Merge branch 'frontier'

config.py

@@ -83,9 +83,9 @@ DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
 
 # 模型选择是 (注意: LLM_MODEL是默认选中的模型, 它*必须*被包含在AVAIL_LLM_MODELS列表中 )
 LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
-AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo", 
+AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo",
                     "gpt-4", "gpt-4-32k", "azure-gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
-# P.S. 其他可用的模型还包括 ["qianfan", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", 
+# P.S. 其他可用的模型还包括 ["qianfan", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613",  "gpt-3.5-random"
 # "spark", "sparkv2", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
 
 
@@ -125,6 +125,11 @@ AUTHENTICATION = []
 CUSTOM_PATH = "/"
 
 
+# HTTPS 秘钥和证书（不需要修改）
+SSL_KEYFILE = ""
+SSL_CERTFILE = ""
+
+
 # 极少数情况下，openai的官方KEY需要伴随组织编码（格式如org-xxxxxxxxxxxxxxxxxxxxxxxx）使用
 API_ORG = ""
 
@@ -140,7 +145,7 @@ AZURE_API_KEY = "填入azure openai api的密钥"    # 建议直接在API_KEY处
 AZURE_ENGINE = "填入你亲手写的部署名"            # 读 docs\use_azure.md
 
 
-# 使用Newbing
+# 使用Newbing (不推荐使用，未来将删除)
 NEWBING_STYLE = "creative"  # ["creative", "balanced", "precise"]
 NEWBING_COOKIES = """
 put your new bing cookies here
@@ -198,6 +203,9 @@ PATH_LOGGING = "gpt_log"
 WHEN_TO_USE_PROXY = ["Download_LLM", "Download_Gradio_Theme", "Connect_Grobid", "Warmup_Modules"]
 
 
+# 自定义按钮的最大数量限制
+NUM_CUSTOM_BASIC_BTN = 4
+
 """
 在线大模型配置关联关系示意图
 │

core_functional.py

@@ -91,8 +91,15 @@ def handle_core_functionality(additional_fn, inputs, history, chatbot):
     import core_functional
     importlib.reload(core_functional)    # 热更新prompt
     core_functional = core_functional.get_core_functions()
-    if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
+    addition = chatbot._cookies['customize_fn_overwrite']
-    inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
+    if additional_fn in addition:
-    if core_functional[additional_fn].get("AutoClearHistory", False):
+        # 自定义功能
-        history = []
+        inputs = addition[additional_fn]["Prefix"] + inputs + addition[additional_fn]["Suffix"]
-    return inputs, history
+        return inputs, history
+    else:
+        # 预制功能
+        if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
+        inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
+        if core_functional[additional_fn].get("AutoClearHistory", False):
+            history = []
+        return inputs, history

crazy_functions/crazy_utils.py

@@ -69,12 +69,15 @@ def request_gpt_model_in_new_thread_with_ui_alive(
     yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
     executor = ThreadPoolExecutor(max_workers=16)
     mutable = ["", time.time(), ""]
+    # 看门狗耐心
+    watch_dog_patience = 5
+    # 请求任务
     def _req_gpt(inputs, history, sys_prompt):
         retry_op = retry_times_at_unknown_error
         exceeded_cnt = 0
         while True:
             # watchdog error
-            if len(mutable) >= 2 and (time.time()-mutable[1]) > 5: 
+            if len(mutable) >= 2 and (time.time()-mutable[1]) > watch_dog_patience: 
                 raise RuntimeError("检测到程序终止。")
             try:
                 # 【第一种情况】：顺利完成
@@ -193,6 +196,9 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
     # 跨线程传递
     mutable = [["", time.time(), "等待中"] for _ in range(n_frag)]
 
+    # 看门狗耐心
+    watch_dog_patience = 5
+
     # 子线程任务
     def _req_gpt(index, inputs, history, sys_prompt):
         gpt_say = ""
@@ -201,7 +207,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
         mutable[index][2] = "执行中"
         while True:
             # watchdog error
-            if len(mutable[index]) >= 2 and (time.time()-mutable[index][1]) > 5: 
+            if len(mutable[index]) >= 2 and (time.time()-mutable[index][1]) > watch_dog_patience: 
                 raise RuntimeError("检测到程序终止。")
             try:
                 # 【第一种情况】：顺利完成
@@ -275,7 +281,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
         # 在前端打印些好玩的东西
         for thread_index, _ in enumerate(worker_done):
             print_something_really_funny = "[ ...`"+mutable[thread_index][0][-scroller_max_len:].\
-                replace('\n', '').replace('```', '...').replace(
+                replace('\n', '').replace('`', '.').replace(
                     ' ', '.').replace('<br/>', '.....').replace('$', '.')+"`... ]"
             observe_win.append(print_something_really_funny)
         # 在前端打印些好玩的东西
@@ -301,7 +307,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
             gpt_res = f.result()
             chatbot.append([inputs_show_user, gpt_res])
             yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
-            time.sleep(0.3)
+            time.sleep(0.5)
     return gpt_response_collection
 
