forked from phoenix/litellm-mirror
Merge pull request #4627 from BerriAI/litellm_fix_thread_auth
[Fix] Authentication on /thread endpoints on Proxy
This commit is contained in:
Ishaan Jaff
GitHub
commit
6bce7e73a3
13 changed files with 493 additions and 25 deletions
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@ -1,19 +1,27 @@
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# What is this?
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## Main file for assistants API logic
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from typing import Iterable
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import asyncio
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import contextvars
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import os
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from functools import partial
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import os, asyncio, contextvars
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from typing import Any, Dict, Iterable, List, Literal, Optional, Union
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import httpx
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from openai import AsyncAzureOpenAI, AsyncOpenAI, AzureOpenAI, OpenAI
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from openai.types.beta.assistant import Assistant
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import litellm
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from openai import OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI
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from litellm import client
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from litellm.types.router import GenericLiteLLMParams
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from litellm.utils import (
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supports_httpx_timeout,
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exception_type,
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get_llm_provider,
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get_secret,
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supports_httpx_timeout,
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)
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from ..llms.openai import OpenAIAssistantsAPI
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from ..llms.azure import AzureAssistantsAPI
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from ..llms.openai import OpenAIAssistantsAPI
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from ..types.llms.openai import *
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from ..types.router import *
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from .utils import get_optional_params_add_message
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@ -178,6 +186,159 @@ def get_assistants(
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return response
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async def acreate_assistants(
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custom_llm_provider: Literal["openai", "azure"],
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client: Optional[AsyncOpenAI] = None,
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**kwargs,
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) -> Assistant:
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loop = asyncio.get_event_loop()
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### PASS ARGS TO GET ASSISTANTS ###
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kwargs["async_create_assistants"] = True
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try:
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model = kwargs.pop("model", None)
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kwargs["client"] = client
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# Use a partial function to pass your keyword arguments
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func = partial(create_assistants, custom_llm_provider, model, **kwargs)
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# Add the context to the function
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ctx = contextvars.copy_context()
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func_with_context = partial(ctx.run, func)
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_, custom_llm_provider, _, _ = get_llm_provider( # type: ignore
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model=model, custom_llm_provider=custom_llm_provider
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) # type: ignore
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# Await normally
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init_response = await loop.run_in_executor(None, func_with_context)
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if asyncio.iscoroutine(init_response):
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response = await init_response
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else:
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response = init_response
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return response # type: ignore
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except Exception as e:
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raise exception_type(
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model=model,
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custom_llm_provider=custom_llm_provider,
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original_exception=e,
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completion_kwargs={},
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extra_kwargs=kwargs,
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)
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def create_assistants(
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custom_llm_provider: Literal["openai", "azure"],
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model: str,
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name: Optional[str] = None,
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description: Optional[str] = None,
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instructions: Optional[str] = None,
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tools: Optional[List[Dict[str, Any]]] = None,
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tool_resources: Optional[Dict[str, Any]] = None,
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metadata: Optional[Dict[str, str]] = None,
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temperature: Optional[float] = None,
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top_p: Optional[float] = None,
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response_format: Optional[Union[str, Dict[str, str]]] = None,
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client: Optional[Any] = None,
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api_key: Optional[str] = None,
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api_base: Optional[str] = None,
