文件
gpt_academic/request_llms/com_qwenapi.py
binary-husky a01ca93362 Merge Latest Frontier (#1991)
* logging sys to loguru: stage 1 complete

* import loguru: stage 2

* logging -> loguru: stage 3

* support o1-preview and o1-mini

* logging -> loguru stage 4

* update social helper

* logging -> loguru: final stage

* fix: console output

* update translation matrix

* fix: loguru argument error with proxy enabled (#1977)

* relax llama index version

* remove comment

* Added some modules to support openrouter (#1975)

* Added some modules for supporting openrouter model

Added some modules for supporting openrouter model

* Update config.py

* Update .gitignore

* Update bridge_openrouter.py

* Not changed actually

* Refactor logging in bridge_openrouter.py

---------

Co-authored-by: binary-husky <qingxu.fu@outlook.com>

* remove logging extra

---------

Co-authored-by: Steven Moder <java20131114@gmail.com>
Co-authored-by: Ren Lifei <2602264455@qq.com>
2024-10-05 17:09:18 +08:00

102 行
3.8 KiB
Python

from http import HTTPStatus
from toolbox import get_conf
import threading
timeout_bot_msg = '[Local Message] Request timeout. Network error.'
class QwenRequestInstance():
def __init__(self):
import dashscope
self.time_to_yield_event = threading.Event()
self.time_to_exit_event = threading.Event()
self.result_buf = ""
def validate_key():
DASHSCOPE_API_KEY = get_conf("DASHSCOPE_API_KEY")
if DASHSCOPE_API_KEY == '': return False
return True
if not validate_key():
raise RuntimeError('请配置 DASHSCOPE_API_KEY')
dashscope.api_key = get_conf("DASHSCOPE_API_KEY")
def generate(self, inputs, llm_kwargs, history, system_prompt):
# import _thread as thread
from dashscope import Generation
QWEN_MODEL = {
'qwen-turbo': Generation.Models.qwen_turbo,
'qwen-plus': Generation.Models.qwen_plus,
'qwen-max': Generation.Models.qwen_max,
}[llm_kwargs['llm_model']]
top_p = llm_kwargs.get('top_p', 0.8)
if top_p == 0: top_p += 1e-5
if top_p == 1: top_p -= 1e-5
self.result_buf = ""
responses = Generation.call(
model=QWEN_MODEL,
messages=generate_message_payload(inputs, llm_kwargs, history, system_prompt),
top_p=top_p,
temperature=llm_kwargs.get('temperature', 1.0),
result_format='message',
stream=True,
incremental_output=True
)
for response in responses:
if response.status_code == HTTPStatus.OK:
if response.output.choices[0].finish_reason == 'stop':
try:
self.result_buf += response.output.choices[0].message.content
except:
pass
yield self.result_buf
break
elif response.output.choices[0].finish_reason == 'length':
self.result_buf += "[Local Message] 生成长度过长,后续输出被截断"
yield self.result_buf
break
else:
self.result_buf += response.output.choices[0].message.content
yield self.result_buf
else:
self.result_buf += f"[Local Message] 请求错误:状态码:{response.status_code},错误码:{response.code},消息:{response.message}"
yield self.result_buf
break
# 耗尽generator避免报错
while True:
try: next(responses)
except: break
return self.result_buf
def generate_message_payload(inputs, llm_kwargs, history, system_prompt):
conversation_cnt = len(history) // 2
if system_prompt == '': system_prompt = 'Hello!'
messages = [{"role": "user", "content": system_prompt}, {"role": "assistant", "content": "Certainly!"}]
if conversation_cnt:
for index in range(0, 2*conversation_cnt, 2):
what_i_have_asked = {}
what_i_have_asked["role"] = "user"
what_i_have_asked["content"] = history[index]
what_gpt_answer = {}
what_gpt_answer["role"] = "assistant"
what_gpt_answer["content"] = history[index+1]
if what_i_have_asked["content"] != "":
if what_gpt_answer["content"] == "":
continue
if what_gpt_answer["content"] == timeout_bot_msg:
continue
messages.append(what_i_have_asked)
messages.append(what_gpt_answer)
else:
messages[-1]['content'] = what_gpt_answer['content']
what_i_ask_now = {}
what_i_ask_now["role"] = "user"
what_i_ask_now["content"] = inputs
messages.append(what_i_ask_now)
return messages