Topics / #neural-search

Neural-search projects on GitHub

Semantic search engines using neural embeddings instead of keyword matching.

As of , the most-starred Neural-search projects on GitHub are qdrant (35.1K stars), serve (21.9K stars) and weaviate (16.9K stars). GitHub.Locker tracks 5 Neural-search repositories with 99.7K stars combined. The fastest-growing on October 16 was qdrant, with +22 stars in a day.

5Projects
99.7KStars in total
+27Stars in a day
Browse in the catalog →github.com/topics/neural-search ↗

Hot right now

Most stars gained in a day · Oct 16

+22

qdrant

qdrant/qdrant · ★ 35.1K

Qdrant is a high-performance vector similarity search engine and vector database written in Rust, built to store, search, and manage 'points' (vectors plus a JSON payload) for AI applications like semantic search, recommendations, and RAG.

+3

weaviate

weaviate/weaviate · ★ 16.9K

Weaviate is an open-source, cloud-native vector database: it stores objects and vectors together and lets you combine vector search with structured filtering for semantic search at scale.

+1

serve

jina-ai/serve · ★ 21.9K

Jina is an open-source Python framework for building multimodal AI applications on a cloud-native stack — you wrap models into gRPC microservices, chain them into flows, and scale from local to cloud.

+1

PaddleNLP

PaddlePaddle/PaddleNLP · ★ 13K

PaddleNLP is a large language model (LLM) and small language model (SLM) development toolkit built on the PaddlePaddle deep learning framework, offering efficient training, lossless compression, and high-performance inference for large models.

The all-time top

5 projects · by stars

  1. #1 · qdrant/qdrant

    qdrant

    Qdrant is a high-performance vector similarity search engine and vector database written in Rust, built to store, search, and manage 'points' (vectors plus a JSON payload) for AI applications like semantic search, recommendations, and RAG.

    35.1K
  2. #2 · jina-ai/serve

    serve

    Jina is an open-source Python framework for building multimodal AI applications on a cloud-native stack — you wrap models into gRPC microservices, chain them into flows, and scale from local to cloud.

    21.9K
  3. #3 · weaviate/weaviate

    weaviate

    Weaviate is an open-source, cloud-native vector database: it stores objects and vectors together and lets you combine vector search with structured filtering for semantic search at scale.

    16.9K
  1. 4

    PaddleNLP

    13KPaddlePaddle/PaddleNLP · Python

    PaddleNLP is a large language model (LLM) and small language model (SLM) development toolkit built on the PaddlePaddle deep learning framework, offering efficient training, lossless compression, and high-performance inference for large models.

  2. 5

    clip-as-service

    12.8Kjina-ai/clip-as-service · Python

    CLIP-as-service is a low-latency, high-scalability service for embedding images and text with CLIP models, so you can plug it into neural search or cross-modal retrieval apps as a microservice.

Often tagged together