From d1a06ec32e6fe31d8675bd23aa22b4bee84c5339 Mon Sep 17 00:00:00 2001 From: liukuikun <24622904+Harold-lkk@users.noreply.github.com> Date: Mon, 29 Jul 2024 14:57:29 +0800 Subject: [PATCH] [Refactor] remove unused for mindsearch (#210) --- .dockerignore | 7 - Dockerfile | 28 - Dockerfile-base | 26 - README.md | 78 +- README_in_HIN.md | 51 + README_in_beng.md | 55 + README_ja_JP.md | 56 + app.py | 272 - docs/imgs/mindsearch_framework.png | Bin 989604 -> 0 bytes docs/imgs/mindsearch_openset.png | Bin 119228 -> 0 bytes environment.yml | 500 - examples/web_graph_ci_demo.py | 44 - examples/web_graph_gradio_demo.py | 193 - examples/web_graph_streamlit_demo.py | 357 - frontend/.gitignore | 20 - frontend/.prettierignore | 7 - frontend/.prettierrc.json | 7 - frontend/README.md | 14 - frontend/index.html | 14 - frontend/package-lock.json | 9973 ------------------- frontend/package.json | 49 - frontend/src/App.module.less | 54 - frontend/src/App.tsx | 23 - frontend/src/assets/background.png | Bin 36899 -> 0 bytes frontend/src/assets/fold-icon.svg | 3 - frontend/src/assets/logo.svg | 24 - frontend/src/assets/pack-up.svg | 4 - frontend/src/assets/sendIcon.svg | 4 - frontend/src/assets/show-right-icon.png | Bin 8870 -> 0 bytes frontend/src/assets/unflod-icon.svg | 3 - frontend/src/components/iconfont/index.tsx | 7 - frontend/src/config/cgi.ts | 2 - frontend/src/global.d.ts | 1 - frontend/src/index.less | 62 - frontend/src/index.tsx | 10 - frontend/src/pages/render/index.module.less | 848 -- frontend/src/pages/render/index.tsx | 681 -- frontend/src/pages/render/mindMapItem.tsx | 39 - frontend/src/routes/routes.tsx | 38 - frontend/src/utils/tools.ts | 24 - frontend/src/vite-env.d.ts | 9 - frontend/tsconfig.json | 24 - frontend/vite.config.ts | 62 - lagent/agents/mindsearch_agent.py | 395 - 44 files changed, 214 insertions(+), 13854 deletions(-) delete mode 100644 .dockerignore delete mode 100644 Dockerfile delete mode 100644 Dockerfile-base create mode 100644 README_in_HIN.md create mode 100644 README_in_beng.md create mode 100644 README_ja_JP.md delete mode 100644 app.py delete mode 100644 docs/imgs/mindsearch_framework.png delete mode 100644 docs/imgs/mindsearch_openset.png delete mode 100644 environment.yml delete mode 100644 examples/web_graph_ci_demo.py delete mode 100644 examples/web_graph_gradio_demo.py delete mode 100644 examples/web_graph_streamlit_demo.py delete mode 100644 frontend/.gitignore delete mode 100644 frontend/.prettierignore delete mode 100644 frontend/.prettierrc.json delete mode 100644 frontend/README.md delete mode 100644 frontend/index.html delete mode 100644 frontend/package-lock.json delete mode 100644 frontend/package.json delete mode 100644 frontend/src/App.module.less delete mode 100644 frontend/src/App.tsx delete mode 100644 frontend/src/assets/background.png delete mode 100644 frontend/src/assets/fold-icon.svg delete mode 100644 frontend/src/assets/logo.svg delete mode 100644 frontend/src/assets/pack-up.svg delete mode 100644 frontend/src/assets/sendIcon.svg delete mode 100644 frontend/src/assets/show-right-icon.png delete mode 100644 frontend/src/assets/unflod-icon.svg delete mode 100644 frontend/src/components/iconfont/index.tsx delete mode 100644 frontend/src/config/cgi.ts delete mode 100644 frontend/src/global.d.ts delete mode 100644 frontend/src/index.less delete mode 100644 frontend/src/index.tsx delete mode 100644 frontend/src/pages/render/index.module.less delete mode 100644 frontend/src/pages/render/index.tsx delete mode 100644 frontend/src/pages/render/mindMapItem.tsx delete mode 100644 frontend/src/routes/routes.tsx delete mode 100644 frontend/src/utils/tools.ts delete mode 100644 frontend/src/vite-env.d.ts delete mode 100644 frontend/tsconfig.json delete mode 100644 frontend/vite.config.ts delete mode 100644 lagent/agents/mindsearch_agent.py diff --git a/.dockerignore b/.dockerignore deleted file mode 100644 index 5102d2c4..00000000 --- a/.dockerignore +++ /dev/null @@ -1,7 +0,0 @@ -.github/ -.vscode/ -docs/*/_build/ -*.egg-info -lib/ -tmp_dir/ -work_dir/ diff --git a/Dockerfile b/Dockerfile deleted file mode 100644 index eae2993a..00000000 --- a/Dockerfile +++ /dev/null @@ -1,28 +0,0 @@ -FROM continuumio/miniconda3 - -ARG PUYU_API_KEY -ENV PUYU_API_KEY=${PUYU_API_KEY} - -ARG BING_API_KEY -ENV BING_API_KEY=${BING_API_KEY} - -# 设置环境变量 -ENV PATH=/opt/conda/bin:$PATH - -# 创建并激活 fastapi 环境 -RUN conda create --name fastapi python=3.10 -y - -# 克隆git仓库 -RUN git clone --branch ljn/fastapi https://github.com/liujiangning30/lagent.git /app -WORKDIR /app - -# 激活环境并安装依赖包 -RUN /bin/bash -c "source activate fastapi && \ - pip install sse-starlette janus pyvis fastapi uvicorn termcolor -i https://pypi.tuna.tsinghua.edu.cn/simple && \ - pip install -e . -i https://pypi.tuna.tsinghua.edu.cn/simple" - -# 暴露 FastAPI 默认端口 -EXPOSE 8000 - -# 启动 FastAPI 服务 -CMD ["/bin/bash", "-c", "source activate fastapi && uvicorn app:app --host 0.0.0.0 --port 8000"] diff --git a/Dockerfile-base b/Dockerfile-base deleted file mode 100644 index f9a4943b..00000000 --- a/Dockerfile-base +++ /dev/null @@ -1,26 +0,0 @@ -# 使用官方的 Python 镜像作为基础镜像 -FROM python:3.10-slim - -# 安装必要的工具 -RUN apt-get update && apt-get install -y \ - wget \ - bzip2 \ - git \ - && apt-get clean \ - && rm -rf /var/lib/apt/lists/* - -# 下载并安装 Miniconda -RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh && \ - /bin/bash /tmp/miniconda.sh -b -p /opt/conda && \ - rm /tmp/miniconda.sh - -# 设置环境变量 -ENV PATH=/opt/conda/bin:$PATH - -# 创建并激活 fastapi 环境 -RUN conda create --name fastapi python=3.10 -y - -# 激活环境并安装依赖包 -RUN /bin/bash -c "source activate fastapi && \ - pip install sse-starlette janus pyvis -i https://pypi.tuna.tsinghua.edu.cn/simple && \ - pip install lmdeploy==0.2.3 -i https://pypi.tuna.tsinghua.edu.cn/simple" diff --git a/README.md b/README.md index 3b32fb0b..a8b89294 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,6 @@
- -
- -# Lagent $\times$ MindSearch
-[Research Preview](https://mindsearch.netlify.app/) | [Paper]() | [Blog](https://mindsearch.netlify.app/mindsearch) -
-
+ [![docs](https://img.shields.io/badge/docs-latest-blue)](https://lagent.readthedocs.io/en/latest/) [![PyPI](https://img.shields.io/pypi/v/lagent)](https://pypi.org/project/lagent) @@ -16,8 +10,9 @@ ![Visitors](https://api.visitorbadge.io/api/visitors?path=InternLM%2Flagent%20&countColor=%23263759&style=flat) ![GitHub forks](https://img.shields.io/github/forks/InternLM/lagent) ![GitHub Repo stars](https://img.shields.io/github/stars/InternLM/lagent) +![GitHub contributors](https://img.shields.io/github/contributors/InternLM/lagent) -English | [简体中文](README_zh-CN.md) +English | [简体中文](README_zh-CN.md) | [日本語](README_ja_JP.md) | [हिंदी](README_in_HIN.md) | [বাংলা](README_in_beng.md) | [한국어](README_KR_Kr.md)
@@ -25,31 +20,60 @@ English | [简体中文](README_zh-CN.md) 👋 join us on 𝕏 (Twitter), Discord and WeChat

-## ✨ MindSearch: Towards Deeper and Wider AI Search Engine +
+ +https://github.com/InternLM/lagent/assets/24622904/3242f9bf-32d2-4907-8815-e16a75a4ac0e -#### Demo Video here +
-MindSearch is an open-source AI Search Engine Framework with Perplexity.ai Pro performance. You can simply deploy it with your own perplexity.ai style search engine with either close-source LLMs (GPT, Claude) or open-source LLMs (InternLM2.5-7b-chat). It owns following features: -- 🤔 **Ask everything you want to know**: MindSearch is designed to solve any question in your life and use web knowledge. -- 📚 **In-depth Knowledge Discovery**: MindSearch browses hundreds of web pages to answer your question, providing deeper and wider knowledge base answer. -- 🔍 **Detailed Solution Path**: MindSearch exposes all details, allowing users to check everything they want. This greatly improves the credibility of its final response as well as usability. -- 💻 **Optimized UI Experimence**: Providing all kinds of interfaces for users, including React, Streamlit, Terminal. Choose any type based on your need. +## Getting Started -## ⚡️ MindSearch vs other AI Search Engines +Please see the [overview](docs/en/get_started/overview.md) for the general introduction of Lagent. Meanwhile, we provide extremely simple code for quick start. You may refer to [examples](examples/) for more details. -Comparison on human preference based on depth, breadth, factuality of the response generated by ChatGPT-Web, Perplexity.ai (Pro), and MindSearch. Results are obtained on 100 human-crafted real-world questions and evaluated by 5 human experts *. -
- -
-* All experiments are done before July.7 2024. +### Installation -## ⚽️ Getting Started +Install with pip (Recommended). -### Lagent Installation +```bash +pip install lagent +``` -MindSearch backend with Lagent, please see the [overview](docs/en/get_started/overview.md) for the general introduction of Lagent. Meanwhile, we provide extremely simple code for quick start. You may refer to [examples](examples/) for more details. +### Run a Web Demo -### MindSearch +You need to install Streamlit first. + +```bash +# pip install streamlit +streamlit run examples/internlm2_agent_web_demo.py +``` + +## What's Lagent? + +Lagent is a lightweight open-source framework that allows users to efficiently build large language model(LLM)-based agents. It also provides some typical tools to augment LLM. The overview of our framework is shown below: + +![image](https://github.com/InternLM/lagent/assets/24351120/cefc4145-2ad8-4f80-b88b-97c05d1b9d3e) + +## Major Features + +- Stream Output: Provides the `stream_chat` interface for streaming output, allowing cool streaming demos right at your local setup. +- Interfacing is unified, with a comprehensive design upgrade for enhanced extensibility, including: + - Model: Whether it's the OpenAI API, Transformers, or LMDeploy inference acceleration framework, you can seamlessly switch between models. + - Action: Simple inheritance and decoration allow you to create your own personal toolkit, adaptable to both InternLM and GPT. + - Agent: Consistent with the Model's input interface, the transformation from model to intelligent agent only takes one step, facilitating the exploration and implementation of various agents. +- Documentation has been thoroughly upgraded with full API documentation coverage. + +## 💻Tech Stack + +

+ + python + + +### All Thanks To Our Contributors: + + + + ## Citation @@ -66,4 +90,6 @@ If you find this project useful in your research, please consider cite: ## License -This project is released under the [Apache 2.0 license](LICENSE). \ No newline at end of file +This project is released under the [Apache 2.0 license](LICENSE). + +

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diff --git a/README_in_HIN.md b/README_in_HIN.md new file mode 100644 index 00000000..552dbc98 --- /dev/null +++ b/README_in_HIN.md @@ -0,0 +1,51 @@ +
+
+ + +[![docs](https://img.shields.io/badge/docs-latest-blue)](https://lagent.readthedocs.io/en/latest/) +[![PyPI](https://img.shields.io/pypi/v/lagent)](https://pypi.org/project/lagent) +[![license](https://img.shields.io/github/license/InternLM/lagent.svg)](https://github.com/InternLM/lagent/tree/main/LICENSE) +[![issue resolution](https://img.shields.io/github/issues-closed-raw/InternLM/lagent)](https://github.com/InternLM/lagent/issues) +[![open issues](https://img.shields.io/github/issues-raw/InternLM/lagent)](https://github.com/InternLM/lagent/issues) + +English | [简体中文](README_zh-CN.md) | [日本語](README_ja_JP.md) | [हिंदी](README_in_HIN.md) | [বাংলা](README_in_beng.md) | [한국어](README_KR_Kr.md) + +
+ +
+ +https://github.com/InternLM/lagent/assets/24622904/cb851b31-6932-422e-a776-b1aa68f2a64f + +
+ +## शुरू करना + +लैजेंट के सामान्य परिचय के लिए कृपया [अवलोकन](docs/in/get_started/overview.md) देखें। इस बीच, हम त्वरित शुरुआत के लिए अत्यंत सरल कोड प्रदान करते हैं। अधिक जानकारी के लिए आप [उदाहरण](examples/) अधिक जानकारी के लिए। + +### इंस्टालेशन + +pip के साथ स्थापित करें (अनुशंसित)। + +```bash +pip install lagent +``` + +### वेब डेमो चलाएँ + +```bash +# You need to install streamlit first +# pip install streamlit +streamlit run examples/internlm2_agent_web_demo.py +``` + +## परिचय + +Lagent एक हल्का ओपन-सोर्स फ्रेमवर्क है जो उपयोगकर्ताओं को बड़े भाषा मॉडल (एलएलएम)-आधारित एजेंटों को कुशलतापूर्वक बनाने की अनुमति देता है। यह एलएलएम को बढ़ाने के लिए कुछ विशिष्ट उपकरण भी प्रदान करता है। हमारे ढांचे का अवलोकन नीचे दिखाया गया है: + +![image](https://github.com/InternLM/lagent/assets/24351120/cefc4145-2ad8-4f80-b88b-97c05d1b9d3e) + +## लाइसेंस + +यह प्रोजेक्ट [Apache 2.0 license](LICENSE) के तहत जारी किया गया है। + +

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diff --git a/README_in_beng.md b/README_in_beng.md new file mode 100644 index 00000000..31681b83 --- /dev/null +++ b/README_in_beng.md @@ -0,0 +1,55 @@ +
+
+ + +[![docs](https://img.shields.io/badge/docs-latest-blue)](https://lagent.readthedocs.io/en/latest/) +[![PyPI](https://img.shields.io/pypi/v/lagent)](https://pypi.org/project/lagent) +[![license](https://img.shields.io/github/license/InternLM/lagent.svg)](https://github.com/InternLM/lagent/tree/main/LICENSE) +[![issue resolution](https://img.shields.io/github/issues-closed-raw/InternLM/lagent)](https://github.com/InternLM/lagent/issues) +[![open issues](https://img.shields.io/github/issues-raw/InternLM/lagent)](https://github.com/InternLM/lagent/issues) + +English | [简体中文](README_zh-CN.md) | [日本語](README_ja_JP.md) | [हिंदी](README_in_HIN.md) | [বাংলা](README_in_beng.md) | [한국어](README_KR_Kr.md) + +
+ +

+ 👋 Twitter, Discord এবং WeChat সাথে আমাদের সাথে যোগদান করুন +

+ +
+ +https://github.com/InternLM/lagent/assets/24622904/cb851b31-6932-422e-a776-b1aa68f2a64f + +
+ +## শুরু করা + +লেজেন্টের সাধারণ পরিচিতির জন্য [অবলো](docs/en/get_started/overview.md) দেখ + +## ইনস্টলেশন + +পিপ দিয়ে ইনস্টল করুন (সুপারিশ). + +```bash +pip install lagent +``` + +### ওয়েব ডেমো চালান + +```bash +# You need to install streamlit first +# pip install streamlit +streamlit run examples/internlm2_agent_web_demo.py +``` + +## পরিচিতি + +লেজেন্ট হল একটি হালকা ওপেন-সোর্স ফ্রেমওয়ার্ক, যা ব্যবহারকারীদের দ্বারা প্রশাসক ভাষা মডেল (LLM) ভিত্তিক এজেন্ট সৃজনশীলভাবে তৈরি করতে দেয়। এটি লেজেন্ট যেসব প্রধান সরঞ্জাম সরবরাহ করে, সেটি নীচে দেখানো হয়: + +![image](https://github.com/InternLM/lagent/assets/24351120/cefc4145-2ad8-4f80-b88b-97c05d1b9d3e) + +## লাইসেন্স + +এই প্রকল্পটি [Apache 2.0 license](LICENSE) অনুসরণ করে প্রকাশিত হয়। + +