 

crazy_functions/latex_fns/latex_toolbox.py

@@ -342,10 +342,33 @@ def merge_tex_files(project_foler, main_file, mode):
         pattern_opt2 = re.compile(r"\\abstract\{(.*?)\}", flags=re.DOTALL)
         match_opt1 = pattern_opt1.search(main_file)
         match_opt2 = pattern_opt2.search(main_file)
+        if (match_opt1 is None) and (match_opt2 is None):
+            # "Cannot find paper abstract section!"
+            main_file = insert_abstract(main_file)
+        match_opt1 = pattern_opt1.search(main_file)
+        match_opt2 = pattern_opt2.search(main_file)
         assert (match_opt1 is not None) or (match_opt2 is not None), "Cannot find paper abstract section!"
     return main_file
 
 
+insert_missing_abs_str = r"""
+\begin{abstract}
+The GPT-Academic program cannot find abstract section in this paper.
+\end{abstract}
+"""
+
+def insert_abstract(tex_content):
+    if "\\maketitle" in tex_content:
+        # find the position of "\maketitle"
+        find_index = tex_content.index("\\maketitle")
+        # find the nearest ending line
+        end_line_index = tex_content.find("\n", find_index)
+        # insert "abs_str" on the next line
+        modified_tex = tex_content[:end_line_index+1] + '\n\n' + insert_missing_abs_str + '\n\n' + tex_content[end_line_index+1:]
+        return modified_tex
+    else:
+        return tex_content
+
 """
 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 Post process

crazy_functions/live_audio/aliyunASR.py

@@ -1,4 +1,106 @@
-import time, logging, json
+import time, logging, json, sys, struct
+import numpy as np
+from scipy.io.wavfile import WAVE_FORMAT
+
+def write_numpy_to_wave(filename, rate, data, add_header=False):
+    """
+    Write a NumPy array as a WAV file.
+    """
+    def _array_tofile(fid, data):
+        # ravel gives a c-contiguous buffer
+        fid.write(data.ravel().view('b').data)
+
+    if hasattr(filename, 'write'):
+        fid = filename
+    else:
+        fid = open(filename, 'wb')
+
+    fs = rate
+
+    try:
+        dkind = data.dtype.kind
+        if not (dkind == 'i' or dkind == 'f' or (dkind == 'u' and
+                                                 data.dtype.itemsize == 1)):
+            raise ValueError("Unsupported data type '%s'" % data.dtype)
+
+        header_data = b''
+
+        header_data += b'RIFF'
+        header_data += b'\x00\x00\x00\x00'
+        header_data += b'WAVE'
+
+        # fmt chunk
+        header_data += b'fmt '
+        if dkind == 'f':
+            format_tag = WAVE_FORMAT.IEEE_FLOAT
+        else:
+            format_tag = WAVE_FORMAT.PCM
+        if data.ndim == 1:
+            channels = 1
+        else:
+            channels = data.shape[1]
+        bit_depth = data.dtype.itemsize * 8
+        bytes_per_second = fs*(bit_depth // 8)*channels
+        block_align = channels * (bit_depth // 8)
+
+        fmt_chunk_data = struct.pack('<HHIIHH', format_tag, channels, fs,
+                                     bytes_per_second, block_align, bit_depth)
+        if not (dkind == 'i' or dkind == 'u'):
+            # add cbSize field for non-PCM files
+            fmt_chunk_data += b'\x00\x00'
+
+        header_data += struct.pack('<I', len(fmt_chunk_data))
+        header_data += fmt_chunk_data
+
+        # fact chunk (non-PCM files)
+        if not (dkind == 'i' or dkind == 'u'):
+            header_data += b'fact'
+            header_data += struct.pack('<II', 4, data.shape[0])
+
+        # check data size (needs to be immediately before the data chunk)
+        if ((len(header_data)-4-4) + (4+4+data.nbytes)) > 0xFFFFFFFF:
+            raise ValueError("Data exceeds wave file size limit")
+        if add_header:
+            fid.write(header_data)
+            # data chunk
+            fid.write(b'data')
+            fid.write(struct.pack('<I', data.nbytes))
+            if data.dtype.byteorder == '>' or (data.dtype.byteorder == '=' and
+                                            sys.byteorder == 'big'):
+                data = data.byteswap()
+        _array_tofile(fid, data)
+
+        if add_header:
+            # Determine file size and place it in correct
+            #  position at start of the file.
+            size = fid.tell()
+            fid.seek(4)
+            fid.write(struct.pack('<I', size-8))
+
+    finally:
+        if not hasattr(filename, 'write'):
+            fid.close()
+        else:
+            fid.seek(0)
+
+def is_speaker_speaking(vad, data, sample_rate):
+    # Function to detect if the speaker is speaking
+    # The WebRTC VAD only accepts 16-bit mono PCM audio, 
+    # sampled at 8000, 16000, 32000 or 48000 Hz. 
+    # A frame must be either 10, 20, or 30 ms in duration:
+    frame_duration = 30
+    n_bit_each = int(sample_rate * frame_duration / 1000)*2 # x2 because audio is 16 bit (2 bytes)
+    res_list = []
+    for t in range(len(data)):
+        if t!=0 and t % n_bit_each == 0:
+            res_list.append(vad.is_speech(data[t-n_bit_each:t], sample_rate))
+    
+    info = ''.join(['^' if r else '.' for r in res_list])
+    info = info[:10]
+    if any(res_list):
+        return True, info
+    else:
+        return False, info
 