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api_version: Optional[str] = None,
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**kwargs,
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) -> Assistant:
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async_create_assistants: Optional[bool] = kwargs.pop(
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"async_create_assistants", None
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)
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if async_create_assistants is not None and not isinstance(
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async_create_assistants, bool
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):
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raise ValueError(
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"Invalid value passed in for async_create_assistants. Only bool or None allowed"
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)
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optional_params = GenericLiteLLMParams(
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api_key=api_key, api_base=api_base, api_version=api_version, **kwargs
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)
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### TIMEOUT LOGIC ###
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timeout = optional_params.timeout or kwargs.get("request_timeout", 600) or 600
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# set timeout for 10 minutes by default
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if (
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timeout is not None
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and isinstance(timeout, httpx.Timeout)
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and supports_httpx_timeout(custom_llm_provider) == False
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):
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read_timeout = timeout.read or 600
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timeout = read_timeout # default 10 min timeout
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elif timeout is not None and not isinstance(timeout, httpx.Timeout):
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timeout = float(timeout) # type: ignore
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elif timeout is None:
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timeout = 600.0
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response: Optional[Assistant] = None
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if custom_llm_provider == "openai":
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api_base = (
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optional_params.api_base # for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
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or litellm.api_base
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or os.getenv("OPENAI_API_BASE")
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or "https://api.openai.com/v1"
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)
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organization = (
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optional_params.organization
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or litellm.organization
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or os.getenv("OPENAI_ORGANIZATION", None)
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or None # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
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)
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# set API KEY
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api_key = (
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optional_params.api_key
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or litellm.api_key # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
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or litellm.openai_key
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or os.getenv("OPENAI_API_KEY")
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)
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create_assistant_data = {
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"model": model,
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"name": name,
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"description": description,
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"instructions": instructions,
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"tools": tools,
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"tool_resources": tool_resources,
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"metadata": metadata,
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"temperature": temperature,
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"top_p": top_p,
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"response_format": response_format,
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}
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response = openai_assistants_api.create_assistants(
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api_base=api_base,
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api_key=api_key,
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timeout=timeout,
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max_retries=optional_params.max_retries,
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organization=organization,
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create_assistant_data=create_assistant_data,
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client=client,
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async_create_assistants=async_create_assistants, # type: ignore
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) # type: ignore
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else:
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raise litellm.exceptions.BadRequestError(
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message="LiteLLM doesn't support {} for 'create_assistants'. Only 'openai' is supported.".format(
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custom_llm_provider
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),
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model="n/a",
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llm_provider=custom_llm_provider,
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response=httpx.Response(
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status_code=400,
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content="Unsupported provider",
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request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore
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),
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)
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if response is None:
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raise litellm.exceptions.InternalServerError(