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diff --git a/README_ja_JP.md b/README_ja_JP.md new file mode 100644 index 00000000..a53187de --- /dev/null +++ b/README_ja_JP.md @@ -0,0 +1,56 @@ +
+
+ + +[![docs](https://img.shields.io/badge/docs-latest-blue)](https://lagent.readthedocs.io/en/latest/) +[![PyPI](https://img.shields.io/pypi/v/lagent)](https://pypi.org/project/lagent) +[![license](https://img.shields.io/github/license/InternLM/lagent.svg)](https://github.com/InternLM/lagent/tree/main/LICENSE) +[![issue resolution](https://img.shields.io/github/issues-closed-raw/InternLM/lagent)](https://github.com/InternLM/lagent/issues) +[![open issues](https://img.shields.io/github/issues-raw/InternLM/lagent)](https://github.com/InternLM/lagent/issues) + +English | [简体中文](README_zh-CN.md) | [日本語](README_ja_JP.md) | [हिंदी](README_in_HIN.md) | [বাংলা](README_in_beng.md) | [한국어](README_KR_Kr.md) + +
+ +

+ 👋 Twitter, Discord そして WeChat に参加する +

+ +
+ +https://github.com/InternLM/lagent/assets/24622904/cb851b31-6932-422e-a776-b1aa68f2a64f + +
+ +## はじめに + +Lagent の概要については[概要](docs/ja/get_started/overview.md)をご覧ください。また、クイックスタートのために非常にシンプルなコードを用意しています。詳細は [examples](examples/) を参照してください。 + +### インストール + +pip でインストールする(推奨)。 + +```bash +pip install lagent +``` + +### ウェブデモの実行 + +最初に streamlit をインストールする必要があります + +```bash +# pip install streamlit +streamlit run examples/internlm2_agent_web_demo.py +``` + +## はじめに + +Lagent は、大規模言語モデル(LLM)ベースのエージェントを効率的に構築できる軽量なオープンソースフレームワークです。また、LLM を拡張するための典型的なツールも提供します。我々のフレームワークの概要を以下に示します: + +![image](https://github.com/InternLM/lagent/assets/24351120/cefc4145-2ad8-4f80-b88b-97c05d1b9d3e) + +## ライセンス + +このプロジェクトは [Apache 2.0 license](LICENSE) の下でリリースされています。 + +

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diff --git a/app.py b/app.py deleted file mode 100644 index 215db6c5..00000000 --- a/app.py +++ /dev/null @@ -1,272 +0,0 @@ -import asyncio -import json -import logging -import os -from dataclasses import asdict, dataclass -from datetime import datetime -from typing import Dict, List, Optional, Union - -import janus -from fastapi import FastAPI, HTTPException -from fastapi.middleware.cors import CORSMiddleware -from pydantic import BaseModel -from sse_starlette.sse import EventSourceResponse - -import lagent.actions as action_factory -import lagent.agents as agent_factory -import lagent.llms as llm_factory -from lagent.actions import ActionExecutor -from lagent.agents.mindsearch_prompt import (FINAL_RESPONSE_EN, - GRAPH_PROMPT_EN, - searcher_context_template_en, - searcher_input_template_en, - searcher_system_prompt_en) -from lagent.schema import AgentStatusCode - -# from lagent.agents.mindsearch_prompt import (GRAPH_PROMPT_CN, -# searcher_context_template_cn, -# searcher_input_template_cn, -# searcher_system_prompt_cn, -# FINAL_RESPONSE_CN) - - -@dataclass -class InvalidConfig: - type: Optional[str] = None - cfg: Optional[dict] = None - details: Optional[str] = None - - -def init_agent(cfg): - - # from lagent.llms import INTERNLM2_META - - def init_module(module_cfg, module_factory): - try: - module_type = module_cfg.pop('type') - module_class = getattr(module_factory, module_type) - module = module_class(**module_cfg) - return module - except Exception as exc: - logging.exception(str(exc)) - return InvalidConfig( - type=module_type, cfg=module_cfg, details=str(exc)) - - def init_executor(module_cfg): - plugin_executor = None - interpreter_executor = None - if 'plugin' in module_cfg: - actions = [] - plugin_cfg = module_cfg.pop('plugin') - for ac_cfg in plugin_cfg: - ac = init_module(ac_cfg, action_factory) - if isinstance(ac, InvalidConfig): - return ac - actions.append(ac) - plugin_executor = ActionExecutor(actions=actions) - if 'interpreter' in module_cfg: - interpreter_cfg = module_cfg.pop('interpreter') - ci = init_module(interpreter_cfg, action_factory) - if isinstance(ci, InvalidConfig): - return ci - interpreter_executor = ActionExecutor(actions=[ci]) - return plugin_executor, interpreter_executor - - llm_cfg = cfg.get('llm', None) - if not llm_cfg: - # llm_cfg = dict( - # type='LMDeployClient', - # model_name='internlm2-chat-7b', - # url=os.environ.get('LLM_URL', 'http://localhost:23333'), - # meta_template=INTERNLM2_META, - # max_new_tokens=4096, - # top_p=0.8, - # top_k=1, - # temperature=0.8, - # repetition_penalty=1.02, - # stop_words=['<|im_end|>']) - url = 'https://puyu.openxlab.org.cn/puyu/api/v1/chat/completions' - llm_cfg = dict( - type='GPTAPI', - model_type='internlm2.5-latest', - openai_api_base=url, - key=os.environ.get('PUYU_API_KEY', 'YOUR PUYU API KEY'), - meta_template=[ - dict(role='system', api_role='system'), - dict(role='user', api_role='user'), - dict(role='assistant', api_role='assistant'), - dict(role='environment', api_role='environment') - ], - top_p=0.8, - top_k=1, - temperature=0.8, - max_new_tokens=8192, - repetition_penalty=1.02, - stop_words=['<|im_end|>']) - llm = init_module(llm_cfg, llm_factory) - if isinstance(llm, InvalidConfig): - return llm - if cfg.get('type', None) is None: - cfg['type'] = 'MindSearchAgent' - searcher_cfg = cfg.get('searcher', None) - if searcher_cfg: - cfg.pop('searcher') - if cfg['type'] == 'MindSearchAgent' and searcher_cfg is None: - searcher_cfg = dict( - llm=llm, - plugin=[ - dict( - type='BingBrowser', - api_key=os.environ.get('BING_API_KEY', - 'YOUR BING API KEY')) - ], - protocol=dict( - type='MindSearchProtocol', - meta_prompt=datetime.now().strftime( - 'The current date is %Y-%m-%d.'), - plugin_prompt=searcher_system_prompt_en, - ), - template=dict( - input=searcher_input_template_en, - context=searcher_context_template_en)) - if searcher_cfg: - # searcher initialization - if 'type' in searcher_cfg: - searcher_cfg.pop('type') - if isinstance(searcher_cfg['llm'], dict): - searcher_llm = init_module(searcher_cfg['llm'], llm_factory) - if isinstance(searcher_llm, InvalidConfig): - return searcher_llm - searcher_cfg['llm'] = searcher_llm - searcher_protocol = init_module(searcher_cfg['protocol'], - agent_factory) - if isinstance(searcher_protocol, InvalidConfig): - return searcher_protocol - searcher_cfg['protocol'] = searcher_protocol - executors = init_executor(searcher_cfg) - if isinstance(executors, InvalidConfig): - return executors - searcher_cfg['plugin_executor'] = executors[0] - cfg['searcher_cfg'] = searcher_cfg - if cfg.get('protocol', None) is None: - cfg['protocol'] = dict( - type='MindSearchProtocol', - meta_prompt=datetime.now().strftime( - 'The current date is %Y-%m-%d.'), - interpreter_prompt=GRAPH_PROMPT_EN, - response_prompt=FINAL_RESPONSE_EN) - if cfg.get('max_turn', None) is None: - cfg['max_turn'] = 10 - # agent initialization - cfg['llm'] = llm - protocol = init_module(cfg['protocol'], agent_factory) - if isinstance(protocol, InvalidConfig): - return protocol - cfg['protocol'] = protocol - executors = init_executor(cfg) - if isinstance(executors, InvalidConfig): - return executors - if isinstance(executors[0], ActionExecutor): - cfg['plugin_executor'] = executors[0] - if isinstance(executors[1], ActionExecutor): - cfg['interpreter_executor'] = executors[1] - agent = init_module(cfg, agent_factory) - return agent - - -def convert_adjacency_to_tree(adjacency_input, root_name): - - def build_tree(node_name): - node = {'name': node_name, 'children': []} - if node_name in adjacency_input: - for child in adjacency_input[node_name]: - child_node = build_tree(child['name']) - child_node['state'] = child['state'] - child_node['id'] = child['id'] - node['children'].append(child_node) - return node - - return build_tree(root_name) - - -# agent = os.environ.get('agent_cfg', dict()) - -app = FastAPI(docs_url='/') - -app.add_middleware( - CORSMiddleware, - allow_origins=['*'], - allow_credentials=True, - allow_methods=['*'], - allow_headers=['*']) - - -class GenerationParams(BaseModel): - inputs: Union[str, List[Dict]] - agent_cfg: Dict = dict() - - -@app.post('/solve') -async def run(request: GenerationParams): - inputs = request.inputs - agent = init_agent(request.agent_cfg) - if not inputs: - raise HTTPException(status_code=400, detail='Inputs are required') - if isinstance(agent, InvalidConfig): - raise InvalidConfig(**agent) - - async def generate(): - try: - queue = janus.Queue() - - # 使用 run_in_executor 将同步生成器包装成异步生成器 - def sync_generator_wrapper(): - try: - for response in agent.stream_chat(inputs): - queue.sync_q.put(response) - except KeyError as e: - logging.error(f'KeyError in sync_generator_wrapper: {e}') - - async def async_generator_wrapper(): - loop = asyncio.get_event_loop() - loop.run_in_executor(None, sync_generator_wrapper) - while True: - response = await queue.async_q.get() - yield response - if not isinstance( - response, - tuple) and response.state == AgentStatusCode.END: - break - - async for response in async_generator_wrapper(): - if isinstance(response, tuple): - agent_return, node_name = response - else: - agent_return = response - node_name = None - adjacency_list = convert_adjacency_to_tree( - agent_return.adjacency_list, 'root') - assert adjacency_list[ - 'name'] == 'root' and 'children' in adjacency_list - agent_return.adjacency_list = adjacency_list['children'] - response_json = json.dumps( - dict( - response=asdict(agent_return), current_node=node_name), - ensure_ascii=False) - yield {'data': response_json} - # yield f'data: {response_json}\n\n' - except Exception as exc: - msg = 'An error occurred while generating the response.' - logging.exception(msg) - response_json = json.dumps( - dict(error=dict(msg=msg, details=str(exc))), - ensure_ascii=False) - yield {'data': response_json} - # yield f'data: {response_json}\n\n' - - return EventSourceResponse(generate()) - - -if __name__ == '__main__': - import uvicorn - uvicorn.run(app, host='0.0.0.0', port=8000, log_level='info') diff --git a/docs/imgs/mindsearch_framework.png b/docs/imgs/mindsearch_framework.png deleted file mode 100644 index 24c545c1487691d7b4092ca1142a2296f6af2766..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 989604 zcmeFZXH=8j+AT~G0TocBNC%||Nbe<}qV(Q73Wgr4^d^F!AiZ~yUPBL|st5=HLJttC zl+Z&D5Xu*yy`TM_Grk}1*?XLEe!YVM_X=Yr_r0#Q)?D+N^MX&>no4B1=x^cS;gP8* zztF|QyM@BTBNisPiTlkvit;Ah1>aLw={a8Y5aR~!ML5t{#a2TDj|bN#!6U+_#3TIE z1^0!APmf3RR~rvc6`$c>ZC(7w|LjA6hZpI9cjKRZOmWvgP1Qd?{&gk%g8yHi_=Vu_ z-nUR+2>)&q3;%haOo~ks?n3IOY~qQBC;aWtH~!-{rbs-zr+6wap6UDIZ_g10j@z;j z?=>MTEgZPDqiB45Aow+xRPkD z<)7vR17mC0wQ^vx>77)7&4ofzP_ktNnsy~@1#@w$K$Z)dbeo4lO2EiKMe>y(cSEd1QNRc zG?rg-@ZNhidOqj>PiMlO>Zx0`;=?!p>3qKPCLkG_7$SxK$0N|e`wpf56p#O(hH!?I zRnka?YvuiaxFX*v;@?0yvOmB1ABXUN7Qz24g8xB+|3Lzh|5*h87Z$-cT^sWM^*Fjq 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WebAgent Gradio Simple Demo