 
 class AliyunASR():
@@ -66,12 +168,22 @@ class AliyunASR():
                     on_close=self.test_on_close,
                     callback_args=[uuid.hex]
                 )
-
+        timeout_limit_second = 20
         r = sr.start(aformat="pcm",
+                timeout=timeout_limit_second,
                 enable_intermediate_result=True,
                 enable_punctuation_prediction=True,
                 enable_inverse_text_normalization=True)
 
+        import webrtcvad
+        vad = webrtcvad.Vad()
+        vad.set_mode(1)
+
+        is_previous_frame_transmitted = False   # 上一帧是否有人说话
+        previous_frame_data = None
+        echo_cnt = 0        # 在没有声音之后，继续向服务器发送n次音频数据
+        echo_cnt_max = 4   # 在没有声音之后，继续向服务器发送n次音频数据
+        keep_alive_last_send_time = time.time()
         while not self.stop:
             # time.sleep(self.capture_interval)
             audio = rad.read(uuid.hex) 
@@ -79,12 +191,32 @@ class AliyunASR():
                 # convert to pcm file
                 temp_file = f'{temp_folder}/{uuid.hex}.pcm' # 
                 dsdata = change_sample_rate(audio, rad.rate, NEW_SAMPLERATE) # 48000 --> 16000
-                io.wavfile.write(temp_file, NEW_SAMPLERATE, dsdata)
+                write_numpy_to_wave(temp_file, NEW_SAMPLERATE, dsdata)
                 # read pcm binary
                 with open(temp_file, "rb") as f: data = f.read()
-                # print('audio len:', len(audio), '\t ds len:', len(dsdata), '\t need n send:', len(data)//640)
+                is_speaking, info = is_speaker_speaking(vad, data, NEW_SAMPLERATE)
-                slices = zip(*(iter(data),) * 640)    # 640个字节为一组
+
-                for i in slices: sr.send_audio(bytes(i))
+                if is_speaking or echo_cnt > 0:
+                    # 如果话筒激活 / 如果处于回声收尾阶段
+                    echo_cnt -= 1
+                    if not is_previous_frame_transmitted:   # 上一帧没有人声，但是我们把上一帧同样加上
+                        if previous_frame_data is not None: data = previous_frame_data + data
+                    if is_speaking:
+                        echo_cnt = echo_cnt_max
+                    slices = zip(*(iter(data),) * 640)      # 640个字节为一组
+                    for i in slices: sr.send_audio(bytes(i))
+                    keep_alive_last_send_time = time.time()
+                    is_previous_frame_transmitted = True
+                else:
+                    is_previous_frame_transmitted = False
+                    echo_cnt = 0
+                    # 保持链接激活，即使没有声音，也根据时间间隔，发送一些音频片段给服务器
+                    if time.time() - keep_alive_last_send_time > timeout_limit_second/2:
+                        slices = zip(*(iter(data),) * 640)    # 640个字节为一组
+                        for i in slices: sr.send_audio(bytes(i))
+                        keep_alive_last_send_time = time.time()
+                        is_previous_frame_transmitted = True
+                self.audio_shape = info
             else:
                 time.sleep(0.1)
 

