、
、
、< br>和< br/> + return s + + +def update_btn(self, + value: str = None, + variant: str = None, + visible: bool = None, + interactive: bool = None, + elem_id: str = None, + label: str = None +): + if not variant: variant = self.variant + if not visible: visible = self.visible + if not value: value = self.value + if not interactive: interactive = self.interactive + if not elem_id: elem_id = self.elem_id + if not elem_id: label = self.label + return { + "variant": variant, + "visible": visible, + "value": value, + "interactive": interactive, + 'elem_id': elem_id, + 'label': label, + "__type__": "update", + } + +def update_txt(self, + value: str = None, + lines: int = None, + max_lines: int = None, + placeholder: str = None, + label: str = None, + show_label: bool = None, + visible: bool = None, + interactive: bool = None, + type: str = None, + elem_id: str = None + ): + + return { + "lines": self.lines, + "max_lines": self.max_lines, + "placeholder": self.placeholder, + "label": self.label, + "show_label": self.show_label, + "visible": self.visible, + "value": self.value, + "type": self.type, + "interactive": self.interactive, + "elem_id": elem_id, + "__type__": "update", + + } + + +def get_html(filename): + path = os.path.join(base_path, "docs/assets", "html", filename) + if os.path.exists(path): + with open(path, encoding="utf8") as file: + return file.read() + return "" + + +def git_log_list(): + ll = Shell("git log --pretty=format:'%s | %h' -n 10").read()[1].splitlines() + + return [i.split('|') for i in ll if 'branch' not in i][:5] + +import qrcode +from PIL import Image, ImageDraw +def qr_code_generation(data, icon_path=None, file_name='qc_icon.png'): + # 创建qrcode对象 + qr = qrcode.QRCode(version=2, error_correction=qrcode.constants.ERROR_CORRECT_Q, box_size=10, border=2,) + qr.add_data(data) + # 创建二维码图片 + img = qr.make_image() + # 图片转换为RGBA格式 + img = img.convert('RGBA') + # 返回二维码图片的大小 + img_w, img_h = img.size + # 打开logo + if not icon_path: + icon_path = os.path.join(base_path, 'docs/assets/PLAI.jpeg') + logo = Image.open(icon_path) + # logo大小为二维码的四分之一 + logo_w = img_w // 4 + logo_h = img_w // 4 + # 修改logo图片大小 + logo = logo.resize((logo_w, logo_h), Image.LANCZOS) # or Image.Resampling.LANCZOS + # 把logo放置在二维码中间 + w = (img_w - logo_w) // 2 + h = (img_h - logo_h) // 2 + img.paste(logo, (w, h)) + qr_path = os.path.join(logs_path, 'file_name') + img.save() + return qr_path + + +class YamlHandle: + + def __init__(self, file=os.path.join(prompt_path, 'ai_common.yaml')): + if not os.path.exists(file): + Shell(f'touch {file}').read() + self.file = file + self._load = self.load() + + def load(self) -> dict: + with open(file=self.file, mode='r') as f: + data = yaml.safe_load(f) + return data + + def update(self, key, value): + date = self._load + if not date: + date = {} + date[key] = value + with open(file=self.file, mode='w') as f: + yaml.dump(date, f, allow_unicode=True) + return date + + def dump_dict(self, new_dict): + date = self._load + if not date: + date = {} + date.update(new_dict) + with open(file=self.file, mode='w') as f: + yaml.dump(date, f, allow_unicode=True) + return date + + +class JsonHandle: + + def __init__(self, file): + self.file = file + + def load(self) -> object: + with open(self.file, 'r') as f: + data = json.load(f) + return data + + + +if __name__ == '__main__': + pass \ No newline at end of file diff --git a/main.py b/main.py index 2cbb27f..b9a0992 100644 --- a/main.py +++ b/main.py @@ -130,9 +130,9 @@ def main(): ret.update({plugin_advanced_arg: gr.update(visible=("插件参数区" in a))}) if "底部输入区" 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] ) + checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn, area_input_primary, area_input_secondary, txt, clearBtn, clearBtn2, plugin_advanced_arg] ) # 