Mixedbread

baguetter

Baguetter is a flexible, efficient, and hackable search engine library implemented in Python. It's designed for quickly benchmarking, implementing, and testing new search methods. Baguetter supports sparse (traditional), dense (semantic), and hybrid retrieval methods.

batched

The Batched API provides a flexible and efficient way to process multiple requests in a batch, with a primary focus on dynamic batching of inference workloads.

mxbai-rerank

Crispy reranking models by Mixedbread

binary-embeddings

Showcase how mxbai-embed-large-v1 can be used to produce binary embedding. Binary embeddings enabled 32x storage savings and 40x faster retrieval.

ofen

WIP: Ofen is a toolkit aimed at making transformer models production-ready. API included

wiki_demo_app

python-sdk

mixedbread ai python sdk

mixedbread-ai-haystack

laserRMT-encoder

Fork of Fernandos implementation of 'Layer Selective Rank Reduction'

typescript-sdk

eval_reranker

Evaluate rerankers

haystack-integrations

🚀 A list of Haystack Integrations, maintained by the community or deepset.

langchain

⚡ Building applications with LLMs through composability ⚡

langchain-mixedbread-ai

langchainjs

🦜🔗 Build context-aware reasoning applications 🦜🔗

llama_index

LlamaIndex is a data framework for your LLM applications

LlamaIndexTS

LlamaIndex is a data framework for your LLM applications

mteb

MTEB: Massive Text Embedding Benchmark

unstructured

Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.