Merge branch 'main' of https://huggingface.co/spaces/LogicGoInfotechSpaces/SMART_BUDGET_RECOMMENDATION

HUGGINGFACE_DEPLOYMENT.md

@@ -1,156 +0,0 @@
-# Hugging Face Deployment Guide
-
-This guide will help you deploy the Smart Budget Recommendation API to Hugging Face Spaces.
-
-## Prerequisites
-
-1. A Hugging Face account (sign up at https://huggingface.co)
-2. MongoDB connection string ready
-3. Git installed (optional, you can also use the web interface)
-
-## Step-by-Step Deployment
-
-### Step 1: Create a New Space
-
-1. Go to https://huggingface.co/spaces
-2. Click "Create new Space"
-3. Fill in the details:
-   - **Space name**: `smart-budget-recommendation` (or your preferred name)
-   - **SDK**: Select **Docker**
-   - **Visibility**: Choose Public or Private
-4. Click "Create Space"
-
-### Step 2: Add secrets (MongoDB and optional OpenAI)
-
-1. In your Space, go to **Settings** (gear icon)
-2. Navigate to **Variables and secrets** section
-3. Click **New secret**
-4. Add the following secrets:
-   - **Name**: `MONGODB_URI`
-     - **Value**: `mongodb://expenseuser:Kem_6o%3F%3F@165.227.69.221:27017/expense?authSource=admin`
-   - **Name**: `OPENAI_API_KEY` *(optional, enables GPT-based recommendations)*
-     - **Value**: `sk-...`
-5. Click **Add secret** after each entry
-
-### Step 3: Upload Files
-
-You can upload files in two ways:
-
-#### Option A: Using Git (Recommended)
-
-1. Clone your Space repository:
-```bash
-git clone https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
-cd YOUR_SPACE_NAME
-```
-
-2. Copy all files from this project:
-   - `app/` directory (all Python files)
-   - `Dockerfile`
-   - `requirements.txt`
-   - `.dockerignore`
-   - `README.md` (optional)
-
-3. Commit and push:
-```bash
-git add .
-git commit -m "Initial deployment"
-git push
-```
-
-#### Option B: Using Web Interface
-
-1. In your Space, click **Files and versions** tab
-2. Click **Add file** → **Upload files**
-3. Upload all files:
-   - All files from `app/` directory
-   - `Dockerfile`
-   - `requirements.txt`
-   - `.dockerignore`
-
-### Step 4: Wait for Build
-
-1. Hugging Face will automatically detect the `Dockerfile` and start building
-2. You can monitor the build progress in the **Logs** tab
-3. The build typically takes 2-5 minutes
-
-### Step 5: Verify Deployment
-
-Once the build completes:
-
-1. Your API will be available at: `https://YOUR_USERNAME-YOUR_SPACE_NAME.hf.space`
-2. Test the health endpoint: `https://YOUR_USERNAME-YOUR_SPACE_NAME.hf.space/health`
-3. View API documentation: `https://YOUR_USERNAME-YOUR_SPACE_NAME.hf.space/docs`
-
-## Testing Your Deployment
-
-### Using cURL
-
-```bash
-# Health check
-curl https://YOUR_USERNAME-YOUR_SPACE_NAME.hf.space/health
-
-# Get recommendations (replace user123 with actual user_id)
-curl https://YOUR_USERNAME-YOUR_SPACE_NAME.hf.space/recommendations/user123
-```
-
-### Using Python
-
-```python
-import requests
-
-BASE_URL = "https://YOUR_USERNAME-YOUR_SPACE_NAME.hf.space"
-
-# Health check
-response = requests.get(f"{BASE_URL}/health")
-print(response.json())
-
-# Get recommendations
-response = requests.get(f"{BASE_URL}/recommendations/user123")
-print(response.json())
-```
-
-## Important Notes
-
-1. **Port Configuration**: Hugging Face Spaces expect apps to serve on port **7860**, so the Dockerfile exposes and binds to that port.
-
-2. **Environment Variables**: Secrets such as `MONGODB_URI` (and optional `OPENAI_API_KEY`) are injected automatically into the container environment.
-
-3. **Cold Starts**: The first request after inactivity may take longer (cold start). Subsequent requests will be faster
-
-4. **Resource Limits**: Free Hugging Face Spaces have resource limits. For production use, consider upgrading
-
-5. **Custom Domain**: You can add a custom domain in Space settings if needed
-
-## Troubleshooting
-
-### Build Fails
-
-- Check the **Logs** tab for error messages
-- Ensure `Dockerfile` is in the root directory
-- Verify all required files are uploaded
-
-### Connection Errors
-
-- Verify `MONGODB_URI` secret is set correctly
-- Check MongoDB server is accessible from Hugging Face's servers
-- Review connection string encoding (special characters should be URL-encoded)
-
-### API Not Responding
-
-- Check the **Logs** tab for runtime errors
-- Verify the application starts successfully
-- Test the `/health` endpoint first
-
-## Updating Your Deployment
-
-1. Make changes to your code locally
-2. Commit and push to your Space repository
-3. Hugging Face will automatically rebuild and redeploy
-
-## Support
-
-For issues specific to:
-- **Hugging Face Spaces**: Check [Hugging Face Documentation](https://huggingface.co/docs/hub/spaces)
-- **This Application**: Check the main README.md file
-