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message="No response returned from 'create_assistants'",
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model=model,
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llm_provider=custom_llm_provider,
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)
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return response
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### THREADS ###
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@ -2383,6 +2383,63 @@ class OpenAIAssistantsAPI(BaseLLM):
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return response
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# Create Assistant
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async def async_create_assistants(
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self,
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api_key: Optional[str],
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api_base: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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organization: Optional[str],
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client: Optional[AsyncOpenAI],
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create_assistant_data: dict,
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) -> Assistant:
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openai_client = self.async_get_openai_client(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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client=client,
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)
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response = await openai_client.beta.assistants.create(**create_assistant_data)
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return response
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def create_assistants(
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self,
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api_key: Optional[str],
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api_base: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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organization: Optional[str],
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create_assistant_data: dict,
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client=None,
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async_create_assistants=None,
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):
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if async_create_assistants is not None and async_create_assistants == True:
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return self.async_create_assistants(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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client=client,
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create_assistant_data=create_assistant_data,
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)
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openai_client = self.get_openai_client(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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client=client,
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)
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response = openai_client.beta.assistants.create(**create_assistant_data)
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return response
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### MESSAGES ###
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async def a_add_message(
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@ -175,10 +175,12 @@ class LiteLLMRoutes(enum.Enum):
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"/chat/completions",
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"/v1/chat/completions",
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# completions
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"/engines/{model}/completions",
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"/openai/deployments/{model}/completions",
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"/completions",
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"/v1/completions",
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# embeddings
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"/engines/{model}/embeddings",
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"/openai/deployments/{model}/embeddings",
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"/embeddings",
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"/v1/embeddings",
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|
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@ -24,6 +24,7 @@ from litellm.proxy._types import (
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LitellmUserRoles,
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UserAPIKeyAuth,
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)
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from litellm.proxy.auth.auth_utils import is_openai_route
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from litellm.proxy.utils import PrismaClient, ProxyLogging, log_to_opentelemetry
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from litellm.types.services import ServiceLoggerPayload, ServiceTypes
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@ -105,7 +106,7 @@ def common_checks(
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general_settings.get("enforce_user_param", None) is not None
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and general_settings["enforce_user_param"] == True
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):
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if route in LiteLLMRoutes.openai_routes.value and "user" not in request_body:
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if is_openai_route(route=route) and "user" not in request_body:
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raise Exception(
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f"'user' param not passed in. 'enforce_user_param'={general_settings['enforce_user_param']}"
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)
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@ -121,7 +122,7 @@ def common_checks(
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+ CommonProxyErrors.not_premium_user.value
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)
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if route in LiteLLMRoutes.openai_routes.value:
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if is_openai_route(route=route):
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# loop through each enforced param
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# example enforced_params ['user', 'metadata', 'metadata.generation_name']
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for enforced_param in general_settings["enforced_params"]:
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@ -149,7 +150,7 @@ def common_checks(
