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examples/qdrant/README.md

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### Notebooks
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* **[Similarity Search using Qdrant](../examples/qdrant/Qdrant_similarity_search.ipynb)**
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* **[Similarity Search using Qdrant](./Qdrant_similarity_search.ipynb)**
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Load website data, build a semantic search system using embeddings from the Gemini API, store the embeddings in a Qdrant vector DB, and perform similarity search using Gemini-powered queries.
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* **[Movie Recommendation using Qdrant](../examples/qdrant/Movie_Recommendation.ipynb)**
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* **[Movie Recommendation using Qdrant](./Movie_Recommendation.ipynb)**
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Process and embed a large movie dataset with the Gemini API, index movie vectors in Qdrant, and build a semantic movie recommender that returns similar movies based on user input using vector similarity search.
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* Store and search high-dimensional vectors in Qdrant.
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* Use Gemini queries to semantically match user input to relevant content.
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You can use these templates as a foundation for building search, recommendation, or AI assistant systems using Gemini and Qdrant.
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You can use these templates as a foundation for building search, recommendation, or AI assistant systems using Gemini and Qdrant.

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