Files
sglang/docs/sampling_params.md
2024-01-31 10:18:43 -08:00

102 lines
2.5 KiB
Markdown

## Sampling Parameters of SGLang Runtime
This doc describes the sampling parameters of the SGLang Runtime.
The `/generate` endpoint accepts the following arguments in the JSON format.
```python
@dataclass
class GenerateReqInput:
# The input prompt
text: Union[List[str], str]
# The image input
image_data: Optional[Union[List[str], str]] = None
# The sampling_params
sampling_params: Union[List[Dict], Dict] = None
# The request id
rid: Optional[Union[List[str], str]] = None
# Whether return logprobs of the prompts
return_logprob: Optional[Union[List[bool], bool]] = None
# The start location of the prompt for return_logprob
logprob_start_len: Optional[Union[List[int], int]] = None
# Whether to stream output
stream: bool = False
```
The `sampling_params` follows this format
```python
class SamplingParams:
def __init__(
self,
max_new_tokens: int = 16,
stop: Optional[Union[str, List[str]]] = None,
temperature: float = 1.0,
top_p: float = 1.0,
top_k: int = -1,
frequency_penalty: float = 0.0,
presence_penalty: float = 0.0,
ignore_eos: bool = False,
skip_special_tokens: bool = True,
dtype: Optional[str] = None,
regex: Optional[str] = None,
) -> None:
```
## Examples
### Normal
```
python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port 30000
```
```python
import requests
response = requests.post(
"http://localhost:30000/generate",
json={
"text": "The capital of France is",
"sampling_params": {
"temperature": 0,
"max_new_tokens": 32,
},
},
)
print(response.json())
```
### Streaming
```python
import requests, json
response = requests.post(
"http://localhost:30000/generate",
json={
"text": "The capital of France is",
"sampling_params": {
"temperature": 0,
"max_new_tokens": 256,
},
"stream": True,
},
stream=True,
)
prev = 0
for chunk in response.iter_lines(decode_unicode=False):
chunk = chunk.decode("utf-8")
if chunk and chunk.startswith("data:"):
if chunk == "data: [DONE]":
break
data = json.loads(chunk[5:].strip("\n"))
output = data["text"].strip()
print(output[prev:], end="", flush=True)
prev = len(output)
print("")
```
### Multi modal
See [test_httpserver_llava.py](../test/srt/test_httpserver_llava.py).