Oleksandr Kozachuk
2db983c462
- Try to keep at least 3 messages from each channel in the history - Use post processed messages for the history, instead of the raw messages from the openai API
255 lines
11 KiB
Python
255 lines
11 KiB
Python
import json
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import multiline
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import openai
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import aiohttp
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import logging
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import time
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import re
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import pickle
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from pathlib import Path
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from io import BytesIO
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from pprint import pformat
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from typing import Optional, List, Dict, Any, Tuple
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def pp(*args, **kw):
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if 'width' not in kw:
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kw['width'] = 300
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return pformat(*args, **kw)
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def parse_response(content: str) -> Dict:
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content = content.strip()
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try:
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return json.loads(content)
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except Exception:
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try:
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return multiline.loads(content, multiline=True)
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except Exception as err:
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raise err
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def parse_maybe_json(json_string):
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if json_string is None:
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return None
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json_string = json_string.strip()
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try:
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parsed_json = parse_response(json_string)
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except Exception:
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if json_string.startswith('{') and json_string.endswith('}'):
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return parse_maybe_json(json_string[1:-1])
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return json_string
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if isinstance(parsed_json, (list, dict)):
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concatenated_values = []
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for value in parsed_json.values() if isinstance(parsed_json, dict) else parsed_json:
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concatenated_values.append(str(value))
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return '\n'.join(concatenated_values)
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result = str(parsed_json)
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if result.lower() in ('', 'none', 'null', '"none"', '"null"', "'none'", "'null'"):
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return None
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return result
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class AIMessageBase(object):
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def __init__(self) -> None:
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pass
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def __str__(self) -> str:
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return json.dumps(vars(self))
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class AIMessage(AIMessageBase):
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def __init__(self, user: str, message: str, channel: str = "chat", direct: bool = False) -> None:
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self.user = user
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self.message = message
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self.channel = channel
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self.direct = direct
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class AIResponse(AIMessageBase):
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def __init__(self, answer: Optional[str], answer_needed: bool, staff: Optional[str], picture: Optional[str], hack: bool) -> None:
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self.answer = answer
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self.answer_needed = answer_needed
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self.staff = staff
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self.picture = picture
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self.hack = hack
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class AIResponder(object):
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def __init__(self, config: Dict[str, Any], channel: Optional[str] = None) -> None:
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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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openai.api_key = self.config['openai-token']
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self.history_file: Optional[Path] = None
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if 'history-directory' in self.config:
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self.history_file = Path(self.config['history-directory']).expanduser() / f'{self.channel}.dat'
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if self.history_file.exists():
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with open(self.history_file, 'rb') as fd:
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self.history = pickle.load(fd)
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def _message(self, message: AIMessage, limit: Optional[int] = None) -> List[Dict[str, Any]]:
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messages = []
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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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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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self.shrink_history_by_one()
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for msg in self.history:
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messages.append(msg)
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messages.append({"role": "user", "content": str(message)})
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return messages
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async def draw(self, description: str) -> BytesIO:
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for _ in range(3):
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try:
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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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return BytesIO(await image.read())
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except Exception as err:
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logging.warning(f"Failed to generate image {repr(description)}: {repr(err)}")
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raise RuntimeError(f"Failed to generate image {repr(description)} after multiple retries")
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async def post_process(self, message: AIMessage, response: Dict[str, Any]) -> AIResponse:
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for fld in ('answer', 'staff', 'picture'):
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if str(response[fld]).strip().lower() in \
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('none', '', 'null', '"none"', '"null"', "'none'", "'null'"):
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response[fld] = None
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for fld in ('answer_needed', 'hack'):
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if str(response[fld]).strip().lower() == 'true':
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response[fld] = True
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else:
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response[fld] = False
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if response['answer'] is None:
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response['answer_needed'] = False
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else:
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response['answer'] = str(response['answer'])
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response['answer'] = re.sub(r'@\[([^\]]*)\]\([^\)]*\)', r'\1', response['answer'])
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response['answer'] = re.sub(r'\[[^\]]*\]\(([^\)]*)\)', r'\1', response['answer'])
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if message.direct or message.user in message.message:
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response['answer_needed'] = True
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return AIResponse(response['answer'],
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response['answer_needed'],
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parse_maybe_json(response['staff']),
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parse_maybe_json(response['picture']),
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response['hack'])
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def short_path(self, message: AIMessage, limit: int) -> bool:
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if message.direct or 'short-path' not in self.config:
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return False
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for chan_re, user_re in self.config['short-path']:
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chan_ma = re.match(chan_re, message.channel)
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user_ma = re.match(user_re, message.user)
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if chan_ma and user_ma:
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self.history.append({"role": "user", "content": str(message)})
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if len(self.history) > limit:
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self.history = self.history[-limit:]
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if self.history_file is not None:
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with open(self.history_file, 'wb') as fd:
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pickle.dump(self.history, fd)
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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[Dict[str, Any]], int]:
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try:
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result = await openai.ChatCompletion.acreate(model=self.config["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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return answer, limit
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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 Exception as err:
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logging.warning(f"failed to generate response: {repr(err)}")
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return None, limit
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async def fix(self, answer: str) -> str:
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if 'fix-model' not in self.config:
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return answer
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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 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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response = response[start:end + 1]
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logging.info(f"fixed answer:\n{pp(response)}")
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return response
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except Exception as err:
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logging.warning(f"failed to execute a fix for the answer: {repr(err)}")
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return answer
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def shrink_history_by_one(self, index: int = 0) -> None:
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if index >= len(self.history):
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del self.history[0]
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else:
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current = self.history[index]
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count = sum(1 for item in self.history[index:] if item.get('channel') == current.get('channel'))
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if count > 3:
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del self.history[index]
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else:
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self.shrink_history_by_one(index + 1)
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def update_history(self, question: Dict[str, Any], answer: Dict[str, Any], limit: int) -> None:
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self.history.append(question)
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self.history.append(answer)
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while len(self.history) > limit:
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self.shrink_history_by_one()
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if self.history_file is not None:
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with open(self.history_file, 'wb') as fd:
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pickle.dump(self.history, fd)
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async def send(self, message: AIMessage) -> AIResponse:
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limit = self.config["history-limit"]
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if self.short_path(message, limit):
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return AIResponse(None, False, None, None, False)
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retries = 3
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while retries > 0:
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messages = self._message(message, limit)
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logging.info(f"try to send this messages:\n{pp(messages)}")
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answer, limit = await self._acreate(messages, limit)
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if answer is None:
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continue
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try:
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response = parse_response(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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try:
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response = parse_response(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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retries -= 1
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continue
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if 'hack' not in response or type(response.get('picture', None)) not in (type(None), str):
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retries -= 1
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continue
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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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self.update_history(messages[-1], answer, limit)
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logging.info(f"got this answer:\n{str(answer_message)}")
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return answer_message
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raise RuntimeError("Failed to generate answer after multiple retries")
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