124 lines
4.3 KiB
Python
124 lines
4.3 KiB
Python
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import sys
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from fastchat.conversation import Conversation
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from server.model_workers.base import *
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from server.utils import get_httpx_client
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from fastchat import conversation as conv
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import json, httpx
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from typing import List, Dict
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from configs import logger, log_verbose
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class GeminiWorker(ApiModelWorker):
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def __init__(
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self,
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*,
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controller_addr: str = None,
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worker_addr: str = None,
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model_names: List[str] = ["gemini-api"],
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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", 4096)
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super().__init__(**kwargs)
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def create_gemini_messages(self, messages) -> json:
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has_history = any(msg['role'] == 'assistant' for msg in messages)
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gemini_msg = []
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for msg in messages:
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role = msg['role']
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content = msg['content']
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if role == 'system':
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continue
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if has_history:
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if role == 'assistant':
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role = "model"
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transformed_msg = {"role": role, "parts": [{"text": content}]}
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else:
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if role == 'user':
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transformed_msg = {"parts": [{"text": content}]}
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gemini_msg.append(transformed_msg)
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msg = dict(contents=gemini_msg)
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return msg
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def do_chat(self, params: ApiChatParams) -> Dict:
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params.load_config(self.model_names[0])
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data = self.create_gemini_messages(messages=params.messages)
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generationConfig = dict(
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temperature=params.temperature,
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topK=1,
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topP=1,
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maxOutputTokens=4096,
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stopSequences=[]
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)
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data['generationConfig'] = generationConfig
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url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent" + '?key=' + params.api_key
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headers = {
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'Content-Type': 'application/json',
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}
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if log_verbose:
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logger.info(f'{self.__class__.__name__}:url: {url}')
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logger.info(f'{self.__class__.__name__}:headers: {headers}')
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logger.info(f'{self.__class__.__name__}:data: {data}')
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text = ""
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json_string = ""
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timeout = httpx.Timeout(60.0)
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client = get_httpx_client(timeout=timeout)
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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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line = line.strip()
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if not line or "[DONE]" in line:
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continue
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json_string += line
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try:
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resp = json.loads(json_string)
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if 'candidates' in resp:
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for candidate in resp['candidates']:
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content = candidate.get('content', {})
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parts = content.get('parts', [])
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for part in parts:
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if 'text' in part:
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text += part['text']
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yield {
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"error_code": 0,
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"text": text
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}
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print(text)
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except json.JSONDecodeError as e:
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print("Failed to decode JSON:", e)
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print("Invalid JSON string:", json_string)
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def get_embeddings(self, params):
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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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return conv.Conversation(
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name=self.model_names[0],
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system_message="You are a helpful, respectful and honest assistant.",
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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 = GeminiWorker(
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controller_addr="http://127.0.0.1:20001",
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worker_addr="http://127.0.0.1:21012",
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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=21012)
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