Commit 6a583c2f authored by chenych's avatar chenych
Browse files

update dtk to 24.04.1 and modify README

parent 7d576a9a
...@@ -57,6 +57,7 @@ async def generate(request: Request) -> Response: ...@@ -57,6 +57,7 @@ async def generate(request: Request) -> Response:
text_outputs = [ text_outputs = [
prompt + output.text for output in request_output.outputs prompt + output.text for output in request_output.outputs
] ]
print(text_outputs[0])
ret = {"text": text_outputs} ret = {"text": text_outputs}
yield (json.dumps(ret) + "\0").encode("utf-8") yield (json.dumps(ret) + "\0").encode("utf-8")
...@@ -80,6 +81,56 @@ async def generate(request: Request) -> Response: ...@@ -80,6 +81,56 @@ async def generate(request: Request) -> Response:
return JSONResponse(ret) return JSONResponse(ret)
@app.post("/generate1")
async def generate1(request: Request) -> Response:
"""Generate completion for the request.
The request should be a JSON object with the following fields:
- prompt: the prompt to use for the generation.
- stream: whether to stream the results or not.
- other fields: the sampling parameters (See `SamplingParams` for details).
"""
request_dict = await request.json()
prompt = request_dict.pop("prompt")
stream = request_dict.pop("stream", False)
sampling_params = SamplingParams(**request_dict)
request_id = random_uuid()
assert engine is not None
results_generator = engine.generate(prompt, sampling_params, request_id)
# Streaming case
async def stream_results():
async for request_output in results_generator:
prompt = request_output.prompt
# text_outputs = [
# prompt + output.text for output in request_output.outputs
# ]
# ret = {"text": text_outputs}
print(request_output)
yield '\n' + prompt + request_output.outputs[0].text
if stream:
return StreamingResponse(stream_results())
# Non-streaming case
final_output = None
async for request_output in results_generator:
if await request.is_disconnected():
# Abort the request if the client disconnects.
await engine.abort(request_id)
return Response(status_code=499)
final_output = request_output
assert final_output is not None
prompt = final_output.prompt
#text_outputs = [prompt[i] + output.text for i, output in enumerate(final_output.outputs)]
text_outputs = [output.text for i, output in enumerate(final_output.outputs)]
ret = {"text": text_outputs}
return JSONResponse(ret)
if __name__ == "__main__": if __name__ == "__main__":
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument("--host", type=str, default=None) parser.add_argument("--host", type=str, default=None)
......
import asyncio
import importlib
import inspect
import os
from contextlib import asynccontextmanager
from http import HTTPStatus
import json
import fastapi
import uvicorn
from fastapi import Request
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse, Response, StreamingResponse
from prometheus_client import make_asgi_app
import vllm
from vllm.engine.arg_utils import AsyncEngineArgs
from vllm.engine.async_llm_engine import AsyncLLMEngine
from vllm.entrypoints.openai.cli_args import make_arg_parser
from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
CompletionRequest, ErrorResponse)
from vllm.entrypoints.openai.serving_chat import OpenAIServingChat
from vllm.entrypoints.openai.serving_completion import OpenAIServingCompletion
from vllm.logger import init_logger
from vllm.usage.usage_lib import UsageContext
TIMEOUT_KEEP_ALIVE = 5 # seconds
openai_serving_chat: OpenAIServingChat = None
openai_serving_completion: OpenAIServingCompletion = None
logger = init_logger(__name__)
@asynccontextmanager
async def lifespan(app: fastapi.FastAPI):
async def _force_log():
while True:
await asyncio.sleep(10)
await engine.do_log_stats()
if not engine_args.disable_log_stats:
asyncio.create_task(_force_log())
yield
app = fastapi.FastAPI(lifespan=lifespan)
def parse_args():
parser = make_arg_parser()
return parser.parse_args()
# Add prometheus asgi middleware to route /metrics requests
metrics_app = make_asgi_app()
app.mount("/metrics", metrics_app)
@app.exception_handler(RequestValidationError)
async def validation_exception_handler(_, exc):
err = openai_serving_chat.create_error_response(message=str(exc))
return JSONResponse(err.model_dump(), status_code=HTTPStatus.BAD_REQUEST)
@app.get("/health")
async def health() -> Response:
"""Health check."""
