gpt-academicrrrr / predict.py
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add proxy debug funtion
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import json
import gradio as gr
import logging
import traceback
import requests
import importlib
import os
if os.path.exists('config_private.py'):
# 放自己的秘密如API和代理网址
from config_private import proxies, API_URL, API_KEY, TIMEOUT_SECONDS
else:
from config import proxies, API_URL, API_KEY, TIMEOUT_SECONDS
timeout_bot_msg = 'Request timeout, network error. please check proxy settings in config.py.'
def compose_system(system_prompt):
return {"role": "system", "content": system_prompt}
def compose_user(user_input):
return {"role": "user", "content": user_input}
def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', retry=False,
stream = True, additional_fn=None):
if additional_fn is not None:
import functional
importlib.reload(functional)
functional = functional.get_functionals()
inputs = functional[additional_fn]["Prefix"] + inputs + functional[additional_fn]["Suffix"]
if stream:
raw_input = inputs
logging.info(f'[raw_input] {raw_input}')
chatbot.append((inputs, ""))
yield chatbot, history, "等待响应"
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}
chat_counter = len(history) // 2
print(f"chat_counter - {chat_counter}")
messages = [compose_system(system_prompt)]
if chat_counter:
for index in range(0, 2*chat_counter, 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 not (what_gpt_answer["content"] != "" or retry): 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']
if retry and chat_counter:
messages.pop()
else:
what_i_ask_now = {}
what_i_ask_now["role"] = "user"
what_i_ask_now["content"] = inputs
messages.append(what_i_ask_now)
chat_counter += 1
# messages
payload = {
"model": "gpt-3.5-turbo",
# "model": "gpt-4",
"messages": messages,
"temperature": temperature, # 1.0,
"top_p": top_p, # 1.0,
"n": 1,
"stream": stream,
"presence_penalty": 0,
"frequency_penalty": 0,
}
history.append(inputs)
try:
# make a POST request to the API endpoint using the requests.post method, passing in stream=True
response = requests.post(API_URL, headers=headers, proxies=proxies,
json=payload, stream=True, timeout=TIMEOUT_SECONDS)
except:
chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
yield chatbot, history, "请求超时"
raise TimeoutError
token_counter = 0
partial_words = ""
counter = 0
if stream:
stream_response = response.iter_lines()
while True:
chunk = next(stream_response)
if chunk == b'data: [DONE]':
break
if counter == 0:
counter += 1
continue
counter += 1
# check whether each line is non-empty
if chunk:
# decode each line as response data is in bytes
try:
if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
logging.info(f'[response] {chatbot[-1][-1]}')
break
except Exception as e:
traceback.print_exc()
print(chunk.decode())
try:
chunkjson = json.loads(chunk.decode()[6:])
status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}"
partial_words = partial_words + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
if token_counter == 0:
history.append(" " + partial_words)
else:
history[-1] = partial_words
chatbot[-1] = (history[-2], history[-1])
token_counter += 1
yield chatbot, history, status_text
except Exception as e:
traceback.print_exc()
print(chunk.decode())
yield chatbot, history, "Json解析不合常规"