""") - with gr.Row(): - with gr.Column(scale=2, min_width=20): - with gr.Accordion('gen setting', elem_id='Accordion'): - max_new_tokens = gr.Slider( - 0, - 32768, - value=4096, - step=1.0, - label='Max tokens', - interactive=True) - top_p = gr.Slider( - 0, - 1, - value=0.8, - step=0.01, - label='Top P', - interactive=True) - temperature = gr.Slider( - 0, - 1, - value=0.8, - step=0.01, - label='Temperature', - interactive=True) - with gr.Column(scale=10): - with gr.Row(): - with gr.Column(): - planner = gr.Chatbot( - label='planner', - height=700, - show_label=True, - show_copy_button=True, - bubble_full_width=False, - render_markdown=True) - with gr.Column(): - searcher = gr.Chatbot( - label='searcher', - height=700, - show_label=True, - show_copy_button=True, - bubble_full_width=False, - render_markdown=True) - with gr.Row(): - user_input = gr.Textbox( - show_label=False, - placeholder='inputs...', - lines=5, - container=False) - with gr.Row(): - with gr.Column(scale=2): - submitBtn = gr.Button('Submit') - with gr.Column(scale=1, min_width=20): - emptyBtn = gr.Button('Clear History') - - def user(query, history): - return '', history + [[query, '']] - - submitBtn.click( - user, [user_input, planner], [user_input, planner], queue=False).then( - predict, [planner, searcher, max_new_tokens, top_p, temperature], - [planner, searcher]) - emptyBtn.click( - rst_mem, [planner, searcher], [planner, searcher], queue=False) - -demo.queue() -demo.launch( - server_name='127.0.0.1', server_port=7882, inbrowser=True, share=True) diff --git a/examples/web_graph_streamlit_demo.py b/examples/web_graph_streamlit_demo.py deleted file mode 100644 index 01058175..00000000 --- a/examples/web_graph_streamlit_demo.py +++ /dev/null @@ -1,357 +0,0 @@ -import json -import tempfile - -import streamlit as st -from pyvis.network import Network - -from lagent.schema import AgentStatusCode - - -# Function to create the network graph -def create_network_graph(nodes, adjacency_list): - net = Network( - height='500px', width='60%', bgcolor='white', font_color='black') - for node_id, node_data in nodes.items(): - if node_id in ['root', 'response']: - title = node_data.get('content', node_id) - else: - title = node_data['detail'].content - net.add_node( - node_id, label=node_id, title=title, color='#FF5733', size=25) - for node_id, neighbors in adjacency_list.items(): - for neighbor in neighbors: - if neighbor['name'] in nodes: - net.add_edge(node_id, neighbor['name']) - net.show_buttons(filter_=['physics']) - return net - - -# Function to draw the graph and return the HTML file path -def draw_graph(net): - path = tempfile.mktemp(suffix='.html') - net.save_graph(path) - return path - - -# Initialize Streamlit session state -if 'queries' not in st.session_state: - st.session_state['queries'] = [] - st.session_state['responses'] = [] - st.session_state['graphs_html'] = [] - st.session_state['nodes_list'] = [] - st.session_state['adjacency_list_list'] = [] - st.session_state['history'] = [] - st.session_state['already_used_keys'] = list() - -# Set up page layout -st.set_page_config(layout='wide') -st.title('MindSearch-思索') - - -# Function to update chat -def update_chat(query): - with st.chat_message('user'): - st.write(query) - if query not in st.session_state['queries']: - # Mock data to simulate backend response - # response, history, nodes, adjacency_list - st.session_state['queries'].append(query) - st.session_state['responses'].append([]) - history = None - # 暂不支持多轮 - message = [dict(role='user', content=query)] - for resp in st.session_state['agent'].stream_chat(message): - if isinstance(resp, tuple): - agent_return, node_name = resp - if node_name in ['root', 'response']: - continue - else: - agent_return = resp - node_name = None - nodes = agent_return.nodes - adjacency_list = agent_return.adjacency_list - response = agent_return.response - history = agent_return.inner_steps - if nodes: - net = create_network_graph(nodes, adjacency_list) - graph_html_path = draw_graph(net) - with open(graph_html_path, encoding='utf-8') as f: - graph_html = f.read() - else: - graph_html = None - if 'graph_placeholder' not in st.session_state: - st.session_state['graph_placeholder'] = st.empty() - if 'expander_placeholder' not in st.session_state: - st.session_state['expander_placeholder'] = st.empty() - if graph_html: - with st.session_state['expander_placeholder'].expander( - 'Show Graph', expanded=False): - st.session_state['graph_placeholder']._html( - graph_html, height=500) - if 'container_placeholder' not in st.session_state: - st.session_state['container_placeholder'] = st.empty() - with st.session_state['container_placeholder'].container(): - if 'columns_placeholder' not in st.session_state: - st.session_state['columns_placeholder'] = st.empty() - col1, col2 = st.session_state['columns_placeholder'].columns( - [2, 1]) - with col1: - if 'planner_placeholder' not in st.session_state: - st.session_state['planner_placeholder'] = st.empty() - if 'session_info_temp' not in st.session_state: - st.session_state['session_info_temp'] = '' - if not node_name: - if agent_return.state in [ - AgentStatusCode.STREAM_ING, - AgentStatusCode.ANSWER_ING - ]: - st.session_state['session_info_temp'] = response - elif agent_return.state == AgentStatusCode.PLUGIN_START: - thought = st.session_state[ - 'session_info_temp'].split('```')[0] - if agent_return.response.startswith('```'): - st.session_state[ - 'session_info_temp'] = thought + '\n' + response - elif agent_return.state == AgentStatusCode.PLUGIN_RETURN: - assert agent_return.inner_steps[-1][ - 'role'] == 'environment' - st.session_state[ - 'session_info_temp'] += '\n' + agent_return.inner_steps[ - -1]['content'] - st.session_state['planner_placeholder'].markdown( - st.session_state['session_info_temp']) - if agent_return.state == AgentStatusCode.PLUGIN_RETURN: - st.session_state['responses'][-1].append( - st.session_state['session_info_temp']) - st.session_state['session_info_temp'] = '' - else: - st.session_state['planner_placeholder'].markdown( - st.session_state['responses'][-1][-1] if - not st.session_state['session_info_temp'] else st. - session_state['session_info_temp']) - with col2: - if 'selectbox_placeholder' not in st.session_state: - st.session_state['selectbox_placeholder'] = st.empty() - if 'searcher_placeholder' not in st.session_state: - st.session_state['searcher_placeholder'] = st.empty() - # st.session_state['searcher_placeholder'].markdown('') - if node_name: - selected_node_key = f"selected_node_{len(st.session_state['queries'])}_{node_name}" - if selected_node_key not in st.session_state: - st.session_state[selected_node_key] = node_name - if selected_node_key not in st.session_state[ - 'already_used_keys']: - selected_node = st.session_state[ - 'selectbox_placeholder'].selectbox( - 'Select a node:', - list(nodes.keys()), - key=f'key_{selected_node_key}', - index=list(nodes.keys()).index(node_name)) - st.session_state['already_used_keys'].append( - selected_node_key) - else: - selected_node = node_name - st.session_state[selected_node_key] = selected_node - if selected_node in nodes: - node = nodes[selected_node] - agent_return = node['detail'] - node_info_key = f'{selected_node}_info' - if 'node_info_temp' not in st.session_state: - st.session_state[ - 'node_info_temp'] = f'### {agent_return.content}' - if node_info_key not in st.session_state: - st.session_state[node_info_key] = [] - if agent_return.state in [ - AgentStatusCode.STREAM_ING, - AgentStatusCode.ANSWER_ING - ]: - st.session_state[ - 'node_info_temp'] = agent_return.response - elif agent_return.state == AgentStatusCode.PLUGIN_START: - thought = st.session_state[ - 'node_info_temp'].split('```')[0] - if agent_return.response.startswith('```'): - st.session_state[ - 'node_info_temp'] = thought + '\n' + agent_return.response - elif agent_return.state == AgentStatusCode.PLUGIN_END: - thought = st.session_state[ - 'node_info_temp'].split('```')[0] - if isinstance(agent_return.response, dict): - st.session_state[ - 'node_info_temp'] = thought + '\n' + f'```json\n{json.dumps(agent_return.response, ensure_ascii=False, indent=4)}\n```' - elif agent_return.state == AgentStatusCode.PLUGIN_RETURN: - assert agent_return.inner_steps[-1][ - 'role'] == 'environment' - st.session_state[node_info_key].append( - ('thought', - st.session_state['node_info_temp'])) - st.session_state[node_info_key].append( - ('observation', - agent_return.inner_steps[-1]['content'])) - st.session_state['searcher_placeholder'].markdown( - st.session_state['node_info_temp']) - if agent_return.state == AgentStatusCode.END: - st.session_state[node_info_key].append( - ('answer', - st.session_state['node_info_temp'])) - st.session_state['node_info_temp'] = '' - if st.session_state['session_info_temp']: - st.session_state['responses'][-1].append( - st.session_state['session_info_temp']) - st.session_state['session_info_temp'] = '' - # st.session_state['responses'][-1] = '\n'.join(st.session_state['responses'][-1]) - st.session_state['graphs_html'].append(graph_html) - st.session_state['nodes_list'].append(nodes) - st.session_state['adjacency_list_list'].append(adjacency_list) - st.session_state['history'] = history - - -def display_chat_history(): - for i, query in enumerate(st.session_state['queries'][-1:]): - # with st.chat_message('assistant'): - if st.session_state['graphs_html'][i]: - with st.session_state['expander_placeholder'].expander( - 'Show Graph', expanded=False): - st.session_state['graph_placeholder']._html( - st.session_state['graphs_html'][i], height=500) - with st.session_state['container_placeholder'].container(): - col1, col2 = st.session_state['columns_placeholder'].columns( - [2, 1]) - with col1: - st.session_state['planner_placeholder'].markdown( - st.session_state['responses'][-1][-1]) - with col2: - selected_node_key = st.session_state['already_used_keys'][ - -1] - st.session_state['selectbox_placeholder'] = st.empty() - selected_node = st.session_state[ - 'selectbox_placeholder'].selectbox( - 'Select a node:', - list(st.session_state['nodes_list'][i].keys()), - key=f'replay_key_{i}', - index=list(st.session_state['nodes_list'][i].keys( - )).index(st.session_state[selected_node_key])) - st.session_state[selected_node_key] = selected_node - if selected_node not in [ - 'root', 'response' - ] and selected_node in st.session_state['nodes_list'][i]: - node_info_key = f'{selected_node}_info' - for item in st.session_state[node_info_key]: - if item[0] in ['thought', 'answer']: - st.session_state[ - 'searcher_placeholder'] = st.empty() - st.session_state[ - 'searcher_placeholder'].markdown(item[1]) - elif item[0] == 'observation': - st.session_state[ - 'observation_expander'] = st.empty() - with st.session_state[ - 'observation_expander'].expander( - 'Results'): - st.write(item[1]) - # st.session_state['searcher_placeholder'].markdown(st.session_state[node_info_key]) - - -def clean_history(): - st.session_state['queries'] = [] - st.session_state['responses'] = [] - st.session_state['graphs_html'] = [] - st.session_state['nodes_list'] = [] - st.session_state['adjacency_list_list'] = [] - st.session_state['history'] = [] - st.session_state['already_used_keys'] = list() - for k in st.session_state: - if k.endswith('placeholder') or k.endswith('_info'): - del st.session_state[k] - - -# Initialize the agent -def init_agent(): - from datetime import datetime - - from lagent.actions import ActionExecutor, BingBrowser - from lagent.agents.mindsearch_agent import MindSearchAgent, MindSearchProtocol - # from lagent.agents.mindsearch_prompt import GRAPH_PROMPT_EN - # from lagent.agents.mindsearch_prompt import searcher_input_template_en - # from lagent.agents.mindsearch_prompt import searcher_system_prompt_en - from lagent.agents.mindsearch_prompt import (FINAL_RESPONSE_CN, - GRAPH_PROMPT_CN, - searcher_context_template_cn, - searcher_input_template_cn, - searcher_system_prompt_cn) - # from lagent.agents.mindsearch_prompt import GRAPH_PROMPT_EN, searcher_input_template_en, searcher_system_prompt_en, searcher_context_template_en, FINAL_RESPONSE_EN - from lagent.llms import INTERNLM2_META, LMDeployClient - - # from lagent.llms import GPTAPI - - llm = LMDeployClient( - model_name='internlm2-chat-7b', - url='http://22.8.69.5:23333', - meta_template=INTERNLM2_META, - max_new_tokens=4096, - top_p=0.8, - top_k=1, - temperature=0.8, - repetition_penalty=1.0, - stop_words=['<|im_end|>']) - - # api_key = 'Your API Key' - # gpt4_allen = dict( - # type=GPTAPI, - # model_type='gpt-4-turbo', - # key=api_key, - # query_per_second=50, - # max_new_tokens=4096, - # retry=1000) - # gpt4o_allen = dict( - # type=GPTAPI, - # model_type='gpt-4o', - # key=api_key, - # query_per_second=50, - # max_new_tokens=4096, - # retry=1000) - - # llm = gpt4_allen.pop('type')(**gpt4_allen) - # gpt4o_llm = gpt4o_allen.pop('type')(**gpt4o_allen) - # llm = gpt4o_llm - agent = MindSearchAgent( - llm=llm, - searcher_cfg=dict( - llm=llm, - plugin_executor=ActionExecutor(BingBrowser('YOUR BING API KEY')), - protocol=MindSearchProtocol( - meta_prompt=datetime.now().strftime( - 'The current date is %Y-%m-%d.'), - plugin_prompt=searcher_system_prompt_cn, - ), - template=dict( - input=searcher_input_template_cn, - context=searcher_context_template_cn)), - protocol=MindSearchProtocol( - meta_prompt=datetime.now().strftime( - 'The current date is %Y-%m-%d.'), - interpreter_prompt=GRAPH_PROMPT_CN, - response_prompt=FINAL_RESPONSE_CN), - max_turn=10) - return agent - - -# Main function to run the Streamlit app -def main(): - st.sidebar.title('Model Control') - if 'agent' not in st.session_state: - st.session_state['agent'] = init_agent() - - col1, col2 = st.columns([4, 1]) - with col1: - user_input = st.chat_input('Enter your query:') - with col2: - if st.button('Clear History'): - clean_history() - if user_input: - update_chat(user_input) - display_chat_history() - - -if __name__ == '__main__': - main() diff --git a/frontend/.gitignore b/frontend/.gitignore deleted file mode 100644 index 02ff3d24..00000000 --- a/frontend/.gitignore +++ /dev/null @@ -1,20 +0,0 @@ - -# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. - -# dependencies -/node_modules -/.pnp -.pnp.js - -# testing -/coverage - -# production -/build - -# misc -.DS_Store - -npm-debug.log* -yarn-debug.log* -yarn-error.log* \ No newline at end of file diff --git a/frontend/.prettierignore b/frontend/.prettierignore deleted file mode 100644 index 040a2498..00000000 --- a/frontend/.prettierignore +++ /dev/null @@ -1,7 +0,0 @@ -dist -deploy -values -node_modules -.gitignore -.prettierignore -.husky \ No newline at end of file diff --git a/frontend/.prettierrc.json b/frontend/.prettierrc.json deleted file mode 100644 index e5289f30..00000000 --- a/frontend/.prettierrc.