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# Ernie |
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# 文心一言 |
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*author: Jael* |
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<br /> |
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## Description |
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A LLM operator generates answer given prompt in messages using a large language model or service. |
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This operator is implemented with Ernie Bot from [Baidu](https://cloud.baidu.com/wenxin.html). |
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Please note you will need [Ernie API key & Secret key](https://ai.baidu.com/ai-doc/REFERENCE/Lkru0zoz4) to access the service. |
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<br /> |
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## Code Example |
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Use the default model to continue the conversation from given messages. |
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*Write a pipeline with explicit inputs/outputs name specifications:* |
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```python |
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from towhee import pipe, ops |
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p = ( |
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pipe.input('messages') |
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.map('messages', 'answer', ops.LLM.Ernie(api_key=ERNIE_API_KEY, secret_key=ERNIE_SECRET_KEY)) |
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.output('messages', 'answer') |
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) |
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messages=[ |
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{'question': 'Zilliz Cloud 是什么?', 'answer': 'Zilliz Cloud 是一种全托管的向量检索服务。'}, |
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{'question': '它和 Milvus 的关系是什么?'} |
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] |
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answer = p(messages).get()[0] |
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``` |
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<br /> |
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## Factory Constructor |
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Create the operator via the following factory method: |
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***LLM.Ernie(api_key: str, secret_key: str)*** |
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**Parameters:** |
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***api_key***: *str=None* |
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The Ernie API key in string, defaults to None. If None, it will use the environment variable `ERNIE_API_KEY`. |
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***secret_key***: *str=None* |
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The Ernie Secret key in string, defaults to None. If None, it will use the environment variable `ERNIE_SECRET_KEY`. |
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***\*\*kwargs*** |
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Other OpenAI parameters such as temperature, etc. |
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<br /> |
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## Interface |
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The operator takes a piece of text in string as input. |
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It returns answer in json. |
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***\_\_call\_\_(txt)*** |
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**Parameters:** |
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***messages***: *list* |
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A list of messages to set up chat. |
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Must be a list of dictionaries with key value from "question", "answer". For example, [{"question": "a past question?", "answer": "a past answer."}, {"question": "current question?"}]. |
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It also accepts the orignal Ernie message format like [{"role": "user", "content": "a question?"}, {"role": "assistant", "content": "an answer."}] |
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**Returns**: |
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*answer: str* |
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The next answer generated by role "assistant". |
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<br /> |
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from .ernie_chat import ErnieChat |
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def Ernie(*args, **kwargs): |
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return ErnieChat(*args, **kwargs) |
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# Copyright 2021 Zilliz. 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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import os |
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import requests |
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import json |
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from typing import List |
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from towhee.operator.base import PyOperator |
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class ErnieChat(PyOperator): |
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'''Wrapper of OpenAI Chat API''' |
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def __init__(self, |
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api_key: str = None, |
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secret_key: str = None, |
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**kwargs |
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): |
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self.api_key = api_key or os.getenv('ERNIE_API_KEY') |
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self.secret_key = secret_key or os.getenv('ERNIE_SECRET_KEY') |
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self.kwargs = kwargs |
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try: |
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self.access_token = self.get_access_token(api_key=self.api_key, secret_key=self.secret_key) |
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except Exception as e: |
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raise RuntimeError(f'Failed to get access token: {e}') |
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self.url = 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions?access_token=' \ |
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+ self.access_token |
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def __call__(self, messages: List[dict]): |
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messages = self.parse_inputs(messages) |
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self.kwargs['messages'] = messages |
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payload = json.dumps(self.kwargs) |
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headers = { |
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'Content-Type': 'application/json' |
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} |
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response = requests.request('POST', self.url, headers=headers, data=payload) |
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# if self.kwargs.get('stream', False): |
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# return self.stream_output(response) |
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answer = response.json()['result'] |
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return answer |
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def parse_inputs(self, messages: List[dict]): |
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assert isinstance(messages, list), \ |
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'Inputs must be a list of dictionaries with keys from ["question", "answer"] or ["role", "content"].' |
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new_messages = [] |
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for m in messages: |
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if ('role' and 'content' in m) and (m['role'] in ['assistant', 'user']): |
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new_messages.append(m) |
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else: |
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for k, v in m.items(): |
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if k == 'question': |
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new_m = {'role': 'user', 'content': v} |
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elif k == 'answer': |
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new_m = {'role': 'assistant', 'content': v} |
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else: |
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'Invalid message key: only accept key value from ["question", "answer"].' |
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new_messages.append(new_m) |
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return new_messages |
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def stream_output(self, response): |
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# todo |
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pass |
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@staticmethod |
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def get_access_token(api_key, secret_key): |
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url = 'https://aip.baidubce.com/oauth/2.0/token' |
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params = { |
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'grant_type': 'client_credentials', |
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'client_id': api_key, |
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'client_secret': secret_key |
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} |
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return str(requests.post(url, params=params).json().get('access_token')) |
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requests |
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