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import asyncio
import logging
import random
import time
from abc import abstractmethod
from concurrent.futures import ThreadPoolExecutor
from typing import Any, AsyncGenerator, Generator, Optional
from litellm import AuthenticationError
from core.base.abstractions import (
GenerationConfig,
LLMChatCompletion,
LLMChatCompletionChunk,
)
from .base import Provider, ProviderConfig
logger = logging.getLogger()
class CompletionConfig(ProviderConfig):
provider: Optional[str] = None
generation_config: Optional[GenerationConfig] = None
concurrent_request_limit: int = 256
max_retries: int = 3
initial_backoff: float = 1.0
max_backoff: float = 64.0
def validate_config(self) -> None:
if not self.provider:
raise ValueError("Provider must be set.")
if self.provider not in self.supported_providers:
raise ValueError(f"Provider '{self.provider}' is not supported.")
@property
def supported_providers(self) -> list[str]:
return ["anthropic", "litellm", "openai", "r2r"]
class CompletionProvider(Provider):
def __init__(self, config: CompletionConfig) -> None:
if not isinstance(config, CompletionConfig):
raise ValueError(
"CompletionProvider must be initialized with a `CompletionConfig`."
)
logger.info(f"Initializing CompletionProvider with config: {config}")
super().__init__(config)
self.config: CompletionConfig = config
self.semaphore = asyncio.Semaphore(config.concurrent_request_limit)
self.thread_pool = ThreadPoolExecutor(
max_workers=config.concurrent_request_limit
)
async def _execute_with_backoff_async(self, task: dict[str, Any]):
retries = 0
backoff = self.config.initial_backoff
while retries < self.config.max_retries:
try:
async with self.semaphore:
return await self._execute_task(task)
except AuthenticationError:
raise
except Exception as e:
logger.warning(
f"Request failed (attempt {retries + 1}): {str(e)}"
)
retries += 1
if retries == self.config.max_retries:
raise
await asyncio.sleep(random.uniform(0, backoff))
backoff = min(backoff * 2, self.config.max_backoff)
async def _execute_with_backoff_async_stream(
self, task: dict[str, Any]
) -> AsyncGenerator[Any, None]:
retries = 0
backoff = self.config.initial_backoff
while retries < self.config.max_retries:
try:
async with self.semaphore:
async for chunk in await self._execute_task(task):
yield chunk
return # Successful completion of the stream
except AuthenticationError:
raise
except Exception as e:
logger.warning(
f"Streaming request failed (attempt {retries + 1}): {str(e)}"
)
retries += 1
if retries == self.config.max_retries:
raise
await asyncio.sleep(random.uniform(0, backoff))
backoff = min(backoff * 2, self.config.max_backoff)
def _execute_with_backoff_sync(self, task: dict[str, Any]):
retries = 0
backoff = self.config.initial_backoff
while retries < self.config.max_retries:
try:
return self._execute_task_sync(task)
except Exception as e:
logger.warning(
f"Request failed (attempt {retries + 1}): {str(e)}"
)
retries += 1
if retries == self.config.max_retries:
raise
time.sleep(random.uniform(0, backoff))
backoff = min(backoff * 2, self.config.max_backoff)
def _execute_with_backoff_sync_stream(
self, task: dict[str, Any]
) -> Generator[Any, None, None]:
retries = 0
backoff = self.config.initial_backoff
while retries < self.config.max_retries:
try:
yield from self._execute_task_sync(task)
return # Successful completion of the stream
except Exception as e:
logger.warning(
f"Streaming request failed (attempt {retries + 1}): {str(e)}"
)
retries += 1
if retries == self.config.max_retries:
raise
time.sleep(random.uniform(0, backoff))
backoff = min(backoff * 2, self.config.max_backoff)
@abstractmethod
async def _execute_task(self, task: dict[str, Any]):
pass
@abstractmethod
def _execute_task_sync(self, task: dict[str, Any]):
pass
async def aget_completion(
self,
messages: list[dict],
generation_config: GenerationConfig,
**kwargs,
) -> LLMChatCompletion:
task = {
"messages": messages,
"generation_config": generation_config,
"kwargs": kwargs,
}
response = await self._execute_with_backoff_async(task)
return LLMChatCompletion(**response.dict())
async def aget_completion_stream(
self,
messages: list[dict],
generation_config: GenerationConfig,
**kwargs,
) -> AsyncGenerator[LLMChatCompletionChunk, None]:
generation_config.stream = True
task = {
"messages": messages,
"generation_config": generation_config,
"kwargs": kwargs,
}
async for chunk in self._execute_with_backoff_async_stream(task):
if isinstance(chunk, dict):
yield LLMChatCompletionChunk(**chunk)
continue
chunk.choices[0].finish_reason = (
chunk.choices[0].finish_reason
if chunk.choices[0].finish_reason != ""
else None
) # handle error output conventions
chunk.choices[0].finish_reason = (
chunk.choices[0].finish_reason
if chunk.choices[0].finish_reason != "eos"
else "stop"
) # hardcode `eos` to `stop` for consistency
try:
yield LLMChatCompletionChunk(**(chunk.dict()))
except Exception as e:
logger.error(f"Error parsing chunk: {e}")
yield LLMChatCompletionChunk(**(chunk.as_dict()))
def get_completion_stream(
self,
messages: list[dict],
generation_config: GenerationConfig,
**kwargs,
) -> Generator[LLMChatCompletionChunk, None, None]:
generation_config.stream = True
task = {
"messages": messages,
"generation_config": generation_config,
"kwargs": kwargs,
}
for chunk in self._execute_with_backoff_sync_stream(task):
yield LLMChatCompletionChunk(**chunk.dict())
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