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "printWidth": 120, - "tabWidth": 4, - "singleQuote": true, - "quoteProps": "as-needed", - "bracketSpacing": true -} diff --git a/frontend/README.md b/frontend/README.md deleted file mode 100644 index 4f3c10cd..00000000 --- a/frontend/README.md +++ /dev/null @@ -1,14 +0,0 @@ -## 开始 -### 准备node.js开发环境 -如需安装环境,可参照:https://nodejs.org/zh-cn/download/package-manager -如有,跳转下一步 - -### 安装依赖 -npm install - -### 启动 -npm start - -### 知悉 -- 前端服务基于react开发,如需了解react相关知识,可参考:https://react.dev/ -- 如果需要接入后端服务地址,请至src/config/cgi.ts中修改请求链接 \ No newline at end of file diff --git a/frontend/index.html b/frontend/index.html deleted file mode 100644 index d4f0b7cb..00000000 --- a/frontend/index.html +++ /dev/null @@ -1,14 +0,0 @@ - - - - - - - - - - -
- - - diff --git a/frontend/package-lock.json b/frontend/package-lock.json deleted file mode 100644 index e4d0928e..00000000 --- a/frontend/package-lock.json +++ /dev/null @@ -1,9973 +0,0 @@ -{ - "name": "test-react-flow", - "version": "0.0.0", - "lockfileVersion": 3, - "requires": true, - "packages": { - "": { - "name": "test-react-flow", - "version": "0.0.0", - "dependencies": { - "@antv/x6": "^2.18.1", - "@microsoft/fetch-event-source": "^2.0.1", - "antd": "^5.18.3", - "axios": "^1.3.5", - "classnames": "^2.5.1", - "elkjs": "^0.9.3", - "js-cookie": "^3.0.1", - "react-markdown": "^9.0.1", - "react-router": "^6.11.2", - "react-router-dom": "^6.11.2", - "reactflow": "^11.11.3", - "rehype-raw": "^7.0.0" - }, - "devDependencies": { - "@babel/plugin-proposal-optional-chaining": "^7.21.0", - "@types/classnames": "^2.3.1", - "@types/js-cookie": "^3.0.3", - "@types/node": "^18.15.11", - "@types/react": "^18.0.28", - "@types/react-dom": "^18.0.11", - "@vitejs/plugin-legacy": "^4.0.2", - "@vitejs/plugin-react": "^3.1.0", - 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"vite": "^4.2.1", - "vite-babel-plugin": "^0.0.2" - }, - "dependencies": { - "@antv/x6": "^2.18.1", - "@microsoft/fetch-event-source": "^2.0.1", - "antd": "^5.18.3", - "axios": "^1.3.5", - "classnames": "^2.5.1", - "elkjs": "^0.9.3", - "js-cookie": "^3.0.1", - "react-markdown": "^9.0.1", - "react-router": "^6.11.2", - "react-router-dom": "^6.11.2", - "reactflow": "^11.11.3", - "rehype-raw": "^7.0.0" - }, - "lint-staged": { - "**/*.{ts, tsx, less, module.less, json, md, .html}": "prettier --write ." - } -} \ No newline at end of file diff --git a/frontend/src/App.module.less b/frontend/src/App.module.less deleted file mode 100644 index 6fcb0cca..00000000 --- a/frontend/src/App.module.less +++ /dev/null @@ -1,54 +0,0 @@ -.app { - height: 100%; - display: flex; - justify-content: space-between; - background: url(./assets/background.png) rgb(247, 248, 255); - background-size: cover; - overflow: hidden; -} - -.content { - padding-top: 64px; - width: 100%; - height: 100%; - box-sizing: border-box; - // display: flex; - // justify-content: center; -} - -.header { - position: fixed; - padding: 16px 32px; - width: 100%; - display: flex; - align-items: center; - box-sizing: border-box; - - &-nav { - flex: 1; - - img { - height: 40px; - } - - a { - display: inline-block; - text-decoration: none; - color: black; - - &:not(:first-of-type) { - margin-left: 40px; - } - - &.active { - font-weight: bold; - } - } - } - - &-opt { - flex-shrink: 0; - display: flex; - align-items: center; - } -} \ No newline at end of file diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx deleted file mode 100644 index 62cc6d4f..00000000 --- a/frontend/src/App.tsx +++ /dev/null @@ -1,23 +0,0 @@ -import style from "./App.module.less"; -import Logo from "@/assets/logo.svg"; -import { BrowserRouter } from "react-router-dom"; -import RouterRoutes from "@/routes/routes"; - -function App() { - return ( - -
-
-
- -
-
-
- -
-
-
- ); -} - -export default App; diff --git a/frontend/src/assets/background.png b/frontend/src/assets/background.png deleted file mode 100644 index 3c732cb6bbf084415e5cc309934a144e9bc6b5eb..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 36899 zcmX6_2{@G78~-fXca>daiOQ}p7+Vdp(@i9lWXMvMY%>fdx@9Y}WEmQ3g=mmM(k-%$ zWwNh{v6FrGKVSdnx%auxowL2?U4HL!-p{|5=7#Jnf-DdOu^Ss*vWB2zIS@pLXJP=q z*qWtuga0t!H?s4CAXZ-ZUmECTCO`O*#?RVNA1dt-o(2Cy@1|#_2SMcttoyf)K~Ta6 z<4by1gJ>2;W>YfMzsg(AY>XalWQS*#Jy*|_VPKY2U97tn_}VkJT#`Zi+P^zT2cKQj zA!sJ$XBgt#Yv<=`_T2!oq^ADzqROQ+iiyI#||YfU`k)MZlZ?{GvLXVxMxfR z0ymP{GhZH*p6Mo*+PkID#L!FM2|*$}EXldV>+ze1u`3#c?5}QOI(_~DR(xAbIW!RD zXnC*jpY2SG1ieR!Y%S;qpZ(sBPlki*-F#5)6rK1s_FC1=ZH&bmubv_|v6u~He~WOd z)6nodrW4PrO9%PuD>jHUQup!XEhfVJ#6IoD&O&PA$QJX@$@EA%D2J{wq9XZdFL_6$ zk*b9!Hw+EqQcuDMJ6r14?|TeioA48Dbjvv|u38Cir`mB$JCJE-l^5C6BR@Zmis}^I zJAdKth^ZSN~rNxYi1`?b)U9S}}5Nba({j#c$aF^QC^Ppej zm{_I|_jhi1QQU!9%$EXyh-f%lJ z;Tbva+H3RpQQOD8d|%K<_HSHhR3Y7Ocm~%EUt)O*6JZ$$RsthkDL8+p&MeYI>;gQV z55}1Z8WNaz35@(#r5yPZN{pgl&}|?8DwtAz{iurMZ~?h!6$f7AXA7Yc69q40{*jYC z_bqwh<*xLMt{c{e1*6Txs>Qc;!+7$tA4jpFPk?xAG=cu$7EI;|ZsEkp6%EcF@Bg@w zpIdi`q7sxxo$QbQjL}27C-96@#dJmnkN4!8N)hLKt_S3f{In3+D9PWwKnn<LX(4oBWD7!FRCjFj@#UapgXVpOjri3!dldUEpRR_-zj{ZW4D;_r)bUJL%{@IFFAetqi8{?j0rfNBIIIKux#1kr6k9= z{sR^X-rwK&@^)tGibiI!TDMIKX4mHm3Y zJdo{E`Y=70gfJ_dt~d_NwDSaww?HE`wCx}>dL`JD_J>mOmRqujR2smMacRDl4es%j zTTUMgYw~l2n}{7dx5Lor7$Bx`hAgM;_U4|@SbmGI592RuR2XuxZ@`#wshdVxN&>dk zEt7364p$>4JylApFwksn|H%1#@6n%)Opd@%tDf1X&8KRTGVWErNZ6etaDy2U4#ItJ zetzsKSmn~%YH#P>D;y4LkwF(dg-?u(SJX%gaS^8N@lSRgOBN``R7#1jE4h9hg3U&? zg9B95eiV zd-W$Y5^Y0mv!xe^oas~P(k zlW=f4-s;<=b-|Ggt5~uETX#{3aP^P`I5*8d<;H1Dn8o6d&sAM2a|)o;S@T$!>;Wr@IZz2HI`RO9Qg9>tEwz?oeBuZME7TNF3GSDqXy zQ1Dw)8B>AsVAkcZG$ttH$ygrbn3`vX%BAPg?)8>xen1^Zc%6Tm9VAO&I9x`l>v%Gx z$RUwKgDYj`btYgXVtubzY&#G>6GjxRA!RNw-!e8hpjA=7$_Z6DMy#W`pSrwM3Om)A z6y03MxoDMw(GP~(n1so$Xvs(4(G`|D@NV+V$LI3BTdWUn;mPjIg!z2793R>c57<0E z5>?FP2d@Fx$X?kI^T9DhAMvkMCclw+r#2DS^~Kfsu6XU2DtH*8KqwZ=e^RgI}N-g7ZrgT}%W zYuG_SDEaSvS$+KO#&tuvaOu6a3tzki!N9vF08lvsjd8oh#E)qqM9xO48>w!pB^FsKr#D0 zr$IRW_2PUnM`hD}aAnAwcZE{ei{M7a@FMBnBY1Lv@&;;;{u4CD zyz@&&!9xm&>hDnr@p$w;>R%lf%?LFCIU&Q~I+NgK&2xNe;`GoHUVchR-)`5^ zs#VpkWL`*utN%7kOfpp9-AD})=o0F3`Re0#pA zd*io(?(M$HEXq=RG3ZX*Vg_1lJF{J-x9w0kSnafpX;(^oPSTmNV7*n;@Q_V><2+zR zMfa>%3}D4(ZcrnY8XE>UScI#)U2znYurdxVkQuJHgRgq)_Zr>Rc@ewDYBXN zUrkM!`>NHN{HiqK*-z1EmV0X+l^8fw%sGe3wtjh$>AsnzfW@|{+3mR-K&cgrM88VY z3~I)P6&w!`G32K|c&C$^JKO^sw(c!px)x&T(Z2Mfl9Z=C`oSC53oEe&DXrJRN?ksB z^p5Q0y%w2MuB=!tIL_>$0}M^fOoSQ-oR(}J-ZxXEU*tiqb?u@({|>NPjZPQ%?0|5~ zsf8!#>Ag$#xg`a##ysb}ODQWvbdRpue7}`!gKRlDc&2kc0f9B-oPyc-oQFr3f3F4G zA}``PpcBC6^;+A1K?8I0E#Z?55-7HqET3ns@w?}QVzox}Q%Xy4x*$3RNU;u%tBsj& z1(~#ZmAvq(*4Z-C6pm43HTt16rCpa?2~@)fWd!x%!y1Mb$jOp#V_oLrDoA~PfvvFX z(yB5=RM(n>wzjJBJ+Svo*vu_wx{5n4Y%==OCKz}_oFSgSww)prJWyEt?(_k$VTtUjy<=tbI;R!~yszbO_{=3D`iq%$?cXzUT2lFTQKEMmFZ@MIZq}*NO0Sm`wayHEl z>MhcBi2L93MtgWmSE7TvdvD7sRE2o*7K}qsPDn|#Rf%U{$&f6b9v#KCA!_48(c7!r zB*nsBH;QXo&%R&`LY?{W$ztGVZdJ%kq+=NS4t- z!Cqq~Q!%C&{T|xjeu?a}7KpbT8}v^*J|zhcU7y#>?ji^O{E#J=eDmp|brI*VRGx`} zMsNQ2-In>RGf*5k<0&oWqLb7@C$wl9UF0$@2KEYj< zyvu(eEdTQ%Y$=Ftn@-6Yp{Es-Pai_A%qBe^AQnR)RpnHx=Yg?(zLV(xVjV3IkP z^=sDc<$D~5q8^4>wD`gySvYgSVD~+2N@%oZn}V?!osP<_Fr8EFRZIo@L$u;)&4K|Gu8=UPo!i z7Pp!M)!LVO2aP(f`#Hu>HHhAF2&qeUPw*l>BCB>IWx?XZZlz*^bFnB2XzT!u_Jg?8 z?3EhF!B8wLxwsi^u6wgzBARC{@YwQB}-(~qe(3%rfrv_fS19EVWn2>1TO z+Q9bBO}<`1^FeG_DV&Ak`j}g~-_)4Kg+=dT9*MP*PDS_gWw)MC&N|i|32&9B>?;B*+}U0i zCg*s2kG!x}tIg$fg|IPXsrOQ_${n7w(^43316G31I`$txl4bEI;xIB6lPs4QC5Fh> zO&dff;adi-!Av>9gY3J!?d!zq+GlX!LHtePkRnyOMAp}Tm~a+~4fBoy6hVU0Y_y}2 zv7=|4=S=1|G_HgmM^+oa8w(H#^QWC_KxA7gb5tdA>|E|f$U}+$KFy!kYoKrvvyF@M zKQ`Buz&^BsTYl;vza19B*yQ(YinMey)6IvU9OM=a`};U2{BC$0y^UudgZ1`ow~d&D z!>hZ4XGkTzx`J1@k$!zbQ#&9jefKM}R5**e%YO@#P}O$A3s0GzJ-El;XNr~SdT0$C z;J5OLGjNpTgQs;(+p0m*j)uv8u1MC=sJozS-#}sf0!Od2b(M86=#R}<(pWI@jpf%) zIK0+3AzJRt!hyq!pp9Oz*DcEGBv(MCcEji{ahn`YiAg8 zIWk#ZRE7cR_-TxE%F2$w;(K9N3-`4j%eH#4D{oFUQa4Gf!6Iim;G3~@e=GQ> zWBnXKVyGsNX0+SH`JM-(wd_C&kYR%YE$zEgx*YoGaWm~>Rm5mAN~h2^z|&~`v=Ms!=RL`?zN$R-q)rl-VDsgb zVa8l<`wL!$K>7@lkc>eM9g$a`PBz_}cuIeS}X8URbp_@>+@PWi zA@)sBVlj^!s;)MJv0E(dzG_)Yi|q{=VzsZ@3C4GYO*z-L-?E{kaSXVQ+5Xi0edhd< zyh2kN08_fML0<3KV#DGCNoIhgnY5Kh$szYFE?`CX&O*dF?aUKMR)XP!Yj5-$&8G4(G&2$7OKKA; 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/dev/null @@ -1,7 +0,0 @@ -import { createFromIconfontCN } from "@ant-design/icons"; - -const IconFont = createFromIconfontCN({ - scriptUrl: "//at.alicdn.com/t/c/font_3858115_p8dw9q83s0h.js" -}); - -export default IconFont; diff --git a/frontend/src/config/cgi.ts b/frontend/src/config/cgi.ts deleted file mode 100644 index fe7ba7f1..00000000 --- a/frontend/src/config/cgi.ts +++ /dev/null @@ -1,2 +0,0 @@ -export const mode = import.meta.env.MODE; -export const GET_SSE_DATA = '/solve'; diff --git a/frontend/src/global.d.ts b/frontend/src/global.d.ts deleted file mode 100644 index 8bb1c804..00000000 --- a/frontend/src/global.d.ts +++ /dev/null @@ -1 +0,0 @@ -declare module 'event-source-polyfill'; \ No newline at end of file diff --git a/frontend/src/index.less b/frontend/src/index.less deleted file mode 100644 index f48ba612..00000000 --- a/frontend/src/index.less +++ /dev/null @@ -1,62 +0,0 @@ -body, -html, -#root { - padding: 0; - margin: 0; - width: 100%; - height: 100%; - font-family: "PingFang SC"; - font-size: 14px; - line-height: 21px; -} - -#global__message-container { - position: fixed; - left: 0; - right: 0; - top: 72px; - z-index: 999; - display: flex; - flex-direction: column; - justify-content: center; - align-items: center; -} - -.f { - color: #6674D6; - font-family: DIN; - font-size: 12px; - font-style: normal; - font-weight: 500; - line-height: 14px; - position: relative; - top: -4px; - padding: 0 3px; - - &::after { - content: '·'; - position: absolute; - top: 0; - right: -2px; - color: #6674D6; - } -} - -p> :nth-last-child(1).f, -li> :nth-last-child(1).f { - &::after { - content: ''; - opacity: 0; - } -} - -.fnn2 { - color: #6674D6; - font-family: DIN; - font-size: 14px; - font-style: normal; - font-weight: 500; - line-height: 14px; - position: relative; - top: -2px; -} \ No newline at end of file diff --git a/frontend/src/index.tsx b/frontend/src/index.tsx deleted file mode 100644 index d73ff23c..00000000 --- a/frontend/src/index.tsx +++ /dev/null @@ -1,10 +0,0 @@ -import React from "react"; -import ReactDOM from "react-dom/client"; -import "./index.less"; -import App from "./App"; - -ReactDOM.createRoot(document.getElementById("root") as HTMLElement).render( - - - , -); diff --git a/frontend/src/pages/render/index.module.less b/frontend/src/pages/render/index.module.less deleted file mode 100644 index 8e413310..00000000 --- a/frontend/src/pages/render/index.module.less +++ /dev/null @@ -1,848 +0,0 @@ -// inspired by https://www.youtube.com/watch?v=Pl1Gw14pS2I -.mainPage { - display: flex; - justify-content: flex-start; - align-items: flex-start; - padding: 0 60px 60px; - height: 100%; - overflow: hidden; - position: relative; - min-width: 1280px; - max-width: 1920px; - margin: 0 auto; - - .chatContent { - position: relative; - display: flex; - justify-content: flex-start; - flex-direction: column; - flex-grow: 1; - margin-right: 40px; - height: calc(100% - 60px); - overflow-y: hidden; - padding: 32px 0; - box-sizing: border-box; - - .top { - height: calc(100% - 110px); - overflow-y: auto; - margin-bottom: 40px; - } - - .top::-webkit-scrollbar { - width: 6px; - } - - .top::-webkit-scrollbar-track { - background-color: rgba(255, 255, 255, 0); - border-radius: 100px; - } - - .top::-webkit-scrollbar-thumb { - background-color: rgba(255, 255, 255, 0); - border-radius: 100px; - } - - .question { - display: flex; - justify-content: flex-end; - margin-bottom: 40px; - - span { - padding: 12px 20px; - color: #121316; - font-size: 14px; - line-height: 24px; - border-radius: 8px; - background: #FFF; - max-width: 93.75%; - } - } - - .end { - position: absolute; - right: 0; - background-color: #fff; - display: flex; - justify-content: center; - align-items: center; - border-left: 1px solid #D7D8DD; - padding-left: 16px; - - .node { - position: relative; - - &::before { - content: ""; - border: 1px solid #D7D8DD; - border-top: none; - border-left: none; - width: calc(16px - 2px); - height: 0px; - position: absolute; - left: -16px; - top: 50%; - // transform: translateY(-50%); - } - - article { - padding: 8px 16px; - border-radius: 8px; - border: 1px solid transparent; - color: #4082FE; - text-align: center; - font-size: 14px; - line-height: 24px; - box-sizing: border-box; - background: rgba(232, 233, 249); - color: #2126C0; - } - } - } - - .answer { - border-radius: 8px; - background: rgba(33, 38, 192, 0.10); - padding: 12px; - - .inner { - width: 100%; - background-color: #fff; - border-radius: 4px; - padding: 8px; - box-sizing: border-box; - transition: all 0.5s ease; - margin-bottom: 18px; - - .mapArea { - width: 100%; - overflow-x: auto; - overflow-y: hidden; - - &::-webkit-scrollbar { - height: 6px; - } - - &::-webkit-scrollbar-track { - background-color: rgba(255, 255, 255, 0); - border-radius: 10px; - } - - &::-webkit-scrollbar-thumb { - background-color: #d7d8dd; - border-radius: 100px; - } - } - - } - - - .response { - color: #121316; - font-size: 14px; - line-height: 24px; - padding: 18px 42px; - - h3 { - font-size: 24px; - font-weight: 600; - line-height: 36px; - margin: 0 0 16px 0; - } - - h4 { - font-size: 20px; - font-weight: 600; - line-height: 30px; - margin: 0 0 8px 0; - } - - p { - color: rgba(18, 19, 22, 0.80); - font-size: 16px; - font-weight: 400; - line-height: 28px; - margin: 0 0 16px 0; - } - - ul { - margin-bottom: 8px; - padding-left: 22px; - } - - li { - color: rgba(18, 19, 22, 0.80); - font-size: 16px; - font-weight: 400; - line-height: 28px; - - p { - margin-bottom: 4px; - } - } - } - } - - .sendArea { - display: flex; - width: 100%; - box-sizing: border-box; - padding: 10px 12px 10px 24px; - justify-content: space-between; - align-items: center; - border-radius: 8px; - border: 2px solid var(--fill-5, #464A53); - background: #FFF; - position: relative; - - :global { - .ant-input { - &:focus { - box-shadow: none !important; - outline: 0 !important; - } - } - } - - input { - height: 36px; - line-height: 36px; - flex-grow: 1; - border: 0; - outline: 0; - - &:focus { - border: 0; - outline: 0; - } - } - - button { - display: flex; - justify-content: flex-start; - align-items: center; - border: 0; - background-color: #fff; - cursor: pointer; - padding: 8px; - width: 65px; - flex-shrink: 0; - - img { - margin-right: 4px; - } - } - } - - .notice { - color: #12131659; - padding-top: 8px; - text-align: center; - font-weight: 400; - - a { - text-decoration: none; - color: #444; - display: inline-flex; - align-items: center; - - span { - font-size: 18px; - } - } - } - } - - .progressContent { - width: 44.44%; - flex-shrink: 0; - box-sizing: border-box; - padding: 24px; - border-radius: 8px; - border: rgba(33, 38, 192, 0.10); - background: rgba(255, 255, 255, 0.80); - height: calc(100% - 60px); - overflow-y: auto; - position: relative; - - &::-webkit-scrollbar { - width: 6px; - } - - &::-webkit-scrollbar-track { - background-color: rgba(255, 255, 255, 0); - border-radius: 100px; - } - - &::-webkit-scrollbar-thumb { - background-color: rgba(255, 255, 255, 0); - border-radius: 100px; - } - - .toggleIcon { - position: absolute; - right: 24px; - top: 28px; - cursor: pointer; - } - - .titleNode { - color: #121316; - font-size: 24px; - font-weight: 600; - line-height: 36px; - margin-bottom: 24px; - } - - .conclusion { - padding-top: 8px; - color: #121316; - font-size: 14px; - line-height: 24px; - - ul { - padding-left: 24px; - } - } - - .steps { - .title { - color: var(--100-text-5, #121316); - font-size: 20px; - font-weight: 600; - line-height: 30px; - display: flex; - justify-content: flex-start; - align-items: center; - position: relative; - - .open { - position: absolute; - right: 0; - font-size: 20px; - font-weight: normal; - - span { - color: #121316; - opacity: 0.6; - } - } - - i { - width: 12px; - height: 12px; - border-radius: 50%; - background-color: #2126C0; - margin-right: 8px; - } - } - - &.thinking, - &.select { - margin-bottom: 24px; - } - - &.select { - .searchList { - margin-top: 0 !important; - border-radius: 8px; - background: var(--fill-2, #F4F5F9); - padding: 8px; - } - } - - .con { - margin-left: 5px; - padding-top: 8px; - padding-left: 15px; - border-left: 1px solid rgba(33, 38, 192, 0.20); - height: auto; - - &.collapsed { - overflow: hidden; - height: 0; - padding-top: 0; - transition: all 1s; - } - - .subTitle { - color: var(--100-text-5, #121316); - font-size: 14px; - font-weight: 600; - line-height: 24px; - margin-bottom: 4px; - - span { - margin-right: 4px; - } - } - - .query, - >.searchList { - margin-top: 24px; - // margin-bottom: 24px; - } - - .query { - &-Item { - display: inline-flex; - padding: 4px 8px; - margin-right: 4px; - margin-bottom: 4px; - border-radius: 4px; - border: 1px solid #EBECF0; - color: rgba(18, 19, 22, 0.80); - font-size: 14px; - line-height: 24px; - height: 32px; - box-sizing: border-box; - overflow: hidden; - // animation: fadeIn linear 2s; - } - } - - .searchList { - .thought { - color: rgba(18, 19, 22, 0.80); - font-size: 14px; - line-height: 24px; - margin-bottom: 16px; - } - - .scrollCon { - padding-right: 6px; - max-height: 300px; - overflow-y: auto; - position: relative; - } - - .scrollCon::-webkit-scrollbar { - width: 6px; - } - - .scrollCon::-webkit-scrollbar-track { - background-color: rgba(255, 255, 255, 0); - border-radius: 100px; - } - - .scrollCon::-webkit-scrollbar-thumb { - background-color: #d7d8dd; - border-radius: 100px; - } - - .inner { - width: 100%; - border-radius: 8px; - background: var(--fill-2, #F4F5F9); - transition: all 0.5s ease; - box-sizing: border-box; - padding: 8px; - } - - .searchItem { - border-radius: 8px; - background: var(---fill-0, #FFF); - margin-bottom: 6px; - padding: 4px 8px; - transition: all 0.5s ease-in-out; - - &.highLight { - border: 1px solid var(---Success-6, #00B365); - background: linear-gradient(0deg, rgba(218, 242, 228, 0.40) 0%, rgba(218, 242, 228, 0.40) 100%), #FFF; - } - - p { - white-space: nowrap; - max-width: 95%; - overflow: hidden; - text-overflow: ellipsis; - margin: 0; - } - - p.summ { - color: rgba(18, 19, 22, 0.80); - font-size: 13px; - line-height: 20px; - margin-bottom: 2px; - } - - p.url { - color: var(--60-text-3, rgba(18, 19, 22, 0.60)); - font-size: 12px; - line-height: 18px; - padding-left: 20px; - } - } - } - - - } - } - } -} - -pre { - margin: 0; - padding-top: 8px; - color: #121316; - font-size: 14px; - line-height: 24px; - font-family: 'PingFang SC', 'Franklin Gothic Medium', 'Arial Narrow', Arial, sans-serif; - white-space: wrap; -} - -ul { - margin: 0; - padding: 0; -} - -.draft { - width: 100%; - white-space: wrap; - // display: flex; - // justify-content: flex-start; - // align-items: flex-start; - position: relative; - - .loading, - .loading>div { - position: relative; - box-sizing: border-box; - } - - .loading { - display: flex; - justify-content: center; - align-items: center; - font-size: 0; - color: #fff; - background-color: #f90; - width: 20px; - height: 20px; - border-radius: 50%; - margin-right: 3px; - flex-shrink: 0; - position: absolute; - top: 0; - left: 0; - } - - .loading>div { - display: inline-block; - float: none; - background-color: currentColor; - border: 0 solid currentColor; - } - - .loading>div:nth-child(1) { - animation-delay: -200ms; - } - - .loading>div:nth-child(2) { - animation-delay: -100ms; - } - - .loading>div:nth-child(3) { - animation-delay: 0ms; - } - - .loading>div { - width: 3px; - height: 3px; - margin: 2px 1px; - border-radius: 100%; - animation: ball-pulse 1s ease infinite; - } -} - -.mindmap { - position: relative; - - article { - padding: 6px 16px; - border-radius: 8px; - height: 38px; - border: 1px solid transparent; - background: #FFF; - color: #121316; - text-align: center; - font-size: 14px; - line-height: 24px; - position: relative; - box-sizing: border-box; - - &.loading { - line-height: 20px; - border-radius: 8px; - overflow: hidden; - border: 1px solid transparent; - padding: 4px; - - span { - color: #2126C0; - background-color: #fff; - border-radius: 4px; - line-height: 24px; - padding: 2px 12px; - } - - .looping { - --border-width: 4px; - --follow-panel-linear-border: linear-gradient(91deg, - #5551FF 0.58%, - #FF87DE 100.36%); - - position: absolute; - top: 0; - left: 0; - width: calc(100% + var(--border-width) * 2 - 8px); - height: calc(100%); - background: var(--follow-panel-linear-border); - background-size: 300% 300%; - background-position: 0 50%; - animation: moveGradient 4s alternate infinite; - } - } - - &.disabled { - border-radius: 8px; - border: 1px solid #D7D8DD; - color: rgba(18, 19, 22, 0.35); - } - - &.finished { - // cursor: pointer; - border: 1px solid #2126C0; - - .finishDot { - position: absolute; - top: 6px; - right: 6px; - width: 6px; - height: 6px; - background-color: #C9C0FE; - border-radius: 50%; - } - } - - &.init { - border: 1px solid transparent; - cursor: auto; - } - - span { - display: block; - white-space: nowrap; - max-width: 160px; - overflow: hidden; - text-overflow: ellipsis; - position: relative; - z-index: 20; - } - - span.status { - color: #4082FE; - } - - } - - // 第一个article,起始节点 - >li { - >article { - border-radius: 8px; - background: rgba(33, 38, 192, 0.10); - color: #2126C0; - } - } - - li { - list-style: none; - display: flex; - align-items: center; - box-sizing: border-box; - margin: 16px; - line-height: 1; - position: relative; - - &>ul.onlyone { - &:before { - opacity: 0; - } - - >li { - margin-left: 0px; - } - - &>li:after { - opacity: 0; - } - - &>li:before { - // left: 0; - } - } - - &>ul:before { - content: ""; - border: 1px solid #D7D8DD; - border-top: none; - border-left: none; - width: calc(16px - 2px); - height: 0px; - position: absolute; - left: 0; - top: 50%; - // transform: translateY(-50%); - } - - &:before { - content: ""; - border: 1px solid #D7D8DD; - border-top: none; - border-left: none; - width: 16px; - height: 0px; - position: absolute; - left: calc(-16px - 1px); - } - - &:after { - content: ""; - border: 1px solid #D7D8DD; - border-top: none; - border-left: none; - width: 0px; - height: calc(100% / 2 + 33px); - position: absolute; - left: calc(-16px - 2px); - } - - &:first-of-type:after { - top: 50%; - } - - &:last-of-type:after { - bottom: 50%; - } - - ul { - padding: 0 0 0 16px; - position: relative; - } - } - - &>li { - - &:after, - &:before { - display: none; - } - } - - .endLine { - border-bottom: 1px solid #D7D8DD; - width: 3000px; - transition: width 1s ease-in-out; - } -} - -.showRight { - position: fixed; - top: 80px; - right: -10px; - width: 42px; - cursor: pointer; - - img { - width: 100%; - } -} - -@keyframes ball-pulse { - - 0%, - 60%, - 100% { - opacity: 1; - transform: scale(1); - } - - 30% { - opacity: 0.1; - transform: scale(0.01); - } -} - -@keyframes moveGradient { - 50% { - background-position: 100% 50%; - } -} - -@keyframes fadeIn { - 0% { - width: 0; - opacity: 0; - } - - 100% { - width: auto; - opacity: 1; - } -} - -@keyframes unfold { - 0% { - height: auto; - } - - 100% { - height: 0; - } -} - - -.loading99 { - margin: 20px; - position: relative; - width: 1px; - height: 1px; -} - -.loading99:before, -.loading99:after { - position: absolute; - display: inline-block; - width: 15px; - height: 15px; - content: ""; - border-radius: 100%; - background-color: #5551FF; -} - -.loading99:before { - left: -15px; - animation: ball-pulse infinite 0.75s -0.4s cubic-bezier(0.2, 0.68, 0.18, 1.08); -} - -.loading99:after { - right: -15px; - animation: ball-pulse infinite 0.75s cubic-bezier(0.2, 0.68, 0.18, 1.08); -} - -@keyframes ball-pulse { - 0% { - transform: scale(1); - opacity: 1; - } - - 50% { - transform: scale(0.1); - opacity: 0.6; - } - - 100% { - transform: scale(1); - opacity: 1; - } -} \ No newline at end of file diff --git a/frontend/src/pages/render/index.tsx b/frontend/src/pages/render/index.tsx deleted file mode 100644 index 0c881ea3..00000000 --- a/frontend/src/pages/render/index.tsx +++ /dev/null @@ -1,681 +0,0 @@ -import styles from './index.module.less'; -import { useEffect, useState, useRef, Children } from 'react'; -import MindMapItem from './mindMapItem'; -import PackIcon from '@/assets/pack-up.svg'; -import SendIcon from '@/assets/sendIcon.svg'; -import { Tooltip, Input, message } from 'antd'; -import IconFont from '@/components/iconfont'; -import ReactMarkdown from "react-markdown"; -import ShowRightIcon from "@/assets/show-right-icon.png"; -import rehypeRaw from 'rehype-raw'; -import classNames from 'classnames'; -import { fetchEventSource } from '@microsoft/fetch-event-source'; -import { GET_SSE_DATA } from '@/config/cgi'; -import { replaceStr } from '@/utils/tools'; - -const RenderTest = () => { - let eventSource: any = null; - let sseTimer: any = useRef(null); - const [isWaiting, setIsWaiting] = useState(false); - const [question, setQuestion] = useState(""); - const [stashQuestion, setStashQuestion] = useState(""); - const [isEnd, setIsEnd] = useState(false); - const [showEndNode, setShowEndNode] = useState(false); - // 一组节点的渲染草稿 - const [draft, setDraft] = useState(''); - // 一轮完整对话结束 - const [chatIsOver, setChatIsOver] = useState(true); - // 一组节点的思考草稿是不是打印结束 - const [draftEnd, setDraftEnd] = useState(false); - - const [progress1, setProgress1] = useState(''); - const [progress2, setProgress2] = useState(''); - const [progressEnd, setProgressEnd] = useState(false); - - const [conclusion, setConclusion] = useState(''); - const [stashConclusion, setstashConclusion] = useState(''); - - const [query, setQuery] = useState([]); - const [searchList, setSearchList] = useState([]); - // 整体的渲染树 - const [renderData, setRenderData] = useState([]); - const [currentNode, setCurrentNode] = useState(null); - // 渲染minddata里的第几个item - const [renderIndex, setRenderIndex] = useState(0); - const [response, setResponse] = useState(""); - const [currentStep, setCurrentStep] = useState(0); - // steps展开收起的信息 - const [collapseInfo, setCollapseInfo] = useState([true, true]); - const [mapWidth, setMapWidth] = useState(0); - // 是否展示右侧内容 - const [showRight, setShowRight] = useState(true); - - const [currentNodeRendering, setCurrentNodeRendering] = useState(false); - const [selectedIds, setSelectedIds] = useState([]); - const [nodeName, setNodeName] = useState(''); - const hasHighlight = useRef(false); - const conclusionRender = useRef(false); - const nodeDraftRender = useRef(false); - const [obj, setObj] = useState(null); - const [nodeOutputEnd, setNodeEnd] = useState(false); - const [adjList, setAdjList] = useState([]); - - const TEXT_INTERVAL = 20; - const SEARCHLIST_INTERVAL = 80; - - - const toggleRight = () => { - setShowRight(!showRight); - }; - - const findAndUpdateStatus = (nodes: any[], targetNode: any) => { - return nodes.map((node) => { - if (node.state === 1 && node.id !