Multi-step prompt sequences for complex AI workflows.
99 tools found
OpenAI cookbook for storing OpenAI embeddings in Qdrant and running payload-filtered nearest-neighbor search.
OpenAI cookbook demo flow for embedding data and indexing/searching it in a local Qdrant instance with payload metadata.
OpenAI cookbook demo flow for embedding data and running vector plus hybrid search in Redis with RediSearch.
An intro OpenAI Cookbook notebook to Redis as a vector database - deployment options, index creation, and the FLAT vs HNSW tradeoff.
OpenAI cookbook running hybrid vector-plus-lexical search queries on Redis with an e-commerce OpenAI-embedded dataset.
A notebook using Tair, Alibaba Cloud's in-memory vector database, to store and nearest-neighbor search OpenAI embeddings.
OpenAI cookbook demo flow for indexing and searching OpenAI embeddings in a self-hosted Weaviate instance.
OpenAI cookbook using Weaviate's text2vec-openai module to auto-vectorize and semantically search unvectorized data.
OpenAI Cookbook notebook: run hybrid vector + BM25 search in Weaviate with automatic OpenAI vectorization.
Walkthrough for setting up Weaviate with OpenAI's vectorizer and Q&A modules to answer questions over your own data.
Notebook combining OpenAI embeddings with Zilliz metadata filtering to search over 8,000+ movie descriptions.
Promptfoo example comparing GPT, Claude, Llama, and Mistral models side by side on Azure AI Foundry.
