This is the base PyWorker for HuggingFace Text Generation Inference (TGI) servers. See the [Serverless documentation](https://docs.vast.ai/serverless) for guides and how-to's.
The template can be configured via the template interface. You may want to change the model or startup arguments.
2. Follow the [getting started guide](https://docs.vast.ai/documentation/serverless/quickstart) for help with configuring your serverless setup. For testing, we recommend that you use the default options presented by the web interface.
## Client Setup (Demo)
1. Clone the PyWorker repository to your local machine and install the necessary requirements for running the test client.
```bash
git clone https://github.com/vast-ai/pyworker
cd pyworker
pip install uv
uv venv -p 3.12
source .venv/bin/activate
uv pip install -r requirements.txt
```
## Using the Test Client
The test client demonstrates both streaming and non-streaming generation using TGI's native API.
First, set your API key as an environment variable:
```bash
exportVAST_API_KEY=<your_api_key>
```
The `--endpoint` flag is optional. If not provided, it defaults to `my-tgi-endpoint`.
### Generate (Streaming)
Call to `/generate_stream` with streaming response:
`/generate_stream` - Streams the response token by token.
```json
{
"inputs":"Your prompt here",
"parameters":{
"max_new_tokens":1024,
"temperature":0.7,
"do_sample":true,
"return_full_text":false
}
}
```
## Performance Notes
The `max_new_tokens` parameter (not the prompt size) primarily impacts performance. For example, if an instance is benchmarked to process 100 tokens per second, a request with `max_new_tokens = 200` will take approximately 2 seconds to complete.