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fix: Modify the documentation of the Demos and Tutorials chapter (mil…
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Signed-off-by: HuaSheng2000 <[email protected]>
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27 changes: 25 additions & 2 deletions README.md
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Expand Up @@ -93,6 +93,31 @@ Milvus is trusted by AI developers to build applications such as text and image

Here is a selection of demos and tutorials to show how to build various types of AI applications made with Milvus:

You can explore a comprehensive [Tutorials Overview](https://milvus.io/docs/tutorials-overview.md) covering topics such as Retrieval-Augmented Generation (RAG), Semantic Search, Hybrid Search, Question Answering, Recommendation Systems, and various quick-start guides. These resources are designed to help you get started quickly and efficiently.

| Tutorial | Use Case | Related Milvus Features |
| -------- | -------- | --------- |
| [Build RAG with Milvus](https://milvus.io/docs/build-rag-with-milvus.md) | RAG | vector search |
| [Multimodal RAG with Milvus](https://milvus.io/docs/multimodal_rag_with_milvus.md) | RAG | vector search, dynamic field |
| [Image Search with Milvus](https://milvus.io/docs/image_similarity_search.md) | Semantic Search | vector search, dynamic field |
| [Hybrid Search with Milvus](https://milvus.io/docs/hybrid_search_with_milvus.md) | Hybrid Search | hybrid search, multi vector, dense embedding, sparse embedding |
| [Multimodal Search using Multi Vectors](https://milvus.io/docs/multimodal_rag_with_milvus.md) | Semantic Search | multi vector, hybrid search |
| [Question Answering System](https://milvus.io/docs/question_answering_system.md) | Question Answering | vector search |
| [Recommender System](https://milvus.io/docs/recommendation_system.md) | Recommendation System | vector search |
| [Video Similarity Search](https://milvus.io/docs/video_similarity_search.md) | Semantic Search | vector search |
| [Audio Similarity Search](https://milvus.io/docs/audio_similarity_search.md) | Semantic Search | vector search |
| [DNA Classification](https://milvus.io/docs/dna_sequence_classification.md) | Classification | vector search |
| [Text Search Engine](https://milvus.io/docs/text_search_engine.md) | Semantic Search | vector search |
| [Search Image by Text](https://milvus.io/docs/text_image_search.md) | Semantic Search | vector search |
| [Image Deduplication](https://milvus.io/docs/image_deduplication_system.md) | Deduplication | vector search |
| [Graph RAG with Milvus](https://milvus.io/docs/graph_rag_with_milvus.md) | RAG | graph search |
| [Contextual Retrieval with Milvus](https://milvus.io/docs/contextual_retrieval_with_milvus.md) | Quickstart | vector search |
| [HDBSCAN Clustering with Milvus](https://milvus.io/docs/hdbscan_clustering_with_milvus.md) | Quickstart | vector search |
| [Use ColPali for Multi-Modal Retrieval with Milvus](https://milvus.io/docs/use_ColPali_with_milvus.md) | Quickstart | vector search |
| [Vector Visualization](https://milvus.io/docs/vector_visualization.md) | Quickstart | vector search |
| [Movie Recommendation with Milvus](https://milvus.io/docs/movie_recommendation_with_milvus.md) | Recommendation System | vector search |
| [Funnel Search with Matryoshka Embeddings](https://milvus.io/docs/funnel_search_with_matryoshka.md) | Quickstart | vector search |

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</table>

You can explore a comprehensive [Tutorials Overview](https://milvus.io/docs/tutorials-overview.md) covering topics such as Retrieval-Augmented Generation (RAG), Semantic Search, Hybrid Search, Question Answering, Recommendation Systems, and various quick-start guides. These resources are designed to help you get started quickly and efficiently.

## Ecosystem and Integration
Milvus integrates with a comprehensive suite of [AI development tools](https://milvus.io/docs/integrations_overview.md), such as LangChain, LlamaIndex, OpenAI and HuggingFace, making it an ideal vector store for GenAI applications such as Retrieval-Augmented Generation (RAG). Milvus works with both open-source embedding models and embedding service, in text, image and video modalities. Milvus also provides a convenient util [`pymilvus[model]`](https://milvus.io/docs/embeddings.md), users can use the simple wrapper code to transform unstructured data into vector embeddings and leverage reranking models for optimized search results. The Milvus ecosystem also includes [Attu](https://github.com/zilliztech/attu?tab=readme-ov-file#attu) for GUI-based administration, [Birdwatcher](https://milvus.io/docs/birdwatcher_overview.md) for system debugging, [Prometheus/Grafana](https://milvus.io/docs/monitor_overview.md) for monitoring, [Milvus CDC](https://milvus.io/docs/milvus-cdc-overview.md) for data synchronization, [VTS](https://github.com/zilliztech/vts?tab=readme-ov-file#vts) for data migration and data connectors for [Spark](https://milvus.io/docs/integrate_with_spark.md#Spark-Milvus-Connector-User-Guide), [Kafka](https://github.com/zilliztech/kafka-connect-milvus?tab=readme-ov-file#kafka-connect-milvus-connector), [Fivetran](https://fivetran.com/docs/destinations/milvus), and [Airbyte](https://milvus.io/docs/integrate_with_airbyte.md) to build search pipelines.

