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Merge pull request #50 from zhayujie/feat-gpt-3.5
feat: support gpt-3.5 model
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@@ -10,3 +10,4 @@ | |
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| # model | ||
| OPEN_AI = "openai" | ||
| CHATGPT = "chatgpt" | ||
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| # encoding:utf-8 | ||
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| from model.model import Model | ||
| from config import model_conf | ||
| from common import const | ||
| from common import log | ||
| import openai | ||
| import time | ||
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| user_session = dict() | ||
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| # OpenAI对话模型API (可用) | ||
| class ChatGPTModel(Model): | ||
| def __init__(self): | ||
| openai.api_key = model_conf(const.OPEN_AI).get('api_key') | ||
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| def reply(self, query, context=None): | ||
| # acquire reply content | ||
| if not context or not context.get('type') or context.get('type') == 'TEXT': | ||
| log.info("[OPEN_AI] query={}".format(query)) | ||
| from_user_id = context['from_user_id'] | ||
| if query == '#清除记忆': | ||
| Session.clear_session(from_user_id) | ||
| return '记忆已清除' | ||
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| new_query = Session.build_session_query(query, from_user_id) | ||
| log.debug("[OPEN_AI] session query={}".format(new_query)) | ||
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| # if context.get('stream'): | ||
| # # reply in stream | ||
| # return self.reply_text_stream(query, new_query, from_user_id) | ||
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| reply_content = self.reply_text(new_query, from_user_id, 0) | ||
| log.debug("[OPEN_AI] new_query={}, user={}, reply_cont={}".format(new_query, from_user_id, reply_content)) | ||
| if reply_content: | ||
| Session.save_session(query, reply_content, from_user_id) | ||
| return reply_content | ||
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| elif context.get('type', None) == 'IMAGE_CREATE': | ||
| return self.create_img(query, 0) | ||
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| def reply_text(self, query, user_id, retry_count=0): | ||
| try: | ||
| response = openai.ChatCompletion.create( | ||
| model="gpt-3.5-turbo", # 对话模型的名称 | ||
| messages=query, | ||
| temperature=0.9, # 值在[0,1]之间，越大表示回复越具有不确定性 | ||
| max_tokens=1200, # 回复最大的字符数 | ||
| top_p=1, | ||
| frequency_penalty=0.0, # [-2,2]之间，该值越大则更倾向于产生不同的内容 | ||
| presence_penalty=0.0, # [-2,2]之间，该值越大则更倾向于产生不同的内容 | ||
| ) | ||
| # res_content = response.choices[0]['text'].strip().replace('<|endoftext|>', '') | ||
| log.info(response.choices[0]['message']['content']) | ||
| # log.info("[OPEN_AI] reply={}".format(res_content)) | ||
| return response.choices[0]['message']['content'] | ||
| except openai.error.RateLimitError as e: | ||
| # rate limit exception | ||
| log.warn(e) | ||
| if retry_count < 1: | ||
| time.sleep(5) | ||
| log.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1)) | ||
| return self.reply_text(query, user_id, retry_count+1) | ||
| else: | ||
| return "提问太快啦，请休息一下再问我吧" | ||
| except Exception as e: | ||
| # unknown exception | ||
| log.exception(e) | ||
| Session.clear_session(user_id) | ||
| return "请再问我一次吧" | ||
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| def reply_text_stream(self, query, new_query, user_id, retry_count=0): | ||
| try: | ||
| res = openai.Completion.create( | ||
| model="text-davinci-003", # 对话模型的名称 | ||
| prompt=new_query, | ||
| temperature=0.9, # 值在[0,1]之间，越大表示回复越具有不确定性 | ||
| max_tokens=4096, # 回复最大的字符数 | ||
| top_p=1, | ||
| frequency_penalty=0.0, # [-2,2]之间，该值越大则更倾向于产生不同的内容 | ||
| presence_penalty=0.0, # [-2,2]之间，该值越大则更倾向于产生不同的内容 | ||
| stop=["\n\n\n"], | ||
| stream=True | ||
| ) | ||
| return self._process_reply_stream(query, res, user_id) | ||
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| except openai.error.RateLimitError as e: | ||
| # rate limit exception | ||
| log.warn(e) | ||
| if retry_count < 1: | ||
| time.sleep(5) | ||
| log.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1)) | ||
| return self.reply_text(query, user_id, retry_count+1) | ||
| else: | ||
| return "提问太快啦，请休息一下再问我吧" | ||
| except Exception as e: | ||
| # unknown exception | ||
| log.exception(e) | ||
| Session.clear_session(user_id) | ||
| return "请再问我一次吧" | ||
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| def _process_reply_stream( | ||
| self, | ||
| query: str, | ||
| reply: dict, | ||
| user_id: str | ||
| ) -> str: | ||
| full_response = "" | ||
| for response in reply: | ||
| if response.get("choices") is None or len(response["choices"]) == 0: | ||
| raise Exception("OpenAI API returned no choices") | ||
| if response["choices"][0].get("finish_details") is not None: | ||
| break | ||
| if response["choices"][0].get("text") is None: | ||
| raise Exception("OpenAI API returned no text") | ||
| if response["choices"][0]["text"] == "<|endoftext|>": | ||
| break | ||
| yield response["choices"][0]["text"] | ||
| full_response += response["choices"][0]["text"] | ||
| if query and full_response: | ||
| Session.save_session(query, full_response, user_id) | ||
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| def create_img(self, query, retry_count=0): | ||
| try: | ||
| log.info("[OPEN_AI] image_query={}".format(query)) | ||
| response = openai.Image.create( | ||
| prompt=query, #图片描述 | ||
| n=1, #每次生成图片的数量 | ||
| size="256x256" #图片大小,可选有 256x256, 512x512, 1024x1024 | ||
| ) | ||
| image_url = response['data'][0]['url'] | ||
| log.info("[OPEN_AI] image_url={}".format(image_url)) | ||
| return image_url | ||
| except openai.error.RateLimitError as e: | ||
| log.warn(e) | ||
| if retry_count < 1: | ||
| time.sleep(5) | ||
| log.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count+1)) | ||
| return self.reply_text(query, retry_count+1) | ||
| else: | ||
| return "提问太快啦，请休息一下再问我吧" | ||
| except Exception as e: | ||
| log.exception(e) | ||
| return None | ||
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| class Session(object): | ||
| @staticmethod | ||
| def build_session_query(query, user_id): | ||
| ''' | ||
| build query with conversation history | ||
| e.g. [ | ||
| {"role": "system", "content": "You are a helpful assistant."}, | ||
| {"role": "user", "content": "Who won the world series in 2020?"}, | ||
| {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."}, | ||
| {"role": "user", "content": "Where was it played?"} | ||
| ] | ||
| :param query: query content | ||
| :param user_id: from user id | ||
| :return: query content with conversaction | ||
| ''' | ||
| session = user_session.get(user_id, []) | ||
| if len(session) == 0: | ||
| system_prompt = model_conf(const.OPEN_AI).get("character_desc", "") | ||
| system_item = {'role': 'system', 'content': system_prompt} | ||
| session.append(system_item) | ||
| user_session[user_id] = session | ||
| user_item = {'role': 'user', 'content': query} | ||
| session.append(user_item) | ||
| return session | ||
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| @staticmethod | ||
| def save_session(query, answer, user_id): | ||
| session = user_session.get(user_id) | ||
| if session: | ||
| # append conversation | ||
| gpt_item = {'role': 'assistant', 'content': answer} | ||
| session.append(gpt_item) | ||
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| @staticmethod | ||
| def clear_session(user_id): | ||
| user_session[user_id] = [] | ||
|
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