Serverless Semantic Search

The article provides a step-by-step guide for setting up a free, non-commercial semantic search function using AWS Lambda, Rust, and Qdrant. It explains how to leverage free tiers and credits from various services, such as AWS and Cohere, to build a prototype search engine. The process involves using Rust's cargo-lambda tool to compile code for AWS Lambda deployment, creating an embedding with Cohere's API, and managing a Qdrant instance for storing and searching embeddings. Detailed instructions are given for configuring AWS Lambda, handling API keys securely, and implementing the search function in Rust, emphasizing the benefits of using Rust for its efficiency and safety. The guide highlights the advantages of utilizing free resources and underscores the importance of setting up appropriate permissions to avoid potential costs. Despite initial latency in Lambda function calls, the setup offers an accessible and cost-effective solution for those interested in experimenting with semantic search technology.

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