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AstrBot/model/provider/openai_official.py
2024-05-25 18:35:56 +08:00

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import os
import sys
import json
import time
import tiktoken
import threading
import traceback
import base64
from openai import AsyncOpenAI
from openai.types.images_response import ImagesResponse
from openai.types.chat.chat_completion import ChatCompletion
from openai._exceptions import *
from persist.session import dbConn
from model.provider.provider import Provider
from util import general_utils as gu
from util.cmd_config import CmdConfig
from SparkleLogging.utils.core import LogManager
from logging import Logger
from typing import List, Dict
logger: Logger = LogManager.GetLogger(log_name='astrbot-core')
MODELS = {
"gpt-4o": 128000,
"gpt-4o-2024-05-13": 128000,
"gpt-4-turbo": 128000,
"gpt-4-turbo-2024-04-09": 128000,
"gpt-4-turbo-preview": 128000,
"gpt-4-0125-preview": 128000,
"gpt-4-1106-preview": 128000,
"gpt-4-vision-preview": 128000,
"gpt-4-1106-vision-preview": 128000,
"gpt-4": 8192,
"gpt-4-0613": 8192,
"gpt-4-32k": 32768,
"gpt-4-32k-0613": 32768,
"gpt-3.5-turbo-0125": 16385,
"gpt-3.5-turbo": 16385,
"gpt-3.5-turbo-1106": 16385,
"gpt-3.5-turbo-instruct": 4096,
"gpt-3.5-turbo-16k": 16385,
"gpt-3.5-turbo-0613": 16385,
"gpt-3.5-turbo-16k-0613": 16385,
}
class ProviderOpenAIOfficial(Provider):
def __init__(self, cfg) -> None:
super().__init__()
os.makedirs("data/openai", exist_ok=True)
self.cc = CmdConfig
self.key_data_path = "data/openai/keys.json"
self.api_keys = []
self.chosen_api_key = None
self.base_url = None
self.keys_data = {} # 记录超额
if cfg['key']: self.api_keys = cfg['key']
if cfg['api_base']: self.base_url = cfg['api_base']
if not self.api_keys:
logger.warn("看起来你没有添加 OpenAI 的 API 密钥OpenAI LLM 能力将不会启用。")
else:
self.chosen_api_key = self.api_keys[0]
for key in self.api_keys:
self.keys_data[key] = True
self.client = AsyncOpenAI(
api_key=self.chosen_api_key,
base_url=self.base_url
)
self.model_configs: Dict = cfg['chatGPTConfigs']
super().set_curr_model(self.model_configs['model'])
self.image_generator_model_configs: Dict = self.cc.get('openai_image_generate', None)
self.session_memory: Dict[str, List] = {} # 会话记忆
self.session_memory_lock = threading.Lock()
self.max_tokens = self.model_configs['max_tokens'] # 上下文窗口大小
self.tokenizer = tiktoken.get_encoding("cl100k_base") # todo: 根据 model 切换分词器
self.DEFAULT_PERSONALITY = {
"name": "default",
"prompt": "你是一个很有帮助的 AI 助手。"
}
self.curr_personality = self.DEFAULT_PERSONALITY
self.session_personality = {} # 记录了某个session是否已设置人格。
# 从 SQLite DB 读取历史记录
try:
db1 = dbConn()
for session in db1.get_all_session():
self.session_memory_lock.acquire()
self.session_memory[session[0]] = json.loads(session[1])['data']
self.session_memory_lock.release()
except BaseException as e:
logger.warn(f"读取 OpenAI LLM 对话历史记录 失败:{e}。仍可正常使用。")
# 定时保存历史记录
threading.Thread(target=self.dump_history, daemon=True).start()
def dump_history(self):
'''
转储历史记录
'''
time.sleep(10)
db = dbConn()
while True:
try:
for key in self.session_memory:
data = self.session_memory[key]
data_json = {
'data': data
}
if db.check_session(key):
db.update_session(key, json.dumps(data_json))
