Update README.md

README.md

@@ -1,14 +1,32 @@
 ---
-title: LLM Select
-emoji: 🚀
+title: LLM Evaluation Framework
+emoji: 🤖
 colorFrom: blue
-colorTo: blue
-sdk: gradio
-sdk_version: 5.32.1
+colorTo: green
+sdk: streamlit
+sdk_version: 1.28.0
 app_file: app.py
 pinned: false
 license: mit
-short_description: LLM selection framework
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# LLM Quantitative Evaluation Framework
+
+A comprehensive tool for comparing and evaluating Large Language Models based on multiple quantitative criteria.
+
+## Features
+
+- **Multi-criteria evaluation**: Performance, cost, speed, reliability, compliance, and integration
+- **Interactive weights**: Adjust importance of each factor based on your use case
+- **Usage scenario modeling**: Input your specific requirements for accurate cost analysis
+- **Visual comparisons**: Charts and graphs for easy model comparison
+- **Transparent methodology**: Clear scoring algorithms and explanations
+
+## How to Use
+
+1. Adjust the evaluation criteria weights in the sidebar based on your priorities
+2. Configure your usage scenario (monthly requests, token usage)
+3. Review the ranked results and detailed analysis
+4. Use the insights to make informed LLM selection decisions
+
+Built with Streamlit and deployed on Hugging Face Spaces.