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and global_proxy_spend is not None
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# only run global budget checks for OpenAI routes
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# Reason - the Admin UI should continue working if the proxy crosses it's global budget
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and route in LiteLLMRoutes.openai_routes.value
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and is_openai_route(route=route)
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and route != "/v1/models"
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and route != "/models"
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):
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|
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@ -1,4 +1,7 @@
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import re
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from litellm._logging import verbose_proxy_logger
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from litellm.proxy._types import *
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def route_in_additonal_public_routes(current_route: str):
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@ -41,3 +44,31 @@ def route_in_additonal_public_routes(current_route: str):
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except Exception as e:
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verbose_proxy_logger.error(f"route_in_additonal_public_routes: {str(e)}")
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return False
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def is_openai_route(route: str) -> bool:
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"""
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Helper to checks if provided route is an OpenAI route
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Returns:
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- True: if route is an OpenAI route
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- False: if route is not an OpenAI route
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"""
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if route in LiteLLMRoutes.openai_routes.value:
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return True
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# fuzzy match routes like "/v1/threads/thread_49EIN5QF32s4mH20M7GFKdlZ"
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# Check for routes with placeholders
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for openai_route in LiteLLMRoutes.openai_routes.value:
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# Replace placeholders with regex pattern
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# placeholders are written as "/threads/{thread_id}"
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if "{" in openai_route:
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pattern = re.sub(r"\{[^}]+\}", r"[^/]+", openai_route)
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# Anchor the pattern to match the entire string
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pattern = f"^{pattern}$"
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if re.match(pattern, route):
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return True
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return False
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|
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@ -56,7 +56,10 @@ from litellm.proxy.auth.auth_checks import (
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get_user_object,
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log_to_opentelemetry,
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)
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from litellm.proxy.auth.auth_utils import route_in_additonal_public_routes
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from litellm.proxy.auth.auth_utils import (
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is_openai_route,
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route_in_additonal_public_routes,
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)
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from litellm.proxy.common_utils.http_parsing_utils import _read_request_body
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from litellm.proxy.utils import _to_ns
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@ -933,9 +936,9 @@ async def user_api_key_auth(
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_user_role = _get_user_role(user_id_information=user_id_information)
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if not _is_user_proxy_admin(user_id_information): # if non-admin
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if route in LiteLLMRoutes.openai_routes.value:
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if is_openai_route(route=route):
|
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pass
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elif request["route"].name in LiteLLMRoutes.openai_route_names.value:
|
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elif is_openai_route(route=request["route"].name):
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pass
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elif (
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route in LiteLLMRoutes.info_routes.value
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|
|
@ -988,7 +991,7 @@ async def user_api_key_auth(
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|
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pass
|
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elif _user_role == LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY.value:
|
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if route in LiteLLMRoutes.openai_routes.value:
|
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if is_openai_route(route=route):
|
||||
raise HTTPException(
|
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status_code=status.HTTP_403_FORBIDDEN,
|
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detail=f"user not allowed to access this OpenAI routes, role= {_user_role}",
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|
|
|
|||
|
|
@ -33,11 +33,11 @@ def _get_metadata_variable_name(request: Request) -> str:
|
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"""
|
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Helper to return what the "metadata" field should be called in the request data
|
||||
|
||||
For all /thread endpoints we need to call this "litellm_metadata"
|
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For all /thread or /assistant endpoints we need to call this "litellm_metadata"
|
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|
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For ALL other endpoints we call this "metadata
|
||||
"""
|
||||
if "thread" in request.url.path:
|
||||
if "thread" in request.url.path or "assistant" in request.url.path:
|
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return "litellm_metadata"
