mirror of
https://github.com/BerriAI/litellm.git
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fix(cloudflare): route native Workers AI provider through OpenAI-compatible endpoint
This commit is contained in:
mateo-berri
parent
6f6aec2930
commit
1815cc9bee
4 changed files with 261 additions and 286 deletions
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@ -1,26 +1,11 @@
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import json
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import time
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from typing import AsyncIterator, Iterator, List, Optional, Union
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from typing import List, Optional, Union
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import httpx
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import litellm
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from litellm.litellm_core_utils.url_utils import encode_url_path_segments
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from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
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from litellm.llms.base_llm.chat.transformation import (
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BaseConfig,
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BaseLLMException,
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LiteLLMLoggingObj,
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)
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from litellm.llms.base_llm.chat.transformation import BaseLLMException
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from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
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from litellm.secret_managers.main import get_secret_str
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from litellm.types.llms.openai import AllMessageValues
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from litellm.types.utils import (
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ChatCompletionToolCallChunk,
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ChatCompletionUsageBlock,
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GenericStreamingChunk,
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ModelResponse,
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Usage,
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)
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class CloudflareError(BaseLLMException):
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@ -34,26 +19,32 @@ class CloudflareError(BaseLLMException):
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message=message,
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request=self.request,
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response=self.response,
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) # Call the base class constructor with the parameters it needs
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)
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class CloudflareChatConfig(BaseConfig):
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max_tokens: Optional[int] = None
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stream: Optional[bool] = None
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def __init__(
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class CloudflareChatConfig(OpenAIGPTConfig):
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def get_complete_url(
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self,
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max_tokens: Optional[int] = None,
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api_base: Optional[str],
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api_key: Optional[str],
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model: str,
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optional_params: dict,
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litellm_params: dict,
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stream: Optional[bool] = None,
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) -> None:
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locals_ = locals().copy()
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for key, value in locals_.items():
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if key != "self" and value is not None:
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setattr(self.__class__, key, value)
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@classmethod
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def get_config(cls):
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return super().get_config()
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) -> str:
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if api_base is None:
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account_id = get_secret_str("CLOUDFLARE_ACCOUNT_ID")
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api_base = (
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f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1"
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)
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return super().get_complete_url(
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api_base=api_base,
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api_key=api_key,
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model=model,
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optional_params=optional_params,
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litellm_params=litellm_params,
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stream=stream,
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)
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def validate_environment(
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self,
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@ -67,107 +58,18 @@ class CloudflareChatConfig(BaseConfig):
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) -> dict:
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if api_key is None:
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raise ValueError(
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"Missing CloudflareError API Key - A call is being made to cloudflare but no key is set either in the environment variables or via params"
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"Missing Cloudflare API Key - A call is being made to cloudflare but no key is set either in the environment variables or via params"
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)
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headers = {
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"accept": "application/json",
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"content-type": "apbplication/json",
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"Authorization": "Bearer " + api_key,
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}
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return headers
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def get_complete_url(
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self,
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api_base: Optional[str],
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api_key: Optional[str],
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model: str,
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optional_params: dict,
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litellm_params: dict,
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stream: Optional[bool] = None,
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) -> str:
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if api_base is None:
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account_id = get_secret_str("CLOUDFLARE_ACCOUNT_ID")
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api_base = (
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f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/"
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)
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encoded_model = encode_url_path_segments(model, field_name="model")
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return api_base + encoded_model
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def get_supported_openai_params(self, model: str) -> List[str]:
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return [
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"stream",
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"max_tokens",
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]
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def map_openai_params(
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self,
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non_default_params: dict,
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optional_params: dict,
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model: str,
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drop_params: bool,
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) -> dict:
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supported_openai_params = self.get_supported_openai_params(model=model)
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for param, value in non_default_params.items():
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if param == "max_completion_tokens":
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optional_params["max_tokens"] = value
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elif param in supported_openai_params:
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optional_params[param] = value
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return optional_params