else:
db.insert_session(key, json.dumps(data_json))
logger.debug("已保存 OpenAI 会话历史记录")
except BaseException as e:
print(e)
finally:
time.sleep(10*60)
def personality_set(self, default_personality: dict, session_id: str):
if not default_personality: return
if session_id not in self.session_memory:
self.session_memory[session_id] = []
self.curr_personality = default_personality
self.session_personality = {} # 重置
encoded_prompt = self.tokenizer.encode(default_personality['prompt'])
tokens_num = len(encoded_prompt)
model = self.model_configs['model']
if model in MODELS and tokens_num > MODELS[model] - 500:
default_personality['prompt'] = self.tokenizer.decode(encoded_prompt[:MODELS[model] - 500])
new_record = {
"user": {
"role": "system",
"content": default_personality['prompt'],
},
'usage_tokens': 0, # 到该条目的总 token 数
'single-tokens': 0 # 该条目的 token 数
}
self.session_memory[session_id].append(new_record)
async def encode_image_bs64(self, image_url: str) -> str:
'''
将图片转换为 base64
'''
if image_url.startswith("http"):
image_url = await gu.download_image_by_url(image_url)
with open(image_url, "rb") as f:
image_bs64 = base64.b64encode(f.read()).decode()
return "data:image/jpeg;base64," + image_bs64
async def retrieve_context(self, session_id: str):
'''
根据 session_id 获取保存的 OpenAI 格式的上下文
'''
if session_id not in self.session_memory:
raise Exception("会话 ID 不存在")
# 转换为 openai 要求的格式
context = []
is_lvm = await self.is_lvm()
for record in self.session_memory[session_id]:
if "user" in record and record['user']:
if not is_lvm and "content" in record['user'] and isinstance(record['user']['content'], list):
logger.warn(f"由于当前模型 {self.model_configs['model']}不支持视觉,将忽略上下文中的图片输入。如果一直弹出此警告,可以尝试 reset 指令。")
continue
context.append(record['user'])
if "AI" in record and record['AI']:
context.append(record['AI'])
return context
async def is_lvm(self):
'''
是否是 LVM
'''
return self.model_configs['model'].startswith("gpt-4")
async def get_models(self):
'''
获取所有模型
'''
models = await self.client.models.list()
logger.info(f"OpenAI 模型列表:{models}")
return models
async def assemble_context(self, session_id: str, prompt: str, image_url: str = None):
'''
组装上下文,并且根据当前上下文窗口大小截断
'''
if session_id not in self.session_memory:
raise Exception("会话 ID 不存在")
tokens_num = len(self.tokenizer.encode(prompt))
previous_total_tokens_num = 0 if not self.session_memory[session_id] else self.session_memory[session_id][-1]['usage_tokens']
message = {
"usage_tokens": previous_total_tokens_num + tokens_num,
"single_tokens": tokens_num,
"AI": None
}
if image_url:
user_content = {
"role": "user",
"content": [
{
"type": "text",
"text": prompt
},
{
"type": "image_url",
"image_url": {
"url": await self.encode_image_bs64(image_url)
}
}
]
}
else:
user_content = {
"role": "user",
"content": prompt
}
message["user"] = user_content
self.session_memory[session_id].append(message)
# 根据 模型的上下文窗口 淘汰掉多余的记录
curr_model = self.model_configs['model']
if curr_model in MODELS:
maxium_tokens_num = MODELS[curr_model] - 300 # 至少预留 300 给 completion