crazy_functions/live_audio/audio_io.py

@@ -35,7 +35,7 @@ class RealtimeAudioDistribution():
     def read(self, uuid):
         if uuid in self.data:
             res = self.data.pop(uuid)
-            print('\r read-', len(res), '-', max(res), end='', flush=True)
+            # print('\r read-', len(res), '-', max(res), end='', flush=True)
         else:
             res = None
         return res

crazy_functions/语音助手.py

@@ -6,6 +6,7 @@ import threading, time
 import numpy as np
 from .live_audio.aliyunASR import AliyunASR
 import json
+import re
 
 class WatchDog():
     def __init__(self, timeout, bark_fn, interval=3, msg="") -> None:
@@ -38,10 +39,22 @@ def chatbot2history(chatbot):
     history = []
     for c in chatbot:
         for q in c:
-            if q not in ["[请讲话]", "[等待GPT响应]", "[正在等您说完问题]"]:
+            if q in ["[ 请讲话 ]", "[ 等待GPT响应 ]", "[ 正在等您说完问题 ]"]:
+                continue
+            elif q.startswith("[ 正在等您说完问题 ]"):
+                continue
+            else:
                 history.append(q.strip('<div class="markdown-body">').strip('</div>').strip('<p>').strip('</p>'))
     return history
 
+def visualize_audio(chatbot, audio_shape):
+    if len(chatbot) == 0: chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
+    chatbot[-1] = list(chatbot[-1])
+    p1 = '「'
+    p2 = '」'
+    chatbot[-1][-1] = re.sub(p1+r'(.*)'+p2, '', chatbot[-1][-1])
+    chatbot[-1][-1] += (p1+f"`{audio_shape}`"+p2)
+
 class AsyncGptTask():
     def __init__(self) -> None:
         self.observe_future = []
@@ -81,8 +94,9 @@ class InterviewAssistant(AliyunASR):
         self.capture_interval = 0.5 # second
         self.stop = False
         self.parsed_text = ""   # 下个句子中已经说完的部分, 由 test_on_result_chg() 写入
-        self.parsed_sentence = ""   # 某段话的整个句子,由 test_on_sentence_end() 写入
+        self.parsed_sentence = ""   # 某段话的整个句子, 由 test_on_sentence_end() 写入
         self.buffered_sentence = ""    #
+        self.audio_shape = ""   # 音频的可视化表现, 由 audio_convertion_thread() 写入
         self.event_on_result_chg = threading.Event()
         self.event_on_entence_end = threading.Event()
         self.event_on_commit_question = threading.Event()
@@ -117,7 +131,7 @@ class InterviewAssistant(AliyunASR):
     def begin(self, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
         # main plugin function
         self.init(chatbot)
-        chatbot.append(["[请讲话]", "[正在等您说完问题]"])
+        chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         self.plugin_wd.begin_watch()
         self.agt = AsyncGptTask()
@@ -157,14 +171,18 @@ class InterviewAssistant(AliyunASR):
 
                 self.commit_wd.begin_watch()
                 chatbot[-1] = list(chatbot[-1])
-                chatbot[-1] = [self.buffered_sentence, "[等待GPT响应]"]
+                chatbot[-1] = [self.buffered_sentence, "[ 等待GPT响应 ]"]
                 yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
                 # add gpt task 创建子线程请求gpt，避免线程阻塞
                 history = chatbot2history(chatbot)
                 self.agt.add_async_gpt_task(self.buffered_sentence, len(chatbot)-1, llm_kwargs, history, system_prompt)
                 
                 self.buffered_sentence = ""
-                chatbot.append(["[请讲话]", "[正在等您说完问题]"])
+                chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
+                yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+
+            if not self.event_on_result_chg.is_set() and not self.event_on_entence_end.is_set() and not self.event_on_commit_question.is_set():
+                visualize_audio(chatbot, self.audio_shape)
                 yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
         if len(self.stop_msg) != 0:
@@ -183,7 +201,7 @@ def 语音助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
         import nls
         from scipy import io
     except:
-        chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
+        chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         return
 

docs/GithubAction+AllCapacity

@@ -14,7 +14,7 @@ RUN python3 -m pip install colorama Markdown pygments pymupdf
 RUN python3 -m pip install python-docx moviepy pdfminer
 RUN python3 -m pip install zh_langchain==0.2.1 pypinyin
 RUN python3 -m pip install rarfile py7zr
-RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
+RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
 # 下载分支
 WORKDIR /gpt
 RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git

