From 5fcd02506c71ebe60d8845053199c0716f783615 Mon Sep 17 00:00:00 2001 From: binary-husky <96192199+binary-husky@users.noreply.github.com> Date: Tue, 30 Apr 2024 20:37:41 +0800 Subject: [PATCH] version 3.75 (#1702) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Update version to 3.74 * Add support for Yi Model API (#1635) * 更新以支持零一万物模型 * 删除newbing * 修改config --------- Co-authored-by: binary-husky * Refactor function signatures in bridge files * fix qwen api change * rename and ref functions * rename and move some cookie functions * 增加haiku模型，新增endpoint配置说明 (#1626) * haiku added * 新增haiku，新增endpoint配置说明 * Haiku added * 将说明同步至最新Endpoint --------- Co-authored-by: binary-husky * private_upload目录下进行文件鉴权 (#1596) * private_upload目录下进行文件鉴权 * minor fastapi adjustment * Add logging functionality to enable saving conversation records * waiting to fix username retrieve * support 2rd web path * allow accessing default user dir --------- Co-authored-by: binary-husky * remove yaml deps * fix favicon * fix abs path auth problem * forget to write a return * add `dashscope` to deps * fix GHSA-v9q9-xj86-953p * 用户名重叠越权访问patch (#1681) * add cohere model api access * cohere + can_multi_thread * fix block user access(fail) * fix fastapi bug * change cohere api endpoint * explain version * # fix com_zhipuglm.py illegal temperature problem (#1687) * Update com_zhipuglm.py # fix 用户在使用 zhipuai 界面时遇到了关于温度参数的非法参数错误 * allow store lm model dropdown * add a btn to reverse previous reset * remove extra fns * Add support for glm-4v model (#1700) * 修改chatglm3量化加载方式 (#1688) Co-authored-by: zym9804 * save chat stage 1 * consider null cookie situation * 在点击复制按钮时激活语音 * miss some parts * move all to js * done first stage * add edge tts * bug fix * bug fix * remove console log * bug fix * bug fix * bug fix * audio switch * update tts readme * remove tempfile when done * disable auto audio follow * avoid play queue update after shut up * feat: minimizing common.js * improve tts functionality * deterine whether the cached model is in choices * Add support for Ollama (#1740) * print err when doc2x not successful * add icon * adjust url for doc2x key version * prepare merge --------- Co-authored-by: Menghuan1918 Co-authored-by: Skyzayre <120616113+Skyzayre@users.noreply.github.com> Co-authored-by: XIao <46100050+Kilig947@users.noreply.github.com> Co-authored-by: Yuki <903728862@qq.com> Co-authored-by: zyren123 <91042213+zyren123@users.noreply.github.com> Co-authored-by: zym9804 --- .gitignore | 1 + config.py | 16 +- ...71\351\207\217\347\277\273\350\257\221.py" | 6 +- docs/use_tts.md | 58 ++ main.py | 34 +- request_llms/bridge_all.py | 39 +- request_llms/bridge_chatglm3.py | 80 ++- request_llms/bridge_ollama.py | 272 ++++++++ request_llms/bridge_zhipu.py | 4 + request_llms/com_zhipuglm.py | 8 +- requirements.txt | 1 + shared_utils/cookie_manager.py | 29 +- shared_utils/fastapi_server.py | 41 ++ themes/common.css | 1 + themes/common.js | 604 +++++++++++++++++- themes/common.py | 26 +- themes/sovits_audio.js | 0 themes/theme.py | 4 +- version | 4 +- 19 files changed, 1162 insertions(+), 66 deletions(-) create mode 100644 docs/use_tts.md create mode 100644 request_llms/bridge_ollama.py create mode 100644 themes/sovits_audio.js diff --git a/.gitignore b/.gitignore index a50eb8221..3a5e180c2 100644 --- a/.gitignore +++ b/.gitignore @@ -153,3 +153,4 @@ media flagged request_llms/ChatGLM-6b-onnx-u8s8 .pre-commit-config.yaml +themes/common.js.min.*.js \ No newline at end of file diff --git a/config.py b/config.py index 44788bc76..06b90485b 100644 --- a/config.py +++ b/config.py @@ -34,7 +34,7 @@ LLM_MODEL = "gpt-3.5-turbo-16k" # 可选 ↓↓↓ AVAIL_LLM_MODELS = ["gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-preview", "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-3-turbo", + "gpt-4", "gpt-4-32k", "azure-gpt-4", "glm-4", "glm-4v", "glm-3-turbo", "gemini-pro", "chatglm3" ] # --- --- --- --- @@ -50,9 +50,9 @@ # "yi-34b-chat-0205", "yi-34b-chat-200k" # ] # --- --- --- --- -# 此外，为了更灵活地接入one-api多模型管理界面，您还可以在接入one-api时， -# 使用"one-api-*"前缀直接使用非标准方式接入的模型，例如 -# AVAIL_LLM_MODELS = ["one-api-claude-3-sonnet-20240229(max_token=100000)"] +# 此外，您还可以在接入one-api/vllm/ollama时， +# 使用"one-api-*","vllm-*","ollama-*"前缀直接使用非标准方式接入的模型，例如 +# AVAIL_LLM_MODELS = ["one-api-claude-3-sonnet-20240229(max_token=100000)", "ollama-phi3(max_token=4096)"] # --- --- --- --- @@ -60,7 +60,7 @@ # 重新URL重新定向，实现更换API_URL的作用（高危设置! 常规情况下不要修改! 通过修改此设置，您将把您的API-KEY和对话隐私完全暴露给您设定的中间人！） # 格式: API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "在这里填写重定向的api.openai.com的URL"} -# 举例: API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "https://reverse-proxy-url/v1/chat/completions"} +# 举例: API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "https://reverse-proxy-url/v1/chat/completions", "http://localhost:11434/api/chat": "在这里填写您ollama的URL"} API_URL_REDIRECT = {} @@ -195,6 +195,12 @@ ALIYUN_SECRET="" # （无需填写） +# GPT-SOVITS 文本转语音服务的运行地址（将语言模型的生成文本朗读出来） +TTS_TYPE = "DISABLE" # LOCAL / LOCAL_SOVITS_API / DISABLE +GPT_SOVITS_URL = "" +EDGE_TTS_VOICE = "zh-CN-XiaoxiaoNeural" + + # 接入讯飞星火大模型 https://console.xfyun.cn/services/iat XFYUN_APPID = "00000000" XFYUN_API_SECRET = "bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb" diff --git "a/crazy_functions/PDF\346\211\271\351\207\217\347\277\273\350\257\221.py" "b/crazy_functions/PDF\346\211\271\351\207\217\347\277\273\350\257\221.py" index e7f6c291d..0c3d688d7 100644 --- "a/crazy_functions/PDF\346\211\271\351\207\217\347\277\273\350\257\221.py" +++ "b/crazy_functions/PDF\346\211\271\351\207\217\347\277\273\350\257\221.py" @@ -74,8 +74,10 @@ def pdf2markdown(filepath): import requests, json, os markdown_dir = get_log_folder(plugin_name="pdf_ocr") doc2x_api_key = DOC2X_API_KEY - # url = "https://api.doc2x.noedgeai.com/api/v1/pdf" - url = "https://api.doc2x.noedgeai.com/api/platform/pdf" + if doc2x_api_key.startswith('sk-'): + url = "https://api.doc2x.noedgeai.com/api/v1/pdf" + else: + url = "https://api.doc2x.noedgeai.com/api/platform/pdf" chatbot.append((None, "加载PDF文件，发送至DOC2X解析...")) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 diff --git a/docs/use_tts.md b/docs/use_tts.md new file mode 100644 index 000000000..5500847d3 --- /dev/null +++ b/docs/use_tts.md @@ -0,0 +1,58 @@ +# 使用TTS文字转语音 + + +## 1. 使用EDGE-TTS（简单） + +将本项目配置项修改如下即可 + +``` +TTS_TYPE = "EDGE_TTS" +EDGE_TTS_VOICE = "zh-CN-XiaoxiaoNeural" +``` + +## 2. 使用SoVITS（需要有显卡） + +使用以下docker-compose.yml文件，先启动SoVITS服务API + + 1. 创建以下文件夹结构 + ```shell + . + ├── docker-compose.yml + └── reference + ├── clone_target_txt.txt + └── clone_target_wave.mp3 + ``` + 2. 其中`docker-compose.yml`为 + ```yaml + version: '3.8' + services: + gpt-sovits: + image: fuqingxu/sovits_gptac_trim:latest + container_name: sovits_gptac_container + working_dir: /workspace/gpt_sovits_demo + environment: + - is_half=False + - is_share=False + volumes: + - ./reference:/reference + ports: + - "19880:9880" # 19880 为 sovits api 的暴露端口，记住它 + shm_size: 16G + deploy: + resources: + reservations: + devices: + - driver: nvidia + count: "all" + capabilities: [gpu] + command: bash -c "python3 api.py" + ``` + 3. 其中`clone_target_wave.mp3`为需要克隆的角色音频，`clone_target_txt.txt`为该音频对应的文字文本（ https://wiki.biligame.com/ys/%E8%A7%92%E8%89%B2%E8%AF%AD%E9%9F%B3 ） + 4. 运行`docker-compose up` + 5. 将本项目配置项修改如下即可 + (19880 为 sovits api 的暴露端口，与docker-compose.yml中的端口对应) + ``` + TTS_TYPE = "LOCAL_SOVITS_API" + GPT_SOVITS_URL = "http://127.0.0.1:19880" + ``` + 6. 启动本项目 \ No newline at end of file diff --git a/main.py b/main.py index 23c02d370..98ccc1e0e 100644 --- a/main.py +++ b/main.py @@ -1,4 +1,4 @@ -import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染 +import os, json; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染 help_menu_description = \ """Github源代码开源和更新[地址🚀](https://github.com/binary-husky/gpt_academic), @@ -14,7 +14,7 @@