# if message['usage_tokens'] > maxium_tokens_num:
# 淘汰多余的记录,使得最终的 usage_tokens 不超过 maxium_tokens_num - 300
# contexts = self.session_memory[session_id]
# need_to_remove_idx = 0
# freed_tokens_num = contexts[0]['single-tokens']
# while freed_tokens_num < message['usage_tokens'] - maxium_tokens_num:
# need_to_remove_idx += 1
# freed_tokens_num += contexts[need_to_remove_idx]['single-tokens']
# # 更新之后的所有记录的 usage_tokens
# for i in range(len(contexts)):
# if i > need_to_remove_idx:
# contexts[i]['usage_tokens'] -= freed_tokens_num
# logger.debug(f"淘汰上下文记录 {need_to_remove_idx+1} 条,释放 {freed_tokens_num} 个 token。当前上下文总 token 为 {contexts[-1]['usage_tokens']}。")
# self.session_memory[session_id] = contexts[need_to_remove_idx+1:]
while len(self.session_memory[session_id]) and self.session_memory[session_id][-1]['usage_tokens'] > maxium_tokens_num:
self.pop_record(session_id)
async def pop_record(self, session_id: str, pop_system_prompt: bool = False):
'''
弹出第一条记录
'''
if session_id not in self.session_memory:
raise Exception("会话 ID 不存在")
if len(self.session_memory[session_id]) == 0:
return None
for i in range(len(self.session_memory[session_id])):
# 检查是否是 system prompt
if not pop_system_prompt and self.session_memory[session_id][i]['user']['role'] == "system":
# 如果只有一个 system prompt才不删掉
f = False
for j in range(i+1, len(self.session_memory[session_id])):
if self.session_memory[session_id][j]['user']['role'] == "system":
f = True
break
if not f:
continue
record = self.session_memory[session_id].pop(i)
break
# 更新之后所有记录的 usage_tokens
for i in range(len(self.session_memory[session_id])):
self.session_memory[session_id][i]['usage_tokens'] -= record['single-tokens']
logger.debug(f"淘汰上下文记录 1 条,释放 {record['single-tokens']} 个 token。当前上下文总 token 为 {self.session_memory[session_id][-1]['usage_tokens']}")
return record
async def text_chat(self,
prompt: str,
session_id: str,
image_url: None=None,
tools: None=None,
extra_conf: Dict = None,
**kwargs
) -> str:
super().accu_model_stat()
if not session_id:
session_id = "unknown"
if "unknown" in self.session_memory:
del self.session_memory["unknown"]
if session_id not in self.session_memory:
self.session_memory[session_id] = []
if session_id not in self.session_personality or not self.session_personality[session_id]:
self.personality_set(self.curr_personality, session_id)
self.session_personality[session_id] = True
# 如果 prompt 超过了最大窗口,截断。
# 1. 可以保证之后 pop 的时候不会出现问题
# 2. 可以保证不会超过最大 token 数
_encoded_prompt = self.tokenizer.encode(prompt)
curr_model = self.model_configs['model']
if curr_model in MODELS and len(_encoded_prompt) > MODELS[curr_model] - 300:
_encoded_prompt = _encoded_prompt[:MODELS[curr_model] - 300]
prompt = self.tokenizer.decode(_encoded_prompt)
# 组装上下文,并且根据当前上下文窗口大小截断
await self.assemble_context(session_id, prompt, image_url)
# 获取上下文openai 格式
contexts = await self.retrieve_context(session_id)
conf = self.model_configs
if extra_conf: conf.update(extra_conf)
# start request
retry = 0
rate_limit_retry = 0
while retry < 3 or rate_limit_retry < 5:
logger.debug(conf)
logger.debug(contexts)
if tools:
completion_coro = self.client.chat.completions.create(
messages=contexts,
tools=tools,
**conf
)
else:
completion_coro = self.client.chat.completions.create(
messages=contexts,
**conf
)
try:
completion = await completion_coro
break
except AuthenticationError as e:
api_key = self.chosen_api_key[10:] + "..."
