forked from phoenix/litellm-mirror
* feat(proxy_cli.py): add new 'log_config' cli param Allows passing logging.conf to uvicorn on startup * docs(cli.md): add logging conf to uvicorn cli docs * fix(get_llm_provider_logic.py): fix default api base for litellm_proxy Fixes https://github.com/BerriAI/litellm/issues/6332 * feat(openai_like/embedding): Add support for jina ai embeddings Closes https://github.com/BerriAI/litellm/issues/6337 * docs(deploy.md): update entrypoint.sh filepath post-refactor Fixes outdated docs * feat(prometheus.py): emit time_to_first_token metric on prometheus Closes https://github.com/BerriAI/litellm/issues/6334 * fix(prometheus.py): only emit time to first token metric if stream is True enables more accurate ttft usage * test: handle vertex api instability * fix(get_llm_provider_logic.py): fix import * fix(openai.py): fix deepinfra default api base * fix(anthropic/transformation.py): remove anthropic beta header (#6361)
162 lines
5.1 KiB
Python
162 lines
5.1 KiB
Python
import os
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import sys
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import io
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from unittest.mock import patch
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import pytest
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import litellm
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def test_get_llm_provider():
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_, response, _, _ = litellm.get_llm_provider(model="anthropic.claude-v2:1")
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assert response == "bedrock"
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# test_get_llm_provider()
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def test_get_llm_provider_fireworks(): # tests finetuned fireworks models - https://github.com/BerriAI/litellm/issues/4923
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model, custom_llm_provider, _, _ = litellm.get_llm_provider(
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model="fireworks_ai/accounts/my-test-1234"
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)
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assert custom_llm_provider == "fireworks_ai"
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assert model == "accounts/my-test-1234"
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def test_get_llm_provider_catch_all():
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_, response, _, _ = litellm.get_llm_provider(model="*")
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assert response == "openai"
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def test_get_llm_provider_gpt_instruct():
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_, response, _, _ = litellm.get_llm_provider(model="gpt-3.5-turbo-instruct-0914")
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assert response == "text-completion-openai"
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def test_get_llm_provider_mistral_custom_api_base():
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="mistral/mistral-large-fr",
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api_base="https://mistral-large-fr-ishaan.francecentral.inference.ai.azure.com/v1",
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)
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assert custom_llm_provider == "mistral"
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assert model == "mistral-large-fr"
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assert (
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api_base
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== "https://mistral-large-fr-ishaan.francecentral.inference.ai.azure.com/v1"
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)
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def test_get_llm_provider_deepseek_custom_api_base():
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os.environ["DEEPSEEK_API_BASE"] = "MY-FAKE-BASE"
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="deepseek/deep-chat",
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)
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assert custom_llm_provider == "deepseek"
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assert model == "deep-chat"
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assert api_base == "MY-FAKE-BASE"
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os.environ.pop("DEEPSEEK_API_BASE")
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def test_get_llm_provider_vertex_ai_image_models():
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="imagegeneration@006", custom_llm_provider=None
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)
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assert custom_llm_provider == "vertex_ai"
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def test_get_llm_provider_ai21_chat():
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="jamba-1.5-large",
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)
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assert custom_llm_provider == "ai21_chat"
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assert model == "jamba-1.5-large"
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assert api_base == "https://api.ai21.com/studio/v1"
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def test_get_llm_provider_ai21_chat_test2():
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"""
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if user prefix with ai21/ but calls jamba-1.5-large then it should be ai21_chat provider
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"""
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="ai21/jamba-1.5-large",
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)
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print("model=", model)
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print("custom_llm_provider=", custom_llm_provider)
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print("api_base=", api_base)
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assert custom_llm_provider == "ai21_chat"
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assert model == "jamba-1.5-large"
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assert api_base == "https://api.ai21.com/studio/v1"
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def test_get_llm_provider_cohere_chat_test2():
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"""
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if user prefix with cohere/ but calls command-r-plus then it should be cohere_chat provider
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"""
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="cohere/command-r-plus",
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)
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print("model=", model)
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print("custom_llm_provider=", custom_llm_provider)
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print("api_base=", api_base)
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assert custom_llm_provider == "cohere_chat"
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assert model == "command-r-plus"
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def test_get_llm_provider_azure_o1():
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="azure/o1-mini",
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)
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assert custom_llm_provider == "azure"
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assert model == "o1-mini"
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def test_default_api_base():
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from litellm.litellm_core_utils.get_llm_provider_logic import (
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_get_openai_compatible_provider_info,
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)
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# Patch environment variable to remove API base if it's set
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with patch.dict(os.environ, {}, clear=True):
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for provider in litellm.openai_compatible_providers:
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# Get the API base for the given provider
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_, _, _, api_base = _get_openai_compatible_provider_info(
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model=f"{provider}/*", api_base=None, api_key=None, dynamic_api_key=None
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)
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if api_base is None:
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continue
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for other_provider in litellm.provider_list:
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if other_provider != provider and provider != "{}_chat".format(
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other_provider.value
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):
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if provider == "codestral" and other_provider == "mistral":
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continue
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elif provider == "github" and other_provider == "azure":
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continue
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assert other_provider.value not in api_base.replace("/openai", "")
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def test_get_llm_provider_jina_ai():
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model, custom_llm_provider, dynamic_api_key, api_base = litellm.get_llm_provider(
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model="jina_ai/jina-embeddings-v3",
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)
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assert custom_llm_provider == "openai_like"
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assert api_base == "https://api.jina.ai/v1"
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assert model == "jina-embeddings-v3"
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