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] + input_combo = [cookies, max_length_sl, md_dropdown, txt, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg] output_combo = [cookies, chatbot, history, status] predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=input_combo, outputs=output_combo) # 提交按钮、重置按钮 @@ -155,7 +155,7 @@ def main(): 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) # 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], [chatbot, txt, txt2]) + file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt ], [chatbot, txt]) # 函数插件-固定按钮区 for k in crazy_fns: if not crazy_fns[k].get("AsButton", True): continue @@ -174,7 +174,7 @@ def main(): dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt, plugin_advanced_arg] ) def on_md_dropdown_changed(k): return {chatbot: gr.update(label="当前模型："+k)} - md_dropdown.select(on_md_dropdown_changed, [md_dropdown], [chatbot] ) + md_dropdown.select(on_md_dropdown_changed, [md_dropdown], [chatbot]) # 随变按钮的回调函数注册 def route(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 diff --git a/prompt_generator.py b/prompt_generator.py new file mode 100644 index 0000000..0efdc83 --- /dev/null +++ b/prompt_generator.py @@ -0,0 +1,102 @@ +#! .\venv\ +# encoding: utf-8 +# @Time : 2023/4/19 +# @Author : Spike +# @Descr : +import os.path +import sqlite3 +import threading +import functools +import func_box +# 连接到数据库 +base_path = os.path.dirname(__file__) +prompt_path = os.path.join(base_path, 'users_data') + + +def connect_db_close(cls_method): + @functools.wraps(cls_method) + def wrapper(cls=None, *args, **kwargs): + cls._connect_db() + result = cls_method(cls, *args, **kwargs) + cls._close_db() + return result + return wrapper + + +class SqliteHandle: + def __init__(self, table='ai_common', database='ai_prompt.db'): + self.__database = database + self.__connect = sqlite3.connect(os.path.join(prompt_path, self.__database)) + self.__cursor = self.__connect.cursor() + self.__table = table + if self.__table not in self.get_tables(): + self.create_tab() + + def new_connect_db(self): + """多线程操作时，每个线程新建独立的connect""" + self.__connect = sqlite3.connect(os.path.join(prompt_path, self.__database)) + self.__cursor = self.__connect.cursor() + + def new_close_db(self): + self.__cursor.close() + self.__connect.close() + + def create_tab(self): + self.__cursor.execute(f"CREATE TABLE `{self.__table}` ('prompt' TEXT UNIQUE, 'result' TEXT)") + + def get_tables(self): + all_tab = [] + result = self.__cursor.execute("SELECT name FROM sqlite_master WHERE type = 'table';") + for tab in result: + all_tab.append(tab[0]) + return all_tab + + def get_prompt_value(self, find=None): + temp_all = {} + if find: + result = self.__cursor.execute(f"SELECT prompt, result FROM `{self.__table}` WHERE prompt LIKE '%{find}%'").fetchall() + else: + result = self.__cursor.execute(f"SELECT prompt, result FROM `{self.__table}`").fetchall() + for row in result: + temp_all[row[0]] = row[1] + return temp_all + + def inset_prompt(self, prompt: dict): + for key in prompt: + self.__cursor.execute(f"REPLACE INTO `{self.__table}` (prompt, result) VALUES (?, ?);", (str(key), str(prompt[key]))) + self.__connect.commit() + + def delete_prompt(self, name): + self.__cursor.execute(f"DELETE from `{self.__table}` where prompt LIKE '{name}'") + self.__connect.commit() + + def delete_tabls(self, tab): + self.__cursor.execute(f"DROP TABLE `{tab}`;") + self.__connect.commit() + + def find_prompt_result(self, name): + query = self.__cursor.execute(f"SELECT result FROM `{self.__table}` WHERE prompt LIKE '{name}'").fetchall() + if query == []: + query = self.