docs/GithubAction+NoLocal+Latex

@@ -5,6 +5,9 @@
 
 FROM fuqingxu/python311_texlive_ctex:latest
 
+# 删除文档文件以节约空间
+rm -rf /usr/local/texlive/2023/texmf-dist/doc
+
 # 指定路径
 WORKDIR /gpt
 

main.py

@@ -1,4 +1,7 @@
 import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
+import pickle
+import codecs
+import base64
 
 def main():
     import gradio as gr
@@ -10,7 +13,7 @@ def main():
     proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION = get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION')
     CHATBOT_HEIGHT, LAYOUT, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = get_conf('CHATBOT_HEIGHT', 'LAYOUT', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
     ENABLE_AUDIO, AUTO_CLEAR_TXT, PATH_LOGGING, AVAIL_THEMES, THEME = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'PATH_LOGGING', 'AVAIL_THEMES', 'THEME')
-    DARK_MODE, = get_conf('DARK_MODE')
+    DARK_MODE, NUM_CUSTOM_BASIC_BTN, SSL_KEYFILE, SSL_CERTFILE = get_conf('DARK_MODE', 'NUM_CUSTOM_BASIC_BTN', 'SSL_KEYFILE', 'SSL_CERTFILE')
 
     # 如果WEB_PORT是-1, 则随机选取WEB端口
     PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
@@ -68,9 +71,11 @@ def main():
         CHATBOT_HEIGHT /= 2
 
     cancel_handles = []
+    customize_btns = {}
+    predefined_btns = {}
     with gr.Blocks(title="GPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
         gr.HTML(title_html)
-        secret_css, dark_mode = gr.Textbox(visible=False), gr.Textbox(DARK_MODE, visible=False)
+        secret_css, dark_mode, persistent_cookie = gr.Textbox(visible=False), gr.Textbox(DARK_MODE, visible=False), gr.Textbox(visible=False)
         cookies = gr.State(load_chat_cookies())
         with gr_L1():
             with gr_L2(scale=2, elem_id="gpt-chat"):
@@ -94,11 +99,16 @@ def main():
                         status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}", elem_id="state-panel")
                 with gr.Accordion("基础功能区", open=True, elem_id="basic-panel") as area_basic_fn:
                     with gr.Row():
+                        for k in range(NUM_CUSTOM_BASIC_BTN):
+                            customize_btn = gr.Button("自定义按钮" + str(k+1), visible=False, variant="secondary", info_str=f'基础功能区: 自定义按钮')
+                            customize_btn.style(size="sm")
+                            customize_btns.update({"自定义按钮" + str(k+1): customize_btn})
                         for k in functional:
                             if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
                             variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
                             functional[k]["Button"] = gr.Button(k, variant=variant, info_str=f'基础功能区: {k}')
                             functional[k]["Button"].style(size="sm")
+                            predefined_btns.update({k: functional[k]["Button"]})
                 with gr.Accordion("函数插件区", open=True, elem_id="plugin-panel") as area_crazy_fn:
                     with gr.Row():
                         gr.Markdown("插件可读取“输入区”文本/路径作为参数（上传文件自动修正路径）")
@@ -149,6 +159,8 @@ def main():
                     theme_dropdown = gr.Dropdown(AVAIL_THEMES, value=THEME, label="更换UI主题").style(container=False)
                     checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "浮动输入区", "输入清除键", "插件参数区"], 
                                                   value=["基础功能区", "函数插件区"], label="显示/隐藏功能区", elem_id='cbs').style(container=False)
+                    checkboxes_2 = gr.CheckboxGroup(["自定义菜单"], 
+                                                  value=[], label="显示/隐藏自定义菜单", elem_id='cbs').style(container=False)
                     dark_mode_btn = gr.Button("切换界面明暗 ☀", variant="secondary").style(size="sm")
                     dark_mode_btn.click(None, None, None, _js="""() => {
                             if (document.querySelectorAll('.dark').length) {
@@ -173,6 +185,77 @@ def main():
                         stopBtn2 = gr.Button("停止", variant="secondary"); stopBtn2.style(size="sm")
                         clearBtn2 = gr.Button("清除", variant="secondary", visible=False); clearBtn2.style(size="sm")
 
