sample-apps
Weaviate
sample-apps | Weaviate | |
---|---|---|
3 | 76 | |
282 | 9,587 | |
1.1% | 3.7% | |
9.5 | 10.0 | |
11 days ago | about 16 hours ago | |
Jupyter Notebook | Go | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sample-apps
-
[P] I'm building a Neural Search Plugin for Elastic/Opensearch
See this blog post https://blog.vespa.ai/pretrained-transformer-language-models-for-search-part-1/ and the open source sample app it describes: https://github.com/vespa-engine/sample-apps/tree/master/msmarco-ranking
-
Find anything fast with Google's vector search technology
>
Vespa.ai supports combining dense vector search with keyword search and ranking, see https://docs.google.com/presentation/d/1vWKhSvFH-4MFcs4aNa9C...
There is also a Vespa sample application (open source, Apache 2) demonstrating multiple different retrieval and ranking strategies over at https://github.com/vespa-engine/sample-apps/blob/master/msma...
-
What Are Some Open Source NLP Framework Pipelines For QA Task
Look up Vespa.ai. https://github.com/vespa-engine/sample-apps/tree/master/dense-passage-retrieval-with-ann
Weaviate
-
pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
- FLaNK Stack 29 Jan 2024
- Qdrant, the Vector Search Database, raised $28M in a Series A round
-
How to use Weaviate to store and query vector embeddings
In this tutorial, I introduce Weaviate, an open-source vector database, with the thenlper/gte-base embedding model from Alibaba, through Hugging Face's transformers library.
-
Choosing vector database: a side-by-side comparison
This will be solved in Weaviate https://github.com/weaviate/weaviate/issues/2424
-
Who's hiring developer advocates? (October 2023)
Link to GitHub -->
-
Do we think about vector dbs wrong?
Hey @rvrs, I work on Weaviate and we are doing some improvements around increasing write throughput:
1. gRPC. Using gRPC to write vectors has had a really nice performance boost. It is released in Weaviate core but here is still some work on do on the clients. Feel free to get in contact if you would like to try it out.
2. Parameter tuning. lowering `efConstruction` can speed up imports.
3. We are also working on async indexing https://github.com/weaviate/weaviate/issues/3463 which will further speed things up.
In comparison with pgvector, Weaviate has more flexible query options such as hybrid search and quantization to save memory on larger datasets.
- Weaviate vector database
- Weaviate 1.21: Support for ImageBind and GPT4all and more
- Weaviate Vector Database
What are some alternatives?
awesome-vector-search - Collections of vector search related libraries, service and research papers
Milvus - A cloud-native vector database, storage for next generation AI applications
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
faiss - A library for efficient similarity search and clustering of dense vectors.
hnswlib - Header-only C++/python library for fast approximate nearest neighbors
pgvector - Open-source vector similarity search for Postgres
biggraph-wikidata-search-with-weaviate - Search through Facebook Research's PyTorch BigGraph Wikidata-dataset with the Weaviate vector search engine
jina - ☁️ Build multimodal AI applications with cloud-native stack
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
vald - Vald. A Highly Scalable Distributed Vector Search Engine