如何临时更换API_KEY: 在输入区输入临时API_KEY后提交（网页刷新后失效）""" def enable_log(PATH_LOGGING): - import logging, uuid + import logging admin_log_path = os.path.join(PATH_LOGGING, "admin") os.makedirs(admin_log_path, exist_ok=True) log_dir = os.path.join(admin_log_path, "chat_secrets.log") @@ -29,13 +29,14 @@ def main(): if gr.__version__ not in ['3.32.9']: raise ModuleNotFoundError("使用项目内置Gradio获取最优体验! 请运行 `pip install -r requirements.txt` 指令安装内置Gradio及其他依赖, 详情信息见requirements.txt.") from request_llms.bridge_all import predict - from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, load_chat_cookies, DummyWith + from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址 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, ADD_WAIFU = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'PATH_LOGGING', 'AVAIL_THEMES', 'THEME', 'ADD_WAIFU') NUM_CUSTOM_BASIC_BTN, SSL_KEYFILE, SSL_CERTFILE = get_conf('NUM_CUSTOM_BASIC_BTN', 'SSL_KEYFILE', 'SSL_CERTFILE') - DARK_MODE, INIT_SYS_PROMPT, ADD_WAIFU = get_conf('DARK_MODE', 'INIT_SYS_PROMPT', 'ADD_WAIFU') + DARK_MODE, INIT_SYS_PROMPT, ADD_WAIFU, TTS_TYPE = get_conf('DARK_MODE', 'INIT_SYS_PROMPT', 'ADD_WAIFU', 'TTS_TYPE') + if LLM_MODEL not in AVAIL_LLM_MODELS: AVAIL_LLM_MODELS += [LLM_MODEL] # 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 @@ -79,15 +80,18 @@ def main(): cancel_handles = [] customize_btns = {} predefined_btns = {} + from shared_utils.cookie_manager import make_cookie_cache, make_history_cache with gr.Blocks(title="GPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as app_block: gr.HTML(title_html) - secret_css, web_cookie_cache = gr.Textbox(visible=False), gr.Textbox(visible=False) - cookies = gr.State(load_chat_cookies()) + secret_css = gr.Textbox(visible=False, elem_id="secret_css") + + + cookies, web_cookie_cache = make_cookie_cache() # 定义 后端state（cookies）、前端（web_cookie_cache）两兄弟 with gr_L1(): with gr_L2(scale=2, elem_id="gpt-chat"): chatbot = gr.Chatbot(label=f"当前模型：{LLM_MODEL}", elem_id="gpt-chatbot") if LAYOUT == "TOP-DOWN": chatbot.style(height=CHATBOT_HEIGHT) - history = gr.State([]) + history, history_cache, history_cache_update = make_history_cache() # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟 with gr_L2(scale=1, elem_id="gpt-panel"): with gr.Accordion("输入区", open=True, elem_id="input-panel") as area_input_primary: with gr.Row(): @@ -155,7 +159,7 @@ def main(): file_upload_2 = gr.Files(label="任何文件, 推荐上传压缩文件(zip, tar)", file_count="multiple", elem_id="elem_upload_float") with gr.Tab("更换模型", elem_id="interact-panel"): - md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False) + md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, elem_id="elem_model_sel", label="更换LLM模型/请求源").style(container=False) top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",) temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature", elem_id="elem_temperature") max_length_sl = gr.Slider(minimum=256, maximum=1024*32, value=4096, step=128, interactive=True, label="Local LLM MaxLength",) @@ -164,6 +168,8 @@ def main(): _js="""(temperature)=>gpt_academic_gradio_saveload("save", "elem_prompt", "js_temperature_cookie", temperature)""") system_prompt.change(None, inputs=[system_prompt], outputs=None, _js="""(system_prompt)=>gpt_academic_gradio_saveload("save", "elem_prompt", "js_system_prompt_cookie", system_prompt)""") + md_dropdown.change(None, inputs=[md_dropdown], outputs=None, + _js="""(md_dropdown)=>gpt_academic_gradio_saveload("save", "elem_model_sel", "js_md_dropdown_cookie", md_dropdown)""") with gr.Tab("界面外观", elem_id="interact-panel"): theme_dropdown = gr.Dropdown(AVAIL_THEMES, value=THEME, label="更换UI主题").style(container=False) @@ -247,8 +253,10 @@ def fn_area_visibility_2(a): cancel_handles.append(submitBtn2.click(**predict_args)) resetBtn.click(None, None, [chatbot, history, status], _js=js_code_reset) # 先在前端快速清除chatbot&status resetBtn2.click(None, None, [chatbot, history, status], _js=js_code_reset) # 先在前端快速清除chatbot&status - resetBtn.click(lambda: ([], [], "已重置"), None, [chatbot, history, status]) # 再在后端清除history - resetBtn2.click(lambda: ([], [], "已重置"), None, [chatbot, history, status]) # 再在后端清除history + reset_server_side_args = (lambda history: ([], [], "已重置", json.dumps(history)), + [history], [chatbot, history, status, history_cache]) + resetBtn.click(*reset_server_side_args) # 再在后端清除history，把history转存history_cache备用 + resetBtn2.click(*reset_server_side_args) # 再在后端清除history，把history转存history_cache备用 clearBtn.click(None, None, [txt, txt2], _js=js_code_clear) clearBtn2.click(None, None, [txt, txt2], _js=js_code_clear) if AUTO_CLEAR_TXT: @@ -271,7 +279,7 @@ def fn_area_visibility_2(a): for k in plugins: if not plugins[k].get("AsButton", True): continue click_handle = plugins[k]["Button"].click(ArgsGeneralWrapper(plugins[k]["Function"]), [*input_combo], output_combo) - click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot]) + click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot]).then(None, [plugins[k]["Button"]], None, _js=r"(fn)=>on_plugin_exe_complete(fn)") cancel_handles.append(click_handle) # 函数插件-下拉菜单与随变按钮的互动 def on_dropdown_changed(k): @@ -309,7 +317,7 @@ def route(request: gr.Request, k, *args, **kwargs): if k in [r"打开插件列表", r"请先从插件列表中选择"]: return yield from ArgsGeneralWrapper(plugins[k]["Function"])(request, *args, **kwargs) click_handle = switchy_bt.click(route,[switchy_bt, *input_combo], output_combo) - click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot]) + click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot]).then(None, [switchy_bt], None, _js=r"(fn)=>on_plugin_exe_complete(fn)") cancel_handles.append(click_handle) # 终止按钮的回调函数注册 stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles) @@ -342,7 +350,7 @@ def deal_audio(audio, cookies): app_block.load(load_web_cookie_cache, inputs = [web_cookie_cache, cookies], outputs = [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()], _js=js_code_for_persistent_cookie_init) - app_block.load(None, inputs=[], outputs=None, _js=f"""()=>GptAcademicJavaScriptInit("{DARK_MODE}","{INIT_SYS_PROMPT}","{ADD_WAIFU}","{LAYOUT}")""") # 配置暗色主题或亮色主题 + app_block.load(None, inputs=[], outputs=None, _js=f"""()=>GptAcademicJavaScriptInit("{DARK_MODE}","{INIT_SYS_PROMPT}","{ADD_WAIFU}","{LAYOUT}","{TTS_TYPE}")""") # 配置暗色主题或亮色主题 # gradio的inbrowser触发不太稳定，回滚代码到原始的浏览器打开函数 def