Building Search/RAG for an OpenAPI spec - Nick Khami | Vector Space Talks
Blog post from Qdrant
Nick Khami, a full-stack engineer and founder of Trieve, discusses the simplicity and benefits of building search functionalities over an OpenAPI specification using tools like Trieve and Qdrant, particularly highlighting the advantages of a group-based system. Since his involvement with Qdrant in 2022, Khami has developed expertise in vector search and retrieval-augmented generation (RAG) applications, leading to the creation of Trieve to help businesses integrate these technologies. He demonstrates the process of constructing precise search capabilities, emphasizing the potential for improved search experiences and analytics in diverse applications, from e-commerce to legislative apps. Khami elaborates on how Trieve, which evolved after a pivot from an AI-powered argumentation app, provides a managed infrastructure for creating sophisticated search and recommendation systems, and shares insights into the evolving capabilities of Qdrant, including group searches, sparse vector support, and enhanced recommendation patterns.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| RAG | 18 | 1,870 | 233 | 79 | +53% |
| Vector Search | 7 | 2,800 | 287 | 106 | +39% |
| AI Model Fine-tuning | 1 | 793 | 156 | 87 | +37% |
| LLM | 1 | 3,755 | 420 | 157 | +40% |
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