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适配 google gemini 优化为从用户input中提取文件 (#1419)
适配 google gemini 优化为从用户input中提取文件
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,101 @@ | ||
| # encoding: utf-8 | ||
| # @Time : 2023/12/21 | ||
| # @Author : Spike | ||
| # @Descr : | ||
| import json | ||
| import re | ||
| import time | ||
| from request_llms.com_google import GoogleChatInit | ||
| from toolbox import get_conf, update_ui, update_ui_lastest_msg | ||
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| proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY') | ||
| timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \ | ||
| '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。' | ||
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| def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, | ||
| console_slience=False): | ||
| # 检查API_KEY | ||
| if get_conf("GEMINI_API_KEY") == "": | ||
| raise ValueError(f"请配置 GEMINI_API_KEY。") | ||
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| genai = GoogleChatInit() | ||
| watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可 | ||
| gpt_replying_buffer = '' | ||
| stream_response = genai.generate_chat(inputs, llm_kwargs, history, sys_prompt) | ||
| for response in stream_response: | ||
| results = response.decode() | ||
| match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL) | ||
| error_match = re.search(r'\"message\":\s*\"(.*?)\"', results, flags=re.DOTALL) | ||
| if match: | ||
| try: | ||
| paraphrase = json.loads('{"text": "%s"}' % match.group(1)) | ||
| except: | ||
| raise ValueError(f"解析GEMINI消息出错。") | ||
| buffer = paraphrase['text'] | ||
| gpt_replying_buffer += buffer | ||
| if len(observe_window) >= 1: | ||
| observe_window[0] = gpt_replying_buffer | ||
| if len(observe_window) >= 2: | ||
| if (time.time() - observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。") | ||
| if error_match: | ||
| raise RuntimeError(f'{gpt_replying_buffer} 对话错误') | ||
| return gpt_replying_buffer | ||
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| def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream=True, additional_fn=None): | ||
| # 检查API_KEY | ||
| if get_conf("GEMINI_API_KEY") == "": | ||
| yield from update_ui_lastest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0) | ||
| return | ||
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| chatbot.append((inputs, "")) | ||
| yield from update_ui(chatbot=chatbot, history=history) | ||
| genai = GoogleChatInit() | ||
| retry = 0 | ||
| while True: | ||
| try: | ||
| stream_response = genai.generate_chat(inputs, llm_kwargs, history, system_prompt) | ||
| break | ||
| except Exception as e: | ||
| retry += 1 | ||
| chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg)) | ||
| retry_msg = f"，正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else "" | ||
| yield from update_ui(chatbot=chatbot, history=history, msg="请求超时" + retry_msg) # 刷新界面 | ||
| if retry > MAX_RETRY: raise TimeoutError | ||
| gpt_replying_buffer = "" | ||
| gpt_security_policy = "" | ||
| history.extend([inputs, '']) | ||
| for response in stream_response: | ||
| results = response.decode("utf-8") # 被这个解码给耍了。。 | ||
| gpt_security_policy += results | ||
| match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL) | ||
| error_match = re.search(r'\"message\":\s*\"(.*)\"', results, flags=re.DOTALL) | ||
| if match: | ||
| try: | ||
| paraphrase = json.loads('{"text": "%s"}' % match.group(1)) | ||
| except: | ||
| raise ValueError(f"解析GEMINI消息出错。") | ||
| gpt_replying_buffer += paraphrase['text'] # 使用 json 解析库进行处理 | ||
| chatbot[-1] = (inputs, gpt_replying_buffer) | ||
| history[-1] = gpt_replying_buffer | ||
| yield from update_ui(chatbot=chatbot, history=history) | ||
| if error_match: | ||
| history = history[-2] # 错误的不纳入对话 | ||
| chatbot[-1] = (inputs, gpt_replying_buffer + f"对话错误，请查看message\n\n```\n{error_match.group(1)}\n```") | ||
| yield from update_ui(chatbot=chatbot, history=history) | ||
| raise RuntimeError('对话错误') | ||
| if not gpt_replying_buffer: | ||
| history = history[-2] # 错误的不纳入对话 | ||
| chatbot[-1] = (inputs, gpt_replying_buffer + f"触发了Google的安全访问策略，没有回答\n\n```\n{gpt_security_policy}\n```") | ||
