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https://github.com/BerriAI/litellm.git
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fix(openai.py): switch to using openai sdk for text completion calls
This commit is contained in:
Krrish Dholakia
parent
b07788d2a5
commit
919ec86b2b
2 changed files with 116 additions and 110 deletions
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@ -1014,6 +1014,8 @@ class OpenAITextCompletion(BaseLLM):
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optional_params=None,
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litellm_params=None,
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logger_fn=None,
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client=None,
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organization: Optional[str] = None,
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headers: Optional[dict] = None,
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):
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super().completion()
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@ -1024,8 +1026,6 @@ class OpenAITextCompletion(BaseLLM):
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if model is None or messages is None:
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raise OpenAIError(status_code=422, message=f"Missing model or messages")
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api_base = f"{api_base}/completions"
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if (
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len(messages) > 0
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and "content" in messages[0]
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@ -1036,9 +1036,9 @@ class OpenAITextCompletion(BaseLLM):
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prompt = " ".join([message["content"] for message in messages]) # type: ignore
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# don't send max retries to the api, if set
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optional_params.pop("max_retries", None)
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data = {"model": model, "prompt": prompt, **optional_params}
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max_retries = data.pop("max_retries", 2)
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## LOGGING
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logging_obj.pre_call(
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input=messages,
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@ -1054,40 +1054,53 @@ class OpenAITextCompletion(BaseLLM):
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return self.async_streaming(
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logging_obj=logging_obj,
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api_base=api_base,
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api_key=api_key,
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data=data,
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headers=headers,
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model_response=model_response,
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model=model,
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timeout=timeout,
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max_retries=max_retries,
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client=client,
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organization=organization,
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)
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else:
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return self.acompletion(api_base=api_base, data=data, headers=headers, model_response=model_response, prompt=prompt, api_key=api_key, logging_obj=logging_obj, model=model, timeout=timeout) # type: ignore
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return self.acompletion(api_base=api_base, data=data, headers=headers, model_response=model_response, prompt=prompt, api_key=api_key, logging_obj=logging_obj, model=model, timeout=timeout, max_retries=max_retries, organization=organization, client=client) # type: ignore
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elif optional_params.get("stream", False):
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return self.streaming(
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logging_obj=logging_obj,
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api_base=api_base,
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api_key=api_key,
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data=data,
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headers=headers,
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model_response=model_response,
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model=model,
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timeout=timeout,
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max_retries=max_retries, # type: ignore
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client=client,
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organization=organization,
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)
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else:
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response = httpx.post(
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url=f"{api_base}", json=data, headers=headers, timeout=timeout
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)
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if response.status_code != 200:
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raise OpenAIError(
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status_code=response.status_code, message=response.text
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if client is None:
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openai_client = OpenAI(
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api_key=api_key,
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base_url=api_base,
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http_client=litellm.client_session,
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timeout=timeout,
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max_retries=max_retries, # type: ignore
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organization=organization,
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)
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else:
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openai_client = client
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response_json = response.json()
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response = openai_client.completions.create(**data) # type: ignore
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response_json = response.model_dump()
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## LOGGING
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logging_obj.post_call(
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input=prompt,
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api_key=api_key,
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original_response=response,
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original_response=response_json,
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additional_args={
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"headers": headers,
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"api_base": api_base,
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@ -1110,100 +1123,110 @@ class OpenAITextCompletion(BaseLLM):
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api_key: str,
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model: str,
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timeout: float,
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max_retries=None,
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organization: Optional[str] = None,
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client=None,
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):
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async with httpx.AsyncClient(timeout=timeout) as client:
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try:
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response = await client.post(
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api_base,
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json=data,
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headers=headers,
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timeout=litellm.request_timeout,
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)
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response_json = response.json()
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if response.status_code != 200:
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raise OpenAIError(
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status_code=response.status_code, message=response.text
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)
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## LOGGING
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logging_obj.post_call(
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input=prompt,
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try:
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if client is None:
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openai_aclient = AsyncOpenAI(
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api_key=api_key,
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original_response=response,
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additional_args={
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"headers": headers,
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"api_base": api_base,
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},
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base_url=api_base,
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http_client=litellm.aclient_session,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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)
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else:
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openai_aclient = client
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## RESPONSE OBJECT
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return TextCompletionResponse(**response_json)
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except Exception as e:
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raise e
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response = await openai_aclient.completions.create(**data)
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response_json = response.model_dump()
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## LOGGING
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logging_obj.post_call(
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input=prompt,
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api_key=api_key,
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original_response=response,
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additional_args={
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"headers": headers,
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"api_base": api_base,
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},
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)
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## RESPONSE OBJECT
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return TextCompletionResponse(**response_json)
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except Exception as e:
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raise e
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def streaming(
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self,
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logging_obj,
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api_base: str,
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api_key: str,
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data: dict,
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headers: dict,
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model_response: ModelResponse,
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model: str,
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timeout: float,
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api_base: Optional[str] = None,
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max_retries=None,
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client=None,
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organization=None,
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):
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with httpx.stream(
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url=f"{api_base}",
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json=data,
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headers=headers,
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method="POST",
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timeout=timeout,
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) as response:
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if response.status_code != 200:
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raise OpenAIError(
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status_code=response.status_code, message=response.text
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)
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streamwrapper = CustomStreamWrapper(
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completion_stream=response.iter_lines(),
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model=model,
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custom_llm_provider="text-completion-openai",
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logging_obj=logging_obj,
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if client is None:
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openai_client = OpenAI(
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api_key=api_key,
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base_url=api_base,
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http_client=litellm.client_session,
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timeout=timeout,
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max_retries=max_retries, # type: ignore
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organization=organization,
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)
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for transformed_chunk in streamwrapper:
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yield transformed_chunk
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else:
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openai_client = client
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response = openai_client.completions.create(**data)
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streamwrapper = CustomStreamWrapper(
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completion_stream=response,
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model=model,
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custom_llm_provider="text-completion-openai",
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logging_obj=logging_obj,
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)
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for chunk in streamwrapper:
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yield chunk
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async def async_streaming(
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self,
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logging_obj,
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api_base: str,
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api_key: str,
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data: dict,
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headers: dict,
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model_response: ModelResponse,
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model: str,
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timeout: float,
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api_base: Optional[str] = None,
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client=None,
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max_retries=None,
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organization=None,
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):
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client = httpx.AsyncClient()
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async with client.stream(
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url=f"{api_base}",
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json=data,
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headers=headers,
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method="POST",
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timeout=timeout,
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) as response:
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try:
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if response.status_code != 200:
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raise OpenAIError(
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status_code=response.status_code, message=response.text
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)
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if client is None:
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openai_client = AsyncOpenAI(
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api_key=api_key,
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base_url=api_base,
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http_client=litellm.aclient_session,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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)
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else:
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openai_client = client
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streamwrapper = CustomStreamWrapper(
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completion_stream=response.aiter_lines(),
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model=model,
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custom_llm_provider="text-completion-openai",
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logging_obj=logging_obj,
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)
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async for transformed_chunk in streamwrapper:
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yield transformed_chunk
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except Exception as e:
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raise e
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response = await openai_client.completions.create(**data)
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streamwrapper = CustomStreamWrapper(
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completion_stream=response,
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model=model,
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custom_llm_provider="text-completion-openai",
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logging_obj=logging_obj,
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)
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async for transformed_chunk in streamwrapper:
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yield transformed_chunk
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