
Most common position in a pipeline	As the first component in an indexing pipeline
Mandatory init variables	"api_key": An OpenAI API key. Can be set with an environment variable `OPENAI_API_KEY`.
Mandatory run variables	“sources”: A list of paths or binary streams that you want to transcribe
Output variables	“documents”: A list of documents
API reference	Audio
GitHub link	https://github.com/deepset-ai/haystack/blob/main/haystack/components/audio/whisper_remote.py

Overview

RemoteWhisperTranscriber works with OpenAI-compatible clients and isn't limited to just OpenAI as a provider. For example, Groq offers a drop-in replacement that can be used as well. You can set the API key in one of two ways:

Through the api_key initialization parameter, where the key is resolved using Secret API.
By setting it in the OPENAI_API_KEY environment variable, which the system will use to access the key.

from haystack.components.audio import RemoteWhisperTranscriber

transcriber = RemoteWhisperTranscriber()

Additionally, the component requires the following parameters to work:

model specifies the Whisper model.
api_base_url specifies the OpenAI base URL and defaults to "<https://api.openai.com/v1>". If you are using Whisper provider other than OpenAI set this parameter according to provider's documentation.

See other optional parameters in our API documentation.

See the Whisper API documentation and the official Whisper GitHub repo for the supported audio formats and languages.

Usage

On its own

Here’s an example of how to use RemoteWhisperTranscriber to transcribe a local file:

import requests
from haystack.components.audio import RemoteWhisperTranscriber

response = requests.get("https://ia903102.us.archive.org/19/items/100-Best--Speeches/EK_19690725_64kb.mp3")
with open("kennedy_speech.mp3", "wb") as file:
    file.write(response.content)
    
transcriber = RemoteWhisperTranscriber()
transcription = transcriber.run(sources=["./kennedy_speech.mp3"])

print(transcription["documents"][0].content)

In a pipeline

The pipeline below fetches an audio file from a specified URL and transcribes it. It first retrieves the audio file using LinkContentFetcher, then transcribes the audio into text with RemoteWhisperTranscriber, and finally outputs the transcription text.

from haystack.components.audio import RemoteWhisperTranscriber
from haystack.components.fetchers import LinkContentFetcher
from haystack import Pipeline

pipe = Pipeline()
pipe.add_component("fetcher", LinkContentFetcher())
pipe.add_component("transcriber", RemoteWhisperTranscriber())

pipe.connect("fetcher", "transcriber")
result = pipe.run(
    data={"fetcher": {"urls": ["https://ia903102.us.archive.org/19/items/100-Best--Speeches/EK_19690725_64kb.mp3"]}})
print(result["transcriber"]["documents"][0].content)

Additional References

🧑‍🍳 Cookbook: Multilingual RAG from a podcast with Whisper, Qdrant and Mistral