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98 lines
4.0 KiB
Plaintext
98 lines
4.0 KiB
Plaintext
---
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title: "RemoteWhisperTranscriber"
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id: remotewhispertranscriber
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slug: "/remotewhispertranscriber"
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description: "Use `RemoteWhisperTranscriber` to transcribe audio files using OpenAI's Whisper model."
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---
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# RemoteWhisperTranscriber
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Use `RemoteWhisperTranscriber` to transcribe audio files using OpenAI's Whisper model.
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<div className="key-value-table">
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| | |
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| --- | --- |
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| **Most common position in a pipeline** | As the first component in an indexing pipeline |
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| **Mandatory init variables** | `api_key`: An OpenAI API key. Can be set with an environment variable `OPENAI_API_KEY`. |
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| **Mandatory run variables** | `sources`: A list of paths or binary streams that you want to transcribe |
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| **Output variables** | `documents`: A list of documents |
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| **API reference** | [Audio](/reference/audio-api) |
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| **GitHub link** | https://github.com/deepset-ai/haystack/blob/main/haystack/components/audio/whisper_remote.py |
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</div>
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## Overview
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`RemoteWhisperTranscriber` works with OpenAI-compatible clients and isn't limited to just OpenAI as a provider. For example, [Groq](https://console.groq.com/docs/speech-text) offers a drop-in replacement that can be used as well. You can set the API key in one of two ways:
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1. Through the `api_key` initialization parameter, where the key is resolved using [Secret API](../../concepts/secret-management.mdx).
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2. By setting it in the `OPENAI_API_KEY` environment variable, which the system will use to access the key.
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```python
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from haystack.components.audio import RemoteWhisperTranscriber
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transcriber = RemoteWhisperTranscriber()
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```
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Additionally, the component requires the following parameters to work:
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- `model` specifies the Whisper model.
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- `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.
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See other optional parameters in our [API documentation](/reference/audio-api).
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See the [Whisper API documentation](https://platform.openai.com/docs/guides/speech-to-text) and the official Whisper [GitHub repo](https://github.com/openai/whisper) for the supported audio formats and languages.
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## Usage
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### On its own
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Here’s an example of how to use `RemoteWhisperTranscriber` to transcribe a local file:
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```python
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import requests
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from haystack.components.audio import RemoteWhisperTranscriber
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response = requests.get(
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"https://ia903102.us.archive.org/19/items/100-Best--Speeches/EK_19690725_64kb.mp3",
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)
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with open("kennedy_speech.mp3", "wb") as file:
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file.write(response.content)
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transcriber = RemoteWhisperTranscriber()
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transcription = transcriber.run(sources=["./kennedy_speech.mp3"])
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print(transcription["documents"][0].content)
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```
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### In a pipeline
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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.
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```python
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from haystack.components.audio import RemoteWhisperTranscriber
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from haystack.components.fetchers import LinkContentFetcher
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from haystack import Pipeline
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pipe = Pipeline()
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pipe.add_component("fetcher", LinkContentFetcher())
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pipe.add_component("transcriber", RemoteWhisperTranscriber())
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pipe.connect("fetcher", "transcriber")
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result = pipe.run(
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data={
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"fetcher": {
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"urls": [
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"https://ia903102.us.archive.org/19/items/100-Best--Speeches/EK_19690725_64kb.mp3",
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],
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},
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},
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)
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print(result["transcriber"]["documents"][0].content)
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```
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## Additional References
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🧑🍳 Cookbook: [Multilingual RAG from a podcast with Whisper, Qdrant and Mistral](https://haystack.deepset.ai/cookbook/multilingual_rag_podcast)
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