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a2c7aec1e3
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924daf134f
@ -1,4 +1,3 @@
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import os
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import json
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import asyncio
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import random
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@ -120,7 +119,7 @@ class AIResponder(object):
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self.config = config
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self.history: List[Dict[str, Any]] = []
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self.channel = channel if channel is not None else 'system'
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self.client = openai.AsyncOpenAI(api_key=self.config['openai-token'])
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openai.api_key = self.config['openai-token']
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self.rate_limit_backoff = exponential_backoff()
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self.history_file: Optional[Path] = None
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if 'history-directory' in self.config:
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@ -134,11 +133,6 @@ class AIResponder(object):
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system = self.config.get(self.channel, self.config['system'])
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system = system.replace('{date}', time.strftime('%Y-%m-%d'))\
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.replace('{time}', time.strftime('%H:%M:%S'))
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news_feed = self.config.get('news')
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if news_feed and os.path.exists(news_feed):
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with open(news_feed) as fd:
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news_feed = fd.read().strip()
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system = system.replace('{news}', news_feed)
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messages.append({"role": "system", "content": system})
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if limit is not None:
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while len(self.history) > limit:
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@ -156,9 +150,9 @@ class AIResponder(object):
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async def _draw_openai(self, description: str) -> BytesIO:
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for _ in range(3):
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try:
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response = await self.client.images.generate(prompt=description, n=1, size="1024x1024", model="dall-e-3")
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response = await openai.Image.acreate(prompt=description, n=1, size="512x512")
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async with aiohttp.ClientSession() as session:
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async with session.get(response.data[0].url) as image:
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async with session.get(response['data'][0]['url']) as image:
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logging.info(f'Drawed a picture with DALL-E on this description: {repr(description)}')
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return BytesIO(await image.read())
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except Exception as err:
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@ -270,27 +264,29 @@ class AIResponder(object):
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return True
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return False
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async def _acreate(self, messages: List[Dict[str, Any]], limit: int) -> Tuple[Optional[openai.types.chat.ChatCompletionMessage], int]:
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async def _acreate(self, messages: List[Dict[str, Any]], limit: int) -> Tuple[Optional[Dict[str, Any]], int]:
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model = self.config["model"]
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try:
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result = await self.client.chat.completions.create(model=model,
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messages=messages,
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temperature=self.config["temperature"],
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max_tokens=self.config["max-tokens"],
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top_p=self.config["top-p"],
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presence_penalty=self.config["presence-penalty"],
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frequency_penalty=self.config["frequency-penalty"])
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answer = result.choices[0].message
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result = await openai.ChatCompletion.acreate(model=model,
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messages=messages,
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temperature=self.config["temperature"],
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max_tokens=self.config["max-tokens"],
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top_p=self.config["top-p"],
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presence_penalty=self.config["presence-penalty"],
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frequency_penalty=self.config["frequency-penalty"])
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answer = result['choices'][0]['message']
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if type(answer) != dict:
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answer = answer.to_dict()
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self.rate_limit_backoff = exponential_backoff()
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logging.info(f"generated response {result.usage}: {repr(answer)}")
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logging.info(f"generated response {result.get('usage')}: {repr(answer)}")
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return answer, limit
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except openai.BadRequestError as err:
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except openai.error.InvalidRequestError as err:
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if 'maximum context length is' in str(err) and limit > 4:
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logging.warning(f"context length exceeded, reduce the limit {limit}: {str(err)}")
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limit -= 1
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return None, limit
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raise err
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except openai.RateLimitError as err:
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except openai.error.RateLimitError as err:
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rate_limit_sleep = next(self.rate_limit_backoff)
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if "retry-model" in self.config:
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model = self.config["retry-model"]
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@ -306,12 +302,12 @@ class AIResponder(object):
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messages = [{"role": "system", "content": self.config["fix-description"]},
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{"role": "user", "content": answer}]
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try:
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result = await self.client.chat.completions.create(model=self.config["fix-model"],
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messages=messages,
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temperature=0.2,
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max_tokens=2048)
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logging.info(f"got this message as fix:\n{pp(result.choices[0].message.content)}")
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response = result.choices[0].message.content
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result = await openai.ChatCompletion.acreate(model=self.config["fix-model"],
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messages=messages,
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temperature=0.2,
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max_tokens=2048)
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logging.info(f"got this message as fix:\n{pp(result['choices'][0]['message']['content'])}")
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response = result['choices'][0]['message']['content']
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start, end = response.find("{"), response.rfind("}")
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if start == -1 or end == -1 or (start + 3) >= end:
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return answer
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@ -330,11 +326,11 @@ class AIResponder(object):
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f" if it is not already in {language}, otherwise you just copy it."},
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{"role": "user", "content": text}]
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try:
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result = await self.client.chat.completions.create(model=self.config["fix-model"],
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messages=message,
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temperature=0.2,
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max_tokens=2048)
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response = result.choices[0].message.content
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result = await openai.ChatCompletion.acreate(model=self.config["fix-model"],
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messages=message,
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temperature=0.2,
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max_tokens=2048)
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response = result['choices'][0]['message']['content']
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logging.info(f"got this translated message:\n{pp(response)}")
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return response
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except Exception as err:
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@ -390,16 +386,16 @@ class AIResponder(object):
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# Attempt to parse the AI's response
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try:
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response = parse_json(answer.content)
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response = parse_json(answer['content'])
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except Exception as err:
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logging.warning(f"failed to parse the answer: {pp(err)}\n{repr(answer.content)}")
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answer.content = await self.fix(answer['content'])
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logging.warning(f"failed to parse the answer: {pp(err)}\n{repr(answer['content'])}")
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answer['content'] = await self.fix(answer['content'])
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# Retry parsing the fixed content
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try:
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response = parse_json(answer.content)
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response = parse_json(answer['content'])
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except Exception as err:
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logging.error(f"failed to parse the fixed answer: {pp(err)}\n{repr(answer.content)}")
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logging.error(f"failed to parse the fixed answer: {pp(err)}\n{repr(answer['content'])}")
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retries -= 1
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continue
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@ -414,7 +410,7 @@ class AIResponder(object):
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# Post-process the message and update the answer's content
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answer_message = await self.post_process(message, response)
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answer.content = str(answer_message)
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answer['content'] = str(answer_message)
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# Update message history
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self.update_history(messages[-1], answer, limit, message.historise_question)
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