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Support new openai API.

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Fjerkroa Auto 2023-11-14 10:27:03 +01:00
parent 95bc6ce041
commit 488a8ef174
1 changed files with 38 additions and 34 deletions
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48
fjerkroa_bot/ai_responder.py
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@ -1,3 +1,4 @@
import os
import json
import asyncio
import random
@ -119,7 +120,7 @@ class AIResponder(object):
self.config = config
self.history: List[Dict[str, Any]] = []
self.channel = channel if channel is not None else 'system'
openai.api_key = self.config['openai-token']
self.client = openai.AsyncOpenAI(api_key=self.config['openai-token'])
self.rate_limit_backoff = exponential_backoff()
self.history_file: Optional[Path] = None
if 'history-directory' in self.config:
@ -133,6 +134,11 @@ class AIResponder(object):
system = self.config.get(self.channel, self.config['system'])
system = system.replace('{date}', time.strftime('%Y-%m-%d'))\
.replace('{time}', time.strftime('%H:%M:%S'))
news_feed = self.config.get('news')
if news_feed and os.path.exists(news_feed):
with open(news_feed) as fd:
news_feed = fd.read().strip()
system = system.replace('{news}', news_feed)
messages.append({"role": "system", "content": system})
if limit is not None:
while len(self.history) > limit:
@ -150,9 +156,9 @@ class AIResponder(object):
async def _draw_openai(self, description: str) -> BytesIO:
for _ in range(3):
try:
response = await openai.Image.acreate(prompt=description, n=1, size="512x512")
response = await self.client.images.generate(prompt=description, n=1, size="1024x1024", model="dall-e-3")
async with aiohttp.ClientSession() as session:
async with session.get(response['data'][0]['url']) as image:
async with session.get(response.data[0].url) as image:
logging.info(f'Drawed a picture with DALL-E on this description: {repr(description)}')
return BytesIO(await image.read())
except Exception as err:
@ -263,29 +269,27 @@ class AIResponder(object):
return True
return False
async def _acreate(self, messages: List[Dict[str, Any]], limit: int) -> Tuple[Optional[Dict[str, Any]], int]:
async def _acreate(self, messages: List[Dict[str, Any]], limit: int) -> Tuple[Optional[openai.types.chat.ChatCompletionMessage], int]:
model = self.config["model"]
try:
result = await openai.ChatCompletion.acreate(model=model,
result = await self.client.chat.completions.create(model=model,
messages=messages,
temperature=self.config["temperature"],
max_tokens=self.config["max-tokens"],
top_p=self.config["top-p"],
presence_penalty=self.config["presence-penalty"],
frequency_penalty=self.config["frequency-penalty"])
answer = result['choices'][0]['message']
if type(answer) != dict:
answer = answer.to_dict()
answer = result.choices[0].message
self.rate_limit_backoff = exponential_backoff()
logging.info(f"generated response {result.get('usage')}: {repr(answer)}")
logging.info(f"generated response {result.usage}: {repr(answer)}")
return answer, limit
except openai.error.InvalidRequestError as err:
except openai.BadRequestError as err:
if 'maximum context length is' in str(err) and limit > 4:
logging.warning(f"context length exceeded, reduce the limit {limit}: {str(err)}")
limit -= 1
return None, limit
raise err
except openai.error.RateLimitError as err:
except openai.RateLimitError as err:
rate_limit_sleep = next(self.rate_limit_backoff)
if "retry-model" in self.config:
model = self.config["retry-model"]
@ -301,12 +305,12 @@ class AIResponder(object):
messages = [{"role": "system", "content": self.config["fix-description"]},
{"role": "user", "content": answer}]
try:
result = await openai.ChatCompletion.acreate(model=self.config["fix-model"],
result = await self.client.chat.completions.create(model=self.config["fix-model"],
messages=messages,
temperature=0.2,
max_tokens=2048)
logging.info(f"got this message as fix:\n{pp(result['choices'][0]['message']['content'])}")
response = result['choices'][0]['message']['content']
logging.info(f"got this message as fix:\n{pp(result.choices[0].message.content)}")
response = result.choices[0].message.content
start, end = response.find("{"), response.rfind("}")
if start == -1 or end == -1 or (start + 3) >= end:
return answer
@ -325,11 +329,11 @@ class AIResponder(object):
f" if it is not already in {language}, otherwise you just copy it."},
{"role": "user", "content": text}]
try:
result = await openai.ChatCompletion.acreate(model=self.config["fix-model"],
result = await self.client.chat.completions.create(model=self.config["fix-model"],
messages=message,
temperature=0.2,
max_tokens=2048)
response = result['choices'][0]['message']['content']
response = result.choices[0].message.content
logging.info(f"got this translated message:\n{pp(response)}")
return response
except Exception as err:
@ -385,16 +389,16 @@ class AIResponder(object):
# Attempt to parse the AI's response
try:
response = parse_json(answer['content'])
response = parse_json(answer.content)
except Exception as err:
logging.warning(f"failed to parse the answer: {pp(err)}\n{repr(answer['content'])}")
answer['content'] = await self.fix(answer['content'])
logging.warning(f"failed to parse the answer: {pp(err)}\n{repr(answer.content)}")
answer.content = await self.fix(answer['content'])
# Retry parsing the fixed content
try:
response = parse_json(answer['content'])
response = parse_json(answer.content)
except Exception as err:
logging.error(f"failed to parse the fixed answer: {pp(err)}\n{repr(answer['content'])}")
logging.error(f"failed to parse the fixed answer: {pp(err)}\n{repr(answer.content)}")
retries -= 1
continue
@ -409,7 +413,7 @@ class AIResponder(object):
# Post-process the message and update the answer's content
answer_message = await self.post_process(message, response)
answer['content'] = str(answer_message)
answer.content = str(answer_message)
# Update message history
self.update_history(messages[-1], answer, limit, message.historise_question)