diff --git a/config.py b/config.py index 4740717f..39df8bdd 100644 --- a/config.py +++ b/config.py @@ -13,6 +13,9 @@ API_KEY = "在此处填写APIKEY" # 可同时填写多个API-KEY，用英文 # [step 1-2]>> ( 接入通义 qwen-max ) 接入通义千问在线大模型，api-key获取地址 https://dashscope.console.aliyun.com/ DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY +# [step 1-3]>> ( 接入通义 deepseek-reasoner ) 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions" +DEEPSEEK_API_KEY = "" + # [step 2]>> 改为True应用代理，如果直接在海外服务器部署，此处不修改；如果使用本地或无地域限制的大模型时，此处也不需要修改 USE_PROXY = False if USE_PROXY: @@ -39,7 +42,8 @@ AVAIL_LLM_MODELS = ["qwen-max", "o1-mini", "o1-mini-2024-09-12", "o1", "o1-2024- "gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4-turbo-2024-04-09", "gpt-3.5-turbo-1106", "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "gpt-4", "gpt-4-32k", "azure-gpt-4", "glm-4", "glm-4v", "glm-3-turbo", - "gemini-1.5-pro", "chatglm3", "chatglm4" + "gemini-1.5-pro", "chatglm3", "chatglm4", + "deepseek-chat", "deepseek-coder", "deepseek-reasoner" ] EMBEDDING_MODEL = "text-embedding-3-small" @@ -261,9 +265,6 @@ MOONSHOT_API_KEY = "" # 零一万物(Yi Model) API KEY YIMODEL_API_KEY = "" -# 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions" -DEEPSEEK_API_KEY = "" - # 紫东太初大模型 https://ai-maas.wair.ac.cn TAICHU_API_KEY = "" diff --git a/request_llms/bridge_all.py b/request_llms/bridge_all.py index 612f62ff..0679000a 100644 --- a/request_llms/bridge_all.py +++ b/request_llms/bridge_all.py @@ -1090,18 +1090,18 @@ if "deepseekcoder" in AVAIL_LLM_MODELS: # deepseekcoder except: logger.error(trimmed_format_exc()) # -=-=-=-=-=-=- 幻方-深度求索大模型在线API -=-=-=-=-=-=- -if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS: +if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS or "deepseek-reasoner" in AVAIL_LLM_MODELS: try: deepseekapi_noui, deepseekapi_ui = get_predict_function( api_key_conf_name="DEEPSEEK_API_KEY", max_output_token=4096, disable_proxy=False - ) + ) model_info.update({ "deepseek-chat":{ "fn_with_ui": deepseekapi_ui, "fn_without_ui": deepseekapi_noui, "endpoint": deepseekapi_endpoint, "can_multi_thread": True, - "max_token": 32000, + "max_token": 64000, "tokenizer": tokenizer_gpt35, "token_cnt": get_token_num_gpt35, }, @@ -1114,6 +1114,16 @@ if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS: "tokenizer": tokenizer_gpt35, "token_cnt": get_token_num_gpt35, }, + "deepseek-reasoner":{ + "fn_with_ui": deepseekapi_ui, + "fn_without_ui": deepseekapi_noui, + "endpoint": deepseekapi_endpoint, + "can_multi_thread": True, + "max_token": 64000, + "tokenizer": tokenizer_gpt35, + "token_cnt": get_token_num_gpt35, + "enable_reasoning": True + }, }) except: logger.error(trimmed_format_exc()) diff --git a/request_llms/oai_std_model_template.py b/request_llms/oai_std_model_template.py index a19f05bf..973eb10d 100644 --- a/request_llms/oai_std_model_template.py +++ b/request_llms/oai_std_model_template.py @@ -36,10 +36,11 @@ def get_full_error(chunk, stream_response): def decode_chunk(chunk): """ - 用于解读"content"和"finish_reason"的内容 + 用于解读"content"和"finish_reason"的内容（如果支持思维链也会返回"reasoning_content"内容） """ chunk = chunk.decode() respose = "" + reasoning_content = "" finish_reason = "False" try: chunk = json.loads(chunk[6:]) @@ -57,14 +58,20 @@ def decode_chunk(chunk): return respose, finish_reason try: - respose = chunk["choices"][0]["delta"]["content"] + if chunk["choices"][0]["delta"]["content"] is not None: + respose = chunk["choices"][0]["delta"]["content"] + except: + pass + try: + if chunk["choices"][0]["delta"]["reasoning_content"] is not None: + reasoning_content = chunk["choices"][0]["delta"]["reasoning_content"] except: pass try: finish_reason = chunk["choices"][0]["finish_reason"] except: pass - return respose, finish_reason + return respose, reasoning_content, finish_reason def generate_message(input, model, key, history, max_output_token, system_prompt, temperature): @@ -149,6 +156,7 @@ def get_predict_function( observe_window = None： 用于负责跨越线程传递已经输出的部分，大部分时候仅仅为了fancy的视觉效果，留空即可。