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| title: HEA Query | |
| emoji: 🔬 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: "5.45.0" # or any version | |
| app_file: app.py | |
| pinned: true | |
| # 🔬 HEA Query | |
| This Hugging Face Space allows you to **query high-entropy alloys (HEAs)** using a combination of: | |
| - **FAISS vector database** for paper embeddings (semantic search) | |
| - **Structured CSV datasets** with properties like hardness, bulk modulus, yield strength, etc. | |
| - **Large language model (Mistral-7B-Instruct)** for intelligent answers | |
| --- | |
| ## Features | |
| - Query 3000+ HEA research papers via FAISS embeddings | |
| - Filter and rank HEA datasets based on numeric properties or phase (fcc, bcc, hcp, etc.) | |
| - Interactive Gradio interface with: | |
| - LLM answer | |
| - CSV matches table | |
| - Paper context (FAISS) | |
| --- | |
| ## How to Use | |
| 1. Enter your **question about HEAs** in the text box. | |
| Examples: | |
| - `"Which FCC HEAs have hardness > 200 HV?"` | |
| - `"List high bulk modulus BCC alloys"` | |
| 2. Click **Submit**. | |
| 3. View the results: | |
| - **LLM Answer**: AI summary based on papers and datasets | |
| - **CSV Matches**: Table of filtered alloys | |
| - **Paper Context (FAISS)**: Text excerpts from research papers | |
| --- | |
| ## Setup (for developers) | |
| 1. Clone the Space repo: | |
| ```bash | |
| git clone https://huggingface.co/spaces/taradutt007/README.md | |
| cd <space-name> | |