| yield from update_ui(chatbot=chatbot, history=history) | ||
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| if __name__ == '__main__': | ||
| import sys | ||
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| llm_kwargs = {'llm_model': 'gemini-pro'} | ||
| result = predict('Write long a story about a magic backpack.', llm_kwargs, llm_kwargs, []) | ||
| for i in result: | ||
| print(i) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| # encoding: utf-8 | ||
| # @Time : 2023/12/25 | ||
| # @Author : Spike | ||
| # @Descr : | ||
| import json | ||
| import requests | ||
| from typing import List, Dict, Tuple | ||
| from toolbox import get_conf | ||
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| proxies, TIMEOUT_SECONDS = get_conf('proxies', 'TIMEOUT_SECONDS') | ||
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| class GoogleChatInit: | ||
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| def __init__(self): | ||
| self.url_gemini = 'https://generativelanguage.googleapis.com/v1beta/models/%m:streamGenerateContent?key=%k' | ||
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| def __conversation_user(self, user_input): | ||
| from toolbox import input_encode_handler | ||
| what_i_have_asked = {"role": "user", "parts": []} | ||
| if 'vision' not in self.url_gemini: | ||
| input_ = user_input | ||
| encode_img = [] | ||
| else: | ||
| input_, encode_img = input_encode_handler(user_input) | ||
| what_i_have_asked['parts'].append({'text': input_}) | ||
| if encode_img: | ||
| for data in encode_img: | ||
| what_i_have_asked['parts'].append( | ||
| {'inline_data': { | ||
| "mime_type": f"image/{data['type']}", | ||
| "data": data['data'] | ||
| }}) | ||
| return what_i_have_asked | ||
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| def __conversation_history(self, history): | ||
| messages = [] | ||
| conversation_cnt = len(history) // 2 | ||
| if conversation_cnt: | ||
| for index in range(0, 2 * conversation_cnt, 2): | ||
| what_i_have_asked = self.__conversation_user(history[index]) | ||
| what_gpt_answer = { | ||
| "role": "model", | ||
| "parts": [{"text": history[index + 1]}] | ||
| } | ||
| messages.append(what_i_have_asked) | ||
| messages.append(what_gpt_answer) | ||
| return messages | ||
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| def generate_chat(self, inputs, llm_kwargs, history, system_prompt): | ||
| headers, payload = self.generate_message_payload(inputs, llm_kwargs, history, system_prompt) | ||
| response = requests.post(url=self.url_gemini, headers=headers, data=json.dumps(payload), | ||
| stream=True, proxies=proxies, timeout=TIMEOUT_SECONDS) | ||
| return response.iter_lines() | ||
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| def generate_message_payload(self, inputs, llm_kwargs, history, system_prompt) -> Tuple[Dict, Dict]: | ||
| messages = [ | ||
| # {"role": "system", "parts": [{"text": system_prompt}]}, # gemini 不允许对话轮次为偶数，所以这个没有用，看后续支持吧。。。 | ||
| # {"role": "user", "parts": [{"text": ""}]}, | ||
| # {"role": "model", "parts": [{"text": ""}]} | ||
| ] | ||
| self.url_gemini = self.url_gemini.replace( | ||
| '%m', llm_kwargs['llm_model']).replace( | ||
| '%k', get_conf('GEMINI_API_KEY') | ||
| ) | ||
| header = {'Content-Type': 'application/json'} | ||
| if 'vision' not in self.url_gemini: # 不是vision 才处理history | ||
| messages.extend(self.__conversation_history(history)) # 处理 history | ||
| messages.append(self.__conversation_user(inputs)) # 处理用户对话 | ||
| payload = { | ||
| "contents": messages, | ||
| "generationConfig": { | ||
| "stopSequences": str(llm_kwargs.get('stop', '')).split(' '), | ||
| "temperature": llm_kwargs.get('temperature', 1), | ||
| # "maxOutputTokens": 800, | ||
| "topP": llm_kwargs.get('top_p', 0.8), | ||
| "topK": 10 | ||
| } | ||
| } | ||
| return header, payload | ||
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| if __name__ == '__main__': | ||
| google = GoogleChatInit() | ||
| # print(gootle.generate_message_payload('你好呀', {}, | ||
| # ['123123', '3123123'], '')) | ||
| # gootle.input_encode_handle('123123[123123](./123123), ') |
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