+        def to_cookie_str(d):
+            # Pickle the dictionary and encode it as a string
+            pickled_dict = pickle.dumps(d)
+            cookie_value = base64.b64encode(pickled_dict).decode('utf-8')
+            return cookie_value
+        
+        def from_cookie_str(c):
+            # Decode the base64-encoded string and unpickle it into a dictionary
+            pickled_dict = base64.b64decode(c.encode('utf-8'))
+            return pickle.loads(pickled_dict)
+
+        with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_customize:
+            with gr.Accordion("自定义菜单", open=True, elem_id="edit-panel"):
+                with gr.Row() as row:
+                    with gr.Column(scale=10):
+                        AVAIL_BTN = [btn for btn in customize_btns.keys()] + [k for k in functional]
+                        basic_btn_dropdown = gr.Dropdown(AVAIL_BTN, value="自定义按钮1", label="选择一个需要自定义基础功能区按钮").style(container=False)
+                        basic_fn_title = gr.Textbox(show_label=False, placeholder="输入新按钮名称", lines=1).style(container=False)
+                        basic_fn_prefix = gr.Textbox(show_label=False, placeholder="输入新提示前缀", lines=4).style(container=False)
+                        basic_fn_suffix = gr.Textbox(show_label=False, placeholder="输入新提示后缀", lines=4).style(container=False)
+                    with gr.Column(scale=1, min_width=70):
+                        basic_fn_confirm = gr.Button("确认并保存", variant="primary"); basic_fn_confirm.style(size="sm")
+                        basic_fn_load    = gr.Button("加载已保存", variant="primary"); basic_fn_load.style(size="sm")
+                        def assign_btn(persistent_cookie_, cookies_, basic_btn_dropdown_, basic_fn_title, basic_fn_prefix, basic_fn_suffix):
+                            ret = {}
+                            customize_fn_overwrite_ = cookies_['customize_fn_overwrite']
+                            customize_fn_overwrite_.update({
+                                basic_btn_dropdown_:
+                                    {
+                                        "Title":basic_fn_title,
+                                        "Prefix":basic_fn_prefix,
+                                        "Suffix":basic_fn_suffix,
+                                    }
+                                }
+                            )
+                            cookies_.update(customize_fn_overwrite_)
+                            if basic_btn_dropdown_ in customize_btns:
+                                ret.update({customize_btns[basic_btn_dropdown_]: gr.update(visible=True, value=basic_fn_title)})
+                            else:
+                                ret.update({predefined_btns[basic_btn_dropdown_]: gr.update(visible=True, value=basic_fn_title)})
+                            ret.update({cookies: cookies_})
+                            try: persistent_cookie_ = from_cookie_str(persistent_cookie_)    # persistent cookie to dict
+                            except: persistent_cookie_ = {}
+                            persistent_cookie_["custom_bnt"] = customize_fn_overwrite_   # dict update new value
+                            persistent_cookie_ = to_cookie_str(persistent_cookie_)         # persistent cookie to dict
+                            ret.update({persistent_cookie: persistent_cookie_})                             # write persistent cookie
+                            return ret
+                        
+                        def reflesh_btn(persistent_cookie_, cookies_):
+                            ret = {}
+                            for k in customize_btns:
+                                ret.update({customize_btns[k]: gr.update(visible=False, value="")})
+
+                            try: persistent_cookie_ = from_cookie_str(persistent_cookie_)    # persistent cookie to dict
+                            except: return ret
+                            
+                            customize_fn_overwrite_ = persistent_cookie_.get("custom_bnt", {})
+                            cookies_['customize_fn_overwrite'] = customize_fn_overwrite_
+                            ret.update({cookies: cookies_})
+
+                            for k,v in persistent_cookie_["custom_bnt"].items():
+                                if v['Title'] == "": continue
+                                if k in customize_btns: ret.update({customize_btns[k]: gr.update(visible=True, value=v['Title'])})
+                                else: ret.update({predefined_btns[k]: gr.update(visible=True, value=v['Title'])})
+                            return ret
+                        
+                        basic_fn_load.click(reflesh_btn, [persistent_cookie, cookies],[cookies, *customize_btns.values(), *predefined_btns.values()])
+                        h = basic_fn_confirm.click(assign_btn, [persistent_cookie, cookies, basic_btn_dropdown, basic_fn_title, basic_fn_prefix, basic_fn_suffix], 
+                                                   [persistent_cookie, cookies, *customize_btns.values(), *predefined_btns.values()])
+                        h.then(None, [persistent_cookie], None, _js="""(persistent_cookie)=>{setCookie("persistent_cookie", persistent_cookie, 5);}""") # save persistent cookie
+
         # 功能区显示开关与功能区的互动
         def fn_area_visibility(a):
             ret = {}
@@ -186,6 +269,14 @@ def main():
             if "浮动输入区" in a: ret.update({txt: gr.update(value="")})
             return ret
         checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn, area_input_primary, area_input_secondary, txt, txt2, clearBtn, clearBtn2, plugin_advanced_arg] )
+
+        # 功能区显示开关与功能区的互动
+        def fn_area_visibility_2(a):
+            ret = {}
+            ret.update({area_customize: gr.update(visible=("自定义菜单" in a))})
+            return ret
+        checkboxes_2.select(fn_area_visibility_2, [checkboxes_2], [area_customize] )
+
         # 整理反复出现的控件句柄组合
         input_combo = [cookies, max_length_sl, md_dropdown, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg]
         output_combo = [cookies, chatbot, history, status]
@@ -209,6 +300,9 @@ def main():
             if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
             click_handle = functional[k]["Button"].click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(k)], outputs=output_combo)
             cancel_handles.append(click_handle)
+        for btn in customize_btns.values():
+            click_handle = btn.click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(btn.value)], outputs=output_combo)
+            cancel_handles.append(click_handle)
         # 文件上传区，接收文件后与chatbot的互动
         file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies])
         file_upload_2.upload(on_file_uploaded, [file_upload_2, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies])
@@ -307,6 +401,10 @@ def main():
                 }
             }
         }"""
+        load_cookie_js = """(persistent_cookie) => {
+            return getCookie("persistent_cookie");
+        }"""
+        demo.load(None, inputs=None, outputs=[persistent_cookie], _js=load_cookie_js)
         demo.load(None, inputs=[dark_mode], outputs=None, _js=darkmode_js)    # 配置暗色主题或亮色主题
         demo.load(None, inputs=[gr.Textbox(LAYOUT, visible=False)], outputs=None, _js='(LAYOUT)=>{GptAcademicJavaScriptInit(LAYOUT);}')
         
