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

# AssemblyAI

> Deploy AssemblyAI speech-to-text services on Cerebrium

<Note>
  AssemblyAI Partner Service is available from CLI version 1.51.0 and greater
</Note>

Cerebrium's partnership with [AssemblyAI](https://www.assemblyai.com/) helps teams deliver speech-to-text (STT) services with efficient deployment, minimized latency, and region selection for data privacy compliance needs.

## Setup

1. Contact the AssemblyAI team in order to get a self-hosted Contract. You can contact them [here](support@assemblyai.com)

2. Create a simple cerebrium app with the CLI:

```bash theme={null}
cerebrium init assembly-ai
```

3. AssemblyAI services use a simplified TOML configuration with the `[cerebrium.runtime.assemblyai]` section. Create a `cerebrium.toml` file with the following:

```toml theme={null}
[cerebrium.deployment]
name = "assembly-ai"
disable_auth = true

[cerebrium.runtime.assemblyai]
port = 8080
model_name = "english"

[cerebrium.hardware]
cpu = 4
memory = 16
compute = "AMPERE_A10"
gpu_count = 1
region = "us-east-1"

[cerebrium.scaling]
min_replicas = 1
max_replicas = 3
cooldown = 120
replica_concurrency = 32
scaling_metric = "concurrency_utilization"
scaling_target = 70
```

<Note>
  The above disables auth meaning anyone can make requests to your endpoint. If
  you set disable\_auth=false, then you need to use the API key from your
  Cerebrium Dashboard. key
</Note>

4. Run `cerebrium deploy` to deploy the AssemblyAI service - the output of which should appear as follows:

```
App Dashboard: https://dashboard.cerebrium.ai/projects/p-xxxxxxxx/apps/p-xxxxxxxx-assembly-ai
```

5. Use the Deployment url from the output to send requests to the <b>WS</b> AssemblyAI service. We can use their [example repo](https://github.com/AssemblyAI/streaming-self-hosting-stack) to test its working

```
1. git clone https://github.com/AssemblyAI/streaming-self-hosting-stack.git
2. cd streaming_example && python example_with_prerecorded_audio_file.py --audio-file example_audio_file.wav --endpoint wss://api.aws.us-east-1.cerebrium.ai/v4/p-xxxxxx/assembly-ai --language english
```

You should then see the following output:

```
0:00:01.040000-0:00:01.200000, end-of-turn: False: it's true
0:00:01.040000-0:00:01.280000, end-of-turn: False: it's true that
0:00:01.040000-0:00:01.600000, end-of-turn: False: it's true that assem
0:00:01.040000-0:00:01.680000, end-of-turn: False: it's true that assembly
0:00:01.040000-0:00:02.080000, end-of-turn: False: it's true that assembly a
0:00:01.040000-0:00:02.160000, end-of-turn: False: it's true that assembly ai
0:00:01.040000-0:00:02.320000, end-of-turn: False: it's true that assembly ai lets
0:00:01.040000-0:00:02.400000, end-of-turn: False: it's true that assembly ai lets you
0:00:01.040000-0:00:02.560000, end-of-turn: False: it's true that assembly ai lets you build
```

## Scaling and Concurrency

AssemblyAI services support independent scaling configurations:

* **min\_replicas**: Minimum instances to maintain (0 for scale-to-zero). Recommended: 1.
* **max\_replicas**: Maximum instances during high load.
* **replica\_concurrency**: Concurrent requests per instance. Recommended: 3.
* **cooldown**: Seconds an instance remains active after last request. Recommended: 32.
* **compute**: Instance type. Recommended: `AMPERE_A10`.

Adjust these parameters based on traffic patterns and latency requirements. Best would be to consult the Rime team
about concurrency and scalability

For further documentation on AssemblyAI, see the [AssemblyAI documentation](https://www.assemblyai.com/docs/deployment/self-hosted-streaming#getting-the-latest-instructions).