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---
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: 1.0
---
# 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](https://huggingface.co/datasets/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`.*