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README.md

@@ -1,6 +1,12 @@
 <div id="top"></div>
+
+<div align="center">
+
+# 思·索 MindSearch<br>Towards Deeper and Wider Answer Engine with LLM Agents
+| [Research Preview](https://mindsearch.netlify.app/) | [Paper]() |
+</div>
+
 <div align="center">
-  <img src="docs/imgs/lagent_logo.png" width="450"/>
 
 [![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)
@@ -10,70 +16,39 @@
 ![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) | [日本語](README_ja_JP.md) | [हिंदी](README_in_HIN.md) | [বাংলা](README_in_beng.md) | [한국어](README_KR_Kr.md)
+English | [简体中文](README_zh-CN.md)
 
 </div>
 
 <p align="center">
     👋 join us on <a href="https://twitter.com/intern_lm" target="_blank">𝕏 (Twitter)</a>, <a href="https://discord.gg/xa29JuW87d" target="_blank">Discord</a> and <a href="https://r.vansin.top/?r=internwx" target="_blank">WeChat</a>
 </p>
 
-<div align="center">
-
-https://github.com/InternLM/lagent/assets/24622904/3242f9bf-32d2-4907-8815-e16a75a4ac0e
-
-</div>
-
-## Getting Started
+## ✨ Introduction
 
-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.
+#### Demo Video here
 
-### Installation
+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.
 
-Install with pip (Recommended).
+## 👀 How MindSearch Works
 
-```bash
-pip install lagent
-```
-
-### Run a Web Demo
-
-You need to install Streamlit first.
-
-```bash
-# pip install streamlit
-streamlit run examples/internlm2_agent_web_demo.py
-```
+<img src="docs/imgs/mindsearch_framework.png">
 
-## What's Lagent?
+MindSearch consists of a Web Planner and Web Searcher. WebPlanner models the complex problem-solving minds as a dynamic graph construction process: it decomposes the question into sub-queries as graph nodes and progressively extends the graph based on the search result from WebSearcher. Tasked with each sub-query, WebSearcher performs hierarchical information retrieval with search engines and collects valuable information for WebPlanner.
+The multi-agent design of MindSearch dispatches a load of processing massive information to different agents, enabling the whole framework to process a much longer context.
 
-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:
+## ⚽️ Getting Started
 
-![image](https://github.com/InternLM/lagent/assets/24351120/cefc4145-2ad8-4f80-b88b-97c05d1b9d3e)
+### Lagent Installation
 
-## Major Features
+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.
 
-- 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
-
-<p>
-  <a href="">
-    <img src="https://img.shields.io/badge/Python-007ACC?style=for-the-badge&logo=python&logoColor=yellow" alt="python" />
-  </a>
-
-### All Thanks To Our Contributors:
-
-<a href="https://github.com/InternLM/lagent/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=InternLM/lagent" />
-</a>
+### MindSearch
 
 ## Citation
 
@@ -90,6 +65,4 @@ If you find this project useful in your research, please consider cite:
 
 ## License
 
-This project is released under the [Apache 2.0 license](LICENSE).
-
-<p align="right"><a href="#top">🔼 Back to top</a></p>
+This project is released under the [Apache 2.0 license](LICENSE).