== 0) { - return { ...node, state: 3 }; - } - - if (node.name === targetNode) { - return { ...node, state: 1 }; - } - - if (node.children) { - // 递归地在子节点中查找 - node.children = findAndUpdateStatus(node.children, targetNode); - } - - return node; - }); - } - - const generateEndStyle = () => { - // 获取所有class为endline的div元素 - const endlineDivs = document.getElementsByClassName('endline'); - const mindMap = document.getElementById("mindMap"); - // 确保至少有两个元素 - if (endlineDivs.length >= 2 && mindMap) { - // 获取第一个和最后一个元素的边界框(bounding rectangle) - const firstRect = endlineDivs[0].getBoundingClientRect(); - const lastRect = endlineDivs[endlineDivs.length - 1].getBoundingClientRect(); - const mindMapRect = mindMap?.getBoundingClientRect(); - // 计算y值的差值 - const yDiff = lastRect.top - firstRect.top; - // const top = firstRect.top - mindMapRect.top; - // 如果需要包含元素的完整高度(不仅仅是顶部位置),可以加上元素的高度 - // const yDiffWithHeight = yDiff + (lastRect.height - firstRect.height); - return { - top: firstRect.top - mindMapRect.top, - height: yDiff + 1 - }; - } else { - return { - top: '50%', - height: 0 - }; - } - }; - - const generateWidth = () => { - const articles = document.querySelectorAll('article'); - // 确保至少有两个元素 - if (articles?.length) { - let maxRight = 0; - articles.forEach((item, index) => { - if (item.getBoundingClientRect().right > maxRight) { - maxRight = item.getBoundingClientRect().right; - } - }) - const firstArticle = articles[0].getBoundingClientRect(); - if (maxRight - firstArticle.left + 200 > mapWidth) { - return maxRight - firstArticle.left + 200 - } else { - return mapWidth; - } - } else { - return 100; - } - }; - - // 逐字渲染 - const renderDraft = (str: string, type: string, endCallback: () => void) => { - // 已经输出的字符数量 - let outputIndex = 0; - - // 输出字符的函数 - const outputText = () => { - // 给出高亮后draft输出的结束标志 - if (type === 'stepDraft-1' && outputIndex + 3 > str?.length) { - nodeDraftRender.current = true; - } - // 如果还有字符未输出 - if (outputIndex < str?.length) { - // 获取接下来要输出的1个字符(或剩余字符,如果不足3个) - let chunk = str.slice(outputIndex, Math.min(outputIndex + 10, str.length)); - // 更新已输出字符的索引 - outputIndex += chunk.length; - if (type === 'thought') { - setDraft(str.slice(0, outputIndex)); - } else if (type === "stepDraft-0") { - setProgress1(str.slice(0, outputIndex)); - } else if (type === "stepDraft-1") { - setProgress2(str.slice(0, outputIndex)); - } else if (type === "conclusion") { - setConclusion(str.slice(0, outputIndex)); - } else if (type === "response") { - setResponse(str.slice(0, outputIndex)); - } - } else { - // 如果没有更多字符需要输出,则清除定时器 - clearInterval(intervalId); - endCallback && endCallback() - } - } - - // 设定定时器ID - let intervalId = setInterval(outputText, TEXT_INTERVAL); - } - - // 渲染搜索结果renderSearchList - const renderSearchList = () => { - let outputIndex = 0; - const content = JSON.parse(currentNode.actions[currentStep].result[0].content); - - const arr: any = Object.keys(content).map(item => { - return { id: item, ...content[item] }; - }); - const len = Object.keys(content).length; - const outputText = () => { - outputIndex++; - if (outputIndex < len + 1) { - setSearchList(arr.slice(0, outputIndex)); - } else { - clearInterval(intervalId); - } - }; - // 设定定时器ID - let intervalId = setInterval(outputText, SEARCHLIST_INTERVAL); - }; - - // 高亮searchList - const highLightSearchList = (ids: any) => { - setSelectedIds([]); - const newStep = currentStep + 1; - setCurrentStep(newStep); - const highlightArr: any = [...searchList]; - highlightArr.forEach((item: any) => { - if (ids.includes(Number(item.id))) { - item.highLight = true; - } - }) - highlightArr.sort((item1: any, item2: any) => { - if (item1.highLight === item2.highLight) { - return 0; - } - // 如果item1是highlight,放在前面 - if (item1.highLight) { - return -1; - } - // 如果item2是highlight,放在后面 - return 1; - }) - setSearchList(highlightArr); - renderDraft(currentNode.actions[1].thought, `stepDraft-1`, () => { }); - hasHighlight.current = true; // 标记为高亮已执行 - }; - - // 渲染结论 - const renderConclusion = () => { - const res = window.localStorage.getItem('nodeRes') || ''; - const replaced = replaceStr(res); - // setTimeout(() => { setCollapseInfo([false, false]); }, 2000); - setCollapseInfo([false, false]); - setConclusion(replaced); - setstashConclusion(res); - // 给出conclusion结束的条件 - if (stashConclusion.length + 5 > res.length) { - conclusionRender.current = true; - setProgressEnd(true); - } - }; - - // 渲染query - const renderQuery = (endCallback: () => void) => { - const queries = currentNode.actions[currentStep]?.args?.query; - setQuery(queries); - endCallback && endCallback(); - }; - - const renderSteps = () => { - setCurrentNodeRendering(true); - const queryEndCallback = () => { - if (currentNode.actions[currentStep].result[0].content) { - if (currentNode.actions[currentStep].type === "BingBrowser.search" || currentNode.actions[currentStep].type === "BingBrowser") { - renderSearchList(); - } - } - }; - const thoughtEndCallback = () => { - if (currentNode.actions[currentStep]?.args?.query?.length) { - renderQuery(queryEndCallback); - } else { - queryEndCallback(); - } - }; - if (currentNode.actions[currentStep].thought) { - renderDraft(currentNode.actions[currentStep].thought, `stepDraft-${currentStep}`, thoughtEndCallback); - } - } - - // 展开收起 - const toggleCard = (index: number) => { - const arr = [...collapseInfo]; - arr[index] = !arr[index]; - setCollapseInfo(arr); - }; - - // 渲染过程中保持渲染文字可见 - const keepScrollTop = (divA: any, divB: any) => { - // 获取 divB 的当前高度 - const bHeight = divB.offsetHeight; - - // 检查 divA 是否需要滚动(即 divB 的高度是否大于 divA 的可视高度) - if (bHeight > divA.offsetHeight) { - // 滚动到 divB 的底部在 divA 的可视区域内 - divA.scrollTop = bHeight - divA.offsetHeight; - } - }; - - useEffect(() => { - setRenderData([ - { - id: 0, - state: 3, - name: '原始问题', - children: adjList - } - ]) - }, [JSON.stringify(adjList)]); - - useEffect(() => { - console.log('render data changed-----', renderData); - }, [renderData]); - - useEffect(() => { - if (currentStep === 1) { - setCollapseInfo([false, true]); - } - }, [currentStep]); - - useEffect(() => { - if (nodeOutputEnd && !localStorage.getItem('nodeRes')) { - // 如果节点输出结束了,但是response还没有结束,认为节点渲染已结束 - conclusionRender.current = true; - setProgressEnd(true); - return; - } - if (nodeDraftRender.current && localStorage.getItem('nodeRes')) { - renderConclusion(); - } - }, [localStorage.getItem('nodeRes'), nodeDraftRender.current, nodeOutputEnd]); - - useEffect(() => { - if (obj?.response?.nodes[obj.current_node]?.detail?.state !== 1) { - setIsWaiting(true); - } - if (obj?.response?.nodes?.[obj.current_node].detail?.state === 0 && currentNode?.current_node === obj.current_node) { - console.log('node render end-----', obj); - setNodeEnd(true); - } - - if (obj?.current_node && obj?.response?.state === 3) { - // 当node节点的数据可以开始渲染时,给currentnode赋值 - // update conclusion - if (obj.response.nodes[obj.current_node]?.detail?.actions?.length === 2 && - obj.response.nodes[obj.current_node]?.detail?.state === 1 && - obj.response.nodes[obj.current_node]?.detail.response) { - window.localStorage.setItem('nodeRes', obj.response.nodes[obj.current_node]?.detail.response); - } - if (obj.current_node && - (obj.response.nodes[obj.current_node]?.detail?.state === 1) && - obj.response.nodes[obj.current_node]?.detail?.actions?.length && - currentStep === 0 && - currentNode?.current_node !== obj?.current_node - ) { - // 更新当前渲染节点 - console.log('update current node----'); - setIsWaiting(false); - setCurrentNode({ ...obj.response.nodes[obj.current_node]?.detail, current_node: obj.current_node }); - } - - // 设置highlight - if (!selectedIds.length && - obj.response.nodes[obj.current_node]?.detail?.actions?.[1]?.type === 'BingBrowser.select' && - (obj.response.nodes[obj.current_node]?.detail?.state === 1)) { - setSelectedIds(obj.response.nodes[obj.current_node]?.detail?.actions?.[1]?.args?.select_ids || []); - setCurrentNode({ ...obj.response.nodes[obj.current_node]?.detail, current_node: obj.current_node }); - } - } - }, [obj]); - - useEffect(() => { - // 输出思考过程 - if (!currentNode || currentNodeRendering) { return; } - renderSteps(); - }, [currentNode, currentNodeRendering, selectedIds]); - - useEffect(() => { - if (!hasHighlight.current && selectedIds.length && currentNode?.actions.length === 2) { - // 渲染高亮的search信息 - highLightSearchList(selectedIds); - } - }, [selectedIds, currentNode]); - - useEffect(() => { - // 当前节点渲染结束 - if (nodeName && nodeName !== currentNode?.current_node && progressEnd && !isEnd) { - resetNode(nodeName); - setMapWidth(generateWidth()); - } - }, [nodeName, currentNode, progressEnd, isEnd]); - - let responseTimer: any = useRef(null); - useEffect(() => { - if (isEnd) { - responseTimer.current = setInterval(() => { - const divA = document.getElementById('chatArea') as HTMLDivElement; - const divB = document.getElementById('messageWindowId') as HTMLDivElement; - keepScrollTop(divA, divB); - if (chatIsOver) { - clearInterval(responseTimer.current); - } - }, 500); - setTimeout(() => { - setShowEndNode(true); - }, 300); - } else if (responseTimer.current) { - // 如果 isEnd 变为 false,清除定时器 - clearInterval(responseTimer.current); - responseTimer.current = null; - } - - // 返回清理函数,确保组件卸载时清除定时器 - return () => { - if (responseTimer.current) { - clearInterval(responseTimer.current); - responseTimer.current = null; - } - }; - }, [isEnd, chatIsOver]); - - useEffect(() => { - setRenderData([]); - setResponse(''); - setDraft(''); - setIsEnd(false); - setShowRight(true); - window.localStorage.setItem('nodeRes', ''); - window.localStorage.setItem('finishedNodes', ''); - }, [question]); - - const resetNode = (targetNode: string) => { - if (targetNode === 'response') return; // 如果开始response了,所有节点都渲染完了,不需要reset - // 渲染下一个节点前,初始化状态 - const newData = findAndUpdateStatus(renderData, targetNode); - console.log('reset node------', targetNode, renderData); - setCurrentStep(0); - setQuery([]); - setSearchList([]); - setConclusion(''); - setCollapseInfo([true, true]); - setProgress1(''); - setProgress2(''); - setProgressEnd(false); - setCurrentNode(null); - setCurrentNodeRendering(false); - setSelectedIds([]); - setNodeEnd(false); - hasHighlight.current = false; - nodeDraftRender.current = false; - conclusionRender.current = false; - window.localStorage.setItem('nodeRes', ''); - }; - - const formatData = (data: any) => { - try { - setIsWaiting(false); - const obj = JSON.parse(data); - if (!obj.current_node && obj.response.state === 0) { - console.log('chat is over end-------'); - setChatIsOver(true); - return; - } - if (!obj.current_node && obj.response.state === 9) { - setShowRight(false); - setIsEnd(true); - const replaced = replaceStr(obj.response.response); - setResponse(replaced); - return; - } - if (!obj.current_node && obj.response.state === 1 && !currentNode) { - // 有thought,没有node - setDraftEnd(false); - setDraft(obj.response.response); - } - if (!obj.current_node && (obj.response.state !== 1 || obj.response.state !== 0 || obj.response.state !== 9)) { - // 有thought,没有node, 不用处理渲染 - //console.log('loading-------------', obj); - setDraftEnd(true); - setIsWaiting(true); - } - if (obj.current_node && obj.response.state === 3) { - setNodeName(obj.current_node); - // 有node - setObj(obj); - const newAdjList = obj.response?.adjacency_list; - if (newAdjList?.length > 0) { - setAdjList(newAdjList); - } - } - } catch (err) { - console.log('format error-----', err); - } - }; - - const startEventSource = () => { - if (!chatIsOver) { - message.warning('有对话进行中!'); - return; - } - setQuestion(stashQuestion); - setChatIsOver(false); - const postData = { - inputs: [ - { - role: 'user', - content: stashQuestion - } - ] - } - const ctrl = new AbortController(); - eventSource = fetchEventSource(GET_SSE_DATA, { - method: 'POST', - headers: { - 'Content-Type': 'application/json', - }, - body: JSON.stringify(postData), - onmessage(ev) { - formatData(ev.data); - }, - onerror(err) { - console.log('sse error------', err); - }, - // signal: ctrl.signal, - }); - }; - - const abortEventSource = () => { - if (eventSource) { - eventSource.close(); // 或使用其他方法关闭连接,具体取决于库的API - eventSource = null; - console.log('EventSource connection aborted due to timeout.'); - message.error('连接中断,2s后即将刷新页面---'); - setTimeout(() => { - location.reload(); - }, 2000); - } - }; - - return

-}; - -export default RenderTest; \ No newline at end of file diff --git a/frontend/src/pages/render/mindMapItem.tsx b/frontend/src/pages/render/mindMapItem.tsx deleted file mode 100644 index e37618f5..00000000 --- a/frontend/src/pages/render/mindMapItem.tsx +++ /dev/null @@ -1,39 +0,0 @@ -import styles from './index.module.less'; -import classNames from 'classnames'; - -// 递归组件用于渲染mindMap中的节点 -const MindMapItem = ({ item, isEnd }: any) => { - // 递归渲染子节点 - const renderChildren = () => { - if (item.children && item.children.length > 0) { - return ( -
    - {item.children.map((child: any) => ( - - ))} -
- ); - } - return null; - }; - - return ( -
  • -
    - {item.name} - {item.state === 1 &&
    } - {item.id !== 0 &&
    } -
    - {item.children.length > 0 && renderChildren()} - { - isEnd && item.children?.length === 0 &&
    - } -
  • - ); -}; - -export default MindMapItem; \ No newline at end of file diff --git a/frontend/src/routes/routes.tsx b/frontend/src/routes/routes.tsx deleted file mode 100644 index 42b8f9c4..00000000 --- a/frontend/src/routes/routes.tsx +++ /dev/null @@ -1,38 +0,0 @@ -import RenderTest from "@/pages/render"; - -import { ReactElement } from "react"; -import { Navigate, useRoutes } from "react-router-dom"; - -interface RouteItem { - path: string; - needLogin?: boolean; - element: ReactElement; -} - -const routes: RouteItem[] = [ - { - path: "/", - needLogin: false, - element: , - }, - { - path: "*", - element: , - }, -]; - -const WrapperRoutes = () => { - return useRoutes( - routes.map((item: RouteItem) => { - if (item.needLogin) { - return { - ...item, - element: <>, - }; - } - return item; - }), - ); -}; - -export default WrapperRoutes; diff --git a/frontend/src/utils/tools.ts b/frontend/src/utils/tools.ts deleted file mode 100644 index 0c509256..00000000 --- a/frontend/src/utils/tools.ts +++ /dev/null @@ -1,24 +0,0 @@ -export const getQueryString = (search: string, name: string) => { - if (!search) return ""; - const reg = new RegExp("(^|&)" + name + "=([^&]*)(&|$)"); - const result = search.substring(1).match(reg); - if (result != null) return result[2]; - return ""; -}; - -export const isInWhiteList = (url: string = "", list: string[] = []) => { - const baseUrl = url.split("?")[0]; - for (let whiteApi of list) { - if (baseUrl.endsWith(whiteApi)) { - return true; - } - } - return false; -}; - -export const replaceStr = (str: string) => { - return str.replace(/\[\[(\d+)\]\]/g, (match: any, number: any) => { - // 创建一个带有class为'fnn2'的span元素,并将数字作为文本内容 - return `${number}`; - }); -}; \ No newline at end of file diff --git a/frontend/src/vite-env.d.ts b/frontend/src/vite-env.d.ts deleted file mode 100644 index d81164dc..00000000 --- a/frontend/src/vite-env.d.ts +++ /dev/null @@ -1,9 +0,0 @@ -/// - -interface ImportMetaEnv { - readonly VITE_SSO_URL: string; -} - -interface ImportMeta { - readonly env: ImportMetaEnv; -} diff --git a/frontend/tsconfig.json b/frontend/tsconfig.json deleted file mode 100644 index c1e581c6..00000000 --- a/frontend/tsconfig.json +++ /dev/null @@ -1,24 +0,0 @@ -{ - "compilerOptions": { - "target": "ES5", - "useDefineForClassFields": true, - "lib": ["DOM", "DOM.Iterable", "ESNext"], - "allowJs": false, - "skipLibCheck": true, - "esModuleInterop": false, - "allowSyntheticDefaultImports": true, - "strict": true, - "forceConsistentCasingInFileNames": true, - "module": "ESNext", - "moduleResolution": "Node", - "resolveJsonModule": true, - "isolatedModules": true, - "noEmit": true, - "jsx": "react-jsx", - "baseUrl": "./", - "paths": { - "@/*": ["src/*"] - } - }, - "include": ["src"] -} diff --git a/frontend/vite.config.ts b/frontend/vite.config.ts deleted file mode 100644 index dbcb72c1..00000000 --- a/frontend/vite.config.ts +++ /dev/null @@ -1,62 +0,0 @@ -import { defineConfig } from "vite"; -import react from "@vitejs/plugin-react"; -import path from "path"; -import legacy from "@vitejs/plugin-legacy"; - -// https://vitejs.dev/config/ -export default defineConfig({ - plugins: [ - react({ - babel: { - plugins: [ - "@babel/plugin-proposal-optional-chaining", // 兼容老版本浏览器的语法解译 - ], - }, - }), - legacy({ - targets: ["defaults", "ie >= 11", "chrome >= 52"], //需要兼容的目标列表,可以设置多个 - additionalLegacyPolyfills: ["regenerator-runtime/runtime"], - renderLegacyChunks: true, - polyfills: [ - "es.symbol", - "es.array.filter", - "es.promise", - "es.promise.finally", - "es/map", - "es/set", - "es.array.for-each", - "es.object.define-properties", - "es.object.define-property", - "es.object.get-own-property-descriptor", - "es.object.get-own-property-descriptors", - "es.object.keys", - "es.object.to-string", - "web.dom-collections.for-each", - "esnext.global-this", - "esnext.string.match-all", - ], - }), - ], - build: { - target: "es5", - }, - resolve: { - alias: { - "@": path.resolve(__dirname, "src"), - }, - }, - css: { - modules: { - localsConvention: "camelCase", - }, - }, - server: { - port: 8080, - proxy: { - // "/solve": { - // target: "...", - // changeOrigin: true, - // }, - }, - }, -}); diff --git a/lagent/agents/mindsearch_agent.py b/lagent/agents/mindsearch_agent.py deleted file mode 100644 index 4cac3947..00000000 --- a/lagent/agents/mindsearch_agent.py +++ /dev/null @@ -1,395 +0,0 @@ -import json -import logging -import queue -import re -import threading -import uuid -from collections import defaultdict -from concurrent.futures import ThreadPoolExecutor, as_completed -from copy import deepcopy -from dataclasses import asdict -from typing import Dict, List, Optional - -from termcolor import colored - -from lagent.actions import ActionExecutor -from lagent.agents import BaseAgent, Internlm2Agent -from lagent.agents.internlm2_agent import Internlm2Protocol -from lagent.schema import AgentReturn, AgentStatusCode, ModelStatusCode - -# 初始化日志记录 -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger(__name__) - - -class SearcherAgent(Internlm2Agent): - - def __init__(self, template='{query}', **kwargs) -> None: - super().__init__(**kwargs) - self.template = template - - def stream_chat(self, - question: str, - root_question: str = None, - parent_response: List[dict] = None, - **kwargs) -> AgentReturn: - message = self.template['input'].format( - question=question, topic=root_question) - if parent_response: - if 'context' in self.template: - parent_response = [ - self.template['context'].format(**item) - for item in parent_response - ] - message = '\n'.join(parent_response + [message]) - print(colored(f'current query: {message}', 'green')) - for agent_return in super().stream_chat(message, **kwargs): - agent_return.type = 'searcher' - agent_return.content = question - yield deepcopy(agent_return) - - -class MindSearchProtocol(Internlm2Protocol): - - def __init__( - self, - meta_prompt: str = None, - interpreter_prompt: str = None, - plugin_prompt: str = None, - few_shot: Optional[List] = None, - response_prompt: str = None, - language: Dict = dict( - begin='', - end='', - belong='assistant', - ), - tool: Dict = dict( - begin='{start_token}{name}\n', - start_token='<|action_start|>', - name_map=dict(plugin='<|plugin|>', interpreter='<|interpreter|>'), - belong='assistant', - end='<|action_end|>\n', - ), - execute: Dict = dict( - role='execute', begin='', end='', fallback_role='environment'), - ) -> None: - self.response_prompt = response_prompt - super().__init__( - meta_prompt=meta_prompt, - interpreter_prompt=interpreter_prompt, - plugin_prompt=plugin_prompt, - few_shot=few_shot, - language=language, - tool=tool, - execute=execute) - - def format(self, - inner_step: List[Dict], - plugin_executor: ActionExecutor = None, - **kwargs) -> list: - formatted = [] - if self.meta_prompt: - formatted.append(dict(role='system', content=self.meta_prompt)) - if self.plugin_prompt: - plugin_prompt = self.plugin_prompt.format( - tool_info=json.dumps( - plugin_executor.get_actions_info(), ensure_ascii=False)) - formatted.append( - dict(role='system', content=plugin_prompt, name='plugin')) - if self.interpreter_prompt: - formatted.append( - dict( - role='system', - content=self.interpreter_prompt, - name='interpreter')) - if self.few_shot: - for few_shot in self.few_shot: - formatted += self.format_sub_role(few_shot) - formatted += self.format_sub_role(inner_step) - return formatted - - -class WebSearchGraph: - end_signal = 'end' - searcher_cfg = dict() - - def __init__(self): - self.nodes = {} - self.adjacency_list = defaultdict(list) - self.executor = ThreadPoolExecutor(max_workers=10) - self.future_to_query = dict() - self.searcher_resp_queue = queue.Queue() - - def add_root_node(self, node_content, node_name='root'): - self.nodes[node_name] = dict(content=node_content, type='root') - self.adjacency_list[node_name] = [] - self.searcher_resp_queue.put((node_name, self.nodes[node_name], [])) - - def add_node(self, node_name, node_content): - self.nodes[node_name] = dict(content=node_content, type='searcher') - self.adjacency_list[node_name] = [] - - def model_stream_thread(): - agent = SearcherAgent(**self.searcher_cfg) - try: - parent_nodes = [] - for start_node, adj in self.adjacency_list.items(): - for neighbor in adj: - if node_name == neighbor[ - 'name'] and start_node in self.nodes and 'response' in self.nodes[ - start_node]: - parent_nodes.append(self.nodes[start_node]) - parent_response = [ - dict(question=node['content'], answer=node['response']) - for node in parent_nodes - ] - for answer in agent.stream_chat( - node_content, - self.nodes['root']['content'], - parent_response=parent_response): - self.searcher_resp_queue.put( - deepcopy( - (node_name, - dict(response=answer.response, - detail=answer), []))) - self.nodes[node_name]['response'] = answer.response - self.nodes[node_name]['detail'] = answer - except Exception as e: - logger.exception(f'Error in model_stream_thread: {e}') - - self.future_to_query[self.executor.submit( - model_stream_thread)] = f'{node_name}-{node_content}' - - def add_response_node(self, node_name='response'): - self.nodes[node_name] = dict(type='end') - self.searcher_resp_queue.put((node_name, self.nodes[node_name], [])) - - def add_edge(self, start_node, end_node): - self.adjacency_list[start_node].append( - dict(id=str(uuid.uuid4()), name=end_node, state=2)) - self.searcher_resp_queue.put((start_node, self.nodes[start_node], - self.adjacency_list[start_node])) - - def reset(self): - self.nodes = {} - self.adjacency_list = defaultdict(list) - - def node(self, node_name): - return self.nodes[node_name].copy() - - -class MindSearchAgent(BaseAgent): - - def __init__(self, - llm, - searcher_cfg, - protocol=MindSearchProtocol(), - max_turn=3): - self.local_dict = {} - self.ptr = 0 - self.llm = llm - self.max_turn = max_turn - WebSearchGraph.searcher_cfg = searcher_cfg - super().__init__(llm=llm, action_executor=None, protocol=protocol) - - def stream_chat(self, message, **kwargs): - if isinstance(message, str): - message = [{'role': 'user', 'content': message}] - elif isinstance(message, dict): - message = [message] - self.local_dict.clear() - self.ptr = 0 - inner_history = message[:] - agent_return = AgentReturn() - agent_return.type = 'planner' - agent_return.nodes = {} - agent_return.adjacency_list = {} - agent_return.inner_steps = deepcopy(inner_history) - - for _ in range(self.max_turn): - prompt = self._protocol.format(inner_step=inner_history) - for model_state, response, _ in self.llm.stream_chat( - prompt, **kwargs): - if model_state.value < 0: - agent_return.state = getattr(AgentStatusCode, - model_state.name) - yield deepcopy(agent_return) - return - _, language, action = self._protocol.parse(response) - if not language and not action: - continue - code = action['parameters']['command'] if action else '' - agent_return.state = self._determine_agent_state( - model_state, code, agent_return) - agent_return.response = language if not code else code - - # if agent_return.state == AgentStatusCode.STREAM_ING: - yield deepcopy(agent_return) - - inner_history.append({'role': 'language', 'content': language}) - print(colored(response, 'blue')) - - if code: - yield from self._process_code(agent_return, - inner_history, code, - kwargs.get('as_dict', False)) - else: - agent_return.state = AgentStatusCode.END - yield deepcopy(agent_return) - return - - agent_return.state = AgentStatusCode.END - yield deepcopy(agent_return) - - def _determine_agent_state(self, model_state, code, agent_return): - if code: - return AgentStatusCode.PLUGIN_START if model_state == ModelStatusCode.END else AgentStatusCode.PLUGIN_START - return AgentStatusCode.ANSWER_ING if agent_return.nodes and 'response' in agent_return.nodes else AgentStatusCode.STREAM_ING - - def _process_code(self, agent_return, inner_history, code, as_dict=False): - for node_name, node, adj in self.execute_code(code): - if as_dict and 'detail' in node: - node['detail'] = asdict(node['detail']) - if not adj: - agent_return.nodes[node_name] = node - else: - agent_return.adjacency_list[node_name] = adj - # state 1进行中,2未开始,3已结束 - for start_node, neighbors in agent_return.adjacency_list.items(): - for neighbor in neighbors: - if neighbor['name'] not in agent_return.nodes: - state = 2 - elif 'detail' not in agent_return.nodes[neighbor['name']]: - state = 2 - elif agent_return.nodes[neighbor['name']][ - 'detail'].state == AgentStatusCode.END: - state = 3 - else: - state = 1 - neighbor['state'] = state - if not adj: - yield deepcopy((agent_return, node_name)) - reference, references_url = self._generate_reference( - agent_return, code, as_dict) - inner_history.append({ - 'role': 'tool', - 'content': code, - 'name': 'plugin' - }) - inner_history.append({ - 'role': 'environment', - 'content': reference, - 'name': 'plugin' - }) - agent_return.inner_steps = deepcopy(inner_history) - agent_return.state = AgentStatusCode.PLUGIN_RETURN - agent_return.references.update(references_url) - yield deepcopy(agent_return) - - def _generate_reference(self, agent_return, code, as_dict): - node_list = [ - node.strip().strip('\"') for node in re.findall( - r'graph\.node\("((?:[^"\\]|\\.)*?)"\)', code) - ] - if 'add_response_node' in code: - return self._protocol.response_prompt, dict() - references = [] - references_url = dict() - for node_name in node_list: - if as_dict: - ref_results = agent_return.nodes[node_name]['detail'][ - 'actions'][0]['result'][0]['content'] - else: - ref_results = agent_return.nodes[node_name]['detail'].actions[ - 0].result[0]['content'] - ref_results = json.loads(ref_results) - ref2url = {idx: item['url'] for idx, item in ref_results.items()} - ref = f"## {node_name}\n\n{agent_return.nodes[node_name]['response']}\n" - updated_ref = re.sub( - r'\[\[(\d+)\]\]', - lambda match: f'[[{int(match.group(1)) + self.ptr}]]', ref) - numbers = [int(n) for n in re.findall(r'\[\[(\d+)\]\]', ref)] - if numbers: - assert all(str(elem) in ref2url for elem in numbers) - references_url.update({ - str(idx + self.ptr): ref2url[str(idx)] - for idx in set(numbers) - }) - self.ptr += max(numbers) + 1 - references.append(updated_ref) - return '\n'.join(references), references_url - - def execute_code(self, command: str): - - def extract_code(text: str) -> str: - text = re.sub(r'from ([\w.]+) import', - 'from lagent.agents.mindsearch_agent import', text) - triple_match = re.search(r'```[^\n]*\n(.+?)```', text, re.DOTALL) - single_match = re.search(r'`([^`]*)`', text, re.DOTALL) - if triple_match: - return triple_match.group(1) - elif single_match: - return single_match.group(1) - return text - - def run_command(cmd): - try: - exec(cmd, globals(), self.local_dict) - plan_graph = self.local_dict.get('graph') - assert plan_graph is not None - for future in as_completed(plan_graph.future_to_query): - future.result() - plan_graph.future_to_query.clear() - plan_graph.searcher_resp_queue.put(plan_graph.end_signal) - except Exception as e: - logger.exception(f'Error executing code: {e}') - - command = extract_code(command) - producer_thread = threading.Thread( - target=run_command, args=(command, )) - producer_thread.start() - - responses = defaultdict(list) - ordered_nodes = [] - active_node = None - - while True: - try: - item = self.local_dict.get('graph').searcher_resp_queue.get( - timeout=60) - if item is WebSearchGraph.end_signal: - for node_name in ordered_nodes: - # resp = None - for resp in responses[node_name]: - yield deepcopy(resp) - # if resp: - # assert resp[1][ - # 'detail'].state == AgentStatusCode.END - break - node_name, node, adj = item - if node_name in ['root', 'response']: - yield deepcopy((node_name, node, adj)) - else: - if node_name not in ordered_nodes: - ordered_nodes.append(node_name) - responses[node_name].append((node_name, node, adj)) - if not active_node and ordered_nodes: - active_node = ordered_nodes[0] - while active_node and responses[active_node]: - if 'detail' in responses[active_node][-1][ - 1] and responses[active_node][-1][1][ - 'detail'].state == AgentStatusCode.END: - item = responses[active_node][-1] - else: - item = responses[active_node].pop(0) - if 'detail' in item[1] and item[1][ - 'detail'].state == AgentStatusCode.END: - ordered_nodes.pop(0) - responses[active_node].clear() - active_node = None - yield deepcopy(item) - except queue.Empty: - if not producer_thread.is_alive(): - break - producer_thread.join() - return
    - - {showRight &&
    - { - currentNode && <> -
    - - -
    -
    {currentNode?.content || currentNode?.node}
    - { - currentNode?.actions?.length ? <> - { - currentNode.actions.map((item: any, idx: number) => ( - currentStep >= idx &&
    -
    - {item.type === "BingBrowser.search" ? "思考" : item.type === "BingBrowser.select" ? "信息来源" : "信息整合"} -
    { toggleCard(idx) }}> - -
    -
    -
    - { - item.type === "BingBrowser.search" &&
    - {progress1} -
    - } - { - item.type === "BingBrowser.search" && query.length > 0 &&
    -
    搜索关键词
    - { - query.map((item, index) => (
    - {item} -
    )) - } -
    - } - { - currentStep === idx && searchList.length > 0 &&
    - {item.type === "BingBrowser.search" &&
    信息来源
    } - { - item.type === "BingBrowser.select" &&
    - {progress2} -
    - } -
    5 && currentStep === 0) ? { height: '300px' } : {}}> - -
    5 && currentStep === 0) ? { position: 'absolute', bottom: 0, left: 0 } : {}}> - - { - searchList.map((item: any, num: number) => ( -
    -

