From 56b9fe2c5f226ba903a11b3de3db22a6bf01260b Mon Sep 17 00:00:00 2001 From: Richard Abrich Date: Sat, 17 Jan 2026 01:30:48 -0500 Subject: [PATCH 1/2] fix: Use filename-based GitHub Actions badge URL The workflow-name-based badge URL was showing "no status" because GitHub requires workflow runs on the specified branch. Using the filename-based URL format (actions/workflows/publish.yml/badge.svg) is more reliable and works regardless of when the workflow last ran. Co-Authored-By: Claude Sonnet 4.5 --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e658206..8a6ba71 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # openadapt-retrieval -[![Build Status](https://github.com/OpenAdaptAI/openadapt-retrieval/workflows/Publish%20to%20PyPI/badge.svg?branch=main)](https://github.com/OpenAdaptAI/openadapt-retrieval/actions) +[![Build Status](https://github.com/OpenAdaptAI/openadapt-retrieval/actions/workflows/publish.yml/badge.svg)](https://github.com/OpenAdaptAI/openadapt-retrieval/actions/workflows/publish.yml) [![PyPI version](https://img.shields.io/pypi/v/openadapt-retrieval.svg)](https://pypi.org/project/openadapt-retrieval/) [![Downloads](https://img.shields.io/pypi/dm/openadapt-retrieval.svg)](https://pypi.org/project/openadapt-retrieval/) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) From a2ffd02e3291e6985361042cb9d2588d0c25c7ee Mon Sep 17 00:00:00 2001 From: Richard Abrich Date: Sat, 17 Jan 2026 01:31:50 -0500 Subject: [PATCH 2/2] docs: remove unsubstantiated SOTA claim from README Changed "state-of-the-art VLM" to just "Qwen3-VL model" since SOTA claims require citations or benchmark comparisons to be defensible. Co-Authored-By: Claude Sonnet 4.5 --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8a6ba71..d83fed0 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,7 @@ Multimodal demo retrieval using VLM embeddings for GUI automation. **Key Features:** - **Multimodal Embeddings**: Embed text, images, or both into a shared vector space -- **Qwen3-VL-Embedding Support**: Primary embedder using Alibaba's state-of-the-art VLM +- **Qwen3-VL-Embedding Support**: Primary embedder using Alibaba's Qwen3-VL model - **Matryoshka Representation Learning (MRL)**: Flexible embedding dimensions (512-8192) - **FAISS Integration**: Fast similarity search with support for large demo libraries - **Persistence**: Save and load indices with embeddings and metadata