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Merge pull request #268 from akashAD98/tutoral/multomodal-jina
example: food recommendation using jina-clip-v2
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# Multimodal Search Engine with Jina-CLIP v2 and LanceDB | ||
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Welcome to the **Multimodal Search Engine** project! This project utilizes [Jina-CLIP v2](https://jina.ai/news/jina-clip-v2-multilingual-multimodal-embeddings-for-text-and-images/) and [LanceDB](https://lancedb.dev) | ||
to enable robust search functionality across both text and image data in 89 languages. | ||
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## Features | ||
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- **Multimodal Search**: Search across both image and text inputs. | ||
- **Multilingual Support**: Supports 89 languages for text queries and captions. | ||
- **Efficient Retrieval**: Powered by [LanceDB](https://lancedb.dev), ensuring low latency and high throughput. | ||
- **Matryoshka Representations**: Enables hierarchical embedding structures for fine-grained similarity. | ||
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### How It Works | ||
- Input: Accepts either a text query or an image as input. | ||
- Encoding: Uses Jina-CLIP v2 to convert text and images into a shared embedding space. | ||
- Storage: Stores these embeddings in LanceDB for efficient retrieval. | ||
- Search: Matches queries to the most relevant embeddings in the database and returns results. | ||
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## code | ||
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Colab walkthrough <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/multimodal_jina_clipv2/main.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | ||
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