Merge branch 'master' into frontier

README.md

@@ -1,5 +1,6 @@
 > [!IMPORTANT]
-> `master主分支`最新动态(2025.1.28): 增加字体自定义功能  
+> `master主分支`最新动态(2025.2.4): 增加deepseek-r1支持；增加字体自定义功能  
+> `master主分支`最新动态(2025.2.2): 三分钟快速接入最强qwen2.5-max[视频](https://www.bilibili.com/video/BV1LeFuerEG4)  
 > `frontier开发分支`最新动态(2024.12.9): 更新对话时间线功能，优化xelatex论文翻译  
 > `wiki文档`最新动态(2024.12.5): 更新ollama接入指南  
 >

config.py

@@ -13,7 +13,10 @@ 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 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
+# [step 1-3]>> ( 接入 deepseek-reasoner, 即 deepseek-r1 ) 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。如果使用本地或无地域限制的大模型时，此处不修改；如果直接在海外服务器部署，此处不修改
 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 = ""

request_llms/bridge_all.py

@@ -1090,7 +1090,7 @@ 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
@@ -1101,7 +1101,7 @@ if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS:
                 "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())

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:
+        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}")
@@ -163,25 +171,17 @@ 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,
+                    proxies=None if disable_proxy else proxies,
                     json=playload,
                     stream=True,
                     timeout=TIMEOUT_SECONDS,
@@ -195,9 +195,12 @@ def get_predict_function(
                 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 == "":
@@ -299,27 +309,18 @@ def get_predict_function(
             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,
+                    proxies=None if disable_proxy else proxies,
                     json=playload,
                     stream=True,
                     timeout=TIMEOUT_SECONDS,
@@ -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
@@ -379,6 +382,11 @@ def get_predict_function(
                         logger.info(f"[response] {gpt_replying_buffer}")
                         break
                     status_text = f"finish_reason: {finish_reason}"
+                    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

shared_utils/key_pattern_manager.py

@@ -48,6 +48,13 @@ def is_cohere_api_key(key):
 
 
 def is_any_api_key(key):
+    # key 一般只包含字母、数字、下划线、逗号、中划线
+    if not re.match(r"^[a-zA-Z0-9_\-,]+$", key):
+        # 如果配置了 CUSTOM_API_KEY_PATTERN，再检查以下以免误杀
+        if CUSTOM_API_KEY_PATTERN := get_conf('CUSTOM_API_KEY_PATTERN'):
+            return bool(re.match(CUSTOM_API_KEY_PATTERN, key))
+        return False
+
     if ',' in key:
         keys = key.split(',')
         for k in keys:

themes/welcome.js

@@ -85,6 +85,7 @@ 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 +102,19 @@ 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 +142,7 @@ 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 +207,11 @@ 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 +223,22 @@ 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 !
+            // cannot display
-            if (this.visible) {
+            return false;
-                // console.log("remove welcome");
-                this.removeWelcome();
-                this.card_array = [];
-                this.static_welcome_message_previous = [];
         }
-            return;
+        return true;
     }
-        if (this.visible) {
+
-            // console.log("already visible");
+    async update() {
-            return;
+        const can_display = await this.can_display();
-        }
+        if (can_display && !this.visible) {
-        // not overflow, not yet shown, then create and display welcome card
-        // console.log("show welcome");
             this.showWelcome();
+            return;
+        }
+        if (!can_display && this.visible) {
+            this.removeWelcome();
+            return;
+        }
     }
 
     showCard(message) {
@@ -297,6 +305,16 @@ 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 +331,8 @@ 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)

version

@@ -1,5 +1,5 @@
 {
-  "version": 3.92,
+  "version": 3.93,
   "show_feature": true,
-  "new_feature": "字体和字体大小自定义 <-> 优化前端并修复TTS的BUG <-> 添加时间线回溯功能 <-> 支持chatgpt-4o-latest <-> 增加RAG组件 <-> 升级多合一主提交键"
+  "new_feature": "支持deepseek-reason(r1) <-> 字体和字体大小自定义 <-> 优化前端并修复TTS的BUG <-> 添加时间线回溯功能 <-> 支持chatgpt-4o-latest <-> 增加RAG组件 <-> 升级多合一主提交键"
 }