fix: Space README

README.md

@@ -1 +1,57 @@
-# agentbase-platform-test
+---
+title: AgentBase Platform
+emoji: 🤖
+colorFrom: blue
+colorTo: green
+sdk: streamlit
+sdk_version: 1.44.0
+app_file: streamlit_app.py
+pinned: false
+---
+
+# AgentBase Search Platform
+
+**AgentBase** is an interactive search demo for AI agent retrieval, built on nearly 10,000 real-world agents sourced from the [GPT Store](https://chatgpt.com/gpts), [Google Cloud Marketplace](https://cloud.google.com/marketplace), and [AgentAI Platform](https://agent.ai/).
+
+🌐 [Project Page](https://bingo-w.github.io/AgentSearchBench) • 💻 [Codebase](https://github.com/Bingo-W/AgentSearchBench) • 📄 [Paper](https://arxiv.org/abs/2604.22436)
+
+---
+
+## Overview
+
+This Space is a live demo for **AgentSearchBench**: a large-scale benchmark for AI agent search. Given a natural language query, the platform retrieves the most relevant agents from AgentBase using a choice of retrieval models and indexing configurations.
+
+**Retrieval models:**
+- **BGE-Large** — dense retrieval using `BAAI/bge-large-en-v1.5`
+- **ToolRet** — dense retrieval fine-tuned for tool search
+- **BM25** — sparse retrieval baseline
+- **Keyword** — boolean keyword matching
+
+**Indexing configurations:**
+- **v1** — all metadata columns with priority ordering (name and description weighted first)
+- **naive** — agent name and description only
+
+---
+
+## Related Resources
+
+| Resource | Description |
+|----------|-------------|
+| [AgentSearchBench-Tasks](https://huggingface.co/datasets/AgentSearch/AgentSearchBench-Tasks) | Benchmark tasks for agent retrieval and reranking |
+| [AgentSearchBench-Agents](https://huggingface.co/datasets/AgentSearch/AgentSearchBench-Agents) | AgentBase: 9,759 real-world AI agents with metadata |
+| [AgentSearchBench-Responses](https://huggingface.co/datasets/AgentSearch/AgentSearchBench-Responses) | 60K+ raw agent execution responses |
+
+---
+
+## Citation
+
+```bibtex
+@article{wu2026agentsearchbench,
+      title={AgentSearchBench: A Benchmark for AI Agent Search in the Wild}, 
+      author={Bin Wu and Arastun Mammadli and Xiaoyu Zhang and Emine Yilmaz},
+      year={2026},
+      eprint={2604.22436},
+      archivePrefix={arXiv},
+      primaryClass={cs.AI},
+}
+```

pages/interface.py

@@ -87,6 +87,7 @@ class AgentBaseUI:
                 st.write('''
                 - **Retrieval Models**:
                     - **BGE-Large**: a dense retrieval model.
+                    - **ToolRet**: a dense retrieval model fine-tuned for tool search.
                     - **BM25**: a sparse retrieval model.
                     - **Keyword**: simple boolean keyword matching.
                 - **Indexing Configurations**:

pages/retrieval.py

@@ -70,6 +70,7 @@ class AgentBaseUI:
                 st.write('''
                 - **Retrieval Models**:
                     - **BGE-Large**: a dense retrieval model.
+                    - **ToolRet**: a dense retrieval model fine-tuned for tool search.
                     - **BM25**: a sparse retrieval model.
                 - **Indexing Configurations**:
                     - **v1**: using all columns with priority ordering (e.g., name, description come first).