/audio/transcriptions

Overview

Feature	Supported	Notes
Cost Tracking	✅
Logging	✅	works across all integrations
End-user Tracking	✅
Fallbacks	✅	between supported models
Loadbalancing	✅	between supported models
Support llm providers	openai, azure, vertex_ai, gemini, deepgram, groq, fireworks_ai

Quick Start

LiteLLM Python SDK

Python SDK Example

from litellm import transcription
import os 

# set api keys 
os.environ["OPENAI_API_KEY"] = ""
audio_file = open("/path/to/audio.mp3", "rb")

response = transcription(model="whisper", file=audio_file)

print(f"response: {response}")

LiteLLM Proxy

Add model to config

OpenAI

OpenAI Configuration

model_list:
- model_name: whisper
  litellm_params:
    model: whisper-1
    api_key: os.environ/OPENAI_API_KEY
  model_info:
    mode: audio_transcription
    
general_settings:
  master_key: sk-1234

OpenAI + Azure

OpenAI + Azure Configuration

model_list:
- model_name: whisper
  litellm_params:
    model: whisper-1
    api_key: os.environ/OPENAI_API_KEY
  model_info:
    mode: audio_transcription
- model_name: whisper
  litellm_params:
    model: azure/azure-whisper
    api_version: 2024-02-15-preview
    api_base: os.environ/AZURE_EUROPE_API_BASE
    api_key: os.environ/AZURE_EUROPE_API_KEY
  model_info:
    mode: audio_transcription

general_settings:
  master_key: sk-1234

Start proxy

Start Proxy Server

litellm --config /path/to/config.yaml 

# RUNNING on http://0.0.0.0:8000

Test

Curl

Test with cURL

curl --location 'http://0.0.0.0:8000/v1/audio/transcriptions' \
--header 'Authorization: Bearer sk-1234' \
--form 'file=@"/Users/krrishdholakia/Downloads/gettysburg.wav"' \
--form 'model="whisper"'

OpenAI Python SDK

Test with OpenAI Python SDK

from openai import OpenAI
client = openai.OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:8000"
)


audio_file = open("speech.mp3", "rb")
transcript = client.audio.transcriptions.create(
  model="whisper",
  file=audio_file
)

Supported Providers

• OpenAI
• Azure
• Fireworks AI
• Groq
• Deepgram

---

Fallbacks

You can configure fallbacks for audio transcription to automatically retry with different models if the primary model fails.

Curl

Test with cURL and Fallbacks

curl --location 'http://0.0.0.0:4000/v1/audio/transcriptions' \
--header 'Authorization: Bearer sk-1234' \
--form 'file=@"gettysburg.wav"' \
--form 'model="groq/whisper-large-v3"' \
--form 'fallbacks[]="openai/whisper-1"'

OpenAI Python SDK

Test with OpenAI Python SDK and Fallbacks

from openai import OpenAI
client = OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:4000"
)

audio_file = open("gettysburg.wav", "rb")
transcript = client.audio.transcriptions.create(
    model="groq/whisper-large-v3",
    file=audio_file,
    extra_body={
        "fallbacks": ["openai/whisper-1"]
    }
)

Testing Fallbacks

You can test your fallback configuration using mock_testing_fallbacks=true to simulate failures:

Curl

Test Fallbacks with Mock Testing

curl --location 'http://0.0.0.0:4000/v1/audio/transcriptions' \
--header 'Authorization: Bearer sk-1234' \
--form 'file=@"gettysburg.wav"' \
--form 'model="groq/whisper-large-v3"' \
--form 'fallbacks[]="openai/whisper-1"' \
--form 'mock_testing_fallbacks=true'

OpenAI Python SDK

Test Fallbacks with Mock Testing

from openai import OpenAI
client = OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:4000"
)

audio_file = open("gettysburg.wav", "rb")
transcript = client.audio.transcriptions.create(
    model="groq/whisper-large-v3",
    file=audio_file,
    extra_body={
        "fallbacks": ["openai/whisper-1"],
        "mock_testing_fallbacks": True
    }
)