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# encoding:utf-8 | |
from bot.bot import Bot | |
from config import conf | |
from common.log import logger | |
import openai | |
import time | |
user_session = dict() | |
# OpenAI对话模型API (可用) | |
class OpenAIBot(Bot): | |
def __init__(self): | |
openai.api_key = conf().get('open_ai_api_key') | |
def reply(self, query, context=None): | |
# acquire reply content | |
if not context or not context.get('type') or context.get('type') == 'TEXT': | |
logger.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' | |
elif query == '#清除所有': | |
Session.clear_all_session() | |
return '所有人记忆已清除' | |
new_query = Session.build_session_query(query, from_user_id) | |
logger.debug("[OPEN_AI] session query={}".format(new_query)) | |
reply_content = self.reply_text(new_query, from_user_id, 0) | |
logger.debug("[OPEN_AI] new_query={}, user={}, reply_cont={}".format(new_query, from_user_id, reply_content)) | |
if reply_content and query: | |
Session.save_session(query, reply_content, from_user_id) | |
return reply_content | |
elif context.get('type', None) == 'IMAGE_CREATE': | |
return self.create_img(query, 0) | |
def reply_text(self, query, user_id, retry_count=0): | |
try: | |
response = openai.Completion.create( | |
model="text-davinci-003", # 对话模型的名称 | |
prompt=query, | |
temperature=1, # 值在[0,1]之间,越大表示回复越具有不确定性 | |
max_tokens=500, # 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"] | |
) | |
res_content = response.choices[0]['text'].strip().replace('<|endoftext|>', '') | |
logger.info("[OPEN_AI] reply={}".format(res_content)) | |
return res_content | |
except openai.error.RateLimitError as e: | |
# rate limit exception | |
logger.warn(e) | |
if retry_count < 1: | |
time.sleep(5) | |
logger.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 | |
logger.exception(e) | |
Session.clear_session(user_id) | |
return "请再问我一次吧" | |
def create_img(self, query, retry_count=0): | |
try: | |
logger.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="1024x1024" #图片大小,可选有 256x256, 512x512, 1024x1024 | |
) | |
image_url = response['data'][0]['url'] | |
logger.info("[OPEN_AI] image_url={}".format(image_url)) | |
return image_url | |
except openai.error.RateLimitError as e: | |
logger.warn(e) | |
if retry_count < 1: | |
time.sleep(5) | |
logger.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: | |
logger.exception(e) | |
return None | |
class Session(object): | |
def build_session_query(query, user_id): | |
''' | |
build query with conversation history | |
e.g. Q: xxx | |
A: xxx | |
Q: xxx | |
:param query: query content | |
:param user_id: from user id | |
:return: query content with conversaction | |
''' | |
prompt = conf().get("character_desc", "") | |
if prompt: | |
prompt += "<|endoftext|>\n\n\n" | |
session = user_session.get(user_id, None) | |
if session: | |
for conversation in session: | |
prompt += "Q: " + conversation["question"] + "\n\n\nA: " + conversation["answer"] + "<|endoftext|>\n" | |
prompt += "Q: " + query + "\nA: " | |
return prompt | |
else: | |
return prompt + "Q: " + query + "\nA: " | |
def save_session(query, answer, user_id): | |
max_tokens = conf().get("conversation_max_tokens") | |
if not max_tokens: | |
# default 3000 | |
max_tokens = 1000 | |
conversation = dict() | |
conversation["question"] = query | |
conversation["answer"] = answer | |
session = user_session.get(user_id) | |
logger.debug(conversation) | |
logger.debug(session) | |
if session: | |
# append conversation | |
session.append(conversation) | |
else: | |
# create session | |
queue = list() | |
queue.append(conversation) | |
user_session[user_id] = queue | |
# discard exceed limit conversation | |
Session.discard_exceed_conversation(user_session[user_id], max_tokens) | |
def discard_exceed_conversation(session, max_tokens): | |
count = 0 | |
count_list = list() | |
for i in range(len(session)-1, -1, -1): | |
# count tokens of conversation list | |
history_conv = session[i] | |
count += len(history_conv["question"]) + len(history_conv["answer"]) | |
count_list.append(count) | |
for c in count_list: | |
if c > max_tokens: | |
# pop first conversation | |
session.pop(0) | |
def clear_session(user_id): | |
user_session[user_id] = [] | |
def clear_all_session(): | |
user_session.clear() |