cognee/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py
2024-12-18 14:39:54 +01:00

103 lines
3.2 KiB
Python

import asyncio
import logging
import math
from typing import List, Optional
import litellm
import os
from cognee.infrastructure.databases.vector.embeddings.EmbeddingEngine import EmbeddingEngine
litellm.set_verbose = False
logger = logging.getLogger("LiteLLMEmbeddingEngine")
class LiteLLMEmbeddingEngine(EmbeddingEngine):
api_key: str
endpoint: str
api_version: str
model: str
dimensions: int
mock:bool
def __init__(
self,
model: Optional[str] = "text-embedding-3-large",
dimensions: Optional[int] = 3072,
api_key: str = None,
endpoint: str = None,
api_version: str = None,
):
self.api_key = api_key
self.endpoint = endpoint
self.api_version = api_version
self.model = model
self.dimensions = dimensions
enable_mocking = os.getenv("MOCK_EMBEDDING", "false")
if isinstance(enable_mocking, bool):
enable_mocking= str(enable_mocking).lower()
self.mock = enable_mocking in ("true", "1", "yes")
MAX_RETRIES = 5
retry_count = 0
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(
self.model,
input = text,
api_key = self.api_key,
api_base = self.endpoint,
api_version = self.api_version
)
self.retry_count = 0
return [data["embedding"] for data in response.data]
except litellm.exceptions.ContextWindowExceededError as error:
if isinstance(text, list):
if len(text) == 1:
parts = [text]
else:
parts = [text[0:math.ceil(len(text)/2)], text[math.ceil(len(text)/2):]]
parts_futures = [self.embed_text(part) for part in parts]
embeddings = await asyncio.gather(*parts_futures)
all_embeddings = []
for embeddings_part in embeddings:
all_embeddings.extend(embeddings_part)
return all_embeddings
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(f"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 Exception as error:
logger.error("Error embedding text: %s", str(error))
raise error
def get_vector_size(self) -> int:
return self.dimensions