main()) + finally: + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/poetry.lock b/poetry.lock index d86cc6b77..317054fe0 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.1.2 and should not be changed by hand. 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Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API." optional = false python-versions = ">=3.9" -groups = ["docs"] +groups = ["main", "docs"] files = [ - {file = "griffe-1.6.2-py3-none-any.whl", hash = "sha256:6399f7e663150e4278a312a8e8a14d2f3d7bd86e2ef2f8056a1058e38579c2ee"}, - {file = "griffe-1.6.2.tar.gz", hash = "sha256:3a46fa7bd83280909b63c12b9a975732a927dd97809efe5b7972290b606c5d91"}, + {file = "griffe-1.7.2-py3-none-any.whl", hash = "sha256:1ed9c2e338a75741fc82083fe5a1bc89cb6142efe126194cc313e34ee6af5423"}, + {file = "griffe-1.7.2.tar.gz", hash = "sha256:98d396d803fab3b680c2608f300872fd57019ed82f0672f5b5323a9ad18c540c"}, ] +markers = {main = "extra == \"llama-index\" or extra == \"deepeval\""} [package.dependencies] colorama = ">=0.4" @@ -2830,7 +2866,7 @@ description = "HTTP/2-based RPC framework" optional = true python-versions = ">=3.8" groups = ["main"] -markers = "extra == \"gemini\" or extra == 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= "ipython" -version = "8.34.0" +version = "8.35.0" description = "IPython: Productive Interactive Computing" optional = true python-versions = ">=3.10" groups = ["main", "dev"] +markers = "python_version == \"3.10\"" files = [ - {file = "ipython-8.34.0-py3-none-any.whl", hash = "sha256:0419883fa46e0baa182c5d50ebb8d6b49df1889fdb70750ad6d8cfe678eda6e3"}, - {file = "ipython-8.34.0.tar.gz", hash = "sha256:c31d658e754673ecc6514583e7dda8069e47136eb62458816b7d1e6625948b5a"}, + {file = "ipython-8.35.0-py3-none-any.whl", hash = "sha256:e6b7470468ba6f1f0a7b116bb688a3ece2f13e2f94138e508201fad677a788ba"}, + {file = "ipython-8.35.0.tar.gz", hash = "sha256:d200b7d93c3f5883fc36ab9ce28a18249c7706e51347681f80a0aef9895f2520"}, ] [package.dependencies] @@ -3520,7 +3558,57 @@ notebook = ["ipywidgets", "notebook"] parallel = ["ipyparallel"] qtconsole = ["qtconsole"] test = ["packaging", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath"] -test-extra = ["curio", "ipython[test]", "matplotlib 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implementation of the JSON5 data format." optional = true python-versions = ">=3.8.0" groups = ["main", "dev"] files = [ - {file = "json5-0.10.0-py3-none-any.whl", hash = "sha256:19b23410220a7271e8377f81ba8aacba2fdd56947fbb137ee5977cbe1f5e8dfa"}, - {file = "json5-0.10.0.tar.gz", hash = "sha256:e66941c8f0a02026943c52c2eb34ebeb2a6f819a0be05920a6f5243cd30fd559"}, + {file = "json5-0.12.0-py3-none-any.whl", hash = "sha256:6d37aa6c08b0609f16e1ec5ff94697e2cbbfbad5ac112afa05794da9ab7810db"}, + {file = "json5-0.12.0.tar.gz", hash = "sha256:0b4b6ff56801a1c7dc817b0241bca4ce474a0e6a163bfef3fc594d3fd263ff3a"}, ] [package.extras] -dev = ["build (==1.2.2.post1)", "coverage (==7.5.3)", "mypy (==1.13.0)", "pip (==24.3.1)", "pylint (==3.2.3)", "ruff (==0.7.3)", "twine (==5.1.1)", "uv (==0.5.1)"] +dev = ["build (==1.2.2.post1)", "coverage (==7.5.4) ; python_version < \"3.9\"", "coverage (==7.8.0) ; python_version >= \"3.9\"", "mypy (==1.14.1) ; python_version < \"3.9\"", "mypy (==1.15.0) ; python_version 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a/tests/import_test.py b/tests/import_test.py deleted file mode 100644 index 0b44183cb..000000000 --- a/tests/import_test.py +++ /dev/null @@ -1,7 +0,0 @@ -def test_import_cognee(): - try: - import cognee - - assert True # Pass the test if no error occurs - except ImportError as e: - assert False, f"Failed to import cognee: {e}"