README.md

---
title: Sentence Transformers
emoji: 📚
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 5.31.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: Small CNN
---

# 🔍 MiniLM Semantic FAQ Search — Smart, Lightning-Fast Knowledge Retrieval  
[![Hugging Face Space](https://img.shields.io/badge/HF%20Space-Launch-lightgrey?logo=huggingface)](https://huggingface.co/spaces/your-username/minilm-semantic-search)
[![Gradio UI](https://img.shields.io/badge/Gradio-5.31.0-green?logo=gradio)](https://gradio.app)
[![Model](https://img.shields.io/badge/Model-all--MiniLM--L6--v2-blue)](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)
[![License](https://img.shields.io/github/license/your-username/minilm-semantic-search)](LICENSE)

---

## 🚀  TL;DR
**Ask a question → get the three most relevant answers from a curated FAQ — all in real time on a free CPU-only Hugging Face Space.**  
Powered by the _all-MiniLM-L6-v2_ sentence-transformer (∼90 MB, < 1 GB RAM) and a minimalist Gradio 5 UI.

---

## ✨  Why You’ll Love It
| · | Capability | Why It Matters |
|---|------------|----------------|
| ⚡ | **Instant Retrieval** | 50-200 ms response time even on CPU-only hardware. |
| 🧠 | **Semantic Matching** | Goes beyond keywords; understands intent and phrasing. |
| 📈 | **Live Similarity Scores** | Transparent confidence metrics for every hit. |
| 🎛️ | **Interactive Slider** | Choose 1-5 results in a single drag. |
| 🎨 | **Sleek Gradio GUI** | No setup friction — just open a browser and explore. |
| 💸 | **Free-Tier Friendly** | Fits comfortably inside Hugging Face Spaces’ 2 vCPU / 16 GB RAM limit. |
| 🛠️ | **Drop-in Dataset Swap** | Replace `faqs.csv` with thousands of your own Q-A pairs &mdash; no retraining required. |

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## 🏗️  How It Works

1. **Vectorisation**  
   Every FAQ question is embedded with `sentence-transformers/all-MiniLM-L6-v2` into a 384-dimensional vector (done once at start-up).

2. **Inference**  
   A user query is embedded on the fly and cosine-compared with all FAQ vectors via 🤗 `util.cos_sim`.  

3. **Ranking**  
   Top-_k_ indices are extracted with PyTorch’s efficient `topk`, then mapped back to the original FAQ rows.

4. **Presentation**  
   Gradio displays the question, answer and similarity score in a responsive dataframe.

> _No database, no external search engine, just straight Python & PyTorch embeddings._

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## 🖥️  Quick Start (Local Dev, Optional)

```bash
git clone https://github.com/your-username/minilm-semantic-search.git
cd minilm-semantic-search
python -m venv venv && source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt
python app.py