__cursor.execute(f"SELECT result FROM `prompt_127.0.0.1` WHERE prompt LIKE '{name}'").fetchall() + return query[0][0] + else: + return query[0][0] + +def cp_db_data(incloud_tab='prompt'): + sql_ll = sqlite_handle(database='ai_prompt_cp.db') + tabs = sql_ll.get_tables() + for i in tabs: + if str(i).startswith(incloud_tab): + old_data = sqlite_handle(table=i, database='ai_prompt_cp.db').get_prompt_value() + sqlite_handle(table=i).inset_prompt(old_data) + +def inset_127_prompt(): + sql_handle = sqlite_handle(table='prompt_127.0.0.1') + prompt_json = os.path.join(prompt_path, 'prompts-PlexPt.json') + data_list = func_box.JsonHandle(prompt_json).load() + for i in data_list: + sql_handle.inset_prompt(prompt={i['act']: i['prompt']}) + +sqlite_handle = SqliteHandle +if __name__ == '__main__': + cp_db_data() \ No newline at end of file diff --git a/request_llm/bridge_all.py b/request_llm/bridge_all.py index d33f161..d595ad5 100644 --- a/request_llm/bridge_all.py +++ b/request_llm/bridge_all.py @@ -13,8 +13,11 @@ from functools import lru_cache from concurrent.futures import ThreadPoolExecutor from toolbox import get_conf, trimmed_format_exc -from .bridge_chatgpt import predict_no_ui_long_connection as chatgpt_noui -from .bridge_chatgpt import predict as chatgpt_ui +from request_llm.bridge_chatgpt import predict_no_ui_long_connection as chatgpt_noui +from request_llm.bridge_chatgpt import predict as chatgpt_ui + +from .bridge_azure_test import predict_no_ui_long_connection as azure_noui +from .bridge_azure_test import predict as azure_ui from .bridge_azure_test import predict_no_ui_long_connection as azure_noui from .bridge_azure_test import predict as azure_ui @@ -51,10 +54,11 @@ class LazyloadTiktoken(object): return encoder.decode(*args, **kwargs) # Endpoint 重定向 -API_URL_REDIRECT, = get_conf("API_URL_REDIRECT") +API_URL_REDIRECT, PROXY_API_URL = get_conf("API_URL_REDIRECT", 'PROXY_API_URL') openai_endpoint = "https://api.openai.com/v1/chat/completions" api2d_endpoint = "https://openai.api2d.net/v1/chat/completions" newbing_endpoint = "wss://sydney.bing.com/sydney/ChatHub" +proxy_endpoint = PROXY_API_URL # 兼容旧版的配置 try: API_URL, = get_conf("API_URL") @@ -69,6 +73,7 @@ if api2d_endpoint in API_URL_REDIRECT: api2d_endpoint = API_URL_REDIRECT[api2d_e if newbing_endpoint in API_URL_REDIRECT: newbing_endpoint = API_URL_REDIRECT[newbing_endpoint] + # 获取tokenizer tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo") tokenizer_gpt4 = LazyloadTiktoken("gpt-4") @@ -122,6 +127,15 @@ model_info = { "tokenizer": tokenizer_gpt4, "token_cnt": get_token_num_gpt4, }, + # azure openai + "azure-gpt35":{ + "fn_with_ui": azure_ui, + "fn_without_ui": azure_noui, + "endpoint": get_conf("AZURE_ENDPOINT"), + "max_token": 4096, + "tokenizer": tokenizer_gpt35, + "token_cnt": get_token_num_gpt35, + }, # azure openai "azure-gpt35":{ @@ -147,9 +161,9 @@ model_info = { "fn_with_ui": chatgpt_ui, "fn_without_ui": chatgpt_noui, "endpoint": api2d_endpoint, - "max_token": 8192, - "tokenizer": tokenizer_gpt4, - "token_cnt": get_token_num_gpt4, + "max_token": 4096, + "tokenizer": tokenizer_gpt35, + "token_cnt": get_token_num_gpt35, }, # 将 chatglm 直接对齐到 chatglm2 diff --git a/request_llm/bridge_chatgpt.py b/request_llm/bridge_chatgpt.py index eef8fbf..cfca56a 100644 --- a/request_llm/bridge_chatgpt.py +++ b/request_llm/bridge_chatgpt.py @@ -12,12 +12,14 @@ """ import json +import random import time import gradio as gr import logging import traceback import requests import importlib +import func_box # 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 @@ -60,7 +62,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", while True: try: # make a POST request to the API endpoint, stream=False - from .bridge_all import model_info + from request_llm.