|
||||
else:
|
||||
return "metadata"
|
||||
|
|
|
|||
|
|
@ -35,7 +35,6 @@ general_settings:
|
|||
LANGFUSE_SECRET_KEY: "os.environ/LANGFUSE_DEV_SK_KEY"
|
||||
|
||||
litellm_settings:
|
||||
callbacks: ["otel"]
|
||||
guardrails:
|
||||
- prompt_injection:
|
||||
callbacks: [lakera_prompt_injection, hide_secrets]
|
||||
|
|
@ -43,6 +42,9 @@ litellm_settings:
|
|||
- hide_secrets:
|
||||
callbacks: [hide_secrets]
|
||||
default_on: true
|
||||
|
||||
|
||||
assistant_settings:
|
||||
custom_llm_provider: openai
|
||||
litellm_params:
|
||||
api_key: os.environ/OPENAI_API_KEY
|
||||
|
||||
|
|
|
|||
|
|
@ -3960,6 +3960,101 @@ async def get_assistants(
|
|||
)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/v1/assistants",
|
||||
dependencies=[Depends(user_api_key_auth)],
|
||||
tags=["assistants"],
|
||||
)
|
||||
@router.post(
|
||||
"/assistants",
|
||||
dependencies=[Depends(user_api_key_auth)],
|
||||
tags=["assistants"],
|
||||
)
|
||||
async def create_assistant(
|
||||
request: Request,
|
||||
fastapi_response: Response,
|
||||
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
|
||||
):
|
||||
"""
|
||||
Create assistant
|
||||
|
||||
API Reference docs - https://platform.openai.com/docs/api-reference/assistants/createAssistant
|
||||
"""
|
||||
global proxy_logging_obj
|
||||
try:
|
||||
# Use orjson to parse JSON data, orjson speeds up requests significantly
|
||||
body = await request.body()
|
||||
data = orjson.loads(body)
|
||||
|
||||
# Include original request and headers in the data
|
||||
data = await add_litellm_data_to_request(
|
||||
data=data,
|
||||
request=request,
|
||||
general_settings=general_settings,
|
||||
user_api_key_dict=user_api_key_dict,
|
||||
version=version,
|
||||
proxy_config=proxy_config,
|
||||
)
|
||||
|
||||
# for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
|
||||
if llm_router is None:
|
||||
raise HTTPException(
|
||||
status_code=500, detail={"error": CommonProxyErrors.no_llm_router.value}
|
||||
)
|
||||
response = await llm_router.acreate_assistants(**data)
|
||||
|
||||
### ALERTING ###
|
||||
asyncio.create_task(
|
||||
proxy_logging_obj.update_request_status(
|
||||
litellm_call_id=data.get("litellm_call_id", ""), status="success"
|
||||
)
|
||||
)
|
||||
|
||||
### RESPONSE HEADERS ###
|
||||
hidden_params = getattr(response, "_hidden_params", {}) or {}
|
||||
model_id = hidden_params.get("model_id", None) or ""
|
||||
cache_key = hidden_params.get("cache_key", None) or ""
|
||||
api_base = hidden_params.get("api_base", None) or ""
|
||||
|
||||
fastapi_response.headers.update(
|
||||
get_custom_headers(
|
||||
user_api_key_dict=user_api_key_dict,
|
||||
model_id=model_id,
|
||||
cache_key=cache_key,
|
||||
api_base=api_base,
|
||||
version=version,
|
||||
model_region=getattr(user_api_key_dict, "allowed_model_region", ""),
|
||||
)
|
||||
)
|
||||
|
||||
return response
|
||||
except Exception as e:
|
||||
await proxy_logging_obj.post_call_failure_hook(
|
||||
user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data
|
||||
)
|
||||
verbose_proxy_logger.error(
|
||||
"litellm.proxy.proxy_server.create_assistant(): Exception occured - {}".format(
|
||||
str(e)
|
||||
)
|
||||
)
|
||||
verbose_proxy_logger.debug(traceback.format_exc())
|
||||
if isinstance(e, HTTPException):
|
||||
raise ProxyException(
|
||||
message=getattr(e, "message", str(e.detail)),
|
||||
type=getattr(e, "type", "None"),
|
||||
param=getattr(e, "param", "None"),
|
||||
code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
|
||||
)
|
||||
else:
|
||||
error_msg = f"{str(e)}"
|
||||
raise ProxyException(
|
||||
message=getattr(e, "message", error_msg),
|
||||
type=getattr(e, "type", "None"),
|
||||
param=getattr(e, "param", "None"),
|
||||
code=getattr(e, "status_code", 500),
|
||||
)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/v1/threads",
|
||||
dependencies=[Depends(user_api_key_auth)],
|
||||
|
|
|
|||
|
|
@ -1970,6 +1970,25 @@ class Router:
|
|||
|
||||
#### ASSISTANTS API ####
|
||||
|
||||
async def acreate_assistants(
|
||||
self,
|
||||
custom_llm_provider: Optional[Literal["openai", "azure"]] = None,
|
||||
client: Optional[AsyncOpenAI] = None,
|
||||
**kwargs,
|
||||
) -> Assistant:
|
||||
if custom_llm_provider is None:
|
||||
if self.assistants_config is not None:
|
||||
custom_llm_provider = self.assistants_config["custom_llm_provider"]
|
||||
kwargs.update(self.assistants_config["litellm_params"])
|
||||
else:
|
||||
raise Exception(
|
||||
"'custom_llm_provider' must be set. Either via:\n `Router(assistants_config={'custom_llm_provider': ..})` \nor\n `router.arun_thread(custom_llm_provider=..)`"
|
||||
)
|
||||
|
||||
return await litellm.acreate_assistants(
|
||||
custom_llm_provider=custom_llm_provider, client=client, **kwargs
|
||||
)
|
||||
|
||||
async def aget_assistants(
|
||||
self,
|
||||
custom_llm_provider: Optional[Literal["openai", "azure"]] = None,
|
||||
|
|
|
|||
|
|
@ -1,27 +1,34 @@
|
|||
# What is this?
|
||||
## Unit Tests for OpenAI Assistants API
|
||||
import sys, os, json
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
import traceback
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv()
|
||||
sys.path.insert(
|
||||
0, os.path.abspath("../..")
|
||||
) # Adds the parent directory to the system path
|
||||
import pytest, logging, asyncio
|
||||
import asyncio
|
||||
import logging
|
||||
|
||||
import pytest
|
||||
from openai.types.beta.assistant import Assistant
|
||||
from typing_extensions import override
|
||||
|
||||
import litellm
|
||||
from litellm import create_thread, get_thread
|
||||
from litellm.llms.openai import (
|
||||
OpenAIAssistantsAPI,
|
||||
MessageData,
|
||||
Thread,
|
||||
OpenAIMessage as Message,
|
||||
AsyncCursorPage,
|
||||
SyncCursorPage,
|
||||
AssistantEventHandler,
|
||||
AsyncAssistantEventHandler,
|
||||
AsyncCursorPage,
|
||||
MessageData,
|
||||
OpenAIAssistantsAPI,
|
||||
)
|
||||
from typing_extensions import override
|
||||
from litellm.llms.openai import OpenAIMessage as Message
|
||||
from litellm.llms.openai import SyncCursorPage, Thread
|
||||
|
||||
"""
|
||||
V0 Scope:
|
||||
|
|
@ -52,6 +59,49 @@ async def test_get_assistants(provider, sync_mode):
|
|||
assert isinstance(assistants, AsyncCursorPage)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("provider", ["openai"])
|
||||
@pytest.mark.parametrize(
|
||||
"sync_mode",
|
||||
[False],
|
||||
)
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_assistants(provider, sync_mode):
|
||||
data = {
|
||||
"custom_llm_provider": provider,
|
||||
}
|
||||
|
||||
if sync_mode == True:
|
||||
assistant = litellm.create_assistants(
|
||||
custom_llm_provider="openai",
|
||||
model="gpt-4-turbo",
|
||||
instructions="You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
|
||||
name="Math Tutor",
|
||||
tools=[{"type": "code_interpreter"}],
|
||||
)
|
||||
print("New assistants", assistant)
|
||||
assert isinstance(assistant, Assistant)
|
||||
assert (
|
||||
assistant.instructions
|
||||
== "You are a personal math tutor. When asked a question, write and run Python code to answer the question."