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def transform_request(
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self,
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model: str,
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messages: List[AllMessageValues],
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optional_params: dict,
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litellm_params: dict,
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headers: dict,
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) -> dict:
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config = litellm.CloudflareChatConfig.get_config()
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for k, v in config.items():
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if k not in optional_params:
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optional_params[k] = v
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data = {
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"messages": messages,
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**optional_params,
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}
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return data
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def transform_response(
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self,
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model: str,
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raw_response: httpx.Response,
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model_response: ModelResponse,
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logging_obj: LiteLLMLoggingObj,
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request_data: dict,
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messages: List[AllMessageValues],
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optional_params: dict,
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litellm_params: dict,
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encoding: str,
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api_key: Optional[str] = None,
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json_mode: Optional[bool] = None,
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) -> ModelResponse:
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completion_response = raw_response.json()
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# Support both "response" and "response_text" keys (newer models like Nemotron use "response_text")
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result = completion_response["result"]
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model_response.choices[0].message.content = result.get("response") if result.get("response") is not None else result.get("response_text", "") # type: ignore
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prompt_tokens = litellm.utils.get_token_count(messages=messages, model=model)
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completion_tokens = len(
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encoding.encode(model_response["choices"][0]["message"].get("content", ""))
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return super().validate_environment(
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headers=headers,
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model=model,
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messages=messages,
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optional_params=optional_params,
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litellm_params=litellm_params,
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api_key=api_key,
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api_base=api_base,
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)
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model_response.created = int(time.time())
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model_response.model = "cloudflare/" + model
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usage = Usage(
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prompt_tokens=prompt_tokens,
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completion_tokens=completion_tokens,
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total_tokens=prompt_tokens + completion_tokens,
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)
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setattr(model_response, "usage", usage)
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return model_response
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def get_error_class(
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self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
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) -> BaseLLMException:
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@ -175,48 +77,3 @@ class CloudflareChatConfig(BaseConfig):
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status_code=status_code,
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message=error_message,
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)
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def get_model_response_iterator(
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self,
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streaming_response: Union[Iterator[str], AsyncIterator[str], ModelResponse],
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sync_stream: bool,
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json_mode: Optional[bool] = False,
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):
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return CloudflareChatResponseIterator(
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streaming_response=streaming_response,
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sync_stream=sync_stream,
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json_mode=json_mode,
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)
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class CloudflareChatResponseIterator(BaseModelResponseIterator):
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def chunk_parser(self, chunk: dict) -> GenericStreamingChunk:
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try:
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text = ""
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tool_use: Optional[ChatCompletionToolCallChunk] = None
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is_finished = False
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finish_reason = ""
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usage: Optional[ChatCompletionUsageBlock] = None
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provider_specific_fields = None
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index = int(chunk.get("index", 0))
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if "response" in chunk and chunk["response"] is not None:
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text = chunk["response"]
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elif "response_text" in chunk and chunk["response_text"] is not None:
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text = chunk["response_text"]
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returned_chunk = GenericStreamingChunk(
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text=text,
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tool_use=tool_use,
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is_finished=is_finished,
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finish_reason=finish_reason,
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usage=usage,
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index=index,
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provider_specific_fields=provider_specific_fields,
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)
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return returned_chunk
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except json.JSONDecodeError:
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raise ValueError(f"Failed to decode JSON from chunk: {chunk}")
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@ -4241,7 +4241,7 @@ def completion( # type: ignore
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api_base
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or litellm.api_base
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or get_secret("CLOUDFLARE_API_BASE")
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or f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/"
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or f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1"
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)
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custom_prompt_dict = custom_prompt_dict or litellm.custom_prompt_dict
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@ -9,9 +9,7 @@ import pytest
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from litellm import acompletion, completion
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
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FAKE_API_BASE = (
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"https://fake-cloudflare.example.com/client/v4/accounts/fake-acct/ai/run/"
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)
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FAKE_API_BASE = "https://fake-cloudflare.example.com/client/v4/accounts/fake-acct/ai/v1"
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FAKE_API_KEY = "fake-cf-api-key"
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@ -26,28 +24,78 @@ def _make_mock_response(json_data: Dict[str, Any]) -> MagicMock:
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def _chat_response() -> Dict[str, Any]:
