llama-stack/llama_toolchain/inference/server.py
2024-07-23 08:32:33 -07:00

119 lines
3 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import asyncio
import signal
import fire
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException, Request
from fastapi.responses import StreamingResponse
from hydra_zen import instantiate
from llama_toolchain.utils import get_default_config_dir, parse_config
from .api.endpoints import ChatCompletionRequest, ChatCompletionResponseStreamChunk
from .api_instance import get_inference_api_instance
load_dotenv()
GLOBAL_CONFIG = None
def get_config():
return GLOBAL_CONFIG
def handle_sigint(*args, **kwargs):
print("SIGINT or CTRL-C detected. Exiting gracefully", args)
loop = asyncio.get_event_loop()
for task in asyncio.all_tasks(loop):
task.cancel()
loop.stop()
app = FastAPI()
@app.on_event("startup")
async def startup():
global InferenceApiInstance
config = get_config()
inference_config = instantiate(config["inference_config"])
InferenceApiInstance = await get_inference_api_instance(
inference_config,
)
await InferenceApiInstance.initialize()
@app.on_event("shutdown")
async def shutdown():
global InferenceApiInstance
print("shutting down")
await InferenceApiInstance.shutdown()
# there's a single model parallel process running serving the model. for now,
# we don't support multiple concurrent requests to this process.
semaphore = asyncio.Semaphore(1)
@app.post(
"/inference/chat_completion", response_model=ChatCompletionResponseStreamChunk
)
def chat_completion(request: Request, exec_request: ChatCompletionRequest):
if semaphore.locked():
raise HTTPException(
status_code=429,
detail="Only a single concurrent request allowed right now.",
)
async def sse_generator(event_gen):
try:
async for event in event_gen:
yield f"data: {event.json()}\n\n"
await asyncio.sleep(0.01)
except asyncio.CancelledError:
print("Generator cancelled")
await event_gen.aclose()
finally:
semaphore.release()
async def event_gen():
async for event in InferenceApiInstance.chat_completion(exec_request):
yield event
return StreamingResponse(
sse_generator(event_gen()),
media_type="text/event-stream",
)
def main(config_path: str, port: int = 5000, disable_ipv6: bool = False):
global GLOBAL_CONFIG
config_dir = get_default_config_dir()
GLOBAL_CONFIG = parse_config(config_dir, config_path)
signal.signal(signal.SIGINT, handle_sigint)
import uvicorn
# FYI this does not do hot-reloads
listen_host = "::" if not disable_ipv6 else "0.0.0.0"
print(f"Listening on {listen_host}:{port}")
uvicorn.run(app, host=listen_host, port=port)
if __name__ == "__main__":
fire.Fire(main)