| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - rag |
| - retrieval |
| - semantic-search |
| - faiss |
| - bm25 |
| - cross-encoder |
| - sentence-transformers |
| - hybrid-search |
| - dense-retrieval |
| - ai |
| - search |
| pipeline_tag: sentence-similarity |
| library_name: sentence-transformers |
| --- |
| # ApexRetriever |
|
|
| A lightweight hybrid retrieval system designed for fast semantic search and RAG pipelines. |
|
|
| Built for: |
| - semantic search |
| - lightweight RAG |
| - AI assistants |
| - retrieval systems |
| - local document QA |
|
|
| --- |
|
|
| # Architecture |
|
|
| ## Stage ① — BM25 Sparse Retrieval |
| Keyword-based retrieval for fast lexical matching. |
|
|
| ## Stage ② — Dense Semantic Search |
| Powered by: |
|
|
| - `BAAI/bge-small-en-v1.5` |
|
|
| Uses FAISS vector indexing. |
|
|
| ## Stage ③ — CrossEncoder Reranking |
| Final neural reranking using: |
|
|
| - `cross-encoder/ms-marco-MiniLM-L-6-v2` |
|
|
| --- |
|
|
| # Features |
|
|
| - Hybrid retrieval |
| - Fast indexing |
| - Dense semantic search |
| - Neural reranking |
| - Lightweight deployment |
| - GPU acceleration |
| - FAISS support |
| - Easy integration |
|
|
| --- |
|
|
| # Repository Structure |
|
|
| ```text |
| ApexRetriever/ |
| │ |
| ├── bi_encoder/ |
| ├── reranker/ |
| ├── pipeline.py |
| └── README.md |
| ```` |
|
|
| --- |
|
|
| # Installation |
|
|
| ```bash |
| pip install -U \ |
| sentence-transformers \ |
| transformers \ |
| faiss-cpu \ |
| rank-bm25 \ |
| torch |
| ``` |
|
|
| --- |
|
|
| # Quick Start |
|
|
| ```python |
| from pipeline import ApexRetriever |
| |
| retriever = ApexRetriever(model_dir=".") |
| |
| # Example documents |
| |
| docs = [ |
| "Python was created by Guido van Rossum.", |
| "Paris is the capital of France." |
| ] |
| |
| retriever.index_documents(docs) |
| |
| results = retriever.retrieve( |
| "Who created Python?", |
| top_k=3 |
| ) |
| |
| print(results) |
| ``` |
|
|
| --- |
|
|
| # Use Cases |
|
|
| * RAG systems |
| * Semantic search |
| * AI chatbots |
| * Knowledge retrieval |
| * Local search engines |
| * Memory systems |
|
|
| --- |
|
|
| # Performance |
|
|
| Recommended: |
|
|
| * CUDA GPU |
| * 8GB+ RAM |
| * Python 3.10+ |
|
|
| --- |
|
|
| # Components |
|
|
| | Component | Model | |
| | ------------- | ------------------------------------ | |
| | Dense Encoder | BAAI/bge-small-en-v1.5 | |
| | Reranker | cross-encoder/ms-marco-MiniLM-L-6-v2 | |
| | Vector Engine | FAISS | |
| | Sparse Search | BM25 | |
|
|
| --- |
|
|
| # License |
|
|
| Apache 2.0 |
|
|
| --- |
| > QuantaSparkLabs |