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return {
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"result": {
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"response": "I am a large language model created to assist you.",
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},
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"success": True,
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"errors": [],
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"messages": [],
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"id": "chatcmpl-cf",
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"object": "chat.completion",
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"created": 1234567890,
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"model": "@cf/meta/llama-2-7b-chat-int8",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": "I am a large language model created to assist you.",
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},
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"finish_reason": "stop",
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}
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],
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"usage": {"prompt_tokens": 8, "completion_tokens": 11, "total_tokens": 19},
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}
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def _tool_call_response() -> Dict[str, Any]:
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return {
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"id": "chatcmpl-cf-tools",
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"object": "chat.completion",
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"created": 1234567890,
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"model": "@cf/meta/llama-2-7b-chat-int8",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": None,
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"tool_calls": [
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{
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"id": "call_1",
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"type": "function",
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"function": {
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"name": "get_weather",
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"arguments": '{"city": "New York"}',
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},
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}
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],
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},
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"finish_reason": "tool_calls",
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}
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],
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"usage": {"prompt_tokens": 20, "completion_tokens": 9, "total_tokens": 29},
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}
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def _streaming_chunks() -> list[str]:
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base = {
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"id": "chatcmpl-cf",
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"object": "chat.completion.chunk",
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"created": 1234567890,
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"model": "@cf/meta/llama-2-7b-chat-int8",
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}
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return [
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json.dumps({"response": "I am"}),
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json.dumps({"response": " a language"}),
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json.dumps({"response": " model."}),
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]
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def _streaming_chunks_response_text() -> list[str]:
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return [
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json.dumps({"response_text": "I am"}),
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json.dumps({"response_text": " a language"}),
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json.dumps({"response_text": " model."}),
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json.dumps({**base, "choices": [{"index": 0, "delta": {"content": "I am"}}]}),
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json.dumps(
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{**base, "choices": [{"index": 0, "delta": {"content": " a language"}}]}
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),
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json.dumps(
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{
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**base,
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"choices": [
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{
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"index": 0,
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"delta": {"content": " model."},
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"finish_reason": "stop",
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}
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],
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}
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),
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]
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@ -85,6 +133,48 @@ def test_completion_cloudflare(sync_mode):
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assert response.choices[0].message.content is not None
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assert "language model" in response.choices[0].message.content.lower()
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called_url = mock_post.call_args.kwargs.get("url") or mock_post.call_args.args[0]
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assert called_url.endswith("/ai/v1/chat/completions")
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assert "/ai/run/" not in called_url
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def test_completion_cloudflare_tool_calls_sent_to_openai_endpoint():
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messages = [{"role": "user", "content": "weather in New York?"}]
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_weather",
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"parameters": {
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"type": "object",
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"properties": {"city": {"type": "string"}},
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"required": ["city"],
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},
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},
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}
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]
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mock_resp = _make_mock_response(_tool_call_response())
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with patch.object(HTTPHandler, "post", return_value=mock_resp) as mock_post:
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response = completion(
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model="cloudflare/@cf/meta/llama-2-7b-chat-int8",
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messages=messages,
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tools=tools,
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tool_choice="auto",
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api_base=FAKE_API_BASE,
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api_key=FAKE_API_KEY,
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)
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mock_post.assert_called_once()
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sent_body = json.loads(mock_post.call_args.kwargs["data"])
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assert sent_body["tools"] == tools
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assert sent_body["tool_choice"] == "auto"
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assert response.choices[0].finish_reason == "tool_calls"
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tool_calls = response.choices[0].message.tool_calls
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assert tool_calls is not None and len(tool_calls) == 1
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assert tool_calls[0].function.name == "get_weather"
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@pytest.mark.parametrize("sync_mode", [True, False])
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def test_completion_cloudflare_stream(sync_mode):
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|
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@ -153,76 +243,3 @@ def test_completion_cloudflare_stream(sync_mode):
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if c.choices[0].delta.content
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)
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assert "language" in content.lower()
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@pytest.mark.parametrize("sync_mode", [True, False])
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def test_completion_cloudflare_stream_response_text(sync_mode):
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"""Newer Cloudflare Workers AI models (e.g. Nemotron) emit `response_text`
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instead of `response` in streamed chunks. The iterator must surface that
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text so streaming output is not silently empty.
