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83 lines
2.9 KiB
Python
83 lines
2.9 KiB
Python
#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from abc import ABC
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from openai import OpenAI
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import openai
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class Base(ABC):
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def __init__(self, key, model_name):
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pass
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def chat(self, system, history, gen_conf):
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raise NotImplementedError("Please implement encode method!")
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class GptTurbo(Base):
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def __init__(self, key, model_name="gpt-3.5-turbo"):
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self.client = OpenAI(api_key=key)
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self.model_name = model_name
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def chat(self, system, history, gen_conf):
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if system: history.insert(0, {"role": "system", "content": system})
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try:
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res = self.client.chat.completions.create(
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model=self.model_name,
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messages=history,
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**gen_conf)
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return res.choices[0].message.content.strip(), res.usage.completion_tokens
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except openai.APIError as e:
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return "ERROR: "+str(e), 0
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from dashscope import Generation
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class QWenChat(Base):
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def __init__(self, key, model_name=Generation.Models.qwen_turbo):
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import dashscope
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dashscope.api_key = key
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self.model_name = model_name
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def chat(self, system, history, gen_conf):
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from http import HTTPStatus
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if system: history.insert(0, {"role": "system", "content": system})
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response = Generation.call(
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self.model_name,
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messages=history,
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result_format='message',
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**gen_conf
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)
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if response.status_code == HTTPStatus.OK:
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return response.output.choices[0]['message']['content'], response.usage.output_tokens
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return "ERROR: " + response.message, 0
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from zhipuai import ZhipuAI
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class ZhipuChat(Base):
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def __init__(self, key, model_name="glm-3-turbo"):
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self.client = ZhipuAI(api_key=key)
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self.model_name = model_name
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def chat(self, system, history, gen_conf):
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from http import HTTPStatus
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if system: history.insert(0, {"role": "system", "content": system})
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response = self.client.chat.completions.create(
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self.model_name,
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messages=history,
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**gen_conf
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)
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if response.status_code == HTTPStatus.OK:
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return response.output.choices[0]['message']['content'], response.usage.completion_tokens
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return "ERROR: " + response.message, 0 |