{"id":13510391,"url":"https://github.com/lancedb/vectordb-recipes","last_synced_at":"2025-10-17T04:43:38.511Z","repository":{"id":176694072,"uuid":"658219396","full_name":"lancedb/vectordb-recipes","owner":"lancedb","description":"High quality resources \u0026 applications for LLMs, multi-modal models and VectorDBs ","archived":false,"fork":false,"pushed_at":"2025-05-10T09:46:14.000Z","size":231985,"stargazers_count":761,"open_issues_count":3,"forks_count":138,"subscribers_count":10,"default_branch":"main","last_synced_at":"2025-05-10T10:33:23.015Z","etag":null,"topics":["agents","ai","deep-learning","embeddings","fine-tuning","gpt","gpt-4-vision","langchain","llama-index","llms","machine-learning","multimodal","openai","rag","vector-database"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lancedb.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2023-06-25T06:10:35.000Z","updated_at":"2025-05-10T09:46:18.000Z","dependencies_parsed_at":"2023-10-15T17:24:22.176Z","dependency_job_id":"5ad675ec-6302-4943-af82-3d8a5a961682","html_url":"https://github.com/lancedb/vectordb-recipes","commit_stats":{"total_commits":449,"total_committers":33,"mean_commits":"13.606060606060606","dds":0.7973273942093542,"last_synced_commit":"d92c09c1fbfd4ae379fdb182378dce14856f8fed"},"previous_names":["lancedb/vectordb-recipes"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lancedb%2Fvectordb-recipes","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lancedb%2Fvectordb-recipes/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lancedb%2Fvectordb-recipes/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lancedb%2Fvectordb-recipes/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lancedb","download_url":"https://codeload.github.com/lancedb/vectordb-recipes/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254254042,"owners_count":22039792,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agents","ai","deep-learning","embeddings","fine-tuning","gpt","gpt-4-vision","langchain","llama-index","llms","machine-learning","multimodal","openai","rag","vector-database"],"created_at":"2024-08-01T02:01:37.173Z","updated_at":"2025-10-17T04:43:28.487Z","avatar_url":"https://github.com/lancedb.png","language":"Jupyter Notebook","funding_links":[],"categories":["Jupyter Notebook","Langchain","Large Language Models ##","ai","Tutorials \u0026 Hands-on Code"],"sub_categories":["Tools"],"readme":"# VectorDB-recipes\n\u003cbr /\u003e\nDive into building GenAI applications!\nThis repository contains examples, applications, starter code, \u0026 tutorials to help you kickstart your GenAI projects.\n\n- These are built using LanceDB, a free, open-source, serverless vectorDB that **requires no setup**. \n- It **integrates into Python data ecosystem** so you can simply start using these in your existing data pipelines in pandas, arrow, pydantic etc.\n- LanceDB has **native Typescript SDK** using which you can **run vector search** in serverless functions!\n\n\u003cimg src=\"https://github.com/lancedb/vectordb-recipes/assets/5846846/d284accb-24b9-4404-8605-56483160e579\" height=\"85%\" width=\"85%\" /\u003e\n\n\u003cbr /\u003e\nJoin our community for support - \u003ca href=\"https://discord.gg/zMM32dvNtd\"\u003eDiscord\u003c/a\u003e •\n\u003ca href=\"https://twitter.com/lancedb\"\u003eTwitter\u003c/a\u003e\n\n---\n\nThis repository is divided into 2 sections:\n- [Examples](#examples) - Get right into the code with minimal introduction, aimed at getting you from an idea to PoC within minutes!\n- [Applications](#projects--applications) - Ready to use Python and web apps using applied LLMs, VectorDB and GenAI tools\n\n\nThe following examples are organized into different tables to make similar types of examples easily accessible.\n\n### Sections\n\n- [Build from Scratch](#build-from-scratch) - Build applications/examples from scratch using LanceDB for efficient vector-based document retrieval.\n- [Multimodal](#multimodal) - Build a multimodal search application with input text or image as queries.\n- [RAG](#rag) - Build a variety of RAG by loading data from different formats and query with text.\n- [Vector Search](#vector-search) - Build vector search application using different search algorithms.\n- [Chatbot](#chatbot) - Build chatbot application where user input queries to retrieve relevant context and generate coherent, context-aware replies.\n- [Evalution](#evaluation) - Evaluate reference and candidate texts to measure their performance on various metrics.\n- [AI Agents](#ai-agents) - Design an application powered with AI agents to exchange information, coordinate tasks, and achieve shared goals effectively.\n- [Recommender Systems](#recommender-systems) - Build Recommendation systems which generate personalized recommendations and enhance user experience.\n- [Concepts](#concepts) - Concepts related to LLM applications pipeline to ensures accurate information retrieval.\n\n\n### 🌟 New 🌟 \n- Multimodal Vector Search: **Voyage AI x LanceDB** - \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/voyagexlancedb/Voyage_x_LanceDB.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e\n- Build autonomous Customer support agent using Langgraph - \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/customer_support_agent_langgraph/LangGraph_LanceDB.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e\n- Comparing **ModernBERT** with series of Bert Models - \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/modernbert_comparison/ModernBERT.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e\n- Comparing **Deepseek's r1 VS OpenAI's o1** for RAG - [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/Deepseek_R1_VS_GPT_4o/README.md)\n- Testing **Deepseek Janus-Pro's** multimodality over Flickr 30K - \n\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Janus-Pro/Janus_Pro.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e\n\n### Build from Scratch\n\nBuild applications/examples using LanceDB for efficient vector-based document retrieval.\n\n| Build from Scratch \u0026nbsp; \u0026nbsp;| Interactive Notebook \u0026 Scripts \u0026nbsp; | \n|-------- | -------------: |\n|||\n| [Build RAG from Scratch](./tutorials/RAG-from-Scratch) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/RAG-from-Scratch/RAG_from_Scratch.ipynb) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|  |\n| [Local RAG from Scratch with Llama3](./tutorials/Local-RAG-from-Scratch) | [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./tutorials/Local-RAG-from-Scratch/rag.py) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|  |\n| [Multi-Head RAG from Scratch](./tutorials/Multi-Head-RAG-from-Scratch/) | [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./tutorials/Multi-Head-RAG-from-Scratch/main.py) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|  |\n||||\n\n### MultiModal\n\nCreate a multimodal search application using LanceDB for efficient vector-based retrieval of text and image data. Input text or image queries to find the most relevant documents and images from your corpus.\n\n| Multimodal \u0026nbsp; \u0026nbsp;| Interactive Notebook \u0026 Scripts \u0026nbsp; | Blog |\n| --------- | -------------------------- | ----------- |\n||||\n| [Multimodal CLIP: DiffusionDB](/examples/multimodal_clip_diffusiondb/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/multimodal_clip_diffusiondb/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/multimodal_clip_diffusiondb/main.py) [![LLM](https://img.shields.io/badge/local-llm-green)](#)    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/multi-modal-ai-made-easy-with-lancedb-clip-5aaf8801c939/)|\n| [Multimodal CLIP: Youtube videos](/examples/multimodal_video_search/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/multimodal_video_search/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/multimodal_video_search/main.py) [![LLM](https://img.shields.io/badge/local-llm-green)](#)    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/multi-modal-ai-made-easy-with-lancedb-clip-5aaf8801c939/)|\n| [Cambrian-1: Vision centric exploration of images](https://www.kaggle.com/code/prasantdixit/cambrian-1-vision-centric-exploration-of-images/) | [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/code/prasantdixit/cambrian-1-vision-centric-exploration-of-images/) [![LLM](https://img.shields.io/badge/local-llm-green)](#)   [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/cambrian-1-vision-centric-exploration/)|\n| [Multimodal Jina CLIP-V2 : Food Search ](/examples/multimodal_jina_clipv2/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/multimodal_jina_clipv2/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/multimodal_jina_clipv2)    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|\n| [Multimodal vector search: Voyage AI X LanceDB](./examples/voyagexlancedb/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/voyagexlancedb/Voyage_x_LanceDB.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)||\n||||\n\n### RAG\n\nDevelop a Retrieval-Augmented Generation (RAG) application using LanceDB for efficient vector-based information retrieval. Input text queries to retrieve relevant documents and generate comprehensive answers by combining retrieved information.\n\n| RAG \u0026nbsp; \u0026nbsp;| Interactive Notebook \u0026 Scripts | Blog |\n| --------- | -------------------------- | ----------- |\n||||\n| [RAG using Deepseek R1 vs OpenAI o1](./examples/Deepseek_R1_VS_GPT_4o) | [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/Deepseek_R1_VS_GPT_4o/README.md)  [![Analysis](https://img.shields.io/badge/Analysis-FF3333)](#) |\n| [RAG On PDF](/examples/RAG-On-PDF/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/RAG-On-PDF/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/local-llm-green)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|\n| [RAG with Contextual Retrieval and Hybrid search](./examples/Contextual-RAG/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Contextual-RAG/Anthropic_Contextual_RAG.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#)  [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/guide-to-use-contextual-retrieval-and-prompt-caching-with-lancedb/) |\n| [RAG with Matryoshka Embeddings and LlamaIndex](./tutorials/RAG-with_MatryoshkaEmbed-Llamaindex/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/RAG-with_MatryoshkaEmbed-Llamaindex/RAG_with_MatryoshkaEmbedding_and_Llamaindex.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)||\n| [RAG with IBM Watsonx](./examples/RAG-with-watsonx/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/RAG-with-watsonx/Watsonx_example.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![watsonx LLM](https://img.shields.io/badge/watsonx-api-lightblue)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)||\n| [Cognee RAG](/examples/cognee-RAG/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/cognee-RAG/cognee_demo.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e ||\n| [Improve RAG with Re-ranking](/examples/RAG_Reranking/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/RAG_Reranking/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/local-llm-green)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/simplest-method-to-improve-rag-pipeline-re-ranking-cf6eaec6d544)|\n| [Instruct-Multitask](./examples/instruct-multitask) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/instruct-multitask/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/instruct-multitask/main.py)  [![LLM](https://img.shields.io/badge/local-llm-green)](#)   [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/multitask-embedding-with-lancedb-be18ec397543)|\n| [Improve RAG with HyDE](/examples/Advance-RAG-with-HyDE/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Advance-RAG-with-HyDE/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e   [![LLM](https://img.shields.io/badge/openai-api-white)](#)  [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/advanced-rag-precise-zero-shot-dense-retrieval-with-hyde-0946c54dfdcb)|\n| [Improve RAG with LOTR ](/examples/Advance_RAG_LOTR/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Advance_RAG_LOTR/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)  [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/better-rag-with-lotr-lord-of-retriever-23c8336b9a35)|\n| [Advanced RAG: Context Enrichment Window](./examples/Advanced_RAG_Context_Enrichment_Window/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Advanced_RAG_Context_Enrichment_Window/Advanced_RAG_Context_Enrichment_Window.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)  [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/https://blog.lancedb.com/advanced-rag-context-enrichment-window/)|\n| [Advanced RAG: Late Chunking](./examples/Advanced_RAG_Late_Chunking/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Advanced_RAG_Late_Chunking/Late_Chunking_(Chunked_Pooling).ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)  [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/late-chunking-aka-chunked-pooling-2/)|\n| [Advanced RAG: Parent Document Retriever](/examples/parent_document_retriever/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/parent_document_retriever/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)  [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/modified-rag-parent-document-bigger-chunk-retriever-62b3d1e79bc6)|\n| [Corrective RAG with Langgraph](./tutorials/Corrective-RAG-with_Langgraph/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/Corrective-RAG-with_Langgraph/CRAG_with_Langgraph.ipynb) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/implementing-corrective-rag-in-the-easiest-way-2/)|\n| [Contextual-Compression-with-RAG](/examples/Contextual-Compression-with-RAG/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Contextual-Compression-with-RAG/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#)   [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/enhance-rag-integrate-contextual-compression-and-filtering-for-precision-a29d4a810301/) |\n| [Improve RAG with FLARE](./examples/better-rag-FLAIR) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/better-rag-FLAIR/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/better-rag-with-active-retrieval-augmented-generation-flare-3b66646e2a9f/) |\n| [Agentic RAG ](/tutorials/Agentic_RAG/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/Agentic_RAG/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)|\n| [GraphRAG ](/examples/Graphrag/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Graphrag/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/graphrag-hierarchical-approach-to-retrieval-augmented-generation/)|\n| [GraphRAG with CSV File ](/tutorials/GraphRAG_CSV/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/GraphRAG_CSV/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://aksdesai1998.medium.com/optimizing-graphrag-with-microsoft-for-csv-data-a-guide-with-lancedb-8e4150b93e37)|\n| [GraphRAG with cognee - Multimedia ](/tutorials/GraphRAG_with_cognee/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/GraphRAG_with_cognee/cognee_multimedia_demo.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)||\n||||\n\n### Vector Search\n\nBuild a vector search application using LanceDB for efficient vector-based document retrieval. Input text queries to find the most relevant documents from your corpus.\n\n| Vector Search \u0026nbsp; \u0026nbsp;| Interactive Notebook \u0026 Scripts \u0026nbsp; | Blog |\n| --------- | -------------------------- | ----------- |\n||||\n| [Inbuilt Hybrid Search](/examples/Inbuilt-Hybrid-Search) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Inbuilt-Hybrid-Search/Inbuilt_Hybrid_Search_with_LanceDB.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#)    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)||\n| [Hybrid search BM25 \u0026 lancedb ](./examples/Hybrid_search_bm25_lancedb/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Hybrid_search_bm25_lancedb/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e   [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#) |[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/hybrid-search-combining-bm25-and-semantic-search-for-better-results-with-lan-1358038fe7e6)|\n| [NER powered Semantic Search](./tutorials/NER-powered-Semantic-Search) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/NER-powered-Semantic-Search/NER_powered_Semantic_Search_with_LanceDB.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/ner-powered-semantic-search-using-lancedb-51051dc3e493) |\n| [Vector Arithmetic with LanceDB](./examples/Vector-Arithmetic-with-LanceDB/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Vector-Arithmetic-with-LanceDB/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e   [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#) |[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/vector-arithmetic-with-lancedb-an-intro-to-vector-embeddings/)|\n| [Summarize and Search Reddit Posts](./examples/Reddit-summarization-and-search/) | \u003ca href=\"https://github.com/lancedb/vectordb-recipes/blob/main/examples/Reddit-summarization-and-search/subreddit_summarization_querying.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|\n| [Imagebind demo app](./examples/imagebind_demo/) | \u003ca href=\"https://huggingface.co/spaces/raghavd99/imagebind2\"\u003e\u003cimg src=\"https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo-with-title.svg\" alt=\"hf spaces\" style=\"width: 80px; vertical-align: middle; background-color: white;\"\u003e\u003c/a\u003e  [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|\n| [Search Within Images](/examples/search-within-images-with-sam-and-clip/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/search-within-images-with-sam-and-clip/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#)   [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/search-within-an-image-331b54e4285e)|\n| [Zero Shot Object Detection with CLIP](./examples/zero-shot-object-detection-CLIP/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/zero-shot-object-detection-CLIP/zero_shot_object_detection_clip.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|\n| [Vector Search with TransformersJS](./examples/js-transformers/) |[![JS](https://img.shields.io/badge/javascript-%23323330.svg?style=for-the-badge\u0026logo=javascript\u0026logoColor=%23F7DF1E)](./examples/js-transformers/index.js) [![LLM](https://img.shields.io/badge/local-llm-green)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)|  |\n| [Geospatial Recommendation System](./examples/Geospatial-Recommendation-System/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Geospatial-Recommendation-System/geospatial-recommendation.ipynb) [![LLM](https://img.shields.io/badge/local-llm-green)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|\n| [Accelerate Vector Search Applications Using OpenVINO](/examples/Accelerate-Vector-Search-Applications-Using-OpenVINO/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Accelerate-Vector-Search-Applications-Using-OpenVINO/clip_text_image_search.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/accelerate-vector-search-applications-using-openvino-lancedb/)|\n||||\n\n### Chatbot\n\nCreate a chatbot application using LanceDB for efficient vector-based response generation. Input user queries to retrieve relevant context and generate coherent, context-aware replies.\n\n| Chatbot \u0026nbsp; \u0026nbsp;| Interactive Notebook \u0026 Scripts \u0026nbsp; | Blog \u0026nbsp;|\n| --------- | -------------------------- | ----------- |\n||||\n| [Databricks DBRX Website Bot](./examples/databricks_DBRX_website_bot/) | [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/databricks_DBRX_website_bot/main.py) [![Databricks LLM](https://img.shields.io/badge/databricks-api-red)](#)    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|\n| [CLI-based SDK Manual Chatbot with Phidata](/examples/CLI-SDK-Manual-Chatbot-Locally/) | [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/CLI-SDK-Manual-Chatbot-Locally/assistant.py) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|\n| [Youtube transcript search bot](/examples/Youtube-Search-QA-Bot/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Youtube-Search-QA-Bot/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/Youtube-Search-QA-Bot/main.py) [![JS](https://img.shields.io/badge/javascript-%23323330.svg?style=for-the-badge\u0026logo=javascript\u0026logoColor=%23F7DF1E)](./examples/Youtube-Search-QA-Bot/index.js) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)||\n| [Langchain: Code Docs QA bot](/examples/Code-Documentation-QA-Bot/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Code-Documentation-QA-Bot/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/Code-Documentation-QA-Bot/main.py) [![JS](https://img.shields.io/badge/javascript-%23323330.svg?style=for-the-badge\u0026logo=javascript\u0026logoColor=%23F7DF1E)](./examples/Code-Documentation-QA-Bot/index.js) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)||\n| [Chatbot with any website using Crawl4AI ](/examples/CrawlerQ\u0026A_website/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/CrawlerQ\u0026A_website/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/Code-Documentation-QA-Bot/main.py) [![LLM](https://img.shields.io/badge/openai-api-white)](#)  [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|\n| [Context-Aware Chatbot using Llama 2 \u0026 LanceDB](./tutorials/chatbot_using_Llama2_\u0026_lanceDB) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/chatbot_using_Llama2_\u0026_lanceDB/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/context-aware-chatbot-using-llama-2-lancedb-as-vector-database-4d771d95c755) |\n||||\n\n\n### Evaluation\n\nDevelop an evaluation application. Input reference and candidate texts to measure their performance on various metrics.\n\n| Evaluation \u0026nbsp; \u0026nbsp;| Interactive Notebook \u0026 Scripts \u0026nbsp; | Blog |\n| --------- | -------------------------- | ----------- |\n||||\n| [Evaluating RAG with RAGAs](./examples/Evaluating_RAG_with_RAGAs/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Evaluating_RAG_with_RAGAs/Evaluating_RAG_with_RAGAs.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e   [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|  |\n||||\n\n### AI Agents\n\nDesign an AI agents coordination application with LanceDB for efficient vector-based communication and collaboration. Input queries to enable AI agents to exchange information, coordinate tasks, and achieve shared goals effectively.\n\n| AI Agents \u0026nbsp; \u0026nbsp;| Interactive Notebook \u0026 Scripts \u0026nbsp; | Blog |\n| --------- | -------------------------- | ----------- |\n||||\n| [AI email assistant with Composio](/examples/AI-Email-Assistant-with-Composio/) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/AI-Email-Assistant-with-Composio/composio-lance.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)   [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|\n| [Assitant Bot with OpenAI Swarm](./examples/assistance-bot-with-swarm/) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/assistance-bot-with-swarm/assitant_bot_with_swarm.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)   [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|\n| [AI Trends Searcher with CrewAI](./examples/AI-Trends-with-CrewAI/) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/AI-Trends-with-CrewAI/CrewAI_AI_Trends.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)    [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/track-ai-trends-crewai-agents-rag/)|\n| [SuperAgent Autogen](/examples/SuperAgent_Autogen) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/SuperAgent_Autogen/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)||\n| [Build autonomous Customer support agent using Langgraph](./examples/customer_support_agent_langgraph/LangGraph_LanceDB.ipynb) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main//examples/customer_support_agent_langgraph/LangGraph_LanceDB.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e     [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/agentic-rag-using-langgraph-building-a-simple-customer-support-autonomous-agent/)|\n| [AI Agents: Reducing Hallucination](/examples/reducing_hallucinations_ai_agents/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/reducing_hallucinations_ai_agents/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/reducing_hallucinations_ai_agents/main.py) [![JS](https://img.shields.io/badge/javascript-%23323330.svg?style=for-the-badge\u0026logo=javascript\u0026logoColor=%23F7DF1E)](./examples/reducing_hallucinations_ai_agents/index.js) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#) |[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/how-to-reduce-hallucinations-from-llm-powered-agents-using-long-term-memory-72f262c3cc1f/)|\n| [Multi Document Agentic RAG](./examples/multi-document-agentic-rag/) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/multi-document-agentic-rag/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)     [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/multi-document-agentic-rag/)|\n| [RASA: Customer Support Bot](./examples/RASA_Customer-support-bot) |\u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/RASA_Customer-support-bot/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e  [![LLM](https://img.shields.io/badge/openai-api-white)](#)     [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)|[![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/customer-support-bot-rasa-x-lancedb/)|\n||||\n\n### Recommender Systems\n\nCreate a recommender system application with LanceDB for efficient vector-based item recommendation. Input user preferences or item features to generate personalized recommendations and enhance user experience.\n\n| Recommender Systems | Interactive Notebook \u0026 Scripts \u0026nbsp; | Blog |\n| --------- | -------------------------- | ----------- |\n||||\n| [Movie Recommender](/examples/movie-recommender/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/movie-recommender/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/movie-recommender/main.py) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|  |\n| [Product Recommender](./examples/product-recommender/) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/product-recommender/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/product-recommender/main.py) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)| |\n| [Arxiv paper recommender](/examples/arxiv-recommender) | \u003ca href=\"https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/arxiv-recommender/main.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./examples/arxiv-recommender/main.py) [![LLM](https://img.shields.io/badge/local-llm-green)](#)  [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|  |\n| [Music Recommender](/applications/Music_Recommendation/) | [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./applications/Music_Recommendation/app_music.py) [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)| |||||\n||||\n\n### Concepts\n\nCheckout concepts of LLM applications pipeline to ensures accurate information retrieval.\n\n| Concepts | Interactive Notebook | Blog |\n| --------- | -------------------------- | ----------- |\n|           |                            |             |\n| [A Primer on Text Chunking and its Types](./tutorials/different-types-text-chunking-in-RAG) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/different-types-text-chunking-in-RAG/Text_Chunking_on_RAG_application_with_LanceDB.ipynb) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/a-primer-on-text-chunking-and-its-types-a420efc96a13) |\n| [Langchain LlamaIndex Chunking](./tutorials/Langchain-LlamaIndex-Chunking) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/Langchain-LlamaIndex-Chunking/Langchain_Llamaindex_chunking.ipynb) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/chunking-techniques-with-langchain-and-llamaindex/) |\n| [Create structured dataset using Instructor](./tutorials/NER-dataset-with-Instructor/) | [![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)](./tutorials/NER-dataset-with-Instructor/main.py) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)| |\n| [Comparing Cohere Rerankers with LanceDB](./tutorials/cohere-reranker) | [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/benchmarking-cohere-reranker-with-lancedb/) |\n| [Product Quantization: Compress High Dimensional Vectors](https://blog.lancedb.com/benchmarking-lancedb-92b01032874a-2/) |[![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#) | [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/benchmarking-lancedb-92b01032874a-2/) |\n| [LLMs, RAG, \u0026 the missing storage layer for AI](https://blog.lancedb.com/llms-rag-the-missing-storage-layer-for-ai-28ded35fa984) | [![intermediate](https://img.shields.io/badge/intermediate-FFDA33)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/llms-rag-the-missing-storage-layer-for-ai-28ded35fa984/) |\n| [Fine-Tuning LLM using PEFT \u0026 QLoRA](./tutorials/fine-tuning_LLM_with_PEFT_QLoRA) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/fine-tuning_LLM_with_PEFT_QLoRA/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/optimizing-llms-a-step-by-step-guide-to-fine-tuning-with-peft-and-qlora-22eddd13d25b) |\n| [Extracting Complex tables-text from PDFs using LlamaParse  ](./tutorials/Advace_RAG_LlamaParser) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/Advace_RAG_LlamaParser/main.ipynb) [![LLM](https://img.shields.io/badge/openai-api-white)](#) [![LlamaCloud](https://img.shields.io/badge/Llama-api-pink)](#) [![beginner](https://img.shields.io/badge/beginner-B5FF33)](#)|  |\n| [Convert any Image dataset to lance Format](./tutorials/cli-sdk-to-convert-image-datasets-to-lance) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/cli-sdk-to-convert-image-datasets-to-lance/main.ipynb) [![advanced](https://img.shields.io/badge/advanced-FF3333)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge\u0026logo=ghost\u0026logoColor=%23F7DF1E)](https://blog.lancedb.com/python-package-to-convert-image-datasets-to-lance-type/) |\n||||\n\n## Projects \u0026 Applications\nThese are ready to use applications built using LanceDB serverless vector database. You can explore these open source projects, use parts of them in your projects or build your applications on top of these.\n\n### Node applications powered by LanceDB\n| Project Name                                        | Description                                                                                                          | Screenshot                                |\n|-----------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|-------------------------------------------|\n| [Writing assistant](https://github.com/lancedb/vectordb-recipes/tree/main/applications/node/lanchain_writing_assistant) | Writing assistant app using lanchain.js with LanceDB, allows you to get real time relevant suggestions and facts based on you written text to help you with your writing.                  | ![Writing assistant](https://github.com/user-attachments/assets/87354e93-df4d-40ad-922b-abcbb62d667c) |\n| [Sentence Auto-Complete](https://github.com/lancedb/vectordb-recipes/tree/main/applications/node/sentance_auto_complete) | Sentance auto complete app using lanchain.js with LanceDB, allows you to get real time relevant auto complete suggestions and facts based on you written text to help you with your writing.You can also upload your data source in the form of a pdf file.You can switch between gpt models to get faster results.                 | ![Sentence auto-complete](https://github.com/lancedb/assets/blob/main/recipes/sentance_Auto_complete.gif) |\n| [Article Recommendation](https://github.com/lancedb/vectordb-recipes/tree/main/applications/node/article_recommender) | Article Recommender: Explore vast data set of articles with Instant, Context-Aware Suggestions. Leveraging Advanced NLP, Vector Search, and Customizable Datasets, Our App Delivers Real-Time, Precise Article Recommendations. Perfect for Research, Content Curation, and Staying Informed. Unlock Smarter Insights with State-of-the-Art Technology in Content Retrieval and Discovery!\".                 | ![Article Recommendation](./applications/node/article_recommender/public/assets/article_recommendation_engine.gif) |\n| [AI Powered Job Search](https://github.com/lancedb/vectordb-recipes/tree/main/applications/node/AI_powered_job_search) | Transform your job search experience with this AI-driven application. Powered by LangChain.js, LanceDB, and advanced semantic search, it provides real-time, highly accurate job listings tailored to your preferences. Featuring customizable datasets and advanced filtering options (e.g., skills, location, job type, and salary range), this app ensures you find the right opportunities quickly and effortlessly. Best suited for job seekers, recruiters, career platforms, custom job boards.                 | ![Job Search](./applications//node/assets/AI-powered-job-search.gif) |\n| [AI Powered Multimodal meme search](https://github.com/lancedb/vectordb-recipes/tree/main/applications/node/multimodal_meme_finder) | An advanced AI-powered meme search engine that allows users to find memes using both text and image queries. By leveraging LanceDB as a high-performance vector database and Roboflow's CLIP model for embedding generation, the platform delivers fast and accurate meme retrieval.     | ![Multimodal meme search](./applications/node/mutimodal_meme_finder/public/assets/AI-powered-multimodal-meme-search.gif) |\n||||\n\n| Project Name                                        | Description                                                                                                          | Screenshot                                |\n|-----------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|-------------------------------------------|\n| [YOLOExplorer](https://github.com/lancedb/yoloexplorer) | Iterate on your YOLO / CV datasets using SQL, Vector semantic search, and more within seconds                  | ![YOLOExplorer](https://github.com/lancedb/vectordb-recipes/assets/15766192/ae513a29-8f15-4e0b-99a1-ccd8272b6131) |\n| [Website Chatbot (Deployable Vercel Template)](https://github.com/lancedb/lancedb-vercel-chatbot) | Create a chatbot from the sitemap of any website/docs of your choice. Built using vectorDB serverless native javascript package. | ![Chatbot](assets/vercel-template.gif)    |\n| [Advanced Chatbot with Parler TTS ](./applications/Chatbot_with_Parler_TTS) | This Chatbot app uses Lancedb Hybrid search, FTS \u0026 reranker method with Parlers TTS library.|![image](./assets/chatbot_tts.png)|\n| [Multi-Modal Search Engine](./applications/multimodal-search/) | Create a Multi-modal search engine app, to search images using both images or text | ![Search](https://github.com/lancedb/vectordb-recipes/assets/15766192/9805fec8-da72-44c0-be12-ddbe1c2d6afc)|\n| [Evaluate RAG](./applications/evaluate_RAG/) | A working Streamlit RAG App designed to demonstrate end to to end production grade evaluation using 50+ scores and metrics which include guards, software metrics, traditional metrics and LLM as judge metrics. It uses mixture of specialised deep learning models and LLM as Judge models to do the evaluations |![image](./applications/evaluate_RAG/APP.png)|\n| [Multi-Agent Collaboration Chatbot](./applications/Multi_collabration_chatbot/) | Multi-Agent collabration chatbot using langgraph for share-market use case using Lancedb \u0026 tools such as Polygon ,Tavily |![image](https://github.com/akashAD98/vectordb-recipes/blob/application/multi_collabartion_chatbot/assets/Streamlite_multicolabration_chat.png)|\n| [Multimodal Myntra Fashion Search Engine](https://github.com/ishandutta0098/lancedb-multimodal-myntra-fashion-search-engine) | This app uses OpenAI's CLIP to make a search engine that can understand and deal with both written words and pictures.|![image](./assets/myntra-search-engine.png)|\n| [Multilingual-RAG](./applications/Multilingual_RAG/) | Multilingual RAG with cohere embedding \u0026 support 100+ languages|![image](https://github.com/akashAD98/vectordb-recipes/assets/62583018/be65eb39-25c4-4441-98fc-6ded09689819)|\n| [Music Recommender](./applications/Music_Recommendation/) | Music Recommendation system using audio feature extraction and vector similarity search. By utilizing **LanceDB**, **PANNs** for audio tagging, and **Librosa** for audio feature extraction, the system finds and recommends tracks with similar audio characteristics based on a query song.|![image](./applications/Music_Recommendation/Music_recommndations_lancedb.png)|\n\n\n\n**🌟 New! 🌟 Applied GenAI and VectorDB course on Udacity**\nLearn about GenAI and vectorDBs using LanceDB in the recently launched [Udacity Course](https://www.udacity.com/course/building-generative-ai-solutions-with-vector-databases--cd12952)\n\n\n\u003cimg src=\"./assets/udacity-course.png\" width=\"80%\" height=\"80%\" /\u003e\n\n\n## Contributing Examples\nIf you're working on some cool applications that you'd like to add to this repo, please open a PR!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flancedb%2Fvectordb-recipes","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flancedb%2Fvectordb-recipes","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flancedb%2Fvectordb-recipes/lists"}