211 lines
7.5 KiB
Python
211 lines
7.5 KiB
Python
# 借鉴了 https://github.com/GaiZhenbiao/ChuanhuChatGPT 项目
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import json
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import gradio as gr
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import logging
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import traceback
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import requests
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import importlib
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# config_private.py放自己的秘密如API和代理网址
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# 读取时首先看是否存在私密的config_private配置文件（不受git管控），如果有，则覆盖原config文件
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try: from config_private import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY
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except: from config import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY
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timeout_bot_msg = '[local] Request timeout, network error. please check proxy settings in config.py.'
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def get_full_error(chunk, stream_response):
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while True:
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try:
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chunk += next(stream_response)
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except:
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break
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return chunk
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def predict_no_ui(inputs, top_p, temperature, history=[]):
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messages = [{"role": "system", "content": ""}]
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#
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chat_counter = len(history) // 2
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if chat_counter > 0:
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for index in range(0, 2*chat_counter, 2):
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what_i_have_asked = {}
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what_i_have_asked["role"] = "user"
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what_i_have_asked["content"] = history[index]
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what_gpt_answer = {}
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what_gpt_answer["role"] = "assistant"
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what_gpt_answer["content"] = history[index+1]
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if what_i_have_asked["content"] != "":
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messages.append(what_i_have_asked)
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messages.append(what_gpt_answer)
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else:
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messages[-1]['content'] = what_gpt_answer['content']
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what_i_ask_now = {}
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what_i_ask_now["role"] = "user"
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what_i_ask_now["content"] = inputs
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messages.append(what_i_ask_now)
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# messages
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payload = {
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"model": "gpt-3.5-turbo",
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# "model": "gpt-4",
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"messages": messages,
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"temperature": temperature, # 1.0,
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"top_p": top_p, # 1.0,
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"n": 1,
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"stream": False,
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"presence_penalty": 0,
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"frequency_penalty": 0,
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}
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {API_KEY}"
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}
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retry = 0
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while True:
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try:
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# make a POST request to the API endpoint using the requests.post method, passing in stream=True
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response = requests.post(API_URL, headers=headers, proxies=proxies,
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json=payload, stream=False, timeout=TIMEOUT_SECONDS*2); break
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except TimeoutError as e:
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retry += 1
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traceback.print_exc()
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if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
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if retry > MAX_RETRY: raise TimeoutError
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try:
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result = json.loads(response.text)["choices"][0]["message"]["content"]
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return result
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except Exception as e:
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if "choices" not in response.text: print(response.text)
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raise ConnectionAbortedError("Json解析不合常规，可能是文本过长" + response.text)
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def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', retry=False,
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stream = True, additional_fn=None):
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if additional_fn is not None:
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import functional
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importlib.reload(functional)
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functional = functional.get_functionals()
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inputs = functional[additional_fn]["Prefix"] + inputs + functional[additional_fn]["Suffix"]
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if stream:
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raw_input = inputs
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logging.info(f'[raw_input] {raw_input}')
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chatbot.append((inputs, ""))
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yield chatbot, history, "等待响应"
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {API_KEY}"
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}
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chat_counter = len(history) // 2
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print(f"chat_counter - {chat_counter}")
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messages = [{"role": "system", "content": system_prompt}]
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if chat_counter:
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for index in range(0, 2*chat_counter, 2):
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what_i_have_asked = {}
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what_i_have_asked["role"] = "user"
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what_i_have_asked["content"] = history[index]
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what_gpt_answer = {}
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what_gpt_answer["role"] = "assistant"
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what_gpt_answer["content"] = history[index+1]
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if what_i_have_asked["content"] != "":
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if not (what_gpt_answer["content"] != "" or retry): continue
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if what_gpt_answer["content"] == timeout_bot_msg: continue
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messages.append(what_i_have_asked)
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messages.append(what_gpt_answer)
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else:
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messages[-1]['content'] = what_gpt_answer['content']
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if retry and chat_counter:
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messages.pop()
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else:
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what_i_ask_now = {}
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what_i_ask_now["role"] = "user"
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what_i_ask_now["content"] = inputs
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messages.append(what_i_ask_now)
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chat_counter += 1
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# messages
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payload = {
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"model": "gpt-3.5-turbo",
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# "model": "gpt-4",
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"messages": messages,
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"temperature": temperature, # 1.0,
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"top_p": top_p, # 1.0,
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"n": 1,
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"stream": stream,
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"presence_penalty": 0,
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"frequency_penalty": 0,
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}
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history.append(inputs)
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retry = 0
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while True:
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try:
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# make a POST request to the API endpoint using the requests.post method, passing in stream=True
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response = requests.post(API_URL, headers=headers, proxies=proxies,
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json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
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except:
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retry += 1
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chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
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retry_msg = f"，正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else ""
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yield chatbot, history, "请求超时"+retry_msg
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if retry > MAX_RETRY: raise TimeoutError
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token_counter = 0
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partial_words = ""
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counter = 0
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if stream:
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stream_response = response.iter_lines()
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while True:
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chunk = next(stream_response)
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if chunk == b'data: [DONE]':
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break
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if counter == 0:
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counter += 1
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continue
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counter += 1
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# check whether each line is non-empty
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if chunk:
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# decode each line as response data is in bytes
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try:
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if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
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logging.info(f'[response] {chatbot[-1][-1]}')
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break
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chunkjson = json.loads(chunk.decode()[6:])
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status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}"
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partial_words = partial_words + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
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if token_counter == 0:
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history.append(" " + partial_words)
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else:
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history[-1] = partial_words
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chatbot[-1] = (history[-2], history[-1])
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token_counter += 1
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yield chatbot, history, status_text
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except Exception as e:
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traceback.print_exc()
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yield chatbot, history, "Json解析不合常规，很可能是文本过长"
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chunk = get_full_error(chunk, stream_response)
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error_msg = chunk.decode()
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if "reduce the length" in error_msg:
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chatbot[-1] = (history[-1], "[local] input is too long, reduce input or clear history.")
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yield chatbot, history, "Json解析不合常规，很可能是文本过长" + error_msg
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return
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