@@ -327,6 +425,9 @@ def main():
     demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
         quiet=True,
         server_name="0.0.0.0", 
+        ssl_keyfile=None if SSL_KEYFILE == "" else SSL_KEYFILE,
+        ssl_certfile=None if SSL_CERTFILE == "" else SSL_CERTFILE,
+        ssl_verify=False,
         server_port=PORT,
         favicon_path="docs/logo.png", 
         auth=AUTHENTICATION if len(AUTHENTICATION) != 0 else None,

request_llm/bridge_all.py

@@ -134,6 +134,15 @@ model_info = {
         "tokenizer": tokenizer_gpt4,
         "token_cnt": get_token_num_gpt4,
     },
+
+    "gpt-3.5-random": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 4096,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
     
     # azure openai
     "azure-gpt-3.5":{

request_llm/bridge_chatgpt.py

@@ -18,6 +18,7 @@ import logging
 import traceback
 import requests
 import importlib
+import random
 
 # config_private.py放自己的秘密如API和代理网址
 # 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
@@ -39,6 +40,21 @@ def get_full_error(chunk, stream_response):
             break
     return chunk
 
+def decode_chunk(chunk):
+    # 提前读取一些信息 （用于判断异常）
+    chunk_decoded = chunk.decode()
+    chunkjson = None
+    has_choices = False
+    has_content = False
+    has_role = False
+    try: 
+        chunkjson = json.loads(chunk_decoded[6:])
+        has_choices = 'choices' in chunkjson
+        if has_choices: has_content = "content" in chunkjson['choices'][0]["delta"]
+        if has_choices: has_role = "role" in chunkjson['choices'][0]["delta"]
+    except: 
+        pass
+    return chunk_decoded, chunkjson, has_choices, has_content, has_role
 
 def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
     """
@@ -191,7 +207,9 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                 yield from update_ui(chatbot=chatbot, history=history, msg="非OpenAI官方接口返回了错误:" + chunk.decode()) # 刷新界面
                 return
             