    {item.id}. {item?.title}

    -

    {item?.url}

    -
    - )) - } -
    -
    -
    - } -
    -
    - )) - } - : <> - } - - } - { - conclusion &&
    -
    - 信息整合 -
    -
    - {conclusion} -
    -
    - } - {isWaiting && question &&
    } -
    } - { - !showRight &&
    - -
    - } - -

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-channels: - - conda-forge - - defaults -dependencies: - - _libgcc_mutex=0.1=conda_forge - - _openmp_mutex=4.5=2_gnu - - aws-c-common=0.4.57=he6710b0_1 - - aws-c-event-stream=0.1.6=h2531618_5 - - aws-checksums=0.1.9=he6710b0_0 - - aws-sdk-cpp=1.8.185=hce553d0_0 - - binutils_impl_linux-64=2.40=hf600244_0 - - bzip2=1.0.8=h7b6447c_0 - - c-ares=1.19.0=h5eee18b_0 - - ca-certificates=2023.5.7=hbcca054_0 - - expat=2.5.0=hcb278e6_1 - - gcc=13.1.0=h8e92de4_0 - - gcc_impl_linux-64=13.1.0=hc4be1a9_0 - - gxx=13.1.0=h8e92de4_0 - - gxx_impl_linux-64=13.1.0=hc4be1a9_0 - - kernel-headers_linux-64=2.6.32=he073ed8_16 - - krb5=1.20.1=h568e23c_1 - - ld_impl_linux-64=2.40=h41732ed_0 - - libcurl=8.1.1=h91b91d3_1 - - libedit=3.1.20221030=h5eee18b_0 - - libev=4.33=h516909a_1 - - libexpat=2.5.0=hcb278e6_1 - - libffi=3.3=he6710b0_2 - - libgcc-devel_linux-64=13.1.0=he3cc6c4_0 - - libgcc-ng=13.1.0=he5830b7_0 - - libgomp=13.1.0=he5830b7_0 - - libnghttp2=1.52.0=ha637b67_1 - - libsanitizer=13.1.0=hfd8a6a1_0 - - libssh2=1.10.0=h37d81fd_2 - - libstdcxx-devel_linux-64=13.1.0=he3cc6c4_0 - - libstdcxx-ng=13.1.0=hfd8a6a1_0 - - libuuid=1.41.5=h5eee18b_0 - - libuv=1.44.2=h166bdaf_0 - - lz4-c=1.9.4=hcb278e6_0 - - make=4.3=hd18ef5c_1 - - ncurses=6.4=h6a678d5_0 - - openssl=1.1.1u=hd590300_0 - - python=3.10.0=h12debd9_5 - - readline=8.2=h5eee18b_0 - - rhash=1.4.3=h166bdaf_0 - - sqlite=3.41.2=h5eee18b_0 - - sysroot_linux-64=2.12=he073ed8_16 - - tk=8.6.12=h1ccaba5_0 - - xz=5.4.2=h5eee18b_0 - - zlib=1.2.13=h5eee18b_0 - - zstd=1.5.5=hc292b87_0 - - pip: - - absl-py==1.4.0 - - accelerate==0.27.2 - - addict==2.4.0 - - aim==3.17.5 - - aim-ui==3.17.5 - - aimrecords==0.0.7 - - aimrocks==0.4.0 - - aiofiles==23.1.0 - - aiohttp==3.9.3 - - aiosignal==1.3.1 - - alabaster==0.7.13 - - alembic==1.11.1 - - aliyun-python-sdk-core==2.14.0 - - aliyun-python-sdk-kms==2.16.2 - - altair==5.2.0 - - annotated-types==0.5.0 - - antlr4-python3-runtime==4.11.0 - - anyio==3.7.1 - - apex==0.1 - - appdirs==1.4.4 - - argon2-cffi==23.1.0 - - argon2-cffi-bindings==21.2.0 - - arrow==1.3.0 - - arxiv==2.1.0 - - astroid==2.15.6 - - asttokens==2.4.1 - - async-lru==2.0.4 - - async-timeout==4.0.3 - - attrs==23.2.0 - - autodoc-pydantic==1.9.0 - - babel==2.12.1 - - backoff==2.2.1 - - base58==2.0.1 - - bcrypt==4.0.1 - - beautifulsoup4==4.12.3 - - benedict==0.3.2 - - bert-score==0.3.13 - - bidict==0.22.1 - - bleach==6.1.0 - - blinker==1.6.2 - - boto3==1.28.7 - - botocore==1.31.7 - - brotli==1.1.0 - - cachetools==5.3.1 - - certifi==2024.2.2 - - cffi==1.15.1 - - cfgv==3.3.1 - - charset-normalizer==3.2.0 - - click==8.1.7 - - cloudpickle==2.2.1 - - cmake==3.27.0 - - colorama==0.4.6 - - coloredlogs==15.0.1 - - colossalai==0.2.0+torch1.13cu11.7 - - comm==0.2.1 - - configobj==5.0.8 - - contexttimer==0.3.3 - - contourpy==1.1.0 - - cpython==0.0.6 - - crcmod==1.7 - - cryptography==41.0.2 - - curl-cffi==0.7.0b4 - - cycler==0.11.0 - - cython==3.0.0 - - databricks-cli==0.17.7 - - dataclasses-json==0.6.6 - - datasets==2.17.1 - - debugpy==1.8.0 - - decorator==5.1.1 - - defusedxml==0.7.1 - - deprecated==1.2.14 - - diffusers==0.26.3 - - dill==0.3.8 - - dirtyjson==1.0.8 - - distlib==0.3.7 - - distro==1.9.0 - - dlc-run==0.0.5 - - dnspython==2.4.2 - - docker==6.1.3 - - docopt==0.6.2 - - docutils==0.18.1 - - dropout-layer-norm==0.1 - - duckduckgo-search==5.3.0b4 - - easydict==1.10 - - einops==0.7.0rc1 - - elastic-transport==8.4.0 - - elasticsearch==8.8.2 - - entrypoints==0.4 - - environs==9.5.0 - - et-xmlfile==1.1.0 - - evaluate==0.4.1 - - eventlet==0.33.3 - - exceptiongroup==1.1.2 - - executing==2.0.1 - - fabric==3.1.0 - - fastapi==0.100.0 - - fastjsonschema==2.19.1 - - feedparser==6.0.10 - - ffmpy==0.3.2 - - filelock==3.12.2 - - fire==0.5.0 - - fitlog==0.9.15 - - flash-attn==2.3.0 - - flask==2.3.2 - - flask-socketio==5.3.6 - - fonttools==4.42.1 - - fqdn==1.5.1 - - frozenlist==1.4.1 - - fsspec==2023.6.0 - - ft-attention==0.1 - - func-timeout==4.3.5 - - fused-dense-lib==0.0.0 - - fused-softmax-lib==0.0.0 - - fuzzywuzzy==0.18.0 - - gitdb==4.0.10 - - gitpython==3.1.32 - - google-auth==2.22.0 - - google-auth-oauthlib==1.0.0 - - google-search-results==2.4.2 - - gputil==1.4.0 - - gradio==4.31.3 - - gradio-client==0.16.3 - - greenlet==2.0.2 - - griffe==0.40.1 - - grpcio==1.56.2 - - gunicorn==20.1.0 - - h11==0.14.0 - - h2==4.1.0 - - hpack==4.0.0 - - httpcore==1.0.3 - - httptools==0.6.1 - - httpx==0.27.0 - - huggingface-hub==0.23.2 - - humanfriendly==10.0 - - humanize==4.7.0 - - hyperframe==6.0.1 - - identify==2.5.25 - - idna==3.4 - - imagesize==1.4.1 - - importlib-metadata==6.8.0 - - importlib-resources==6.4.0 - - iniconfig==2.0.0 - - invoke==2.2.0 - - ipykernel==6.29.2 - - ipython==8.21.0 - - ipywidgets==8.1.2 - - isoduration==20.11.0 - - isort==5.12.0 - - itsdangerous==2.1.2 - - jedi==0.19.1 - - jinja2==3.1.2 - - jmespath==0.10.0 - - joblib==1.3.2 - - json5==0.9.14 - - jsonlines==4.0.0 - - jsonpickle==3.2.1 - - jsonpointer==2.4 - - jsonschema==4.21.1 - - jsonschema-specifications==2023.12.1 - - jupyter==1.0.0 - - jupyter-client==8.6.0 - - jupyter-console==6.6.3 - - jupyter-core==5.7.1 - - jupyter-events==0.9.0 - - jupyter-lsp==2.2.2 - - jupyter-server==2.12.5 - - jupyter-server-terminals==0.5.2 - - jupyterlab==4.1.1 - - jupyterlab-pygments==0.3.0 - - jupyterlab-server==2.25.3 - - jupyterlab-widgets==3.0.10 - - kiwisolver==1.4.5 - - lazy-object-proxy==1.9.0 - - lit==16.0.6 - - livereload==2.6.3 - - llama-index==0.10.40 - - llama-index-agent-openai==0.2.5 - - llama-index-cli==0.1.12 - - llama-index-core==0.10.40 - - llama-index-embeddings-openai==0.1.10 - - llama-index-indices-managed-llama-cloud==0.1.6 - - llama-index-legacy==0.9.48 - - llama-index-llms-huggingface==0.2.0 - - llama-index-llms-openai==0.1.21 - - llama-index-multi-modal-llms-openai==0.1.6 - - llama-index-program-openai==0.1.6 - - llama-index-question-gen-openai==0.1.3 - - llama-index-readers-file==0.1.23 - - llama-index-readers-llama-parse==0.1.4 - - llama-parse==0.4.4 - - llamaindex-py-client==0.1.19 - - lmdeploy==0.2.3 - - loguru==0.7.0 - - lxml==5.1.0 - - makefun==1.15.2 - - mako==1.2.4 - - markdown==3.4.3 - - markdown-it-py==3.0.0 - - markupsafe==2.1.3 - - marshmallow==3.20.1 - - mat4py==0.6.0 - - matplotlib==3.7.2 - - matplotlib-inline==0.1.6 - - mccabe==0.7.0 - - mdit-py-plugins==0.4.0 - - mdurl==0.1.2 - - mistune==3.0.2 - - mlflow==2.5.0 - - mmcv==2.1.0 - - mmengine==0.10.3 - - mmengine-lite==0.10.3 - - mmpretrain==1.2.0 - - model-index==0.1.11 - - modelindex==0.0.2 - - monotonic==1.6 - - mpmath==1.3.0 - - multidict==6.0.5 - - multiprocess==0.70.16 - - multiprocessing-logging==0.3.4 - - mypy-extensions==1.0.0 - - myst-parser==2.0.0 - - nbclient==0.9.0 - - nbconvert==7.16.0 - - nbformat==5.9.2 - - nest-asyncio==1.6.0 - - networkx==3.2.1 - - ninja==1.11.1 - - nltk==3.8.1 - - nodeenv==1.8.0 - - notebook==7.1.0 - - notebook-shim==0.2.4 - - numpy==1.25.1 - - nvidia-cublas-cu11==11.11.3.6 - - nvidia-cublas-cu12==12.1.3.1 - - nvidia-cuda-cupti-cu12==12.1.105 - - nvidia-cuda-nvrtc-cu12==12.1.105 - - nvidia-cuda-runtime-cu11==11.8.89 - - nvidia-cuda-runtime-cu12==12.1.105 - - nvidia-cudnn-cu12==8.9.2.26 - - nvidia-cufft-cu12==11.0.2.54 - - nvidia-curand-cu12==10.3.2.106 - - nvidia-cusolver-cu12==11.4.5.107 - - nvidia-cusparse-cu12==12.1.0.106 - - nvidia-nccl-cu11==2.19.3 - - nvidia-nccl-cu12==2.18.1 - - nvidia-nvjitlink-cu12==12.3.101 - - nvidia-nvtx-cu12==12.1.105 - - oauthlib==3.2.2 - - openai==1.30.5 - - openapi-pydantic==0.4.0 - - opencv-python==4.9.0.80 - - opendatalab==0.0.10 - - openmim==0.3.9 - - openpyxl==3.1.2 - - openxlab==0.0.34 - - ordered-set==4.1.0 - - orjson==3.10.3 - - oss2==2.17.0 - - overrides==7.7.0 - - packaging==23.1 - - pandas==2.0.3 - - pandocfilters==1.5.1 - - paramiko==3.2.0 - - parso==0.8.3 - - pebble==5.0.6 - - peft==0.7.1 - - petrel-oss-sdk==v2.2.1-2-g1505ef3-master - - pexpect==4.9.0 - - phx-class-registry==4.1.0 - - pillow==10.0.0 - - pip==24.0 - - platformdirs==3.9.1 - - pluggy==1.2.0 - - portpicker==1.5.2 - - pre-commit==3.6.2 - - prettytable==3.8.0 - - prometheus-client==0.20.0 - - prompt-toolkit==3.0.43 - - protobuf==4.23.4 - - psutil==5.9.5 - - ptyprocess==0.7.0 - - pure-eval==0.2.2 - - py3nvml==0.2.7 - - pyarrow==12.0.1 - - pyarrow-hotfix==0.6 - - pyasn1==0.5.0 - - pyasn1-modules==0.3.0 - - pybind11==2.11.1 - - pycocotools==2.0.7 - - pycparser==2.21 - - pycryptodome==3.20.0 - - pydantic==2.6.1 - - pydantic-core==2.16.2 - - pydeck==0.8.1b0 - - pydub==0.25.1 - - pyecharts==2.0.3 - - pyee==11.1.0 - - pygments==2.15.1 - - pyjwt==2.8.0 - - pylint==2.17.5 - - pymongo==4.4.1 - - pynacl==1.5.0 - - pynvml==11.5.0 - - pyparsing==3.0.9 - - pypdf==4.2.0 - - pyppeteer==2.0.0 - - pyre-extensions==0.0.23 - - pystack==1.3.0 - - pytest==7.4.0 - - python-benedict==0.33.2 - - python-dateutil==2.8.2 - - python-dotenv==1.0.0 - - python-engineio==4.8.0 - - python-fsutil==0.14.1 - - python-json-logger==2.0.7 - - python-logging-loki==0.3.1 - - python-multipart==0.0.9 - - python-pptx==0.6.23 - - python-rapidjson==1.14 - - python-slugify==8.0.4 - - python-socketio==5.10.0 - - pytz==2023.3 - - pyvis==0.3.2 - - pyyaml==6.0.1 - - pyzmq==25.1.2 - - qtconsole==5.5.1 - - qtpy==2.4.1 - - querystring-parser==1.2.4 - - rapidfuzz==3.6.1 - - referencing==0.33.0 - - regex==2023.6.3 - - requests==2.31.0 - - requests-oauthlib==1.3.1 - - responses==0.18.0 - - restrictedpython==6.1 - - rfc3339==6.2 - - rfc3339-validator==0.1.4 - - rfc3986-validator==0.1.1 - - rich==13.4.2 - - rotary-emb==0.1 - - rpds-py==0.18.0 - - rsa==4.9 - - ruamel-yaml==0.17.32 - - ruamel-yaml-clib==0.2.7 - - ruff==0.4.4 - - s3transfer==0.6.1 - - safetensors==0.4.2 - - scikit-learn==1.3.0 - - scipy==1.11.2 - - segment-analytics-python==2.2.3 - - semantic-version==2.10.0 - - send2trash==1.8.2 - - sentence-transformers==2.6.1 - - sentencepiece==0.1.99 - - setuptools==69.1.1 - - sgmllib3k==1.0.0 - - shellingham==1.5.4 - - shortuuid==1.0.11 - - simple-websocket==1.0.0 - - simplejson==3.19.1 - - six==1.16.0 - - smmap==5.0.0 - - sniffio==1.3.0 - - snowballstemmer==2.2.0 - - socksio==1.0.0 - - soupsieve==2.5 - - sphinx==7.2.6 - - sphinx-autobuild==2021.3.14 - - sphinx-intl==2.1.0 - - sphinx-markdown-tables==0.0.17 - - sphinx-rtd-theme==1.3.0 - - sphinxcontrib-applehelp==1.0.7 - - sphinxcontrib-devhelp==1.0.5 - - sphinxcontrib-htmlhelp==2.0.4 - - sphinxcontrib-jquery==4.1 - - sphinxcontrib-jsmath==1.0.1 - - sphinxcontrib-qthelp==1.0.6 - - sphinxcontrib-serializinghtml==1.1.9 - - sqlalchemy==1.4.49 - - sqlparse==0.4.4 - - sse-starlette==2.1.2 - - stack-data==0.6.3 - - starlette==0.27.0 - - streamlit==1.31.1 - - striprtf==0.0.26 - - sympy==1.12 - - tabulate==0.9.0 - - tenacity==8.2.3 - - tensorboard==2.13.0 - - tensorboard-data-server==0.7.1 - - termcolor==2.4.0 - - terminado==0.18.0 - - text-generation==0.7.0 - - text-unidecode==1.3 - - thefuzz==0.22.1 - - threadpoolctl==3.2.0 - - tiktoken==0.6.0 - - timeout-decorator==0.5.0 - - tinycss2==1.2.1 - - tokenizers==0.15.2 - - toml==0.10.2 - - tomli==2.0.1 - - tomlkit==0.12.0 - - toolz==0.12.1 - - torch==2.1.2 - - torch-scatter==2.1.1+pt113cu117 - - torchvision==0.14.1+cu117 - - tornado==6.3.3 - - tqdm==4.66.4 - - traitlets==5.14.1 - - transformers==4.37.1 - - triton==2.1.0 - - tritonclient==2.42.0 - - typer==0.12.3 - - types-python-dateutil==2.8.19.20240106 - - typing-extensions==4.7.1 - - typing-inspect==0.9.0 - - tzdata==2023.3 - - tzlocal==5.2 - - ujson==5.7.0 - - uniscale-monitoring==0.4.4 - - uri-template==1.3.0 - - urllib3==2.2.1 - - uvicorn==0.23.1 - - uvloop==0.19.0 - - validators==0.22.0 - - virtualenv==20.24.1 - - waitress==2.1.2 - - watchdog==4.0.0 - - watchfiles==0.21.0 - - wcwidth==0.2.6 - - webcolors==1.13 - - webencodings==0.5.1 - - websocket-client==1.6.2 - - websockets==10.4 - - werkzeug==2.3.6 - - wheel==0.42.0 - - widgetsnbextension==4.0.10 - - wrapt==1.15.0 - - wsproto==1.2.0 - - xentropy-cuda-lib==0.1 - - xformers==0.0.17+57edbb7.d20230301 - - xlsxwriter==3.1.9 - - xmltodict==0.13.0 - - xxhash==3.4.1 - - yapf==0.40.2 - - yarl==1.9.4 - - zipp==3.16.2 diff --git a/examples/web_graph_ci_demo.py b/examples/web_graph_ci_demo.py deleted file mode 100644 index c72663f5..00000000 --- a/examples/web_graph_ci_demo.py +++ /dev/null @@ -1,44 +0,0 @@ -from datetime import datetime - -from lagent.actions import ActionExecutor, BingBrowser -from lagent.agents.mindsearch_agent import MindSearchAgent, MindSearchProtocol -from lagent.agents.mindsearch_prompt import GRAPH_PROMPT_CN, searcher_input_template_cn, searcher_system_prompt_cn -from lagent.llms import GPTAPI - -url = 'https://puyu.staging.openxlab.org.cn/puyu/api/v1/chat/completions' -llm = GPTAPI( - model_type='internlm2.5-api-7b-0627', - openai_api_base=url, - key='YOUR API KEY', - meta_template=[ - dict(role='system', api_role='system'), - dict(role='user', api_role='user'), - dict(role='assistant', api_role='assistant'), - dict(role='environment', api_role='environment') - ], - top_p=0.8, - top_k=1, - temperature=0.8, - max_new_tokens=8192, - repetition_penalty=1.02, - stop_words=['<|im_end|>']) - -agent = MindSearchAgent( - llm=llm, - searcher_cfg=dict( - llm=llm, - plugin_executor=ActionExecutor(BingBrowser('YOUR API KEY')), - protocol=MindSearchProtocol( - meta_prompt=datetime.now().strftime( - 'The current date is %Y-%m-%d.'), - plugin_prompt=searcher_system_prompt_cn, - ), - template=searcher_input_template_cn), - protocol=MindSearchProtocol( - meta_prompt=datetime.now().strftime('The current date is %Y-%m-%d.'), - interpreter_prompt=GRAPH_PROMPT_CN, - response_prompt='请根据上文内容对问题给出详细的回复'), - max_turn=10) - -for agent_return in agent.stream_chat('上海今天天气怎么样?'): - print(agent_return) diff --git a/examples/web_graph_gradio_demo.py b/examples/web_graph_gradio_demo.py deleted file mode 100644 index 0b335874..00000000 --- a/examples/web_graph_gradio_demo.py +++ /dev/null @@ -1,193 +0,0 @@ -import json - -import gradio as gr - -from lagent.schema import AgentStatusCode - - -# Initialize the agent -def init_agent(): - from datetime import datetime - - from lagent.actions import ActionExecutor, BingBrowser - from lagent.agents.mindsearch_agent import MindSearchAgent, MindSearchProtocol - # from lagent.agents.mindsearch_prompt import GRAPH_PROMPT_EN - # from lagent.agents.mindsearch_prompt import searcher_input_template_en - # from lagent.agents.mindsearch_prompt import searcher_system_prompt_en - from lagent.agents.mindsearch_prompt import GRAPH_PROMPT_CN, searcher_input_template_cn, searcher_system_prompt_cn - from lagent.llms import INTERNLM2_META, LMDeployClient - - llm = LMDeployClient( - model_name='internlm2-chat-7b', - url='http://22.8.24.123:23333', - meta_template=INTERNLM2_META, - max_new_tokens=4096, - top_p=0.8, - top_k=1, - temperature=0.8, - repetition_penalty=1.0, - stop_words=['<|im_end|>']) - - agent = MindSearchAgent( - llm=llm, - searcher_cfg=dict( - llm=llm, - plugin_executor=ActionExecutor(BingBrowser('Your API Key')), - protocol=MindSearchProtocol( - meta_prompt=datetime.now().strftime( - 'The current date is %Y-%m-%d.'), - plugin_prompt=searcher_system_prompt_cn, - ), - template=searcher_input_template_cn), - protocol=MindSearchProtocol( - meta_prompt=datetime.now().strftime( - 'The current date is %Y-%m-%d.'), - interpreter_prompt=GRAPH_PROMPT_CN, - response_prompt='请根据上文内容对问题给出详细的回复'), - max_turn=10) - return agent - - -plan_agent = init_agent() - -PLANNER_HISTORY = [] -SEARCHER_HISTORY = [] - - -def rst_mem(history_planner: list, history_searcher: list): - ''' - Reset the chatbot memory. - ''' - history_planner = [] - history_searcher = [] - if PLANNER_HISTORY: - PLANNER_HISTORY.clear() - return history_planner, history_searcher - - -def format_response(gr_history, agent_return): - if agent_return.state in [ - AgentStatusCode.STREAM_ING, AgentStatusCode.ANSWER_ING - ]: - gr_history[-1][1] = agent_return.response - elif agent_return.state == AgentStatusCode.PLUGIN_START: - thought = gr_history[-1][1].split('```')[0] - if agent_return.response.startswith('```'): - gr_history[-1][1] = thought + '\n' + agent_return.response - elif agent_return.state == AgentStatusCode.PLUGIN_END: - thought = gr_history[-1][1].split('```')[0] - if isinstance(agent_return.response, dict): - gr_history[-1][ - 1] = thought + '\n' + f'```json\n{json.dumps(agent_return.response, ensure_ascii=False, indent=4)}\n```' - elif agent_return.state == AgentStatusCode.PLUGIN_RETURN: - assert agent_return.inner_steps[-1]['role'] == 'environment' - item = agent_return.inner_steps[-1] - gr_history.append([ - None, - f"```json\n{json.dumps(item['content'], ensure_ascii=False, indent=4)}\n```" - ]) - gr_history.append([None, '']) - return - - -def predict(history_planner, history_searcher, max_new_tokens, top_p, - temperature): - global PLANNER_HISTORY - PLANNER_HISTORY.append(dict(role='user', content=history_planner[-1][0])) - new_search_turn = True - for resp in plan_agent.stream_chat( - PLANNER_HISTORY, - max_new_tokens=max_new_tokens, - top_p=top_p, - temperature=temperature): - if isinstance(resp, tuple): - agent_return, node_name = resp - if node_name in ['root', 'response']: - continue - agent_return = agent_return.nodes[node_name]['detail'] - if new_search_turn: - history_searcher.append([agent_return.content, '']) - new_search_turn = False - format_response(history_searcher, agent_return) - if agent_return.state == AgentStatusCode.END: - new_search_turn = True - yield history_planner, history_searcher - else: - agent_return = resp - new_search_turn = True - format_response(history_planner, agent_return) - if agent_return.state == AgentStatusCode.END: - PLANNER_HISTORY = agent_return.inner_steps - yield history_planner, history_searcher - return history_planner, history_searcher - - -with gr.Blocks() as demo: - gr.HTML("""

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