import argparse import markdown2 import os import sys import uvicorn from pathlib import Path from fastapi import FastAPI, Depends from fastapi.responses import HTMLResponse from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials from pydantic import BaseModel, Field from typing import Union from sse_starlette.sse import EventSourceResponse, ServerSentEvent from utils.logger import logger from networks.message_streamer import MessageStreamer from messagers.message_composer import MessageComposer from mocks.stream_chat_mocker import stream_chat_mock class ChatAPIApp: def __init__(self): self.app = FastAPI( docs_url="/", title="HuggingFace LLM API", swagger_ui_parameters={"defaultModelsExpandDepth": -1}, version="1.0", ) self.setup_routes() def get_available_models(self): # https://platform.openai.com/docs/api-reference/models/list # ANCHOR[id=available-models]: Available models self.available_models = { "object": "list", "data": [ { "id": "mixtral-8x7b", "description": "[mistralai/Mixtral-8x7B-Instruct-v0.1]: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1", "object": "model", "created": 1700000000, "owned_by": "mistralai", }, { "id": "mistral-7b", "description": "[mistralai/Mistral-7B-Instruct-v0.2]: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2", "object": "model", "created": 1700000000, "owned_by": "mistralai", }, { "id": "nous-mixtral-8x7b", "description": "[NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO]: https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", "object": "model", "created": 1700000000, "owned_by": "NousResearch", }, ], } return self.available_models def extract_api_key( credentials: HTTPAuthorizationCredentials = Depends( HTTPBearer(auto_error=False) ), ): api_key = None if credentials: api_key = credentials.credentials else: api_key = os.getenv("HF_TOKEN") if api_key: if api_key.startswith("hf_"): return api_key else: logger.warn(f"Invalid HF Token!") else: logger.warn("Not provide HF Token!") return None class ChatCompletionsPostItem(BaseModel): model: str = Field( default="mixtral-8x7b", description="(str) `mixtral-8x7b`", ) messages: list = Field( default=[{"role": "user", "content": "Hello, who are you?"}], description="(list) Messages", ) temperature: Union[float, None] = Field( default=0.5, description="(float) Temperature", ) top_p: Union[float, None] = Field( default=0.95, description="(float) top p", ) max_tokens: Union[int, None] = Field( default=-1, description="(int) Max tokens", ) use_cache: bool = Field( default=False, description="(bool) Use cache", ) stream: bool = Field( default=True, description="(bool) Stream", ) def chat_completions( self, item: ChatCompletionsPostItem, api_key: str = Depends(extract_api_key) ): streamer = MessageStreamer(model=item.model) composer = MessageComposer(model=item.model) composer.merge(messages=item.messages) # streamer.chat = stream_chat_mock stream_response = streamer.chat_response( prompt=composer.merged_str, temperature=item.temperature, top_p=item.top_p, max_new_tokens=item.max_tokens, api_key=api_key, use_cache=item.use_cache, ) if item.stream: event_source_response = EventSourceResponse( streamer.chat_return_generator(stream_response), media_type="text/event-stream", ping=2000, ping_message_factory=lambda: ServerSentEvent(**{"comment": ""}), ) return event_source_response else: data_response = streamer.chat_return_dict(stream_response) return data_response def get_readme(self): readme_path = Path(__file__).parents[1] / "README.md" with open(readme_path, "r", encoding="utf-8") as rf: readme_str = rf.read() readme_html = markdown2.markdown( readme_str, extras=["table", "fenced-code-blocks", "highlightjs-lang"] ) return readme_html def setup_routes(self): for prefix in ["", "/v1", "/api", "/api/v1"]: if prefix in ["/api/v1"]: include_in_schema = True else: include_in_schema = False self.app.get( prefix + "/models", summary="Get available models", include_in_schema=include_in_schema, )(self.get_available_models) self.app.post( prefix + "/chat/completions", summary="Chat completions in conversation session", include_in_schema=include_in_schema, )(self.chat_completions) self.app.get( "/readme", summary="README of HF LLM API", response_class=HTMLResponse, include_in_schema=False, )(self.get_readme) class ArgParser(argparse.ArgumentParser): def __init__(self, *args, **kwargs): super(ArgParser, self).__init__(*args, **kwargs) self.add_argument( "-s", "--server", type=str, default="0.0.0.0", help="Server IP for HF LLM Chat API", ) self.add_argument( "-p", "--port", type=int, default=23333, help="Server Port for HF LLM Chat API", ) self.add_argument( "-d", "--dev", default=False, action="store_true", help="Run in dev mode", ) self.args = self.parse_args(sys.argv[1:]) app = ChatAPIApp().app if __name__ == "__main__": args = ArgParser().args if args.dev: uvicorn.run("__main__:app", host=args.server, port=args.port, reload=True) else: uvicorn.run("__main__:app", host=args.server, port=args.port, reload=False) # python -m apis.chat_api # [Docker] on product mode # python -m apis.chat_api -d # [Dev] on develop mode