Update README.md

README.md

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 ---
 license: apache-2.0
+language:
+- en
+tags:
+- text-classification
+- support-tickets
+- setfit
+- nlp
+- customer-support
+metrics:
+- f1
 ---
+
+# 🎫 Support Ticket Classifier
+
+Automatically classifies customer support tickets by **category** and **urgency** using a fine-tuned SetFit model trained on 30,000+ real support tickets.
+
+## What It Does
+
+**Input:** Raw support ticket text  
+**Output:** Category + confidence score + urgency level
+
+```json
+{
+  "category": "billing",
+  "confidence": 0.79,
+  "urgency": "high"
+}
+```
+
+## Categories
+
+| Category | Example ticket |
+|---|---|
+| `billing` | "I was charged twice for my subscription" |
+| `technical` | "My account keeps logging me out" |
+| `complaint` | "This service is completely unacceptable" |
+| `refund` | "I want to cancel and get my money back" |
+
+## Urgency Levels
+
+| Level | When assigned |
+|---|---|
+| `high` | Fraud, service down, unauthorized charges, locked out |
+| `medium` | General issues, standard requests |
+| `low` | General questions, curiosity, minor changes |
+
+## Performance
+
+| Metric | Score |
+|---|---|
+| Weighted F1 | **82%** |
+| Complaint F1 | 92% |
+| Technical F1 | 82% |
+| Billing F1 | 79% |
+| Refund F1 | 68% |
+
+Trained on 30,571 labeled tickets from Kaggle + HuggingFace datasets.  
+Evaluated on a held-out test set of 3,058 tickets.
+
+## Why Use This Instead of an LLM?
+
+- ✅ **100x cheaper per call** than GPT-4 at volume
+- ✅ **Fast** — under 200ms per ticket
+- ✅ **Private** — runs on your own server, data never leaves your infrastructure
+- ✅ **No vendor lock-in** — no API key, no per-token billing
+- ✅ **GDPR friendly** — fully on-premise capable
+
+## Quick Start
+
+### Install dependencies
+```bash
+pip install setfit==1.0.3 sentence-transformers==2.7.0 transformers==4.40.2 huggingface_hub==0.23.5 scikit-learn numpy
+```
+
+### Run predictions
+```python
+from predict import predict_ticket
+
+result = predict_ticket("I was charged twice and need a refund immediately")
+print(result)
+# {"category": "billing", "confidence": 0.79, "urgency": "high"}
+```
+
+## Files in This Repo
+
+| File | Description |
+|---|---|
+| `predict.py` | Ready-to-run prediction script |
+| `requirements.txt` | Pinned dependencies |
+| `category_model/` | Fine-tuned SetFit classifier |
+| `calibration.pkl` | Platt scaling confidence calibration |
+| `label_mappings.pkl` | Label encoders |
+
+## Tech Stack
+
+- **Model:** SetFit (Sentence Transformers fine-tuning)
+- **Base model:** `paraphrase-MiniLM-L3-v2`
+- **Training data:** 30,571 labeled support tickets
+- **Confidence calibration:** Platt scaling on held-out validation set
+- **Urgency:** Keyword-rule layer (transparent and auditable)
+
+## Get the Full Docker API Version
+
+Want a production-ready REST API you can deploy to your own server in minutes?
+
+The **Docker version** includes:
+- FastAPI wrapper (`POST /predict` endpoint)
+- Dockerfile — one command to deploy anywhere
+- Full setup guide
+
+👉 **[Get the Docker API version on Gumroad](#)** 
+## Sample Results