Files
pipelines/prompt_bench/vllm_client.py
2026-04-13 15:43:01 -04:00

69 lines
2.1 KiB
Python

"""OpenAI-compatible client for vLLM's API."""
from __future__ import annotations
import logging
import time
from typing import Self
import httpx
logger = logging.getLogger(__name__)
READY_POLL_INTERVAL = 2.0
class VLLMClient:
"""Talk to a vLLM server via its OpenAI-compatible API.
Args:
host: vLLM host.
port: vLLM port.
timeout: Per-request timeout in seconds.
"""
def __init__(self, *, host: str = "localhost", port: int = 8000, timeout: int = 300) -> None:
"""Create a client connected to a vLLM server."""
self._client = httpx.Client(base_url=f"http://{host}:{port}", timeout=timeout)
def wait_ready(self, max_wait: int) -> None:
"""Poll /v1/models until the server is ready or timeout."""
deadline = time.monotonic() + max_wait
while time.monotonic() < deadline:
try:
response = self._client.get("/v1/models")
if response.is_success:
logger.info("vLLM server is ready")
return
except httpx.TransportError:
pass
time.sleep(READY_POLL_INTERVAL)
msg = f"vLLM server not ready after {max_wait}s"
raise TimeoutError(msg)
def complete(self, prompt: str, model: str, *, temperature: float = 0.0, max_tokens: int = 4096) -> str:
"""Send a prompt to /v1/completions and return the response text."""
payload = {
"model": model,
"prompt": prompt,
"temperature": temperature,
"max_tokens": max_tokens,
}
logger.info("Sending prompt to %s (%d chars)", model, len(prompt))
response = self._client.post("/v1/completions", json=payload)
response.raise_for_status()
data = response.json()
return data["choices"][0]["text"]
def close(self) -> None:
"""Close the HTTP client."""
self._client.close()
def __enter__(self) -> Self:
"""Enter the context manager."""
return self
def __exit__(self, *args: object) -> None:
"""Close the HTTP client on exit."""
self.close()