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 @@ -106,7 +108,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", return result -def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None): +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。 @@ -134,24 +136,22 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"] raw_input = inputs - logging.info(f'[raw_input] {raw_input}') + logging.info(f'[raw_input]_{llm_kwargs["ipaddr"]} {raw_input}') chatbot.append((inputs, "")) - yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面 - + loading_msg = func_box.spinner_chatbot_loading(chatbot) + yield from update_ui(chatbot=loading_msg, history=history, msg="等待响应") # 刷新界面 try: headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt, stream) except RuntimeError as e: chatbot[-1] = (inputs, f"您提供的api-key不满足要求，不包含任何可用于{llm_kwargs['llm_model']}的api-key。您可能选择了错误的模型或请求源。") yield from update_ui(chatbot=chatbot, history=history, msg="api-key不满足要求") # 刷新界面 return - history.append(inputs); history.append("") - retry = 0 while True: try: # make a POST request to the API endpoint, stream=True - from .bridge_all import model_info + from request_llm.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 @@ -163,7 +163,6 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp if retry > MAX_RETRY: raise TimeoutError gpt_replying_buffer = "" - is_head_of_the_stream = True if stream: stream_response = response.iter_lines() @@ -181,24 +180,26 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp if is_head_of_the_stream and (r'"object":"error"' not in chunk.decode()): # 数据流的第一帧不携带content is_head_of_the_stream = False; continue - + if chunk: try: chunk_decoded = chunk.decode() # 前者API2D的 if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['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}') + logging.info(f'[response]_{llm_kwargs["ipaddr"]} {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]['finish_reason']}" + # 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 + json.loads(chunk_decoded[6:])['choices'][0]["delta"]["content"] history[-1] = gpt_replying_buffer chatbot[-1] = (history[-2], history[-1]) + count_time = round(time.time() - llm_kwargs['start_time'], 3) + status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}\t" \ + f"本次对话耗时: {func_box.html_tag_color(tag=f'{count_time}s')}" yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面 - except Exception as e: traceback.print_exc() yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面 @@ -207,7 +208,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp error_msg = chunk_decoded if "reduce the length" in error_msg: if len(history) >= 2: history[-1] = ""; history[-2] = "" # 清除当前溢出的输入：history[-2] 是本次输入, history[-1] 是本次输出 - history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'], + history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'], max_token_limit=(model_info[llm_kwargs['llm_model']]['max_token'])) # history至少释放二分之一 chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长, 或历史数据过长. 历史缓存数据已部分释放, 您可以请再次尝试. (若再次失败则更可能是因为输入过长.)") # history = [] # 清除历史 @@ -227,6 +228,9 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded)}") yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面 return + count_tokens = func_box.num_tokens_from_string(listing=history) + status_text += f'\t 本次对话使用tokens: {func_box.html_tag_color(count_tokens)}' + yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面 def generate_payload(inputs, llm_kwargs, history, system_prompt, stream): """ @@ -234,13 +238,18 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream): """ if not is_any_api_key(llm_kwargs['api_key']): raise AssertionError("你提供了错误的API_KEY。\n\n1. 临时解决方案：直接在输入区键入api_key，然后回车提交。\n\n2. 