run_delayed_tasks(): diff --git a/request_llms/bridge_all.py b/request_llms/bridge_all.py index 7213c5210..a014bd78e 100644 --- a/request_llms/bridge_all.py +++ b/request_llms/bridge_all.py @@ -67,7 +67,8 @@ def decode(self, *args, **kwargs): gemini_endpoint = "https://generativelanguage.googleapis.com/v1beta/models" claude_endpoint = "https://api.anthropic.com/v1/messages" yimodel_endpoint = "https://api.lingyiwanwu.com/v1/chat/completions" -cohere_endpoint = 'https://api.cohere.ai/v1/chat' +cohere_endpoint = "https://api.cohere.ai/v1/chat" +ollama_endpoint = "http://localhost:11434/api/chat" if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/' azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15' @@ -87,6 +88,7 @@ def decode(self, *args, **kwargs): if claude_endpoint in API_URL_REDIRECT: claude_endpoint = API_URL_REDIRECT[claude_endpoint] if yimodel_endpoint in API_URL_REDIRECT: yimodel_endpoint = API_URL_REDIRECT[yimodel_endpoint] if cohere_endpoint in API_URL_REDIRECT: cohere_endpoint = API_URL_REDIRECT[cohere_endpoint] +if ollama_endpoint in API_URL_REDIRECT: ollama_endpoint = API_URL_REDIRECT[ollama_endpoint] # 获取tokenizer tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo") @@ -266,6 +268,14 @@ def decode(self, *args, **kwargs): "tokenizer": tokenizer_gpt35, "token_cnt": get_token_num_gpt35, }, + "glm-4v": { + "fn_with_ui": zhipu_ui, + "fn_without_ui": zhipu_noui, + "endpoint": None, + "max_token": 1000, + "tokenizer": tokenizer_gpt35, + "token_cnt": get_token_num_gpt35, + }, "glm-3-turbo": { "fn_with_ui": zhipu_ui, "fn_without_ui": zhipu_noui, @@ -827,7 +837,32 @@ def decode(self, *args, **kwargs): "token_cnt": get_token_num_gpt35, }, }) - +# -=-=-=-=-=-=- ollama 对齐支持 -=-=-=-=-=-=- +for model in [m for m in AVAIL_LLM_MODELS if m.startswith("ollama-")]: + from .bridge_ollama import predict_no_ui_long_connection as ollama_noui + from .bridge_ollama import predict as ollama_ui + break +for model in [m for m in AVAIL_LLM_MODELS if m.startswith("ollama-")]: + # 为了更灵活地接入ollama多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["ollama-phi3(max_token=6666)"] + # 其中 + # "ollama-" 是前缀（必要） + # "phi3" 是模型名（必要） + # "(max_token=6666)" 是配置（非必要） + try: + _, max_token_tmp = read_one_api_model_name(model) + except: + print(f"ollama模型 {model} 的 max_token 配置不是整数，请检查配置文件。") + continue + model_info.update({ + model: { + "fn_with_ui": ollama_ui, + "fn_without_ui": ollama_noui, + "endpoint": ollama_endpoint, + "max_token": max_token_tmp, + "tokenizer": tokenizer_gpt35, + "token_cnt": get_token_num_gpt35, + }, + }) # -=-=-=-=-=-=- azure模型对齐支持 -=-=-=-=-=-=- AZURE_CFG_ARRAY = get_conf("AZURE_CFG_ARRAY") # <-- 用于定义和切换多个azure模型 --> diff --git a/request_llms/bridge_chatglm3.py b/request_llms/bridge_chatglm3.py index aecfc6920..d79067b67 100644 --- a/request_llms/bridge_chatglm3.py +++ b/request_llms/bridge_chatglm3.py @@ -6,7 +6,6 @@ from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns - # ------------------------------------------------------------------------------------------------------------------------ # 🔌💻 Local Model # ------------------------------------------------------------------------------------------------------------------------ @@ -23,20 +22,45 @@ def load_model_and_tokenizer(self): import os, glob import os import platform - LOCAL_MODEL_QUANT, device = get_conf('LOCAL_MODEL_QUANT', 'LOCAL_MODEL_DEVICE') - if LOCAL_MODEL_QUANT == "INT4": # INT4 - _model_name_ = "THUDM/chatglm3-6b-int4" - elif LOCAL_MODEL_QUANT == "INT8": # INT8 - _model_name_ = "THUDM/chatglm3-6b-int8" - else: - _model_name_ = "THUDM/chatglm3-6b" # FP16 - with ProxyNetworkActivate('Download_LLM'): - chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True) - if device=='cpu': - chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True, device='cpu').float() + LOCAL_MODEL_QUANT, device = get_conf("LOCAL_MODEL_QUANT", "LOCAL_MODEL_DEVICE") + _model_name_ = "THUDM/chatglm3-6b" + # if LOCAL_MODEL_QUANT == "INT4": # INT4 + # _model_name_ = "THUDM/chatglm3-6b-int4" + # elif LOCAL_MODEL_QUANT == "INT8": # INT8 + # _model_name_ = "THUDM/chatglm3-6b-int8" + # else: + # _model_name_ = "THUDM/chatglm3-6b" # FP16 + with ProxyNetworkActivate("Download_LLM"): + chatglm_tokenizer = AutoTokenizer.from_pretrained( + _model_name_, trust_remote_code=True + ) + if device == "cpu": + chatglm_model = AutoModel.from_pretrained( + _model_name_, + trust_remote_code=True, + device="cpu", + ).float() + elif LOCAL_MODEL_QUANT == "INT4": # INT4 + chatglm_model = AutoModel.from_pretrained( + pretrained_model_name_or_path=_model_name_, + trust_remote_code=True, + device="cuda", + load_in_4bit=True, + ) + elif LOCAL_MODEL_QUANT == "INT8": # INT8 + chatglm_model = AutoModel.from_pretrained( + pretrained_model_name_or_path=_model_name_, + trust_remote_code=True, + device="cuda", + load_in_8bit=True, + ) else: - chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True, device='cuda') + chatglm_model = AutoModel.from_pretrained( + pretrained_model_name_or_path=_model_name_, + trust_remote_code=True, + device="cuda", + ) chatglm_model = chatglm_model.eval() self._model = chatglm_model @@ -46,32 +70,36 @@ def load_model_and_tokenizer(self): def llm_stream_generator(self, **kwargs): # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 def adaptor(kwargs): - query = kwargs['query'] - max_length = kwargs['max_length'] - top_p = kwargs['top_p'] - temperature = kwargs['temperature'] - history = kwargs['history'] + query = kwargs["query"] + max_length = kwargs["max_length"] + top_p = kwargs["top_p"] + temperature = kwargs["temperature"] + history = kwargs["history"] return query, max_length, top_p, temperature, history query, max_length, top_p, temperature, history = adaptor(kwargs) - for response, history in self._model.stream_chat(self._tokenizer, - query, - history, - max_length=max_length, - top_p=top_p, - temperature=temperature, - ): + for response, history in self._model.stream_chat( + self._tokenizer, + query, + history, + max_length=max_length, + top_p=top_p, + temperature=temperature, + ): yield response def try_to_import_special_deps(self, **kwargs): # import something that will raise error if the user does not install requirement_*.txt # 🏃‍♂️🏃‍♂️🏃‍♂️ 主进程执行 import importlib + # importlib.import_module('modelscope') # ------------------------------------------------------------------------------------------------------------------------ # 🔌💻 GPT-Academic Interface # ------------------------------------------------------------------------------------------------------------------------ -predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetGLM3Handle, model_name, history_format='chatglm3') \ No newline at end of file +predict_no_ui_long_connection, predict = get_local_llm_predict_fns( + GetGLM3Handle, model_name, history_format="chatglm3" +) diff --git a/request_llms/bridge_ollama.py b/request_llms/bridge_ollama.py new file mode 100644 index 000000000..96f305032 --- /dev/null +++ b/request_llms/bridge_ollama.py @@ -0,0 +1,272 @@ +# 借鉴自同目录下的bridge_chatgpt.py + +""" + 该文件中主要包含三个函数 + + 不具备多线程能力的函数： + 1. predict: 正常对话时使用，具备完备的交互功能，不可多线程 + + 具备多线程调用能力的函数 + 2. predict_no_ui_long_connection：支持多线程 +""" + +import json +import time +import gradio as gr +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 +from toolbox import get_conf, update_ui, trimmed_format_exc, is_the_upload_folder, read_one_api_model_name +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。' + +def get_full_error(chunk, stream_response): + """ + 获取完整的从Openai返回的报错 + """ + while True: + try: + chunk += next(stream_response) + except: + 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 + is_last_chunk = False + try: + chunkjson = json.loads(chunk_decoded) + is_last_chunk = chunkjson.get("done", False) + except: + pass + return chunk_decoded, chunkjson, is_last_chunk + +def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False): + """ + 发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。 + inputs： + 是本次问询的输入 + sys_prompt: + 系统静默prompt + llm_kwargs： + chatGPT的内部调优参数 + history： + 是之前的对话列表 + 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 + """ + watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可 + if inputs == "": inputs = "空空如也的输入栏" + headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True) + retry = 0 + while True: + try: + # make a POST request to the API endpoint, stream=False + from .bridge_all import model_info + endpoint = model_info[llm_kwargs['llm_model']]['endpoint'] + response = requests.post(endpoint, headers=headers, proxies=proxies, + json=payload, stream=True, timeout=TIMEOUT_SECONDS); break + except requests.exceptions.ReadTimeout as e: + retry += 1 + traceback.print_exc() + if retry > MAX_RETRY: raise TimeoutError + if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……') + + stream_response = response.iter_lines() + result = '' + while True: + try: chunk = next(stream_response) + except StopIteration: + break + except requests.exceptions.ConnectionError: + chunk = next(stream_response) # 失败了，重试一次？再失败就没办法了。 + chunk_decoded, chunkjson, is_last_chunk = decode_chunk(chunk) + if chunk: + try: + if is_last_chunk: + # 判定为数据流的结束，gpt_replying_buffer也写完了 + logging.info(f'[response] {result}') + break + result += chunkjson['message']["content"] + if not console_slience: print(chunkjson['message']["content"], end='') + 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: + observe_window[0] += chunkjson['message']["content"] + # 看门狗，如果超过期限没有喂狗，则终止 + if len(observe_window) >= 2: + if (time.time()-observe_window[1]) > watch_dog_patience: + raise RuntimeError("用户取消了程序。") + except Exception as e: + chunk = get_full_error(chunk, stream_response) + chunk_decoded = chunk.decode() + error_msg = chunk_decoded + print(error_msg) + raise RuntimeError("Json解析不合常规") + return result + + +def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None): + """ + 发送至chatGPT，流式获取输出。 + 用于基础的对话功能。 + inputs 是本次问询的输入 + top_p, temperature是chatGPT的内部调优参数 + history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误） + 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 + """ + if inputs == "": inputs = "空空如也的输入栏" + user_input = inputs + if additional_fn is not None: + from core_functional import handle_core_functionality + inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) + + raw_input = inputs + logging.info(f'[raw_input] {raw_input}') + chatbot.append((inputs, "")) + yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面 + + # check mis-behavior + if is_the_upload_folder(user_input): + chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误！当您上传文档之后，需点击“**函数插件区**”按钮进行处理，请勿点击“提交”按钮或者“基础功能区”按钮。") + yield from update_ui(chatbot=chatbot, history=history, msg="正常") # 刷新界面 + time.sleep(2) + + headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt, stream) + + from .bridge_all import model_info + endpoint = model_info[llm_kwargs['llm_model']]['endpoint'] + + history.append(inputs); history.append("") + + retry = 0 + while True: + try: + # make a POST request to the API endpoint, stream=True + response = requests.post(endpoint, headers=headers, proxies=proxies, + json=payload, stream=True, timeout=TIMEOUT_SECONDS);break + except: + 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 = "" + + if stream: + stream_response = response.iter_lines() + while True: + try: + chunk = next(stream_response) + except StopIteration: + break + except requests.exceptions.ConnectionError: + chunk = next(stream_response) # 失败了，重试一次？再失败就没办法了。 + + # 提前读取一些信息 （用于判断异常） + chunk_decoded, chunkjson, is_last_chunk = decode_chunk(chunk) + + if chunk: + try: + if is_last_chunk: + # 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 + try: + status_text = f"finish_reason: {chunkjson['error'].get('message', 'null')}" + except: + status_text = "finish_reason: null" + gpt_replying_buffer = gpt_replying_buffer + chunkjson['message']["content"] + # 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) # 刷新界面 + except Exception as e: + yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面 + chunk = get_full_error(chunk, stream_response) + chunk_decoded = chunk.decode() + error_msg = chunk_decoded + chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg) + yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面 + print(error_msg) + return + +def handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg): + from .bridge_all import model_info + if "bad_request" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] 已经超过了模型的最大上下文或是模型格式错误,请尝试削减单次输入的文本量。") + elif "authentication_error" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key. 请确保API key有效。") + elif "not_found" in error_msg: + chatbot[-1] = (chatbot[-1][0], f"[Local Message] {llm_kwargs['llm_model']} 无效，请确保使用小写的模型名称。") + elif "rate_limit" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] 遇到了控制请求速率限制，请一分钟后重试。") + elif "system_busy" in error_msg: + chatbot[-1] = (chatbot[-1][0], "[Local Message] 系统繁忙，请一分钟后重试。") + else: + from toolbox import regular_txt_to_markdown + tb_str = '```\n' + trimmed_format_exc() + '```' + chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded)}") + return chatbot, history + +def generate_payload(inputs, llm_kwargs, history, system_prompt, stream): + """ + 整合所有信息，选择LLM模型，生成http请求，为发送请求做准备 + """ + + headers = { + "Content-Type": "application/json", + } + + conversation_cnt = len(history) // 2 + + messages = [{"role": "system", "content": system_prompt}] + if conversation_cnt: + for index in range(0, 2*conversation_cnt, 2): + what_i_have_asked = {} + what_i_have_asked["role"] = "user" + what_i_have_asked["content"] = history[index] + what_gpt_answer = {} + what_gpt_answer["role"] = "assistant" + what_gpt_answer["content"] = history[index+1] + if what_i_have_asked["content"] != "": + if what_gpt_answer["content"] == "": continue + if what_gpt_answer["content"] == timeout_bot_msg: continue + messages.append(what_i_have_asked) + messages.append(what_gpt_answer) + else: + messages[-1]['content'] = what_gpt_answer['content'] + + what_i_ask_now = {} + what_i_ask_now["role"] = "user" + what_i_ask_now["content"] = inputs + messages.append(what_i_ask_now) + model = llm_kwargs['llm_model'] + if