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Fix langfuse prompt management on proxy (#7535)

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* fix(types/utils.py): support langfuse + humanloop routes on llm router

* fix(main.py): remove acompletion elif block

just await if coroutine returned
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Krish Dholakia 2025-01-03 12:42:37 -08:00 • committed by GitHub
parent 24589c49af
commit f6698e871f
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3 changed files with 28 additions and 67 deletions
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86
litellm/main.py
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@ -435,74 +435,26 @@ async def acompletion(
ctx = contextvars.copy_context()
func_with_context = partial(ctx.run, func)
if (
custom_llm_provider == "openai"
or custom_llm_provider == "azure"
or custom_llm_provider == "azure_text"
or custom_llm_provider == "custom_openai"
or custom_llm_provider == "anyscale"
or custom_llm_provider == "mistral"
or custom_llm_provider == "openrouter"
or custom_llm_provider == "deepinfra"
or custom_llm_provider == "perplexity"
or custom_llm_provider == "groq"
or custom_llm_provider == "nvidia_nim"
or custom_llm_provider == "cohere_chat"
or custom_llm_provider == "cohere"
or custom_llm_provider == "cerebras"
or custom_llm_provider == "sambanova"
or custom_llm_provider == "ai21_chat"
or custom_llm_provider == "ai21"
or custom_llm_provider == "volcengine"
or custom_llm_provider == "codestral"
or custom_llm_provider == "text-completion-codestral"
or custom_llm_provider == "deepseek"
or custom_llm_provider == "text-completion-openai"
or custom_llm_provider == "huggingface"
or custom_llm_provider == "ollama"
or custom_llm_provider == "ollama_chat"
or custom_llm_provider == "replicate"
or custom_llm_provider == "vertex_ai"
or custom_llm_provider == "vertex_ai_beta"
or custom_llm_provider == "gemini"
or custom_llm_provider == "sagemaker"
or custom_llm_provider == "sagemaker_chat"
or custom_llm_provider == "anthropic"
or custom_llm_provider == "anthropic_text"
or custom_llm_provider == "predibase"
or custom_llm_provider == "bedrock"
or custom_llm_provider == "databricks"
or custom_llm_provider == "triton"
or custom_llm_provider == "clarifai"
or custom_llm_provider == "watsonx"
or custom_llm_provider == "cloudflare"
or custom_llm_provider == "aiohttp_openai"
or custom_llm_provider in litellm.openai_compatible_providers
or custom_llm_provider in litellm._custom_providers
): # currently implemented aiohttp calls for just azure, openai, hf, ollama, vertex ai soon all.
init_response = await loop.run_in_executor(None, func_with_context)
if isinstance(init_response, dict) or isinstance(
init_response, ModelResponse
): ## CACHING SCENARIO
if isinstance(init_response, dict):
response = ModelResponse(**init_response)
response = init_response
elif asyncio.iscoroutine(init_response):
response = await init_response
else:
response = init_response # type: ignore
if (
custom_llm_provider == "text-completion-openai"
or custom_llm_provider == "text-completion-codestral"
) and isinstance(response, TextCompletionResponse):
response = litellm.OpenAITextCompletionConfig().convert_to_chat_model_response_object(
response_object=response,
model_response_object=litellm.ModelResponse(),
)
init_response = await loop.run_in_executor(None, func_with_context)
if isinstance(init_response, dict) or isinstance(
init_response, ModelResponse
): ## CACHING SCENARIO
if isinstance(init_response, dict):
response = ModelResponse(**init_response)
response = init_response
elif asyncio.iscoroutine(init_response):
response = await init_response
else:
# Call the synchronous function using run_in_executor
response = await loop.run_in_executor(None, func_with_context) # type: ignore
response = init_response # type: ignore
if (
custom_llm_provider == "text-completion-openai"
or custom_llm_provider == "text-completion-codestral"
) and isinstance(response, TextCompletionResponse):
response = litellm.OpenAITextCompletionConfig().convert_to_chat_model_response_object(
response_object=response,
model_response_object=litellm.ModelResponse(),
)
if isinstance(response, CustomStreamWrapper):
response.set_logging_event_loop(
loop=loop