> ## Documentation Index
> Fetch the complete documentation index at: https://assembly-preview.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 🦜️🔗 LangChain Python Integration with AssemblyAI

> To apply LLMs to speech, you first need to transcribe the audio to text, which is what the AssemblyAI integration for LangChain helps you with.

<Note>
  Looking for the LangChain JavaScript/TypeScript integration? [Go to the LangChain.JS integration](/docs/integrations/langchain/js).
</Note>

## Quickstart

Install [the AssemblyAI package](https://github.com/langchain-ai/langchain) and [the AssemblyAI Python SDK](https://github.com/AssemblyAI/assemblyai-python-sdk):

```
pip install langchain
pip install assemblyai
```

Set your AssemblyAI API key as an environment variable named `ASSEMBLYAI_API_KEY`. You can [get a free AssemblyAI API key from the AssemblyAI dashboard](https://www.assemblyai.com/dashboard/signup).

```
# Mac/Linux:
export ASSEMBLYAI_API_KEY=YOUR_API_KEY

# Windows:
set ASSEMBLYAI_API_KEY=YOUR_API_KEY
```

Import the `AssemblyAIAudioTranscriptLoader` from `langchain.document_loaders`.

```
from langchain.document_loaders import AssemblyAIAudioTranscriptLoader
```

1. Pass the local file path or URL as the `file_path` argument of the `AssemblyAIAudioTranscriptLoader`.
2. Call the `load` method to get the transcript as LangChain documents.

```python theme={"system"}
audio_file = "https://assembly.ai/sports_injuries.mp3"
# or a local file path: audio_file = "./sports_injuries.mp3"

loader = AssemblyAIAudioTranscriptLoader(file_path=audio_file)

docs = loader.load()
```

The `load` method returns an array of documents, but by default, there's only one document in the array with the full transcript.

The transcribed text is available in the `page_content` attribute:

```
docs[0].page_content# Load time, a new president and new congressional makeup. Same old ...
```

The `metadata` contains the full JSON response with more meta information:

```python theme={"system"}
{
  'language_code': <LanguageCode.en_us: 'en_us'>,
  'audio_url': 'https://assembly.ai/nbc.mp3',
  'punctuate': True,
  'format_text': True,
  ...
}
```

## Transcript formats

You can specify the `transcript_format` argument to load the transcript in different formats.

Depending on the format, `load_data()` returns either one or more documents. These are the different `TranscriptFormat` options:

* `TEXT`: One document with the transcription text
* `SENTENCES`: Multiple documents, splits the transcription by each sentence
* `PARAGRAPHS`: Multiple documents, splits the transcription by each paragraph
* `SUBTITLES_SRT`: One document with the transcript exported in SRT subtitles format
* `SUBTITLES_VTT`: One document with the transcript exported in VTT subtitles format

```python theme={"system"}
from langchain.document_loaders.assemblyai import TranscriptFormat

loader = AssemblyAIAudioTranscriptLoader(
    file_path="./your_file.mp3",
    transcript_format=TranscriptFormat.SENTENCES,
)

docs = loader.load()
```

## Transcription config

You can also specify the `config` argument to use different transcript features and audio intelligence models. Here's an example of using the `config` argument to enable speaker labels, auto chapters, and entity detection:

```python theme={"system"}
import assemblyai as aai

config = aai.TranscriptionConfig(
    speaker_labels=True, auto_chapters=True, entity_detection=True
)

loader = AssemblyAIAudioTranscriptLoader(file_path="./your_file.mp3", config=config)
```

<Info>
  For the full list of options, see [Transcript API reference](https://assemblyai.com/docs/api-reference/transcripts/submit#request).
</Info>

## Pass the AssemblyAI API key as an argument

Instead of configuring the AssemblyAI API key as the `ASSEMBLYAI_API_KEY` environment variable, you can also pass it as the `api_key` argument.

```python theme={"system"}
loader = AssemblyAIAudioTranscriptLoader(
    file_path="./your_file.mp3", api_key="YOUR_API_KEY"
)
```

## Additional resources[​](#additional-resources "Direct link to Additional resources")

You can learn more about using LangChain with AssemblyAI in these resources.

* [LangChain docs for the AssemblyAI document loader](https://python.langchain.com/docs/integrations/document_loaders/assemblyai)
* [How to use audio data in LangChain with Python](https://www.assemblyai.com/blog/load-audio-langchain-python/)
* [Retrieval Augmented Generation on audio data with LangChain and Chroma](https://www.assemblyai.com/blog/retrieval-augmented-generation-audio-langchain/)
* [Build LangChain Audio Apps with Python in 5 Minutes](https://www.youtube.com/watch?v=7w7ysaDz2W4)
* [How to use LangChain for RAG over audio files](https://www.youtube.com/watch?v=l9YJrLg61ac)
* [AssemblyAI Python SDK](https://github.com/AssemblyAI/assemblyai-python-sdk)