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Refine and improve the language clarity and quality across all example pages in the documentation to ensure better understanding and readability. --------- Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
23 lines
3.5 KiB
Markdown
23 lines
3.5 KiB
Markdown
# Overview : Python Examples
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To help you get started, we provide some examples, projects, and applications that use the LanceDB Python API. These examples are designed to get you right into the code with minimal introduction, enabling you to move from an idea to a proof of concept in minutes.
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You can find the latest examples in our [VectorDB Recipes](https://github.com/lancedb/vectordb-recipes) repository.
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**Introduction**
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Explore applied examples available as Colab notebooks or Python scripts to integrate into your applications. You can also checkout our blog posts related to the particular example for deeper understanding.
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| Explore | Description |
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| [**Build from Scratch with LanceDB** 🛠️🚀](python_examples/build_from_scratch.md) | Start building your **GenAI applications** from the **ground up** using **LanceDB's** efficient vector-based document retrieval capabilities! Get started quickly with a solid foundation. |
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| [**Multimodal Search with LanceDB** 🤹♂️🔍](python_examples/multimodal.md) | Combine **text** and **image queries** to find the most relevant results using **LanceDB’s multimodal** capabilities. Leverage the efficient vector-based similarity search. |
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| [**RAG (Retrieval-Augmented Generation) with LanceDB** 🔓🧐](python_examples/rag.md) | Build RAG (Retrieval-Augmented Generation) with **LanceDB** for efficient **vector-based information retrieval** and more accurate responses from AI. |
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| [**Vector Search: Efficient Retrieval** 🔓👀](python_examples/vector_search.md) | Use **LanceDB's** vector search capabilities to perform efficient and accurate **similarity searches**, enabling rapid discovery and retrieval of relevant documents in Large datasets. |
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| [**Chatbot applications with LanceDB** 🤖](python_examples/chatbot.md) | Create **chatbots** that retrieves relevant context for **coherent and context-aware replies**, enhancing user experience through advanced conversational AI. |
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| [**Evaluation: Assessing Text Performance with Precision** 📊💡](python_examples/evaluations.md) | Develop **evaluation** applications that allows you to input reference and candidate texts to **measure** their performance across various metrics. |
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| [**AI Agents: Intelligent Collaboration** 🤖](python_examples/aiagent.md) | Enable **AI agents** to communicate and collaborate efficiently through dense vector representations, achieving shared goals seamlessly. |
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| [**Recommender Systems: Personalized Discovery** 🍿📺](python_examples/recommendersystem.md) | Deliver **personalized experiences** by efficiently storing and querying item embeddings with **LanceDB's** powerful vector database capabilities. |
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| **Miscellaneous Examples🌟** | Find other **unique examples** and **creative solutions** using **LanceDB**, showcasing the flexibility and broad applicability of the platform. |
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