118 lines
4.1 KiB
Python
118 lines
4.1 KiB
Python
import sys
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from fastchat.conversation import Conversation
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from server.model_workers.base import ApiModelWorker
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from server.utils import get_model_worker_config, get_httpx_client
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from fastchat import conversation as conv
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import json
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from typing import List, Dict
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from configs import TEMPERATURE
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def request_azure_api(
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messages: List[Dict[str, str]],
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resource_name: str = None,
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api_key: str = None,
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deployment_name: str = None,
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api_version: str = "2023-07-01-preview",
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temperature: float = TEMPERATURE,
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max_tokens: int = None,
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model_name: str = "azure-api",
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):
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config = get_model_worker_config(model_name)
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data = dict(
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens,
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stream=True,
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)
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url = f"https://{resource_name}.openai.azure.com/openai/deployments/{deployment_name}/chat/completions?api-version={api_version}"
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headers = {
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'Content-Type': 'application/json',
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'Accept': 'application/json',
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'api-key': api_key,
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}
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with get_httpx_client() as client:
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with client.stream("POST", url, headers=headers, json=data) as response:
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for line in response.iter_lines():
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if not line.strip() or "[DONE]" in line:
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continue
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if line.startswith("data: "):
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line = line[6:]
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resp = json.loads(line)
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yield resp
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class AzureWorker(ApiModelWorker):
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def __init__(
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self,
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*,
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controller_addr: str,
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worker_addr: str,
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model_names: List[str] = ["azure-api"],
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version: str = "gpt-35-turbo",
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**kwargs,
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):
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kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
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kwargs.setdefault("context_len", 8192)
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super().__init__(**kwargs)
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config = self.get_config()
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self.resource_name = config.get("resource_name")
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self.api_key = config.get("api_key")
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self.api_version = config.get("api_version")
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self.version = version
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self.deployment_name = config.get("deployment_name")
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def generate_stream_gate(self, params):
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super().generate_stream_gate(params)
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messages = self.prompt_to_messages(params["prompt"])
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text = ""
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for resp in request_azure_api(messages=messages,
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resource_name=self.resource_name,
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api_key=self.api_key,
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api_version=self.api_version,
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deployment_name=self.deployment_name,
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temperature=params.get("temperature"),
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max_tokens=params.get("max_tokens")):
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if choices := resp["choices"]:
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if chunk := choices[0].get("delta", {}).get("content"):
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text += chunk
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yield json.dumps(
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{
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"error_code": 0,
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"text": text
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},
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ensure_ascii=False
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).encode() + b"\0"
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def get_embeddings(self, params):
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# TODO: 支持embeddings
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print("embedding")
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print(params)
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def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
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# TODO: 确认模板是否需要修改
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return conv.Conversation(
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name=self.model_names[0],
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system_message="",
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messages=[],
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roles=["user", "assistant"],
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sep="\n### ",
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stop_str="###",
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)
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if __name__ == "__main__":
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import uvicorn
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from server.utils import MakeFastAPIOffline
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from fastchat.serve.base_model_worker import app
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worker = AzureWorker(
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controller_addr="http://127.0.0.1:20001",
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worker_addr="http://127.0.0.1:21008",
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)
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sys.modules["fastchat.serve.model_worker"].worker = worker
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MakeFastAPIOffline(app)
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uvicorn.run(app, port=21008)
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