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"""
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messages = [{"role": "user", "content": "what llm are you"}]
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raw_chunks = _streaming_chunks_response_text()
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|
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if sync_mode:
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|
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def _iter_lines():
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for chunk in raw_chunks:
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yield f"data: {chunk}"
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yield "data: [DONE]"
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mock_resp = MagicMock()
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mock_resp.iter_lines.return_value = _iter_lines()
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mock_resp.status_code = 200
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mock_resp.headers = {"content-type": "text/event-stream"}
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with patch.object(HTTPHandler, "post", return_value=mock_resp) as mock_post:
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response = completion(
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model="cloudflare/@cf/nvidia/nemotron-mini-4b-instruct",
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messages=messages,
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max_tokens=15,
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stream=True,
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api_base=FAKE_API_BASE,
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api_key=FAKE_API_KEY,
|
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)
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chunks_received = list(response)
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mock_post.assert_called_once()
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else:
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|
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async def _aiter_lines():
|
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for chunk in raw_chunks:
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yield f"data: {chunk}"
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yield "data: [DONE]"
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mock_resp = MagicMock()
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mock_resp.aiter_lines.return_value = _aiter_lines()
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mock_resp.status_code = 200
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mock_resp.headers = {"content-type": "text/event-stream"}
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async def _run():
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with patch.object(
|
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AsyncHTTPHandler, "post", new_callable=AsyncMock, return_value=mock_resp
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) as mock_post:
|
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resp = await acompletion(
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model="cloudflare/@cf/nvidia/nemotron-mini-4b-instruct",
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messages=messages,
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max_tokens=15,
|
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stream=True,
|
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api_base=FAKE_API_BASE,
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api_key=FAKE_API_KEY,
|
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)
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received = []
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async for chunk in resp:
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received.append(chunk)
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mock_post.assert_called_once()
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return received
|
||||
|
||||
chunks_received = asyncio.run(_run())
|
||||
|
||||
assert len(chunks_received) > 0
|
||||
content = "".join(
|
||||
c.choices[0].delta.content
|
||||
for c in chunks_received
|
||||
if c.choices[0].delta.content
|
||||
)
|
||||
assert "language" in content.lower()
|
||||
|
|
|
|||
|
|
@ -3,25 +3,126 @@ import pytest
|