|
||||
)
|
||||
assert assistant.id is not None
|
||||
else:
|
||||
assistant = await litellm.acreate_assistants(
|
||||
custom_llm_provider="openai",
|
||||
model="gpt-4-turbo",
|
||||
instructions="You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
|
||||
name="Math Tutor",
|
||||
tools=[{"type": "code_interpreter"}],
|
||||
)
|
||||
print("New assistants", assistant)
|
||||
assert isinstance(assistant, Assistant)
|
||||
assert (
|
||||
assistant.instructions
|
||||
== "You are a personal math tutor. When asked a question, write and run Python code to answer the question."
|
||||
)
|
||||
assert assistant.id is not None
|
||||
|
||||
|
||||
@pytest.mark.parametrize("provider", ["openai", "azure"])
|
||||
@pytest.mark.parametrize("sync_mode", [True, False])
|
||||
@pytest.mark.asyncio
|
||||
|
|
|
|||
|
|
@ -213,6 +213,10 @@ async def test_new_user_response(prisma_client):
|
|||
# model_list
|
||||
APIRoute(path="/v1/models", endpoint=model_list),
|
||||
APIRoute(path="/models", endpoint=model_list),
|
||||
# threads
|
||||
APIRoute(
|
||||
path="/v1/threads/thread_49EIN5QF32s4mH20M7GFKdlZ", endpoint=model_list
|
||||
),
|
||||
],
|
||||
ids=lambda route: str(dict(route=route.endpoint.__name__, path=route.path)),
|
||||
)
|
||||
|
|
|
|||
|
|
@ -19,6 +19,7 @@ import pytest
|
|||
|
||||
import litellm
|
||||
from litellm.proxy._types import LiteLLMRoutes
|
||||
from litellm.proxy.auth.auth_utils import is_openai_route
|
||||
from litellm.proxy.proxy_server import router
|
||||
|
||||
# Configure logging
|
||||
|
|
@ -50,3 +51,45 @@ def test_routes_on_litellm_proxy():
|
|||
|
||||
for route in LiteLLMRoutes.openai_routes.value:
|
||||
assert route in _all_routes
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"route,expected",
|
||||
[
|
||||
# Test exact matches
|
||||
("/chat/completions", True),
|
||||
("/v1/chat/completions", True),
|
||||
("/embeddings", True),
|
||||
("/v1/models", True),
|
||||
("/utils/token_counter", True),
|
||||
# Test routes with placeholders
|
||||
("/engines/gpt-4/chat/completions", True),
|
||||
("/openai/deployments/gpt-3.5-turbo/chat/completions", True),
|
||||
("/threads/thread_49EIN5QF32s4mH20M7GFKdlZ", True),
|
||||
("/v1/threads/thread_49EIN5QF32s4mH20M7GFKdlZ", True),
|
||||
("/threads/thread_49EIN5QF32s4mH20M7GFKdlZ/messages", True),
|
||||
("/v1/threads/thread_49EIN5QF32s4mH20M7GFKdlZ/runs", True),
|
||||
("/v1/batches123456", True),
|
||||
# Test non-OpenAI routes
|
||||
("/some/random/route", False),
|
||||
("/v2/chat/completions", False),
|
||||
("/threads/invalid/format", False),
|
||||
("/v1/non_existent_endpoint", False),
|
||||
],
|
||||
)
|
||||
def test_is_openai_route(route: str, expected: bool):
|
||||
assert is_openai_route(route) == expected
|
||||
|
||||
|
||||
# Test case for routes that are similar but should return False
|
||||
@pytest.mark.parametrize(
|
||||
"route",
|
||||
[
|
||||
"/v1/threads/thread_id/invalid",
|
||||
"/threads/thread_id/invalid",
|
||||
"/v1/batches/123/invalid",
|
||||
"/engines/model/invalid/completions",
|
||||
],
|
||||
)
|
||||
def test_is_openai_route_similar_but_false(route: str):
|
||||
assert is_openai_route(route) == False
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue