diff --git a/.github/workflows/docs_test.yml b/.github/workflows/docs_test.yml index 6bfea4cf..cde9dc19 100644 --- a/.github/workflows/docs_test.yml +++ b/.github/workflows/docs_test.yml @@ -30,9 +30,13 @@ jobs: uses: actions/checkout@v4 - name: Print CPU capabilities run: cat /proc/cpuinfo + - name: Install protobuf + run: | + sudo apt update + sudo apt install -y protobuf-compiler - name: Install dependecies needed for ubuntu run: | - sudo apt install -y protobuf-compiler libssl-dev + sudo apt install -y libssl-dev rustup update && rustup default - name: Set up Python uses: actions/setup-python@v5 @@ -72,9 +76,13 @@ jobs: uses: actions/setup-node@v4 with: node-version: 20 + - name: Install protobuf + run: | + sudo apt update + sudo apt install -y protobuf-compiler - name: Install dependecies needed for ubuntu run: | - sudo apt install -y protobuf-compiler libssl-dev + sudo apt install -y libssl-dev rustup update && rustup default - name: Rust cache uses: swatinem/rust-cache@v2 diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 5588c497..387db5c3 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -150,6 +150,7 @@ nav: - Chatbot: examples/python_examples/chatbot.md - Evaluation: examples/python_examples/evaluations.md - AI Agent: examples/python_examples/aiagent.md + - Recommender System: examples/python_examples/recommendersystem.md - Miscellaneous: - YouTube Transcript Search: notebooks/youtube_transcript_search.ipynb - Documentation QA Bot using LangChain: notebooks/code_qa_bot.ipynb @@ -241,6 +242,7 @@ nav: - Chatbot: examples/python_examples/chatbot.md - Evaluation: examples/python_examples/evaluations.md - AI Agent: examples/python_examples/aiagent.md + - Recommender System: examples/python_examples/recommendersystem.md - Miscellaneous: - YouTube Transcript Search: notebooks/youtube_transcript_search.ipynb - Documentation QA Bot using LangChain: notebooks/code_qa_bot.ipynb diff --git a/docs/src/examples/python_examples/rag.md b/docs/src/examples/python_examples/rag.md index 48a6411f..3d9f89fa 100644 --- a/docs/src/examples/python_examples/rag.md +++ b/docs/src/examples/python_examples/rag.md @@ -2,11 +2,11 @@ **RAG: Revolutionize Information Retrieval with LanceDB ๐Ÿ”“๐Ÿง** ==================================================================== -Unlock the full potential of Retrieval-Augmented Generation (RAG) with LanceDB, a solution for efficient vector-based information retrieval ๐Ÿ“Š. +Build RAG (Retrieval-Augmented Generation) with LanceDB, a powerful solution for efficient vector-based information retrieval ๐Ÿ“Š. **Experience the Future of Search ๐Ÿ”„** -RAG integrates large language models (LLMs) with scalable knowledge bases, enabling efficient information retrieval and answer generation ๐Ÿค–. By applying RAG to industry-specific use cases, developers can optimize query processing ๐Ÿ“Š, reduce response latency โฑ๏ธ, and improve resource utilization ๐Ÿ’ป. LanceDB provides a robust framework for integrating LLMs with external knowledge sources, facilitating accurate and informative responses ๐Ÿ“. +๐Ÿค– RAG enables AI to **retrieve** relevant information from external sources and use it to **generate** more accurate and context-specific responses. ๐Ÿ’ป LanceDB provides a robust framework for integrating LLMs with external knowledge sources ๐Ÿ“. | **RAG** | **Description** | **Links** | |----------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------| diff --git a/docs/src/examples/python_examples/recommendersystem.md b/docs/src/examples/python_examples/recommendersystem.md new file mode 100644 index 00000000..ab7e4064 --- /dev/null +++ b/docs/src/examples/python_examples/recommendersystem.md @@ -0,0 +1,37 @@ +**Recommender Systems: Personalized Discovery๐Ÿฟ๐Ÿ“บ** +============================================================== +Deliver personalized experiences with Recommender Systems. ๐ŸŽ + +**Technical Overview๐Ÿ“œ** + +๐Ÿ”๏ธ LanceDB's powerful vector database capabilities can efficiently store and query item embeddings. Recommender Systems can utilize it and provide personalized recommendations based on user preferences ๐Ÿค and item features ๐Ÿ“Š and therefore enhance the user experience.๐Ÿ—‚๏ธ + +| **Recommender System** | **Description** | **Links** | +| ---------------------- | --------------- | --------- | +| **Movie Recommender System๐ŸŽฌ** | ๐Ÿค Use **collaborative filtering** to predict user preferences, assuming similar users will like similar movies, and leverage **Singular Value Decomposition** (SVD) from Numpy for precise matrix factorization and accurate recommendations๐Ÿ“Š | [![Github](../../assets/github.svg)][movie_github]
[![Open In Collab](../../assets/colab.svg)][movie_colab]
[![Python](../../assets/python.svg)][movie_python] | +| **๐ŸŽฅ Movie Recommendation with Genres** | ๐Ÿ” Creates movie embeddings using Doc2Vec, capturing genre and characteristic nuances, and leverages VectorDB for efficient storage and querying, enabling accurate genre classification and personalized movie recommendations through similarity searches๐ŸŽฅ | [![Github](../../assets/github.svg)][genre_github]
[![Open In Collab](../../assets/colab.svg)][genre_colab]
[![Ghost](../../assets/ghost.svg)][genre_ghost] | +| **๐Ÿ›๏ธ Product Recommender using Collaborative Filtering and LanceDB** | ๐Ÿ“ˆ Using **Collaborative Filtering** and **LanceDB** to analyze your past purchases, recommends products based on user's past purchases. Demonstrated with the Instacart dataset in our example๐Ÿ›’ | [![Github](../../assets/github.svg)][product_github]
[![Open In Collab](../../assets/colab.svg)][product_colab]
[![Python](../../assets/python.svg)][product_python] | +| **๐Ÿ” Arxiv Search with OpenCLIP and LanceDB** | ๐Ÿ’ก Build a semantic search engine for Arxiv papers using LanceDB, and benchmarks its performance against traditional keyword-based search on Nomic's Atlas, to demonstrate the power of semantic search in finding relevant research papers๐Ÿ“š | [![Github](../../assets/github.svg)][arxiv_github]
[![Open In Collab](../../assets/colab.svg)][arxiv_colab]
[![Python](../../assets/python.svg)][arxiv_python] | +| **Food Recommendation System๐Ÿด** | ๐Ÿ” Build a food recommendation system with LanceDB, featuring vector-based recommendations, full-text search, hybrid search, and reranking model integration for personalized and accurate food suggestions๐Ÿ‘Œ | [![Github](../../assets/github.svg)][food_github]
[![Open In Collab](../../assets/colab.svg)][food_colab] | + +[movie_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/movie-recommender +[movie_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/movie-recommender/main.ipynb +[movie_python]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/movie-recommender/main.py + + +[genre_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/movie-recommendation-with-genres +[genre_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/movie-recommendation-with-genres/movie_recommendation_with_doc2vec_and_lancedb.ipynb +[genre_ghost]: https://blog.lancedb.com/movie-recommendation-system-using-lancedb-and-doc2vec/ + +[product_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/product-recommender +[product_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/product-recommender/main.ipynb +[product_python]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/product-recommender/main.py + + +[arxiv_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/arxiv-recommender +[arxiv_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/arxiv-recommender/main.ipynb +[arxiv_python]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/arxiv-recommender/main.py + + +[food_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/Food_recommendation +[food_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Food_recommendation/main.ipynb diff --git a/docs/src/examples/python_examples/vector_search.md b/docs/src/examples/python_examples/vector_search.md index d0713ef2..7182eb09 100644 --- a/docs/src/examples/python_examples/vector_search.md +++ b/docs/src/examples/python_examples/vector_search.md @@ -1,7 +1,7 @@ **Vector Search: Unlock Efficient Document Retrieval ๐Ÿ”“๐Ÿ‘€** ==================================================================== -Unlock the power of vector search with LanceDB, a cutting-edge solution for efficient vector-based document retrieval ๐Ÿ“Š. +Vector search with LanceDB, is a solution for efficient and accurate similarity searches in large datasets ๐Ÿ“Š. **Vector Search Capabilities in LanceDB๐Ÿ”**