|||
from litellm.llms.cloudflare.chat.transformation import CloudflareChatConfig
|
||||
|
||||
|
||||
def test_get_complete_url_encodes_model_path_segment():
|
||||
def test_supported_params_include_tools_and_tool_choice():
|
||||
config = CloudflareChatConfig()
|
||||
|
||||
assert (
|
||||
config.get_complete_url(
|
||||
api_base="https://api.cloudflare.com/client/v4/accounts/acct/ai/run/",
|
||||
api_key="cf-key",
|
||||
model="@cf/meta/llama?x=1#frag",
|
||||
optional_params={},
|
||||
litellm_params={},
|
||||
)
|
||||
== "https://api.cloudflare.com/client/v4/accounts/acct/ai/run/%40cf/meta/llama%3Fx%3D1%23frag"
|
||||
params = config.get_supported_openai_params(model="@cf/meta/llama-2-7b-chat-int8")
|
||||
|
||||
assert "tools" in params
|
||||
assert "tool_choice" in params
|
||||
assert "stream" in params
|
||||
assert "max_tokens" in params
|
||||
|
||||
|
||||
def test_get_complete_url_defaults_to_openai_compatible_endpoint(monkeypatch):
|
||||
monkeypatch.setenv("CLOUDFLARE_ACCOUNT_ID", "acct")
|
||||
config = CloudflareChatConfig()
|
||||
|
||||
url = config.get_complete_url(
|
||||
api_base=None,
|
||||
api_key="cf-key",
|
||||
model="@cf/meta/llama-2-7b-chat-int8",
|
||||
optional_params={},
|
||||
litellm_params={},
|
||||
)
|
||||
|
||||
with pytest.raises(ValueError, match="dot path segment"):
|
||||
config.get_complete_url(
|
||||
api_base="https://api.cloudflare.com/client/v4/accounts/acct/ai/run/",
|
||||
api_key="cf-key",
|
||||
model="../../accounts/other",
|
||||
assert (
|
||||
url
|
||||
== "https://api.cloudflare.com/client/v4/accounts/acct/ai/v1/chat/completions"
|
||||
)
|
||||
assert "/ai/run/" not in url
|
||||
|
||||
|
||||
def test_get_complete_url_appends_chat_completions_to_explicit_base():
|
||||
config = CloudflareChatConfig()
|
||||
|
||||
url = config.get_complete_url(
|
||||
api_base="https://api.cloudflare.com/client/v4/accounts/acct/ai/v1",
|
||||
api_key="cf-key",
|
||||
model="@cf/meta/llama-2-7b-chat-int8",
|
||||
optional_params={},
|
||||
litellm_params={},
|
||||
)
|
||||
|
||||
assert (
|
||||
url
|
||||
== "https://api.cloudflare.com/client/v4/accounts/acct/ai/v1/chat/completions"
|
||||
)
|
||||
assert "/ai/run/" not in url
|
||||
|
||||
|
||||
def test_get_complete_url_is_idempotent_for_full_base():
|
||||
config = CloudflareChatConfig()
|
||||
|
||||
url = config.get_complete_url(
|
||||
api_base="https://api.cloudflare.com/client/v4/accounts/acct/ai/v1/chat/completions",
|
||||
api_key="cf-key",
|
||||
model="@cf/meta/llama-2-7b-chat-int8",
|
||||
optional_params={},
|
||||
litellm_params={},
|
||||
)
|
||||
|
||||
assert (
|
||||
url
|
||||
== "https://api.cloudflare.com/client/v4/accounts/acct/ai/v1/chat/completions"
|
||||
)
|
||||
|
||||
|
||||
def test_transform_request_passes_tools_through_in_openai_format():
|
||||
config = CloudflareChatConfig()
|
||||
tools = [
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_weather",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {"city": {"type": "string"}},
|
||||
},
|
||||
},
|
||||
}
|
||||
]
|
||||
messages = [{"role": "user", "content": "weather in nyc?"}]
|
||||
|
||||
body = config.transform_request(
|
||||
model="@cf/meta/llama-2-7b-chat-int8",
|
||||
messages=messages,
|
||||
optional_params={"tools": tools, "tool_choice": "auto"},
|
||||
litellm_params={},
|
||||
headers={},
|
||||
)
|
||||
|
||||
assert body["messages"] == messages
|
||||
assert body["model"] == "@cf/meta/llama-2-7b-chat-int8"
|
||||
assert body["tools"] == tools
|
||||
assert body["tool_choice"] == "auto"
|
||||
|
||||
|
||||
def test_validate_environment_requires_api_key():
|
||||
config = CloudflareChatConfig()
|
||||
|
||||
with pytest.raises(ValueError, match="Missing Cloudflare API Key"):
|
||||
config.validate_environment(
|
||||
headers={},
|
||||
model="@cf/meta/llama-2-7b-chat-int8",
|
||||
messages=[],
|
||||
optional_params={},
|
||||
litellm_params={},
|
||||
api_key=None,
|
||||
)
|
||||
|
||||
|
||||
def test_validate_environment_sets_bearer_and_content_type():
|
||||
config = CloudflareChatConfig()
|
||||
|
||||
headers = config.validate_environment(
|
||||
headers={},
|
||||
model="@cf/meta/llama-2-7b-chat-int8",
|
||||
messages=[],
|
||||
optional_params={},
|
||||
litellm_params={},
|
||||
api_key="cf-key",
|
||||
)
|
||||
|
||||
assert headers["Authorization"] == "Bearer cf-key"
|
||||
assert headers["Content-Type"] == "application/json"
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue