/audio/transcriptions

Overview

Feature	Supported	Notes
Cost Tracking	✅	Works with all supported models
Logging	✅	Works across all integrations
End-user Tracking	✅
Fallbacks	✅	Works between supported models
Loadbalancing	✅	Works between supported models
Guardrails	✅	Applies to output transcribed text (non-streaming only)
Supported Providers	openai, azure, vertex_ai, gemini, deepgram, groq, fireworks_ai, ovhcloud, mistral

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
• Mistral (Voxtral)
• OVHcloud AI Endpoints

---

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

Deprecated for Proxy requests

Starting in LiteLLM Proxy v1.85.0, mock_testing_fallbacks is stripped from incoming Proxy requests and has no effect. It remains supported only for direct litellm.Router calls in tests.

To validate audio transcription fallbacks through the Proxy, trigger an actual provider error in a non-production environment and send a normal request with the fallback configuration.