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# OpenAI |
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# OpenAI Chat Completion |
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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 Chat Completion method from [OpenAI](https://platform.openai.com/docs/guides/chat). |
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Please note you need an [OpenAI API key](https://platform.openai.com/account/api-keys) to access OpenAI. |
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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.OpenAI(api_key=OPENAI_API_KEY)) |
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.output('messages', 'answer') |
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) |
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messages=[ |
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{'question': 'Who won the world series in 2020?', 'answer': 'The Los Angeles Dodgers won the World Series in 2020.'}, |
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{'question': 'Where was it played?'} |
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] |
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answer = p(messages) |
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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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***chatbot.openai(model_name: str, api_key: str)*** |
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**Parameters:** |
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***model_name***: *str* |
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The model name in string, defaults to 'gpt-3.5-turbo'. Supported model names: |
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- gpt-3.5-turbo |
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- pt-3.5-turbo-0301 |
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***api_key***: *str=None* |
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The OpenAI API key in string, defaults to None. |
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***\*\*kwargs*** |
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Other OpenAI parameters such as max_tokens, stream, 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 "system", "question", "answer". For example, [{"question": "a past question?", "answer": "a past answer."}, {"question": "current question?"}] |
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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 .openai_chat import OpenAI |
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def OpenAI(*args, **kwargs): |
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return OpenAI(*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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from typing import List |
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import openai |
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from towhee.operator.base import PyOperator |
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class OpenAI(PyOperator): |
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'''Wrapper of OpenAI Chat API''' |
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def __init__(self, |
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model_name: str = 'gpt-3.5-turbo', |
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api_key: str = None, |
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**kwargs |
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): |
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openai.api_key = os.getenv('OPENAI_API_KEY', api_key) |
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self._model = model_name |
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self.kwargs = kwargs |
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def __call__(self, messages: List[dict]): |
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messages = self.parse_inputs(messages) |
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response = openai.ChatCompletion.create( |
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model=self._model, |
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messages=messages, |
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n=1, |
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**self.kwargs |
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) |
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if self.kwargs.get('stream'): |
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for chunk in response: |
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ans = chunk['choices'][0]['delta'] |
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yield ans |
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else: |
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answer = response['choices'][0]['message']['content'] |
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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 ["system", "question", "answer"].' |
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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 ['system', '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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elif k == 'system': |
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new_m = {'role': 'system', 'content': v} |
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else: |
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'Invalid message key: only accept key value from ["system", "question", "answer"].' |
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new_messages.append(new_m) |
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return new_messages |
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@staticmethod |
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def supported_model_names(): |
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model_list = [ |
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'gpt-3.5-turbo', |
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'gpt-3.5-turbo-0301' |
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] |
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model_list.sort() |
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return model_list |
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openai>=0.27 |
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