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Getting Started](./qdrant_101_getting_started) | Introduction to semantic search and the recommendation API of Qdrant | NumPy and Faker |\n| [Qdrant 101 - Text Data](./qdrant_101_text_data) | Introduction to the intersection of Vector Databases and Natural Language Processing | transformers, datasets, GPT-2, Sentence Transformers, PyTorch |\n| [Qdrant 101 - Audio Data](./qdrant_101_audio_data) | Introduction to audio data, audio embeddings, and music recommendation systems | transformers, librosa, openl3, panns_inference, streamlit, datasets, PyTorch |\n| [Ecommerce - reverse image search](./ecommerce_reverse_image_search) | Notebook demonstrating how to implement a reverse image search for ecommerce | CLIP, semantic image search, Sentence-Transformers |\n| [Serverless Semantic Search](./lambda-search) | Get a semantic page search without setting up a server | Rust, AWS lambda, Cohere embedding |\n| [Basic RAG](./rag-openai-qdrant) | Basic RAG pipeline with Qdrant and OpenAI SDKs | OpenAI, Qdrant, FastEmbed |\n| [Step-back prompting in Langchain RAG](./langchain-qdrant-step-back-prompting) | Step-back prompting for RAG, implemented in Langchain | OpenAI, Qdrant, Cohere, Langchain |\n| [Collaborative Filtering and MovieLens](./sparse-vectors-movies-reco) | A notebook demonstrating how to build a collaborative filtering system using Qdrant | Sparse Vectors, Qdrant |\n| [Use semantic search to navigate your codebase](./code-search/) | Implement semantic search application for code search task | Qdrant, Python, sentence-transformers, Jina |\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqdrant%2Fexamples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fqdrant%2Fexamples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqdrant%2Fexamples/lists"}