长效解决方案：在config.py中配置。") - - api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model']) - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {api_key}" - } + if llm_kwargs['llm_model'].startswith('proxy-'): + api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model']) + headers = { + "Content-Type": "application/json", + "api-key": f"{api_key}" + } + else: + api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model']) + headers = { + "Content-Type": "application/json", + "Authorization": f"Bearer {api_key}" + } conversation_cnt = len(history) // 2 @@ -277,9 +286,20 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream): "frequency_penalty": 0, } try: - print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........") + print("\033[1;35m", f"{llm_kwargs['llm_model']}_{llm_kwargs['ipaddr']} :", "\033[0m", f"{conversation_cnt} : {inputs[:100]} ..........") except: print('输入中可能存在乱码。') - return headers,payload - + return headers, payload +if __name__ == '__main__': + llm_kwargs = { + 'api_key': 'sk-', + 'llm_model': 'gpt-3.5-turbo', + 'top_p': 1, + 'max_length': 512, + 'temperature': 1, + # 'ipaddr': ipaddr.client.host + } + chat = [] + predict('你好', llm_kwargs=llm_kwargs, chatbot=chat, plugin_kwargs={}) + print(chat) \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 1d70323..110e0ae 100644 --- a/requirements.txt +++ b/requirements.txt @@ -15,4 +15,11 @@ pymupdf openai numpy arxiv -rich \ No newline at end of file +pymupdf +pyperclip +scikit-learn +psutil +distro +python-dotenv +rich +Levenshtein \ No newline at end of file diff --git a/theme.py b/theme.py index 5ef7e96..ed39e45 100644 --- a/theme.py +++ b/theme.py @@ -1,6 +1,6 @@ import gradio as gr from toolbox import get_conf -CODE_HIGHLIGHT, ADD_WAIFU = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU') +CODE_HIGHLIGHT, ADD_WAIFU, ADD_CHUANHU = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'ADD_CHUANHU') # gradio可用颜色列表 # gr.themes.utils.colors.slate (石板色) # gr.themes.utils.colors.gray (灰色) @@ -29,105 +29,185 @@ CODE_HIGHLIGHT, ADD_WAIFU = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU') def adjust_theme(): try: - color_er = gr.themes.utils.colors.fuchsia - set_theme = gr.themes.Default( - primary_hue=gr.themes.utils.colors.orange, - neutral_hue=gr.themes.utils.colors.gray, - font=["sans-serif", "Microsoft YaHei", "ui-sans-serif", "system-ui", - "sans-serif", gr.themes.utils.fonts.GoogleFont("Source Sans Pro")], - font_mono=["ui-monospace", "Consolas", "monospace", gr.themes.utils.fonts.GoogleFont("IBM Plex Mono")]) - set_theme.set( - # Colors - input_background_fill_dark="*neutral_800", - # Transition - button_transition="none", - # Shadows - button_shadow="*shadow_drop", - button_shadow_hover="*shadow_drop_lg", - button_shadow_active="*shadow_inset", - input_shadow="0 0 0 *shadow_spread transparent, *shadow_inset", - input_shadow_focus="0 0 0 *shadow_spread *secondary_50, *shadow_inset", - input_shadow_focus_dark="0 0 0 *shadow_spread *neutral_700, *shadow_inset", - checkbox_label_shadow="*shadow_drop", - block_shadow="*shadow_drop", - form_gap_width="1px", - # Button borders - input_border_width="1px", - input_background_fill="white", - # Gradients - stat_background_fill="linear-gradient(to right, *primary_400, *primary_200)", - stat_background_fill_dark="linear-gradient(to right, *primary_400, *primary_600)", - error_background_fill=f"linear-gradient(to right, {color_er.c100}, *background_fill_secondary)", - error_background_fill_dark="*background_fill_primary", - checkbox_label_background_fill="linear-gradient(to top, *neutral_50, white)", - checkbox_label_background_fill_dark="linear-gradient(to top, *neutral_900, *neutral_800)", - checkbox_label_background_fill_hover="linear-gradient(to top, *neutral_100, white)", - checkbox_label_background_fill_hover_dark="linear-gradient(to top, *neutral_900, *neutral_800)", - button_primary_background_fill="linear-gradient(to