await openai_serving_chat.engine.check_health()
return Response(status_code=200)
@app.get("/v1/models")
async def show_available_models():
models = await openai_serving_chat.show_available_models()
return JSONResponse(content=models.model_dump())
@app.get("/version")
async def show_version():
ver = {"version": vllm.__version__}
return JSONResponse(content=ver)
@app.post("/v1/chat/completions")
async def create_chat_completion(request: ChatCompletionRequest,
raw_request: Request):
generator = await openai_serving_chat.create_chat_completion(
request, raw_request)
if isinstance(generator, ErrorResponse):
return JSONResponse(content=generator.model_dump(),
status_code=generator.code)
if request.stream:
return StreamingResponse(content=generator,
media_type="text/event-stream")
else:
return JSONResponse(content=generator.model_dump())
@app.post("/v1/completions")
async def create_completion(request: CompletionRequest, raw_request: Request):
generator = await openai_serving_completion.create_completion(request, raw_request)
if isinstance(generator, ErrorResponse):
return JSONResponse(content=generator.model_dump(),
status_code=generator.code)
#async def stream_results1():
#async for i in generator:
#bb = i.replace('data:', '').strip()
#aa = json.loads(bb)
#print(aa["choices"][0]["text"])
#yield aa["choices"][0]["text"]
if request.stream:
#return StreamingResponse(content=stream_results1(), media_type="text/plain")
return StreamingResponse(content=generator, media_type="text/event-stream")
else:
return JSONResponse(content=generator.model_dump())
if __name__ == "__main__":
args = parse_args()
app.add_middleware(
CORSMiddleware,
allow_origins=args.allowed_origins,
allow_credentials=args.allow_credentials,
allow_methods=args.allowed_methods,
allow_headers=args.allowed_headers,
)
if token := os.environ.get("VLLM_API_KEY") or args.api_key:
@app.middleware("http")
async def authentication(request: Request, call_next):
root_path = "" if args.root_path is None else args.root_path
if not request.url.path.startswith(f"{root_path}/v1"):
return await call_next(request)
if request.headers.get("Authorization") != "Bearer " + token:
return JSONResponse(content={"error": "Unauthorized"},
status_code=401)
return await call_next(request)
for middleware in args.middleware:
module_path, object_name = middleware.rsplit(".", 1)
imported = getattr(importlib.import_module(module_path), object_name)
if inspect.isclass(imported):
app.add_middleware(imported)
elif inspect.iscoroutinefunction(imported):
app.middleware("http")(imported)
else:
raise ValueError(f"Invalid middleware {middleware}. "
f"Must be a function or a class.")
logger.info(f"vLLM API server version {vllm.__version__}")
logger.info(f"args: {args}")
if args.served_model_name is not None:
served_model = args.served_model_name
else:
served_model = args.model
engine_args = AsyncEngineArgs.from_cli_args(args)
engine = AsyncLLMEngine.from_engine_args(
engine_args, usage_context=UsageContext.OPENAI_API_SERVER)
openai_serving_chat = OpenAIServingChat(engine, served_model,
args.response_role,
args.lora_modules,
args.chat_template)
openai_serving_completion = OpenAIServingCompletion(
engine, served_model, args.lora_modules)
app.root_path = args.root_path
uvicorn.run(app,
host=args.host,
port=args.port,
log_level=args.uvicorn_log_level,
timeout_keep_alive=TIMEOUT_KEEP_ALIVE,
ssl_keyfile=args.ssl_keyfile,
ssl_certfile=args.ssl_certfile,
ssl_ca_certs=args.ssl_ca_certs,
ssl_cert_reqs=args.ssl_cert_reqs)
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