Update README.md

README.md

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----
-title: Watchtowerai Log Analyzer
-emoji: 🚀
-colorFrom: red
-colorTo: red
-sdk: docker
-app_port: 8501
-tags:
-- streamlit
-pinned: false
-short_description: Streamlit template space
-license: apache-2.0
----
+#  WatchTowerAI – Log Classification & Automated Runbook Generator
+
+A production-grade AI tool to analyze logs in real-time, classify them using a fine-tuned Flan-T5 model, generate markdown runbooks, and automatically alert your team via Slack — all deployed on Hugging Face Spaces.
+
+##  Features
+
+-  **LLM-powered log classification** (INFO, WARNING, ERROR, CRITICAL, SECURITY)
+-  **Runbook generation** using Flan-T5
+-  **Upload runbooks to AWS S3**
+-  **Send real-time Slack alerts**
+-  Hybrid fallback using rule-based logic if model is uncertain
+-  Streamlit Web UI + `.log` file upload support
+
+##  Tech Stack
+
+- LLM: Fine-tuned [Flan-T5](https://huggingface.co/google/flan-t5)
+- Frontend: Streamlit
+- Cloud: AWS S3
+- Alerts: Slack Webhook
+- Deployment: Hugging Face Spaces
+
+##  Screenshot
 
-# Welcome to Streamlit!
+![screenshot](https://your-screenshot-link)
 
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+##  How to Use
+
+1. Paste or upload a `.log` file
+2. Click “Classify + Generate Runbook”
+3. Download the markdown or view it in S3
+4. Slack alerts will be sent automatically
+
+##  Directory
+
+- `streamlit_app.py` – UI + logic
+- `upload_to_s3.py` – S3 upload function
+- `notify_slack.py` – Slack integration
+- `runbooks/` – Markdown output folder
+- `codementor-flan/` – Your fine-tuned model folder
+
+##  AI Model
+
+Fine-tuned on domain-specific QA + system logs using Flan-T5 for robust multi-class log categorization and response generation.
+
+---
 
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+ Made by [Chetan](https://github.com/chetan10510)