updated README

README.md

@@ -1,12 +1,68 @@
+# Social Media Bot Detection 
+
+This project focuses on detecting automated (bot) accounts using **only user metadata and behavioral features**, without relying on text or content analysis.
+
+The goal is to build a **robust and lightweight bot detection system** that is less sensitive to content manipulation and language changes.
+
+---
+
+## What this project does
+- Uses **user-level metadata** and behavioral signals as input  
+- Performs **feature engineering** to capture activity patterns  
+- Trains **supervised machine learning models** to classify accounts as bot or genuine  
+- Supports an **API-driven setup** for frontend or downstream integration  
+
+This version intentionally avoids text-based features.
+
+---
+
+## Why metadata-only detection?
+Text-based bot detection can break when:
+- Bots generate human-like text
+- Language or topics change frequently
+
+Metadata and behavior:
+- Are harder to fake consistently  
+- Capture long-term patterns  
+- Generalize better across platforms  
+
+---
+
+## Approach (high level)
+1. Collect user metadata  
+2. Clean and preprocess the data  
+3. Engineer behavioral features  
+4. Train supervised ML models  
+5. Evaluate using standard classification metrics  
+6. Serve predictions via an API  
+
+---
+
+## Model & Code
+- Training and inference code are included in this repository  
+- **Model artifacts are not stored here** due to size constraints  
+
+📦 Trained model weights are hosted on Hugging Face:  
+👉 https://huggingface.co/spaces/ASHUT0SH-SiNGH/BotDetection
+
+---
+
+## Notes
+- Focuses on **pipeline design and modeling logic**
+- Frontend components are minimal and not the core focus
+- Designed to be extended with additional metadata features
+
+---
+
+## Status
+- Model trained and evaluated  
+- API-based integration supported  
+- Open to further improvements 
+
+
 ---
 title: BotDetection
-emoji: 🔥😁
-colorFrom: blue
-colorTo: gray
-sdk: streamlit
-sdk_version: 1.42.0
-app_file: app.py
-pinned: false
+
 license: apache-2.0
 ---
 

app.py

@@ -82,7 +82,7 @@ MODEL_FEATURES = [
 
 
 @st.cache_resource
-def load_model(model_path="bot_model.joblib"):
+def load_model(model_path="./bot_model.joblib"):
     try:
         model = joblib.load(model_path)
         return model