logger.error(f"OpenAI API Key {api_key} 验证错误。详细原因:{e}。正在切换到下一个可用的 Key如果有的话")
self.keys_data[self.chosen_api_key] = False
ok = await self.switch_to_next_key()
if ok: continue
else: raise Exception("所有 OpenAI API Key 目前都不可用。")
except BadRequestError as e:
logger.warn(f"OpenAI 请求异常:{e}")
if "image_url is only supported by certain models." in str(e):
raise Exception(f"当前模型 { self.model_configs['model'] } 不支持图片输入,请更换模型。")
retry += 1
except RateLimitError as e:
if "You exceeded your current quota" in str(e):
self.keys_data[self.chosen_api_key] = False
ok = await self.switch_to_next_key()
if ok: continue
else: raise Exception("所有 OpenAI API Key 目前都不可用。")
logger.error(f"OpenAI API Key {self.chosen_api_key} 达到请求速率限制或者官方服务器当前超载。详细原因:{e}")
await self.switch_to_next_key()
rate_limit_retry += 1
time.sleep(1)
except Exception as e:
retry += 1
if retry >= 3:
logger.error(traceback.format_exc())
raise Exception(f"OpenAI 请求失败:{e}。重试次数已达到上限。")
if "maximum context length" in str(e):
logger.warn(f"OpenAI 请求失败:{e}。上下文长度超过限制。尝试弹出最早的记录然后重试。")
self.pop_record(session_id)
logger.warning(f"OpenAI 请求失败:{e}。重试第 {retry} 次。")
time.sleep(1)
assert isinstance(completion, ChatCompletion)
logger.debug(f"openai completion: {completion.usage}")
choice = completion.choices[0]
usage_tokens = completion.usage.total_tokens
completion_tokens = completion.usage.completion_tokens
self.session_memory[session_id][-1]['usage_tokens'] = usage_tokens
self.session_memory[session_id][-1]['single_tokens'] += completion_tokens
if choice.message.content:
# 返回文本
completion_text = str(choice.message.content).strip()
elif choice.message.tool_calls and choice.message.tool_calls:
# tools call (function calling)
return choice.message.tool_calls[0].function
self.session_memory[session_id][-1]['AI'] = {
"role": "assistant",
"content": completion_text
}
return completion_text
async def switch_to_next_key(self):
'''
切换到下一个 API Key
'''
if not self.api_keys:
logger.error("OpenAI API Key 不存在。")
return False
for key in self.keys_data:
if self.keys_data[key]:
# 没超额
self.chosen_api_key = key
self.client.api_key = key
logger.info(f"OpenAI 切换到 API Key {key[:10]}... 成功。")
return True
return False
async def image_generate(self, prompt: str, session_id: str = None, **kwargs) -> str:
'''
生成图片
'''
retry = 0
conf = self.image_generator_model_configs
super().accu_model_stat(model=conf['model'])
if not conf:
logger.error("OpenAI 图片生成模型配置不存在。")
raise Exception("OpenAI 图片生成模型配置不存在。")
while retry < 3:
try:
images_response = await self.client.images.generate(
prompt=prompt,
**conf
)
image_url = images_response.data[0].url
return image_url
except Exception as e:
retry += 1
if retry >= 3:
logger.error(traceback.format_exc())
raise Exception(f"OpenAI 图片生成请求失败:{e}。重试次数已达到上限。")
logger.warning(f"OpenAI 图片生成请求失败:{e}。重试第 {retry} 次。")
time.sleep(1)
async def forget(self, session_id=None, keep_system_prompt: bool=False) -> bool:
if session_id is None: return False
self.session_memory[session_id] = []
if keep_system_prompt:
self.personality_set(self.curr_personality, session_id)
else:
self.curr_personality = self.DEFAULT_PERSONALITY
return True
def dump_contexts_page(self, session_id: str, size=5, page=1,):
'''
获取缓存的会话
'''
# contexts_str = ""
# for i, key in enumerate(self.session_memory):
# if i < (page-1)*size or i >= page*size:
# continue
# contexts_str += f"Session ID: {key}\n"
# for record in self.session_memory[key]:
# if "user" in record:
# contexts_str += f"User: {record['user']['content']}\n"
# if "AI" in record:
# contexts_str += f"AI: {record['AI']['content']}\n"
# contexts_str += "---\n"
contexts_str = ""
if session_id in self.session_memory:
for record in self.session_memory[session_id]:
if "user" in record and record['user']:
text = record['user']['content'][:100] + "..." if len(record['user']['content']) > 100 else record['user']['content']
contexts_str += f"User: {text}\n"
if "AI" in record and record['AI']:
text = record['AI']['content'][:100] + "..." if len(record['AI']['content']) > 100 else record['AI']['content']
contexts_str += f"Assistant: {text}\n"
else:
contexts_str = "会话 ID 不存在。"
return contexts_str, len(self.session_memory[session_id])
def set_model(self, model: str):
self.model_configs['model'] = model
self.cc.put_by_dot_str("openai.chatGPTConfigs.model", model)
super().set_curr_model(model)
def get_configs(self):
return self.model_configs
def get_keys_data(self):
return self.keys_data
def get_curr_key(self):
return self.chosen_api_key
def set_key(self, key):
self.client.api_key = key