bottom right, *primary_100, *primary_300)", - button_primary_background_fill_dark="linear-gradient(to bottom right, *primary_500, *primary_600)", - button_primary_background_fill_hover="linear-gradient(to bottom right, *primary_100, *primary_200)", - button_primary_background_fill_hover_dark="linear-gradient(to bottom right, *primary_500, *primary_500)", - button_primary_border_color_dark="*primary_500", - button_secondary_background_fill="linear-gradient(to bottom right, *neutral_100, *neutral_200)", - button_secondary_background_fill_dark="linear-gradient(to bottom right, *neutral_600, *neutral_700)", - button_secondary_background_fill_hover="linear-gradient(to bottom right, *neutral_100, *neutral_100)", - button_secondary_background_fill_hover_dark="linear-gradient(to bottom right, *neutral_600, *neutral_600)", - button_cancel_background_fill=f"linear-gradient(to bottom right, {color_er.c100}, {color_er.c200})", - button_cancel_background_fill_dark=f"linear-gradient(to bottom right, {color_er.c600}, {color_er.c700})", - button_cancel_background_fill_hover=f"linear-gradient(to bottom right, {color_er.c100}, {color_er.c100})", - button_cancel_background_fill_hover_dark=f"linear-gradient(to bottom right, {color_er.c600}, {color_er.c600})", - button_cancel_border_color=color_er.c200, - button_cancel_border_color_dark=color_er.c600, - button_cancel_text_color=color_er.c600, - button_cancel_text_color_dark="white", - ) + set_theme = gr.themes.Soft( + primary_hue=gr.themes.Color( + c50="#EBFAF2", + c100="#CFF3E1", + c200="#A8EAC8", + c300="#77DEA9", + c400="#3FD086", + c500="#02C160", + c600="#06AE56", + c700="#05974E", + c800="#057F45", + c900="#04673D", + c950="#2E5541", + name="small_and_beautiful", + ), + secondary_hue=gr.themes.Color( + c50="#576b95", + c100="#576b95", + c200="#576b95", + c300="#576b95", + c400="#576b95", + c500="#576b95", + c600="#576b95", + c700="#576b95", + c800="#576b95", + c900="#576b95", + c950="#576b95", + ), + neutral_hue=gr.themes.Color( + name="gray", + c50="#f6f7f8", + # c100="#f3f4f6", + c100="#F2F2F2", + c200="#e5e7eb", + c300="#d1d5db", + c400="#B2B2B2", + c500="#808080", + c600="#636363", + c700="#515151", + c800="#393939", + # c900="#272727", + c900="#2B2B2B", + c950="#171717", + ), + radius_size=gr.themes.sizes.radius_sm, + ).set( + button_primary_background_fill="*primary_500", + button_primary_background_fill_dark="*primary_600", + button_primary_background_fill_hover="*primary_400", + button_primary_border_color="*primary_500", + button_primary_border_color_dark="*primary_600", + button_primary_text_color="wihte", + button_primary_text_color_dark="white", + button_secondary_background_fill="*neutral_100", + button_secondary_background_fill_hover="*neutral_50", + button_secondary_background_fill_dark="*neutral_900", + button_secondary_text_color="*neutral_800", + button_secondary_text_color_dark="white", + background_fill_primary="#F7F7F7", + background_fill_primary_dark="#1F1F1F", + block_title_text_color="*primary_500", + block_title_background_fill_dark="*primary_900", + block_label_background_fill_dark="*primary_900", + input_background_fill="#F6F6F6", + chatbot_code_background_color="*neutral_950", + chatbot_code_background_color_dark="*neutral_950", + ) + js = '' + if ADD_CHUANHU: + with open("./docs/assets/custom.js", "r", encoding="utf-8") as f, \ + open("./docs/assets/external-scripts.js", "r", encoding="utf-8") as f1: + customJS = f.read() + externalScripts = f1.read() + js += f'' # 添加一个萌萌的看板娘 if ADD_WAIFU: - js = """ + js += """ """ - gradio_original_template_fn = gr.routes.templates.TemplateResponse - def gradio_new_template_fn(*args, **kwargs): - res = gradio_original_template_fn(*args, **kwargs) - res.body = res.body.replace(b'