Spaces:
Runtime error
Runtime error
File size: 4,141 Bytes
444f09e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
from toolbox import get_conf
import threading
import logging
import os
timeout_bot_msg = '[Local Message] Request timeout. Network error.'
#os.environ['VOLC_ACCESSKEY'] = ''
#os.environ['VOLC_SECRETKEY'] = ''
class YUNQUERequestInstance():
def __init__(self):
self.time_to_yield_event = threading.Event()
self.time_to_exit_event = threading.Event()
self.result_buf = ""
def generate(self, inputs, llm_kwargs, history, system_prompt):
# import _thread as thread
from volcengine.maas import MaasService, MaasException
maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', 'cn-beijing')
YUNQUE_SECRET_KEY, YUNQUE_ACCESS_KEY,YUNQUE_MODEL = get_conf("YUNQUE_SECRET_KEY", "YUNQUE_ACCESS_KEY","YUNQUE_MODEL")
maas.set_ak(YUNQUE_ACCESS_KEY) #填写 VOLC_ACCESSKEY
maas.set_sk(YUNQUE_SECRET_KEY) #填写 'VOLC_SECRETKEY'
self.result_buf = ""
req = {
"model": {
"name": YUNQUE_MODEL,
"version": "1.0", # use default version if not specified.
},
"parameters": {
"max_new_tokens": 4000, # 输出文本的最大tokens限制
"min_new_tokens": 1, # 输出文本的最小tokens限制
"temperature": llm_kwargs['temperature'], # 用于控制生成文本的随机性和创造性，Temperature值越大随机性越大，取值范围0~1
"top_p": llm_kwargs['top_p'], # 用于控制输出tokens的多样性，TopP值越大输出的tokens类型越丰富，取值范围0~1
"top_k": 0, # 选择预测值最大的k个token进行采样，取值范围0-1000，0表示不生效
"max_prompt_tokens": 4000, # 最大输入 token 数，如果给出的 prompt 的 token 长度超过此限制，取最后 max_prompt_tokens 个 token 输入模型。
},
"messages": self.generate_message_payload(inputs, llm_kwargs, history, system_prompt)
}
response = maas.stream_chat(req)
for resp in response:
self.result_buf += resp.choice.message.content
yield self.result_buf
'''
for event in response.events():
if event.event == "add":
self.result_buf += event.data
yield self.result_buf
elif event.event == "error" or event.event == "interrupted":
raise RuntimeError("Unknown error:" + event.data)
elif event.event == "finish":
yield self.result_buf
break
else:
raise RuntimeError("Unknown error:" + str(event))
logging.info(f'[raw_input] {inputs}')
logging.info(f'[response] {self.result_buf}')
'''
return self.result_buf
def generate_message_payload(inputs, llm_kwargs, history, system_prompt):
from volcengine.maas import ChatRole
conversation_cnt = len(history) // 2
messages = [{"role": ChatRole.USER, "content": system_prompt},
{"role": ChatRole.ASSISTANT, "content": "Certainly!"}]
if conversation_cnt:
for index in range(0, 2 * conversation_cnt, 2):
what_i_have_asked = {}
what_i_have_asked["role"] = ChatRole.USER
what_i_have_asked["content"] = history[index]
what_gpt_answer = {}
what_gpt_answer["role"] = ChatRole.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"] = ChatRole.USER
what_i_ask_now["content"] = inputs
messages.append(what_i_ask_now)
return messages |