You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
2362d96acc
|
2 weeks ago | |
|---|---|---|
| .. | ||
| PolarDB | 4 months ago | |
| SingleStoreDB | 4 months ago | |
| analyticdb | 4 months ago | |
| azuresearch | 3 months ago | |
| cassandra_astradb | 4 months ago | |
| chroma | 4 months ago | |
| deeplake | 4 months ago | |
| elasticsearch | 4 months ago | |
| hologres | 4 months ago | |
| kusto | 4 months ago | |
| milvus | 4 months ago | |
| mongodb_atlas | 4 months ago | |
| myscale | 4 months ago | |
| neon | 4 months ago | |
| pinecone | 3 months ago | |
| qdrant | 3 months ago | |
| redis | 4 months ago | |
| supabase | 4 months ago | |
| tair | 4 months ago | |
| typesense | 4 months ago | |
| weaviate | 4 months ago | |
| zilliz | 4 months ago | |
| README.md | 2 weeks ago | |
README.md
Vector Databases
This section of the OpenAI Cookbook showcases many of the vector databases available to support your semantic search use cases.
Vector databases can be a great accompaniment for knowledge retrieval applications, which reduce hallucinations by providing the LLM with the relevant context to answer questions.
Each provider has their own named directory, with a standard notebook to introduce you to using our API with their product, and any supplementary notebooks they choose to add to showcase their functionality.