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## 入门指南

### 教程

你可以从[教程概述](https://milvus.io/docs/tutorials-overview.md)中,找到涵盖 RAG(检索增强生成)、语义搜索、混合搜索、问答、推荐系统等主题以及各种快速入门指南。这些资源旨在帮助你快速高效地入门。

| 教程 | 使用场景 | 相关 Milvus 功能 |
| -------- | -------- | --------- |
| [使用 Milvus 构建 RAG](https://milvus.io/docs/build-rag-with-milvus.md) | RAG | 向量搜索 |
| [使用 Milvus 构建多模态 RAG](https://milvus.io/docs/multimodal_rag_with_milvus.md) | RAG | 向量搜索, 动态字段 |
| [使用 Milvus 进行图像搜索](https://milvus.io/docs/image_similarity_search.md) | 语义搜索 | 向量搜索, 动态字段 |
| [使用 Milvus 进行混合搜索](https://milvus.io/docs/hybrid_search_with_milvus.md) | 混合搜索 | 混合搜索, 多向量, 密集嵌入, 稀疏嵌入 |
| [使用多向量实现多模态搜索](https://milvus.io/docs/multimodal_rag_with_milvus.md) | 语义搜索 | 多向量, 混合搜索 |
| [问答系统](https://milvus.io/docs/question_answering_system.md) | 问答系统 | 向量搜索 |
| [推荐系统](https://milvus.io/docs/recommendation_system.md) | 推荐系统 | 向量搜索 |
| [视频相似性搜索](https://milvus.io/docs/video_similarity_search.md) | 语义搜索 | 向量搜索 |
| [音频相似性搜索](https://milvus.io/docs/audio_similarity_search.md) | 语义搜索 | 向量搜索 |
| [DNA 分类](https://milvus.io/docs/dna_sequence_classification.md) | 分类 | 向量搜索 |
| [文本搜索引擎](https://milvus.io/docs/text_search_engine.md) | 语义搜索 | 向量搜索 |
| [通过文本搜索图像](https://milvus.io/docs/text_image_search.md) | 语义搜索 | 向量搜索 |
| [图像去重](https://milvus.io/docs/image_deduplication_system.md) | 重复数据删除 | 向量搜索 |
| [使用 Milvus 构建图形 RAG](https://milvus.io/docs/graph_rag_with_milvus.md) | RAG | 图搜索 |
| [使用 Milvus 进行上下文检索](https://milvus.io/docs/contextual_retrieval_with_milvus.md) | 快速入门 | 向量搜索 |
| [使用 Milvus 进行 HDBSCAN 聚类](https://milvus.io/docs/hdbscan_clustering_with_milvus.md) | 快速入门 | 向量搜索 |
| [使用 ColPali 实现多模态检索](https://milvus.io/docs/use_ColPali_with_milvus.md) | 快速入门 | 向量搜索 |
| [向量可视化](https://milvus.io/docs/vector_visualization.md) | 快速入门 | 向量搜索 |
| [基于 Milvus 的电影推荐](https://milvus.io/docs/movie_recommendation_with_milvus.md) | 推荐系统 | 向量搜索 |
| [使用 Matryoshka 嵌入进行漏斗搜索](https://milvus.io/docs/funnel_search_with_matryoshka.md) | 快速入门 | 向量搜索 |

### 应用场景

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迅速检索相似化学分子式。

### 教程

你可以从[教程概述](https://milvus.io/docs/tutorials-overview.md)中,找到涵盖 RAG(检索增强生成)、语义搜索、混合搜索、问答、推荐系统等主题以及各种快速入门指南。这些资源旨在帮助你快速高效地入门。

## 训练营

Milvus [训练营](https://github.com/milvus-io/bootcamp)能够帮助你了解向量数据库的操作及各种应用场景。通过 Milvus 训练营探索如何进行 Milvus 性能测评,搭建智能问答机器人、推荐系统、以图搜图系统、分子式检索系统等。
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