-            chunk_decoded = chunk.decode()
+            # 提前读取一些信息 （用于判断异常）
+            chunk_decoded, chunkjson, has_choices, has_content, has_role = decode_chunk(chunk)
+
             if is_head_of_the_stream and (r'"object":"error"' not in chunk_decoded) and (r"content" not in chunk_decoded):
                 # 数据流的第一帧不携带content
                 is_head_of_the_stream = False; continue
@@ -199,15 +217,23 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
             if chunk:
                 try:
                     # 前者是API2D的结束条件，后者是OPENAI的结束条件
-                    if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['choices'][0]["delta"]) == 0):
+                    if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
                         # 判定为数据流的结束，gpt_replying_buffer也写完了
                         logging.info(f'[response] {gpt_replying_buffer}')
                         break
                     # 处理数据流的主体
-                    chunkjson = json.loads(chunk_decoded[6:])
                     status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
                     # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出
-                    gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
+                    if has_content:
+                        # 正常情况
+                        gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
+                    elif has_role:
+                        # 一些第三方接口的出现这样的错误，兼容一下吧
+                        continue
+                    else:
+                        # 一些垃圾第三方接口的出现这样的错误
+                        gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
+
                     history[-1] = gpt_replying_buffer
                     chatbot[-1] = (history[-2], history[-1])
                     yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
@@ -288,9 +314,19 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     what_i_ask_now["role"] = "user"
     what_i_ask_now["content"] = inputs
     messages.append(what_i_ask_now)
+    model = llm_kwargs['llm_model'].strip('api2d-')
+    if model == "gpt-3.5-random": # 随机选择, 绕过openai访问频率限制
+        model = random.choice([
+            "gpt-3.5-turbo", 
+            "gpt-3.5-turbo-16k",
+            "gpt-3.5-turbo-0613",
+            "gpt-3.5-turbo-16k-0613",
+            "gpt-3.5-turbo-0301",
+        ])
+        logging.info("Random select model:" + model)
 
     payload = {
-        "model": llm_kwargs['llm_model'].strip('api2d-'),
+        "model": model,
         "messages": messages, 
         "temperature": llm_kwargs['temperature'],  # 1.0,
         "top_p": llm_kwargs['top_p'],  # 1.0,

tests/test_plugins.py

@@ -9,7 +9,9 @@ validate_path() # 返回项目根路径
 
 if __name__ == "__main__":
     from tests.test_utils import plugin_test
-    plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"})
+    # plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"})
+
+    plugin_test(plugin='crazy_functions.Latex输出PDF结果->Latex翻译中文并重新编译PDF', main_input="2307.07522")
 
     # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep')
 

themes/common.js

@@ -10,9 +10,33 @@ function gradioApp() {
     return elem.shadowRoot ? elem.shadowRoot : elem;
 }
 
+function setCookie(name, value, days) {
+    var expires = "";
+  
+    if (days) {
+      var date = new Date();
+      date.setTime(date.getTime() + (days * 24 * 60 * 60 * 1000));
+      expires = "; expires=" + date.toUTCString();
+    }
+  
+    document.cookie = name + "=" + value + expires + "; path=/";
+}
 
-
+function getCookie(name) {
-
+    var decodedCookie = decodeURIComponent(document.cookie);
+    var cookies = decodedCookie.split(';');
+  
+    for (var i = 0; i < cookies.length; i++) {
+      var cookie = cookies[i].trim();
+  
+      if (cookie.indexOf(name + "=") === 0) {
+        return cookie.substring(name.length + 1, cookie.length);
+      }
+    }
+  
+    return null;
+  }
+  
 function addCopyButton(botElement) {
     // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
     // Copy bot button

toolbox.py

@@ -621,10 +621,20 @@ def on_report_generated(cookies, files, chatbot):
 
 def load_chat_cookies():
     API_KEY, LLM_MODEL, AZURE_API_KEY = get_conf('API_KEY', 'LLM_MODEL', 'AZURE_API_KEY')
+    DARK_MODE, NUM_CUSTOM_BASIC_BTN = get_conf('DARK_MODE', 'NUM_CUSTOM_BASIC_BTN')
     if is_any_api_key(AZURE_API_KEY):
         if is_any_api_key(API_KEY): API_KEY = API_KEY + ',' + AZURE_API_KEY
         else: API_KEY = AZURE_API_KEY
-    return {'api_key': API_KEY, 'llm_model': LLM_MODEL}
+    customize_fn_overwrite_ = {}
+    for k in range(NUM_CUSTOM_BASIC_BTN):
+        customize_fn_overwrite_.update({  
+            "自定义按钮" + str(k+1):{
+                "Title":    r"",
+                "Prefix":   r"请在自定义菜单中定义提示词前缀.",
+                "Suffix":   r"请在自定义菜单中定义提示词后缀",
+            }
+        })
+    return {'api_key': API_KEY, 'llm_model': LLM_MODEL, 'customize_fn_overwrite': customize_fn_overwrite_}
 
 def is_openai_api_key(key):
     CUSTOM_API_KEY_PATTERN, = get_conf('CUSTOM_API_KEY_PATTERN')