metadata
license: mit
library_name: colbert
tags:
- rag
- visual-rag
- colqwen
- sceletium-tortuosum
- thesis
model-index:
- name: LAYRA v2
results:
- task:
type: retrieval-augmented-generation
name: Retrieval Augmented Generation
dataset:
name: Kanna RAG Gold Standard
type: SAINTHALF/kanna-rag-gold-standard
metrics:
- name: MRR@20
type: mrr
value: 0.7403174603174603
- name: Recall@20
type: recall
value: 1
LAYRA v2 (Large Academic Visual RAG Agent)
LAYRA v2 is a specialized Visual RAG system designed for the ethnopharmacology of Sceletium tortuosum. It processes full PDF pages as images, preserving layout and visual information, and uses a hybrid retrieval stack.
Architecture
- Visual Encoder: ColQwen 2.5 (ColBERT + Qwen-VL)
- Retrieval: Hybrid (Sparse BM25 + Dense ColBERT)
- Reranking: LLM-based Reranking (Generative Listwise)
- Vector DB: Milvus 2.5.5
- Infrastructure: Docker Compose (Lean Stack)
Performance
Evaluated on SAINTHALF/kanna-rag-gold-standard:
| Metric | Score |
|---|---|
| MRR@20 | 0.7403 |
| Recall@20 | 1.0000 |
| Latency (P50) | 1.2s |
Usage
This model represents the deployed system configuration described in the thesis.
Supersedes SAINTHALF/layra-v1-hybrid.