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"""
Handles the chat completion request for groq
"""
from typing import Callable, List, Optional, Union, cast
from httpx._config import Timeout
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import CustomStreamingDecoder
from litellm.utils import ModelResponse
from ...groq.chat.transformation import GroqChatConfig
from ...openai_like.chat.handler import OpenAILikeChatHandler
class GroqChatCompletion(OpenAILikeChatHandler):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def completion(
self,
*,
model: str,
messages: list,
api_base: str,
custom_llm_provider: str,
custom_prompt_dict: dict,
model_response: ModelResponse,
print_verbose: Callable,
encoding,
api_key: Optional[str],
logging_obj,
optional_params: dict,
acompletion=None,
litellm_params=None,
logger_fn=None,
headers: Optional[dict] = None,
timeout: Optional[Union[float, Timeout]] = None,
client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
custom_endpoint: Optional[bool] = None,
streaming_decoder: Optional[CustomStreamingDecoder] = None,
fake_stream: bool = False,
):
messages = GroqChatConfig()._transform_messages(
messages=cast(List[AllMessageValues], messages), model=model
)
if optional_params.get("stream") is True:
fake_stream = GroqChatConfig()._should_fake_stream(optional_params)
else:
fake_stream = False
return super().completion(
model=model,
messages=messages,
api_base=api_base,
custom_llm_provider=custom_llm_provider,
custom_prompt_dict=custom_prompt_dict,
model_response=model_response,
print_verbose=print_verbose,
encoding=encoding,
api_key=api_key,
logging_obj=logging_obj,
optional_params=optional_params,
acompletion=acompletion,
litellm_params=litellm_params,
logger_fn=logger_fn,
headers=headers,
timeout=timeout,
client=client,
custom_endpoint=custom_endpoint,
streaming_decoder=streaming_decoder,
fake_stream=fake_stream,
)
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