Unverified Commit 269c457e authored by Michael Yao's avatar Michael Yao Committed by GitHub
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[Docs] Update runtime/engine/readme.md (#5737)


Signed-off-by: default avatarwindsonsea <haifeng.yao@daocloud.io>
parent 18ce468d
# SGLang Engine
## Introduction
SGLang provides a direct inference engine without the need for an HTTP server. There are generally two use cases:
SGLang provides a direct inference engine without the need for an HTTP server. There are generally these use cases:
1. **Offline Batch Inference**
2. **Embedding Generation**
3. **Custom Server on Top of the Engine**
4. **Inference Using FastAPI**
- [Offline Batch Inference](#offline-batch-inference)
- [Embedding Generation](#embedding-generation)
- [Custom Server](#custom-server)
- [Token-In-Token-Out for RLHF](#token-in-token-out-for-rlhf)
- [Inference Using FastAPI](#inference-using-fastapi)
## Examples
......@@ -22,28 +22,28 @@ In this example, we launch an SGLang engine and feed a batch of inputs for embed
This example demonstrates how to create a custom server on top of the SGLang Engine. We use [Sanic](https://sanic.dev/en/) as an example. The server supports both non-streaming and streaming endpoints.
#### Steps:
#### Steps
1. Install Sanic:
```bash
pip install sanic
```
```bash
pip install sanic
```
2. Run the server:
```bash
python custom_server
```
```bash
python custom_server
```
3. Send requests:
```bash
curl -X POST http://localhost:8000/generate -H "Content-Type: application/json" -d '{"prompt": "The Transformer architecture is..."}'
curl -X POST http://localhost:8000/generate_stream -H "Content-Type: application/json" -d '{"prompt": "The Transformer architecture is..."}' --no-buffer
```
```bash
curl -X POST http://localhost:8000/generate -H "Content-Type: application/json" -d '{"prompt": "The Transformer architecture is..."}'
curl -X POST http://localhost:8000/generate_stream -H "Content-Type: application/json" -d '{"prompt": "The Transformer architecture is..."}' --no-buffer
```
This will send both non-streaming and streaming requests to the server.
This will send both non-streaming and streaming requests to the server.
### [Token-In-Token-Out for RLHF](../token_in_token_out)
......
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