llm_kwargs['llm_model'].startswith('ollama-'): + model = llm_kwargs['llm_model'][len('ollama-'):] + model, _ = read_one_api_model_name(model) + options = {"temperature": llm_kwargs['temperature']} + payload = { + "model": model, + "messages": messages, + "options": options, + } + try: + print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........") + except: + print('输入中可能存在乱码。') + return headers,payload diff --git a/request_llms/bridge_zhipu.py b/request_llms/bridge_zhipu.py index f1db2e205..e82229132 100644 --- a/request_llms/bridge_zhipu.py +++ b/request_llms/bridge_zhipu.py @@ -75,6 +75,10 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith llm_kwargs["llm_model"] = zhipuai_default_model if llm_kwargs["llm_model"] in ["glm-4v"]: + if (len(inputs) + sum(len(temp) for temp in history) + 1047) > 2000: + chatbot.append((inputs, "上下文长度超过glm-4v上限2000tokens，注意图片大约占用1,047个tokens")) + yield from update_ui(chatbot=chatbot, history=history) + return have_recent_file, image_paths = have_any_recent_upload_image_files(chatbot) if not have_recent_file: chatbot.append((inputs, "没有检测到任何近期上传的图像文件，请上传jpg格式的图片，此外，请注意拓展名需要小写")) diff --git a/request_llms/com_zhipuglm.py b/request_llms/com_zhipuglm.py index d0326cfde..3aa9f2107 100644 --- a/request_llms/com_zhipuglm.py +++ b/request_llms/com_zhipuglm.py @@ -36,8 +36,14 @@ def __conversation_user(self, user_input: str, llm_kwargs:dict): what_i_have_asked = {"role": "user", "content": []} what_i_have_asked['content'].append({"type": 'text', "text": user_input}) if encode_img: + if len(encode_img) > 1: + logging.warning("glm-4v只支持一张图片,将只取第一张图片进行处理") + print("glm-4v只支持一张图片,将只取第一张图片进行处理") img_d = {"type": "image_url", - "image_url": {'url': encode_img}} + "image_url": { + "url": encode_img[0]['data'] + } + } what_i_have_asked['content'].append(img_d) return what_i_have_asked diff --git a/requirements.txt b/requirements.txt index 019efa58f..190b7acae 100644 --- a/requirements.txt +++ b/requirements.txt @@ -24,6 +24,7 @@ Markdown pygments pymupdf openai +rjsmin arxiv numpy rich \ No newline at end of file diff --git a/shared_utils/cookie_manager.py b/shared_utils/cookie_manager.py index bdfdbd58c..4481de704 100644 --- a/shared_utils/cookie_manager.py +++ b/shared_utils/cookie_manager.py @@ -1,4 +1,6 @@ +import json from typing import Callable + def load_web_cookie_cache__fn_builder(customize_btns, cookies, predefined_btns)->Callable: def load_web_cookie_cache(persistent_cookie_, cookies_): import gradio as gr @@ -22,7 +24,6 @@ def load_web_cookie_cache(persistent_cookie_, cookies_): return ret return load_web_cookie_cache - def assign_btn__fn_builder(customize_btns, predefined_btns, cookies, web_cookie_cache)->Callable: def assign_btn(persistent_cookie_, cookies_, basic_btn_dropdown_, basic_fn_title, basic_fn_prefix, basic_fn_suffix, clean_up=False): import gradio as gr @@ -59,3 +60,29 @@ def assign_btn(persistent_cookie_, cookies_, basic_btn_dropdown_, basic_fn_title return ret return assign_btn +# cookies, web_cookie_cache = make_cookie_cache() +def make_cookie_cache(): + # 定义 后端state（cookies）、前端（web_cookie_cache）两兄弟 + import gradio as gr + from toolbox import load_chat_cookies + # 定义cookies的后端state + cookies = gr.State(load_chat_cookies()) + # 定义cookies的一个孪生的前端存储区（隐藏） + web_cookie_cache = gr.Textbox(visible=False, elem_id="web_cookie_cache") + return cookies, web_cookie_cache + +# history, history_cache, history_cache_update = make_history_cache() +def make_history_cache(): + # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟 + import gradio as gr + # 定义history的后端state + history = gr.State([]) + # 定义history的一个孪生的前端存储区（隐藏） + history_cache = gr.Textbox(visible=False, elem_id="history_cache") + # 定义history_cache->history的更新方法（隐藏）。在触发这个按钮时，会先执行js代码更新history_cache，然后再执行python代码更新history + def process_history_cache(history_cache): + return json.loads(history_cache) + # 另一种更简单的setter方法 + history_cache_update = gr.Button("", elem_id="elem_update_history", visible=False).click( + process_history_cache, inputs=[history_cache], outputs=[history]) + return history, history_cache, history_cache_update diff --git a/shared_utils/fastapi_server.py b/shared_utils/fastapi_server.py index 9d3334b9c..20c37f079 100644 --- a/shared_utils/fastapi_server.py +++ b/shared_utils/fastapi_server.py @@ -137,6 +137,47 @@ async def file(path_or_url: str, request: fastapi.Request): return "越权访问!" return await endpoint(path_or_url, request) + TTS_TYPE = get_conf("TTS_TYPE") + if TTS_TYPE != "DISABLE": + # audio generation functionality + import httpx + from fastapi import FastAPI, Request, HTTPException + from starlette.responses import Response + async def forward_request(request: Request, method: str) -> Response: + async with httpx.AsyncClient() as client: + try: + # Forward the request to the target service + if TTS_TYPE == "EDGE_TTS": + import tempfile + import edge_tts + import wave + import uuid + from pydub import AudioSegment + json = await request.json() + voice = get_conf("EDGE_TTS_VOICE") + tts = edge_tts.Communicate(text=json['text'], voice=voice) + temp_folder = tempfile.gettempdir() + temp_file_name = str(uuid.uuid4().hex) + temp_file = os.path.join(temp_folder, f'{temp_file_name}.mp3') + await tts.save(temp_file) + mp3_audio = AudioSegment.from_file(temp_file, format="mp3") + mp3_audio.export(temp_file, format="wav") + with open(temp_file, 'rb') as wav_file: t = wav_file.read() + os.remove(temp_file) + return Response(content=t) + if TTS_TYPE == "LOCAL_SOVITS_API": + # Forward the request to the target service + TARGET_URL = get_conf("GPT_SOVITS_URL") + body = await request.body() + resp = await client.post(TARGET_URL, content=body, timeout=60) + # Return the response from the target service + return Response(content=resp.content, status_code=resp.status_code, headers=dict(resp.headers)) + except httpx.RequestError as e: + raise HTTPException(status_code=400, detail=f"Request to the target service failed: {str(e)}") + @gradio_app.post("/vits") + async def forward_post_request(request: Request): + return await forward_request(request, "POST") + # --- --- app_lifespan --- --- from contextlib import asynccontextmanager @asynccontextmanager diff --git a/themes/common.css b/themes/common.css index e4b453d72..d9ade2bc4 100644 --- a/themes/common.css +++ b/themes/common.css @@ -38,6 +38,7 @@ left: calc(100% + 3px); top: 0; display: flex; + flex-direction: column; justify-content: space-between; } /* .message-btn-row-leading, .message-btn-row-trailing { diff --git a/themes/common.js b/themes/common.js index cccbcb947..0f99e2c01 100644 --- a/themes/common.js +++ b/themes/common.js @@ -7,6 +7,9 @@ function push_data_to_gradio_component(DAT, ELEM_ID, TYPE) { if (TYPE == "str") { // convert dat to string: do nothing } + else if (TYPE == "obj") { + // convert dat to string: do nothing + } else if (TYPE == "no_conversion") { // no nothing } @@ -254,11 +257,22 @@ function cancel_loading_status() { // 第 2 部分: 复制按钮 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= -function addCopyButton(botElement) { + +var allow_auto_read_continously = true; +var allow_auto_read_tts_flag = false; +function addCopyButton(botElement, index, is_last_in_arr) { // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript // Copy bot button const copiedIcon = ''; const copyIcon = ''; + // const audioIcon = ''; + const audioIcon = ''; + // const cancelAudioIcon = ''; + + // 此功能没准备好 + if (allow_auto_read_continously && is_last_in_arr && allow_auto_read_tts_flag) { + process_latest_text_output(botElement.innerText, index); + } const messageBtnColumnElement = botElement.querySelector('.message-btn-row'); if (messageBtnColumnElement) { @@ -273,6 +287,7 @@ function addCopyButton(botElement) { copyButton.addEventListener('click', async () => { const textToCopy = botElement.innerText; try { + // push_text_to_audio(textToCopy).catch(console.error); if ("clipboard" in navigator) { await navigator.clipboard.writeText(textToCopy); copyButton.innerHTML = copiedIcon; @@ -299,9 +314,35 @@ function addCopyButton(botElement) { console.error("Copy failed: ", error); } }); + + if (enable_tts){ + var audioButton = document.createElement('button'); + audioButton.classList.add('audio-toggle-btn'); + audioButton.innerHTML = audioIcon; + audioButton.addEventListener('click', async () => { + if (audioPlayer.isPlaying) { + allow_auto_read_tts_flag = false; + toast_push('自动朗读已禁用。', 3000); + audioPlayer.stop(); + setCookie("js_auto_read_cookie", "False", 365); + + } else { + allow_auto_read_tts_flag = true; + toast_push('正在合成语音 & 自动朗读已开启 (再次点击此按钮可禁用自动朗读)。', 3000); + // toast_push('正在合成语音', 3000); + const readText = botElement.innerText; + push_text_to_audio(readText); + setCookie("js_auto_read_cookie", "True", 365); + } + }); + } + var messageBtnColumn = document.createElement('div'); messageBtnColumn.classList.add('message-btn-row'); messageBtnColumn.appendChild(copyButton); + if (enable_tts){ + messageBtnColumn.appendChild(audioButton); + } botElement.appendChild(messageBtnColumn); } @@ -337,7 +378,15 @@ function chatbotContentChanged(attempt = 1, force = false) { // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript for (var i = 0; i < attempt; i++) { setTimeout(() => { - gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot').forEach(addCopyButton); + const messages = gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot'); + messages.forEach((message, index, arr) => { + // Check if the current message is the last in the array + const is_last_in_arr = index === arr.length - 1; + + // Now pass both the message element and the is_last_in_arr boolean to addCopyButton + addCopyButton(message, index, is_last_in_arr); + }); + // gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot').forEach(addCopyButton); }, i === 0 ? 0 : 200); } // we have moved mermaid-related code to gradio-fix repository: binary-husky/gradio-fix@32150d0 @@ -621,16 +670,16 @@ function monitoring_input_box() { if (elem_input_main) { if (elem_input_main.querySelector("textarea")) { - register_func_paste(elem_input_main.querySelector("textarea")) + register_func_paste(elem_input_main.querySelector("textarea")); } } if (elem_input_float) { if (elem_input_float.querySelector("textarea")) { - register_func_paste(elem_input_float.querySelector("textarea")) + register_func_paste(elem_input_float.querySelector("textarea")); } } if (elem_chatbot) { - register_func_drag(elem_chatbot) + register_func_drag(elem_chatbot); } } @@ -737,7 +786,7 @@ function minor_ui_adjustment() { } setInterval(function () { - auto_hide_toolbar() + auto_hide_toolbar(); }, 200); // 每50毫秒执行一次 } @@ -857,8 +906,8 @@ function gpt_academic_gradio_saveload( } } - -async function GptAcademicJavaScriptInit(dark, prompt, live2d, layout) { +enable_tts = false; +async function GptAcademicJavaScriptInit(dark, prompt, live2d, layout, tts) { // 第一部分，布局初始化 audio_fn_init(); minor_ui_adjustment(); @@ -873,7 +922,6 @@ async function GptAcademicJavaScriptInit(dark, prompt, live2d, layout) { // 第二部分，读取Cookie，初始话界面 let searchString = ""; let bool_value = ""; - // darkmode 深色模式 if (getCookie("js_darkmode_cookie")) { dark = getCookie("js_darkmode_cookie") @@ -889,11 +937,39 @@ async function GptAcademicJavaScriptInit(dark, prompt, live2d, layout) { } } + // 自动朗读 + if (tts != "DISABLE"){ + enable_tts = true; + if (getCookie("js_auto_read_cookie")) { + auto_read_tts = getCookie("js_auto_read_cookie") + auto_read_tts = auto_read_tts == "True"; + if (auto_read_tts) { + allow_auto_read_tts_flag = true; + } + } + } + // SysPrompt 系统静默提示词 gpt_academic_gradio_saveload("load", "elem_prompt", "js_system_prompt_cookie", null, "str"); - // Temperature 大模型温度参数 gpt_academic_gradio_saveload("load", "elem_temperature", "js_temperature_cookie", null, "float"); + // md_dropdown 大模型类型选择 + if (getCookie("js_md_dropdown_cookie")) { + const cached_model = getCookie("js_md_dropdown_cookie"); + var model_sel = await get_gradio_component("elem_model_sel"); + // deterine whether the cached model is in the choices + if (model_sel.props.choices.includes(cached_model)){ + // change dropdown + gpt_academic_gradio_saveload("load", "elem_model_sel", "js_md_dropdown_cookie", null, "str"); + // 连锁修改chatbot的label + push_data_to_gradio_component({ + label: '当前模型：' + getCookie("js_md_dropdown_cookie"), + __type__: 'update' + }, "gpt-chatbot", "obj") + } + } + + // clearButton 自动清除按钮 if (getCookie("js_clearbtn_show_cookie")) { @@ -953,4 +1029,510 @@ async function GptAcademicJavaScriptInit(dark, prompt, live2d, layout) { } } -} \ No newline at end of file +} + + +function reset_conversation(a, b) { + console.log("js_code_reset"); + a = btoa(unescape(encodeURIComponent(JSON.stringify(a)))); + setCookie("js_previous_chat_cookie", a, 1); + gen_restore_btn(); + return [[], [], "已重置"]; +} + +// clear -> 将 history 缓存至 history_cache -> 点击复原 -> restore_previous_chat() -> 触发elem_update_history -> 读取 history_cache +function restore_previous_chat() { + console.log("restore_previous_chat"); + let chat = getCookie("js_previous_chat_cookie"); + chat = JSON.parse(decodeURIComponent(escape(atob(chat)))); + push_data_to_gradio_component(chat, "gpt-chatbot", "obj"); + document.querySelector("#elem_update_history").click(); // in order to call set_history_gr_state, and send history state to server +} + +function gen_restore_btn() { + + + // 创建按钮元素 + const button = document.createElement('div'); + // const recvIcon = ''; + const rec_svg = '' + const recvIcon = '' + rec_svg + ''; + + // 设置按钮的样式和属性 + button.id = 'floatingButton'; + button.className = 'glow'; + button.style.textAlign = 'center'; + button.style.position = 'fixed'; + button.style.bottom = '10px'; + button.style.left = '10px'; + button.style.width = '50px'; + button.style.height = '50px'; + button.style.borderRadius = '50%'; + button.style.backgroundColor = '#007bff'; + button.style.color = 'white'; + button.style.display = 'flex'; + button.style.alignItems = 'center'; + button.style.justifyContent = 'center'; + button.style.cursor = 'pointer'; + button.style.transition = 'all 0.3s ease'; + button.style.boxShadow = '0 0 10px rgba(0,0,0,0.2)'; + + button.innerHTML = recvIcon; + + // 添加发光动画的关键帧 + const styleSheet = document.createElement('style'); + styleSheet.id = 'floatingButtonStyle'; + styleSheet.innerText = ` + @keyframes glow { + from { + box-shadow: 0 0 10px rgba(0,0,0,0.2); + } + to { + box-shadow: 0 0 13px rgba(0,0,0,0.5); + } + } + #floatingButton.glow { + animation: glow 1s infinite alternate; + } + #floatingButton:hover { + transform: scale(1.2); + box-shadow: 0 0 20px rgba(0,0,0,0.4); + } + #floatingButton.disappearing { + animation: shrinkAndDisappear 0.5s forwards; + } + `; + + // only add when not exist + if (!document.getElementById('recvButtonStyle')) + { + document.head.appendChild(styleSheet); + } + + // 鼠标悬停和移开的事件监听器 + button.addEventListener('mouseover', function () { + this.textContent = "还原\n对话"; + }); + + button.addEventListener('mouseout', function () { + this.innerHTML = recvIcon; + }); + + // 点击事件监听器 + button.addEventListener('click', function () { + // 添加一个类来触发缩小和消失的动画 + restore_previous_chat(); + this.classList.add('disappearing'); + // 在动画结束后移除按钮 + document.body.removeChild(this); + }); + // only add when not exist + if (!document.getElementById('recvButton')) + { + document.body.appendChild(button); + } + + // 将按钮添加到页面中 + +} + +async function on_plugin_exe_complete(fn_name) { + console.log(fn_name); + if (fn_name === "保存当前的对话") { + // get chat profile path + let chatbot = await get_data_from_gradio_component('gpt-chatbot'); + let may_have_chat_profile_info = chatbot[chatbot.length - 1][1]; + + function get_href(htmlString) { + const parser = new DOMParser(); + const doc = parser.parseFromString(htmlString, 'text/html'); + const anchor = doc.querySelector('a'); + + if (anchor) { + return anchor.getAttribute('href'); + } else { + return null; + } + } + let href = get_href(may_have_chat_profile_info); + if (href) { + const cleanedHref = href.replace('file=', ''); // /home/fuqingxu/chatgpt_academic/gpt_log/default_user/chat_history/GPT-Academic对话存档2024-04-12-00-35-06.html + console.log(cleanedHref); + } + + } +} + + + + + + + + +// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= +// 第 8 部分: TTS语音生成函数 +// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= + +class AudioPlayer { + constructor() { + this.audioCtx = new (window.AudioContext || window.webkitAudioContext)(); + this.queue = []; + this.isPlaying = false; + this.currentSource = null; // 添加属性来保存当前播放的源 + } + + // Base64 编码的字符串转换为 ArrayBuffer + base64ToArrayBuffer(base64) { + const binaryString = window.atob(base64); + const len = binaryString.length; + const bytes = new Uint8Array(len); + for (let i = 0; i < len; i++) { + bytes[i] = binaryString.charCodeAt(i); + } + return bytes.buffer; + } + + // 检查音频播放队列并播放音频 + checkQueue() { + if (!this.isPlaying && this.queue.length > 0) { + this.isPlaying = true; + const nextAudio = this.queue.shift(); + this.play_wave(nextAudio); + } + } + + // 将音频添加到播放队列 + enqueueAudio(audio_buf_wave) { + if (allow_auto_read_tts_flag) { + this.queue.push(audio_buf_wave); + this.checkQueue(); + } + } + + // 播放音频 + async play_wave(encodedAudio) { + //const audioData = this.base64ToArrayBuffer(encodedAudio); + const audioData = encodedAudio; + try { + const buffer = await this.audioCtx.decodeAudioData(audioData); + const source = this.audioCtx.createBufferSource(); + source.buffer = buffer; + source.connect(this.audioCtx.destination); + source.onended = () => { + if (allow_auto_read_tts_flag) { + this.isPlaying = false; + this.currentSource = null; // 播放结束后清空当前源 + this.checkQueue(); + } + }; + this.currentSource = source; // 保存当前播放的源 + source.start(); + } catch (e) { + console.log("Audio error!", e); + this.isPlaying = false; + this.currentSource = null; // 出错时也应清空当前源 + this.checkQueue(); + } + } + + // 新增：立即停止播放音频的方法 + stop() { + if (this.currentSource) { + this.queue = []; // 清空队列 + this.currentSource.stop(); // 停止当前源 + this.currentSource = null; // 清空当前源 + this.isPlaying = false; // 更新播放状态 + // 关闭音频上下文可能会导致无法再次播放音频，因此仅停止当前源 + // this.audioCtx.close(); // 可选：如果需要可以关闭音频上下文 + } + } +} + +const audioPlayer = new AudioPlayer(); + +class FIFOLock { + constructor() { + this.queue = []; + this.currentTaskExecuting = false; + } + + lock() { + let resolveLock; + const lock = new Promise(resolve => { + resolveLock = resolve; + }); + + this.queue.push(resolveLock); + + if (!this.currentTaskExecuting) { + this._dequeueNext(); + } + + return lock; + } + + _dequeueNext() { + if (this.queue.length === 0) { + this.currentTaskExecuting = false; + return; + } + this.currentTaskExecuting = true; + const resolveLock = this.queue.shift(); + resolveLock(); + } + + unlock() { + this.currentTaskExecuting = false; + this._dequeueNext(); + } +} + + + + + + + + +function delay(ms) { + return new Promise(resolve => setTimeout(resolve, ms)); +} + +// Define the trigger function with delay parameter T in milliseconds +function trigger(T, fire) { + // Variable to keep track of the timer ID + let timeoutID = null; + // Variable to store the latest arguments + let lastArgs = null; + + return function (...args) { + // Update lastArgs with the latest arguments + lastArgs = args; + // Clear the existing timer if the function is called again + if (timeoutID !== null) { + clearTimeout(timeoutID); + } + // Set a new timer that calls the `fire` function with the latest arguments after T milliseconds + timeoutID = setTimeout(() => { + fire(...lastArgs); + }, T); + }; +} + + +prev_text = ""; +prev_text_already_pushed = ""; +prev_chatbot_index = -1; +const delay_live_text_update = trigger(3000, on_live_stream_terminate); + +function on_live_stream_terminate(latest_text) { + // remove `prev_text_already_pushed` from `latest_text` + console.log("on_live_stream_terminate", latest_text) + remaining_text = latest_text.slice(prev_text_already_pushed.length); + if ((!isEmptyOrWhitespaceOnly(remaining_text)) && remaining_text.length != 0) { + prev_text_already_pushed = latest_text; + push_text_to_audio(remaining_text); + } +} +function is_continue_from_prev(text, prev_text) { + abl = 5 + if (text.length < prev_text.length - abl) { + return false; + } + if (prev_text.length > 10) { + return text.startsWith(prev_text.slice(0, Math.min(prev_text.length - abl, 100))); + } else { + return text.startsWith(prev_text); + } +} +function isEmptyOrWhitespaceOnly(remaining_text) { + // Replace \n and 。 with empty strings + let textWithoutSpecifiedCharacters = remaining_text.replace(/[\n。]/g, ''); + // Check if the remaining string is empty + return textWithoutSpecifiedCharacters.trim().length === 0; +} +function process_increased_text(remaining_text) { + // console.log('[is continue], remaining_text: ', remaining_text) + // remaining_text starts with \n or 。, then move these chars into prev_text_already_pushed + while (remaining_text.startsWith('\n') || remaining_text.startsWith('。')) { + prev_text_already_pushed = prev_text_already_pushed + remaining_text[0]; + remaining_text = remaining_text.slice(1); + } + if (remaining_text.includes('\n') || remaining_text.includes('。')) { // determine remaining_text contain \n or 。 + // new message begin! + index_of_last_sep = Math.max(remaining_text.lastIndexOf('\n'), remaining_text.lastIndexOf('。')); + // break the text into two parts + tobe_pushed = remaining_text.slice(0, index_of_last_sep + 1); + prev_text_already_pushed = prev_text_already_pushed + tobe_pushed; + // console.log('[is continue], push: ', tobe_pushed) + // console.log('[is continue], update prev_text_already_pushed: ', prev_text_already_pushed) + if (!isEmptyOrWhitespaceOnly(tobe_pushed)) { + // console.log('[is continue], remaining_text is empty') + push_text_to_audio(tobe_pushed); + } + } +} +function process_latest_text_output(text, chatbot_index) { + if (text.length == 0) { + prev_text = text; + prev_text_mask = text; + // console.log('empty text') + return; + } + if (text == prev_text) { + // console.log('[nothing changed]') + return; + } + + var is_continue = is_continue_from_prev(text, prev_text_already_pushed); + if (chatbot_index == prev_chatbot_index && is_continue) { + // on_text_continue_grow + remaining_text = text.slice(prev_text_already_pushed.length); + process_increased_text(remaining_text); + delay_live_text_update(text); // in case of no \n or 。 in the text, this timer will finally commit + } + else if (chatbot_index == prev_chatbot_index && !is_continue) { + console.log('---------------------') + console.log('text twisting!') + console.log('[new message begin]', 'text', text, 'prev_text_already_pushed', prev_text_already_pushed) + console.log('---------------------') + prev_text_already_pushed = ""; + delay_live_text_update(text); // in case of no \n or 。 in the text, this timer will finally commit + } + else { + // on_new_message_begin, we have to clear `prev_text_already_pushed` + console.log('---------------------') + console.log('new message begin!') + console.log('[new message begin]', 'text', text, 'prev_text_already_pushed', prev_text_already_pushed) + console.log('---------------------') + prev_text_already_pushed = ""; + process_increased_text(text); + delay_live_text_update(text); // in case of no \n or 。 in the text, this timer will finally commit + } + prev_text = text; + prev_chatbot_index = chatbot_index; +} + +const audio_push_lock = new FIFOLock(); +async function push_text_to_audio(text) { + if (!allow_auto_read_tts_flag) { + return; + } + await audio_push_lock.lock(); + var lines = text.split(/[\n。]/); + for (const audio_buf_text of lines) { + if (audio_buf_text) { + // Append '/vits' to the current URL to form the target endpoint + const url = `${window.location.href}vits`; + // Define the payload to be sent in the POST request + const payload = { + text: audio_buf_text, // Ensure 'audio_buf_text' is defined with valid data + text_language: "zh" + }; + // Call the async postData function and log the response + post_text(url, payload, send_index); + send_index = send_index + 1; + console.log(send_index, audio_buf_text) + // sleep 2 seconds + if (allow_auto_read_tts_flag) { + await delay(3000); + } + } + } + audio_push_lock.unlock(); +} + + +send_index = 0; +recv_index = 0; +to_be_processed = []; +async function UpdatePlayQueue(cnt, audio_buf_wave) { + if (cnt != recv_index) { + to_be_processed.push([cnt, audio_buf_wave]); + console.log('cache', cnt); + } + else { + console.log('processing', cnt); + recv_index = recv_index + 1; + if (audio_buf_wave) { + audioPlayer.enqueueAudio(audio_buf_wave); + } + // deal with other cached audio + while (true) { + find_any = false; + for (i = to_be_processed.length - 1; i >= 0; i--) { + if (to_be_processed[i][0] == recv_index) { + console.log('processing cached', recv_index); + if (to_be_processed[i][1]) { + audioPlayer.enqueueAudio(to_be_processed[i][1]); + } + to_be_processed.pop(i); + find_any = true; + recv_index = recv_index + 1; + } + } + if (!find_any) { break; } + } + } +} + +function post_text(url, payload, cnt) { + if (allow_auto_read_tts_flag) { + postData(url, payload, cnt) + .then(data => { + UpdatePlayQueue(cnt, data); + return; + }); + } else { + UpdatePlayQueue(cnt, null); + return; + } +} + +notify_user_error = false +// Create an async function to perform the POST request +async function postData(url = '', data = {}) { + try { + // Use the Fetch API with await + const response = await fetch(url, { + method: 'POST', // Specify the request method + body: JSON.stringify(data), // Convert the JavaScript object to a JSON string + }); + // Check if the response is ok (status in the range 200-299) + if (!response.ok) { + // If not OK, throw an error + console.info('There was a problem during audio generation requests:', response.status); + // if (!notify_user_error){ + // notify_user_error = true; + // alert('There was a problem during audio generation requests:', response.status); + // } + return null; + } + // If OK, parse and return the JSON response + return await response.arrayBuffer(); + } catch (error) { + // Log any errors that occur during the fetch operation + console.info('There was a problem during audio generation requests:', error); + // if (!notify_user_error){ + // notify_user_error = true; + // alert('There was a problem during audio generation requests:', error); + // } + return null; + } +} + + + + + + + + + + + + + + + diff --git a/themes/common.py b/themes/common.py index 65ff9a3e4..50a9e6e49 100644 --- a/themes/common.py +++ b/themes/common.py @@ -1,10 +1,34 @@ from toolbox import get_conf CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT") +def minimize_js(common_js_path): + try: + import rjsmin, hashlib, glob, os + # clean up old minimized js files, matching `common_js_path + '.min.*'` + for old_min_js in glob.glob(common_js_path + '.min.*.js'): + os.remove(old_min_js) + # use rjsmin to minimize `common_js_path` + c_jsmin = rjsmin.jsmin + with open(common_js_path, "r") as f: + js_content = f.read() + minimized_js_content = c_jsmin(js_content) + # compute sha256 hash of minimized js content + sha_hash = hashlib.sha256(minimized_js_content.encode()).hexdigest()[:8] + minimized_js_path = common_js_path + '.min.' + sha_hash + '.js' + # save to minimized js file + with open(minimized_js_path, "w") as f: + f.write(minimized_js_content) + # return minimized js file path + return minimized_js_path + except: + return common_js_path + def get_common_html_javascript_code(): js = "\n" + common_js_path = "themes/common.js" + minimized_js_path = minimize_js(common_js_path) for jsf in [ - "file=themes/common.js", + f"file={minimized_js_path}", ]: js += f"""\n""" diff --git a/themes/sovits_audio.js b/themes/sovits_audio.js new file mode 100644 index 000000000..e69de29bb diff --git a/themes/theme.py b/themes/theme.py index 6ccf36b45..3dc6732da 100644 --- a/themes/theme.py +++ b/themes/theme.py @@ -111,10 +111,10 @@ def from_cookie_str(c): } """ - +# 详见 themes/common.js js_code_reset = """ (a,b,c)=>{ - return [[], [], "已重置"]; + return reset_conversation(a,b); } """ diff --git a/version b/version index 5d450de57..e82505bde 100644 --- a/version +++ b/version @@ -1,5 +1,5 @@ { - "version": 3.74, + "version": 3.75, "show_feature": true, - "new_feature": "增加多用户文件鉴权验证提高安全性 <-> 优化oneapi接入方法 <-> 接入Cohere和月之暗面模型 <-> 简化挂载二级目录的步骤 <-> 支持Mermaid绘图库（让大模型绘制脑图）" + "new_feature": "添加TTS语音输出（EdgeTTS和SoVits语音克隆） <-> Doc2x PDF翻译 <-> 添加回溯对话按钮" }