import sys from fastchat.conversation import Conversation from .base import * # from server.utils import get_httpx_client from cachetools import cached, TTLCache import json from fastchat import conversation as conv import sys from typing import List, Literal, Dict from configs import logger, log_verbose MODEL_VERSIONS = { "ernie-bot-4": "completions_pro", "ernie-bot": "completions", "ernie-bot-turbo": "eb-instant", "bloomz-7b": "bloomz_7b1", "qianfan-bloomz-7b-c": "qianfan_bloomz_7b_compressed", "llama2-7b-chat": "llama_2_7b", "llama2-13b-chat": "llama_2_13b", "llama2-70b-chat": "llama_2_70b", "qianfan-llama2-ch-7b": "qianfan_chinese_llama_2_7b", "chatglm2-6b-32k": "chatglm2_6b_32k", "aquilachat-7b": "aquilachat_7b", # "linly-llama2-ch-7b": "", # 暂未发布 # "linly-llama2-ch-13b": "", # 暂未发布 # "chatglm2-6b": "", # 暂未发布 # "chatglm2-6b-int4": "", # 暂未发布 # "falcon-7b": "", # 暂未发布 # "falcon-180b-chat": "", # 暂未发布 # "falcon-40b": "", # 暂未发布 # "rwkv4-world": "", # 暂未发布 # "rwkv5-world": "", # 暂未发布 # "rwkv4-pile-14b": "", # 暂未发布 # "rwkv4-raven-14b": "", # 暂未发布 # "open-llama-7b": "", # 暂未发布 # "dolly-12b": "", # 暂未发布 # "mpt-7b-instruct": "", # 暂未发布 # "mpt-30b-instruct": "", # 暂未发布 # "OA-Pythia-12B-SFT-4": "", # 暂未发布 # "xverse-13b": "", # 暂未发布 # # 以下为企业测试，需要单独申请 # "flan-ul2": "", # "Cerebras-GPT-6.7B": "" # "Pythia-6.9B": "" } @cached(TTLCache(1, 1800)) # 经过测试，缓存的token可以使用，目前每30分钟刷新一次 def get_baidu_access_token(api_key: str, secret_key: str) -> str: """ 使用 AK，SK 生成鉴权签名（Access Token） :return: access_token，或是None(如果错误) """ url = "https://aip.baidubce.com/oauth/2.0/token" params = {"grant_type": "client_credentials", "client_id": api_key, "client_secret": secret_key} try: with get_httpx_client() as client: return client.get(url, params=params).json().get("access_token") except Exception as e: print(f"failed to get token from baidu: {e}") class QianFanWorker(ApiModelWorker): """ 百度千帆 """ DEFAULT_EMBED_MODEL = "embedding-v1" def __init__( self, *, version: Literal["ernie-bot", "ernie-bot-turbo"] = "ernie-bot", model_names: List[str] = ["qianfan-api"], controller_addr: str = None, worker_addr: str = None, **kwargs, ): kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr) kwargs.setdefault("context_len", 16384) super().__init__(**kwargs) self.version = version def do_chat(self, params: ApiChatParams) -> Dict: params.load_config(self.model_names[0]) # import qianfan # comp = qianfan.ChatCompletion(model=params.version, # endpoint=params.version_url, # ak=params.api_key, # sk=params.secret_key,) # text = "" # for resp in comp.do(messages=params.messages, # temperature=params.temperature, # top_p=params.top_p, # stream=True): # if resp.code == 200: # if chunk := resp.body.get("result"): # text += chunk # yield { # "error_code": 0, # "text": text # } # else: # yield { # "error_code": resp.code, # "text": str(resp.body), # } BASE_URL = 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat' \ '/{model_version}?access_token={access_token}' access_token = get_baidu_access_token(params.api_key, params.secret_key) if not access_token: yield { "error_code": 403, "text": f"failed to get access token. have you set the correct api_key and secret key?", } url = BASE_URL.format( model_version=params.version_url or MODEL_VERSIONS[params.version.lower()], access_token=access_token, ) payload = { "messages": params.messages, "temperature": params.temperature, "stream": True } headers = { 'Content-Type': 'application/json', 'Accept': 'application/json', } text = "" if log_verbose: logger.info(f'{self.__class__.__name__}:data: {payload}') logger.info(f'{self.__class__.__name__}:url: {url}') logger.info(f'{self.__class__.__name__}:headers: {headers}') with get_httpx_client() as client: with client.stream("POST", url, headers=headers, json=payload) as response: for line in response.iter_lines(): if not line.strip(): continue if line.startswith("data: "): line = line[6:] resp = json.loads(line) if "result" in resp.keys(): text += resp["result"] yield { "error_code": 0, "text": text } else: data = { "error_code": resp["error_code"], "text": resp["error_msg"], "error": { "message": resp["error_msg"], "type": "invalid_request_error", "param": None, "code": None, } } self.logger.error(f"请求千帆 API 时发生错误：{data}") yield data def do_embeddings(self, params: ApiEmbeddingsParams) -> Dict: params.load_config(self.model_names[0]) # import qianfan # embed = qianfan.Embedding(ak=params.api_key, sk=params.secret_key) # resp = embed.do(texts = params.texts, model=params.embed_model or self.DEFAULT_EMBED_MODEL) # if resp.code == 200: # embeddings = [x.embedding for x in resp.body.get("data", [])] # return {"code": 200, "embeddings": embeddings} # else: # return {"code": resp.code, "msg": str(resp.body)} embed_model = params.embed_model or self.DEFAULT_EMBED_MODEL access_token = get_baidu_access_token(params.api_key, params.secret_key) url = f"https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/{embed_model}?access_token={access_token}" if log_verbose: logger.info(f'{self.__class__.__name__}:url: {url}') with get_httpx_client() as client: result = [] i = 0 batch_size = 10 while i < len(params.texts): texts = params.texts[i:i+batch_size] resp = client.post(url, json={"input": texts}).json() if "error_code" in resp: data = { "code": resp["error_code"], "msg": resp["error_msg"], "error": { "message": resp["error_msg"], "type": "invalid_request_error", "param": None, "code": None, } } self.logger.error(f"请求千帆 API 时发生错误：{data}") return data else: embeddings = [x["embedding"] for x in resp.get("data", [])] result += embeddings i += batch_size return {"code": 200, "data": result} # TODO: qianfan支持续写模型 def get_embeddings(self, params): # TODO: 支持embeddings print("embedding") print(params) def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation: # TODO: 确认模板是否需要修改 return conv.Conversation( name=self.model_names[0], system_message="你是一个聪明的助手，请根据用户的提示来完成任务", messages=[], roles=["user", "assistant"], sep="\n### ", stop_str="###", ) if __name__ == "__main__": import uvicorn from server.utils import MakeFastAPIOffline from fastchat.serve.model_worker import app worker = QianFanWorker( controller_addr="http://127.0.0.1:20001", worker_addr="http://127.0.0.1:21004" ) sys.modules["fastchat.serve.model_worker"].worker = worker MakeFastAPIOffline(app) uvicorn.run(app, port=21004)