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https://github.com/BerriAI/litellm.git
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760328b6ad
* test: add new test image embedding to base llm unit tests Addresses https://github.com/BerriAI/litellm/issues/6515 * fix(bedrock/embed/multimodal-embeddings): strip data prefix from image urls for bedrock multimodal embeddings Fix https://github.com/BerriAI/litellm/issues/6515 * feat: initial commit for fireworks ai audio transcription support Relevant issue: https://github.com/BerriAI/litellm/issues/7134 * test: initial fireworks ai test * feat(fireworks_ai/): implemented fireworks ai audio transcription config * fix(utils.py): register fireworks ai audio transcription config, in config manager * fix(utils.py): add fireworks ai param translation to 'get_optional_params_transcription' * refactor(fireworks_ai/): define text completion route with model name handling moves model name handling to specific fireworks routes, as required by their api * refactor(fireworks_ai/chat): define transform_Request - allows fixing model if accounts/ is missing * fix: fix linting errors * fix: fix linting errors * fix: fix linting errors * fix: fix linting errors * fix(handler.py): fix linting errors * fix(main.py): fix tgai text completion route * refactor(together_ai/completion): refactors together ai text completion route to just use provider transform request * refactor: move test_fine_tuning_api out of local_testing reduces local testing ci/cd time
86 lines
2.9 KiB
Python
86 lines
2.9 KiB
Python
import httpx
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import json
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import pytest
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import sys
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from typing import Any, Dict, List
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from unittest.mock import MagicMock, Mock, patch
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import os
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import uuid
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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 litellm
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from litellm import transcription
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from litellm.litellm_core_utils.get_supported_openai_params import (
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get_supported_openai_params,
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)
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from litellm.llms.base_llm.audio_transcription.transformation import (
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BaseAudioTranscriptionConfig,
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)
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from litellm.utils import ProviderConfigManager
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from abc import ABC, abstractmethod
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pwd = os.path.dirname(os.path.realpath(__file__))
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print(pwd)
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file_path = os.path.join(pwd, "gettysburg.wav")
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audio_file = open(file_path, "rb")
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class BaseLLMAudioTranscriptionTest(ABC):
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@abstractmethod
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def get_base_audio_transcription_call_args(self) -> dict:
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"""Must return the base audio transcription call args"""
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pass
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@abstractmethod
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def get_custom_llm_provider(self) -> litellm.LlmProviders:
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"""Must return the custom llm provider"""
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pass
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def test_audio_transcription(self):
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"""
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Test that the audio transcription is translated correctly.
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"""
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litellm.set_verbose = True
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transcription_call_args = self.get_base_audio_transcription_call_args()
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transcript = transcription(**transcription_call_args, file=audio_file)
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print(f"transcript: {transcript.model_dump()}")
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print(f"transcript hidden params: {transcript._hidden_params}")
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assert transcript.text is not None
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def test_audio_transcription_optional_params(self):
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"""
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Test that the audio transcription is translated correctly.
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"""
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transcription_args = self.get_base_audio_transcription_call_args()
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model = transcription_args["model"]
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custom_llm_provider = self.get_custom_llm_provider()
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optional_params = get_supported_openai_params(
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model=model,
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custom_llm_provider=custom_llm_provider.value,
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request_type="transcription",
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)
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print(f"optional_params: {optional_params}")
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assert optional_params is not None
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assert (
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"max_completion_tokens" not in optional_params
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) # assert default chat completion response not returned
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def test_audio_transcription_config(self):
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"""
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Test that the audio transcription config is implemented and correctly instrumented.
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"""
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transcription_args = self.get_base_audio_transcription_call_args()
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model = transcription_args["model"]
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custom_llm_provider = self.get_custom_llm_provider()
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config = ProviderConfigManager.get_provider_audio_transcription_config(
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model=model,
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provider=custom_llm_provider,
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)
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print(f"config: {config}")
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assert config is not None
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assert isinstance(config, BaseAudioTranscriptionConfig)
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