observe_window[0]：观测窗。observe_window[1]：看门狗 """ + from .bridge_all import model_info watch_dog_patience = 5 # 看门狗的耐心，设置5秒不准咬人(咬的也不是人 if len(APIKEY) == 0: raise RuntimeError(f"APIKEY为空,请检查配置文件的{APIKEY}") @@ -163,29 +171,21 @@ def get_predict_function( system_prompt=sys_prompt, temperature=llm_kwargs["temperature"], ) + + reasoning = model_info[llm_kwargs['llm_model']].get('enable_reasoning', False) + retry = 0 while True: try: - from .bridge_all import model_info - endpoint = model_info[llm_kwargs["llm_model"]]["endpoint"] - if not disable_proxy: - response = requests.post( - endpoint, - headers=headers, - proxies=proxies, - json=playload, - stream=True, - timeout=TIMEOUT_SECONDS, - ) - else: - response = requests.post( - endpoint, - headers=headers, - json=playload, - stream=True, - timeout=TIMEOUT_SECONDS, - ) + response = requests.post( + endpoint, + headers=headers, + proxies=None if disable_proxy else proxies, + json=playload, + stream=True, + timeout=TIMEOUT_SECONDS, + ) break except: retry += 1 @@ -194,10 +194,13 @@ def get_predict_function( raise TimeoutError if MAX_RETRY != 0: logger.error(f"请求超时，正在重试 ({retry}/{MAX_RETRY}) ……") - - stream_response = response.iter_lines() + result = "" finish_reason = "" + if reasoning: + resoning_buffer = "" + + stream_response = response.iter_lines() while True: try: chunk = next(stream_response) @@ -207,9 +210,9 @@ def get_predict_function( break except requests.exceptions.ConnectionError: chunk = next(stream_response) # 失败了，重试一次？再失败就没办法了。 - response_text, finish_reason = decode_chunk(chunk) + response_text, reasoning_content, finish_reason = decode_chunk(chunk) # 返回的数据流第一次为空，继续等待 - if response_text == "" and finish_reason != "False": + if response_text == "" and (reasoning == False or reasoning_content == "") and finish_reason != "False": continue if response_text == "API_ERROR" and ( finish_reason != "False" or finish_reason != "stop" @@ -227,6 +230,8 @@ def get_predict_function( print(f"[response] {result}") break result += response_text + if reasoning: + resoning_buffer += reasoning_content if observe_window is not None: # 观测窗，把已经获取的数据显示出去 if len(observe_window) >= 1: @@ -241,6 +246,10 @@ def get_predict_function( error_msg = chunk_decoded logger.error(error_msg) raise RuntimeError("Json解析不合常规") + if reasoning: + # reasoning 的部分加上框 (>) + return '\n'.join(map(lambda x: '> ' + x, resoning_buffer.split('\n'))) + \ + '\n\n' + result return result def predict( @@ -262,6 +271,7 @@ def get_predict_function( chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容 additional_fn代表点击的哪个按钮，按钮见functional.py """ + from .bridge_all import model_info if len(APIKEY) == 0: raise RuntimeError(f"APIKEY为空,请检查配置文件的{APIKEY}") if inputs == "": @@ -298,32 +308,23 @@ def get_predict_function( system_prompt=system_prompt, temperature=llm_kwargs["temperature"], ) + + reasoning = model_info[llm_kwargs['llm_model']].get('enable_reasoning', False) history.append(inputs) history.append("") retry = 0 while True: try: - from .bridge_all import model_info - endpoint = model_info[llm_kwargs["llm_model"]]["endpoint"] - if not disable_proxy: - response = requests.post( - endpoint, - headers=headers, - proxies=proxies, - json=playload, - stream=True, - timeout=TIMEOUT_SECONDS, - ) - else: - response = requests.post( - endpoint, - headers=headers, - json=playload, - stream=True, - timeout=TIMEOUT_SECONDS, - ) + response = requests.post( + endpoint, + headers=headers, + proxies=None if disable_proxy else proxies, + json=playload, + stream=True, + timeout=TIMEOUT_SECONDS, + ) break except: retry += 1 @@ -338,6 +339,8 @@ def get_predict_function( raise TimeoutError gpt_replying_buffer = "" + if reasoning: + gpt_reasoning_buffer = "" stream_response = response.iter_lines() while True: @@ -347,9 +350,9 @@ def get_predict_function( break except requests.exceptions.ConnectionError: chunk = next(stream_response) # 失败了，重试一次？再失败就没办法了。 - response_text, finish_reason = decode_chunk(chunk) + response_text, reasoning_content, finish_reason = decode_chunk(chunk) # 返回的数据流第一次为空，继续等待 - if response_text == "" and finish_reason != "False": + if response_text == "" and (reasoning == False or reasoning_content == "") and finish_reason != "False": status_text = f"finish_reason: {finish_reason}" yield from update_ui( chatbot=chatbot, history=history, msg=status_text @@ -379,9 +382,14 @@ def get_predict_function( logger.info(f"[response] {gpt_replying_buffer}") break status_text = f"finish_reason: {finish_reason}" - gpt_replying_buffer += response_text - # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出 - history[-1] = gpt_replying_buffer + if reasoning: + gpt_replying_buffer += response_text + gpt_reasoning_buffer += reasoning_content + history[-1] = '\n'.join(map(lambda x: '> ' + x, gpt_reasoning_buffer.split('\n'))) + '\n\n' + gpt_replying_buffer + else: + gpt_replying_buffer += response_text + # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出 + history[-1] = gpt_replying_buffer chatbot[-1] = (history[-2], history[-1]) yield from update_ui( chatbot=chatbot, history=history, msg=status_text diff --git a/themes/welcome.js b/themes/welcome.js index 54c15d07..c07645de 100644 --- a/themes/welcome.js +++ b/themes/welcome.js @@ -2,12 +2,19 @@ class WelcomeMessage { constructor() { this.static_welcome_message = [ { - title: "环境配置教程", - content: "配置模型和插件，释放大语言模型的学术应用潜力。", - svg: "file=themes/svg/conf.svg", + title: "改变主题外观", + content: "点击「界面外观」，然后「更换UI主题」或「切换界面明暗」。", + svg: "file=themes/svg/theme.svg", url: "https://github.com/binary-husky/gpt_academic/wiki/%E9%A1%B9%E7%9B%AE%E9%85%8D%E7%BD%AE%E8%AF%B4%E6%98%8E", }, { + title: "修改回答语言偏好", + content: "点击「更改模型」，删除「System prompt」并输入「用某语言回答」。", + svg: "file=themes/svg/prompt.svg", + url: "https://github.com/binary-husky/gpt_academic", + }, + { + title: "Arxiv论文一键翻译", title: "Arxiv论文翻译", content: "无缝切换学术阅读语言，最优英文转中文的学术论文阅读体验。", svg: "file=themes/svg/arxiv.svg", @@ -19,6 +26,12 @@ class WelcomeMessage { svg: "file=themes/svg/mm.svg", url: "https://github.com/binary-husky/gpt_academic", }, + { + title: "获取多个模型的答案", + content: "输入问题后点击「询问多个GPT模型」，消耗算子低于单词询问gpt-4o。", + svg: "file=themes/svg/model_multiple.svg", + url: "https://github.com/binary-husky/gpt_academic", + }, { title: "文档与源码批处理", content: "您可以将任意文件拖入「此处」，随后调用对应插件功能。", @@ -52,7 +65,13 @@ class WelcomeMessage { { title: "实时语音对话", content: "配置实时语音对话功能，无须任何激活词，我将一直倾听。", - svg: "file=themes/svg/default.svg", + svg: "file=themes/svg/voice.svg", + url: "https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md", + }, + { + title: "联网回答问题", + content: "输入问题后，点击右侧插件区的「查互联网后回答」插件。", + svg: "file=themes/svg/Internet.svg", url: "https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md", }, { @@ -85,6 +104,7 @@ class WelcomeMessage { this.card_array = []; this.static_welcome_message_previous = []; this.reflesh_time_interval = 15 * 1000; + this.update_time_interval = 2 * 1000; this.major_title = "欢迎使用GPT-Academic"; const reflesh_render_status = () => { @@ -101,12 +121,19 @@ class WelcomeMessage { window.addEventListener('resize', this.update.bind(this)); // add a loop to reflesh cards this.startRefleshCards(); + this.startAutoUpdate(); } begin_render() { this.update(); } + async startAutoUpdate() { + // sleep certain time + await new Promise(r => setTimeout(r, this.update_time_interval)); + this.update(); + } + async startRefleshCards() { // sleep certain time await new Promise(r => setTimeout(r, this.reflesh_time_interval)); @@ -134,6 +161,7 @@ class WelcomeMessage { // combine two lists this.static_welcome_message_previous = not_shown_previously.concat(already_shown_previously); + this.static_welcome_message_previous = this.static_welcome_message_previous.slice(0, this.max_welcome_card_num); (async () => { // 使用 for...of 循环来处理异步操作 @@ -198,12 +226,11 @@ class WelcomeMessage { return array; } - async update() { + async can_display() { // update the card visibility const elem_chatbot = document.getElementById('gpt-chatbot'); const chatbot_top = elem_chatbot.getBoundingClientRect().top; const welcome_card_container = document.getElementsByClassName('welcome-card-container')[0]; - // detect if welcome card overflow let welcome_card_overflow = false; if (welcome_card_container) { @@ -215,22 +242,22 @@ class WelcomeMessage { var page_width = document.documentElement.clientWidth; const width_to_hide_welcome = 1200; if (!await this.isChatbotEmpty() || page_width < width_to_hide_welcome || welcome_card_overflow) { - // overflow ! - if (this.visible) { - // console.log("remove welcome"); - this.removeWelcome(); - this.card_array = []; - this.static_welcome_message_previous = []; - } + // cannot display + return false; + } + return true; + } + + async update() { + const can_display = await this.can_display(); + if (can_display && !this.visible) { + this.showWelcome(); return; } - if (this.visible) { - // console.log("already visible"); + if (!can_display && this.visible) { + this.removeWelcome(); return; } - // not overflow, not yet shown, then create and display welcome card - // console.log("show welcome"); - this.showWelcome(); } showCard(message) { @@ -297,6 +324,16 @@ class WelcomeMessage { }); elem_chatbot.appendChild(welcome_card_container); + const can_display = await this.can_display(); + if (!can_display) { + // undo + this.visible = false; + this.card_array = []; + this.static_welcome_message_previous = []; + elem_chatbot.removeChild(welcome_card_container); + await new Promise(r => setTimeout(r, this.update_time_interval / 2)); + return; + } // 添加显示动画 requestAnimationFrame(() => { @@ -313,6 +350,8 @@ class WelcomeMessage { welcome_card_container.classList.add('hide'); welcome_card_container.addEventListener('transitionend', () => { elem_chatbot.removeChild(welcome_card_container); + this.card_array = []; + this.static_welcome_message_previous = []; }, { once: true }); // add a fail safe timeout const timeout = 600; // 与 CSS 中 transition 的时间保持一致(1s)