QUICKSTART.md

@@ -1,84 +0,0 @@
-# Quick Start Guide
-
-## Local Development
-
-1. **Install dependencies:**
-```bash
-pip install -r requirements.txt
-```
-
-2. **Set environment variable:**
-```bash
-# Windows PowerShell
-$env:MONGODB_URI="mongodb://expenseuser:Kem_6o%3F%3F@165.227.69.221:27017/expense?authSource=admin"
-
-# Linux/Mac
-export MONGODB_URI="mongodb://expenseuser:Kem_6o%3F%3F@165.227.69.221:27017/expense?authSource=admin"
-```
-
-3. **Run the application:**
-```bash
-uvicorn app.main:app --reload
-```
-
-4. **Access the API:**
-- API: http://localhost:8000
-- Docs: http://localhost:8000/docs
-- Health: http://localhost:8000/health
-
-## Test the Smart Budget Recommendation
-
-1. **Create some sample expenses:**
-```bash
-curl -X POST "http://localhost:8000/expenses" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "user_id": "user123",
-    "amount": 3800,
-    "category": "Groceries",
-    "description": "Monthly groceries",
-    "date": "2024-01-15T00:00:00",
-    "type": "expense"
-  }'
-```
-
-2. **Get recommendations:**
-```bash
-curl "http://localhost:8000/recommendations/user123?month=2&year=2024"
-```
-
-Expected response:
-```json
-[
-  {
-    "category": "Groceries",
-    "average_expense": 3800.0,
-    "recommended_budget": 4000.0,
-    "reason": "Your average monthly grocery expense is Rs.3,800. We suggest setting your budget to Rs.4,000 for next month (includes a 5% buffer for variability).",
-    "confidence": 0.85
-  }
-]
-```
-
-## Docker Deployment
-
-1. **Build the image:**
-```bash
-docker build -t smart-budget-recommendation .
-```
-
-2. **Run the container:**
-```bash
-docker run -p 8000:8000 -e MONGODB_URI="your_mongodb_uri" smart-budget-recommendation
-```
-
-## Hugging Face Deployment
-
-See `HUGGINGFACE_DEPLOYMENT.md` for detailed instructions.
-
-Quick steps:
-1. Create a new Docker Space on Hugging Face
-2. Add `MONGODB_URI` as a secret
-3. Upload all files
-4. Wait for automatic build and deployment
-

README.md

@@ -3,161 +3,8 @@ license: mit
 title: SMART_BUDGET_RECOMMENDATION
 sdk: docker
 emoji: ⚡
-colorFrom: blue
-colorTo: pink
+colorFrom: green
+colorTo: yellow
+pinned: true
 ---
 # Smart Budget Recommendation API
-
-A FastAPI-based service that provides intelligent budget recommendations based on past spending behavior. This service analyzes historical expense data and suggests personalized budgets for each category.
-
-## Features
-
-- **Smart Budget Recommendations**: Analyzes past spending patterns and recommends personalized budgets
-- **Category-based Analysis**: Provides recommendations for each expense category
-- **Confidence Scoring**: Each recommendation includes a confidence score based on data quality
-- **MongoDB Integration**: Stores expenses and budgets in MongoDB
-- **RESTful API**: Clean API endpoints for expense tracking and budget management
-
-## Example Recommendation
-
-```json
-{
-  "category": "Groceries",
-  "average_expense": 3800.0,
-  "recommended_budget": 4000.0,
-  "reason": "Your average monthly grocery expense is Rs.3,800. We suggest setting your budget to Rs.4,000 for next month (includes a 5% buffer for variability).",
-  "confidence": 0.85
-}
-```
-
-## API Endpoints
-
-### Health Check
-- `GET /health` - Check API and database connection status
-
-### Expenses
-- `POST /expenses` - Create a new expense
-- `GET /expenses?user_id={user_id}` - Get expenses for a user
-
-### Budgets
-- `POST /budgets` - Create a new budget
-- `GET /budgets?user_id={user_id}` - Get budgets for a user
-
-### Recommendations
-- `GET /recommendations/{user_id}?month={month}&year={year}` - Get smart budget recommendations
-- `GET /category-expenses/{user_id}?months={months}` - Get average expenses by category
-
-## Local Development
-
-### Prerequisites
-- Python 3.11+
-- MongoDB connection string
-
-### Setup
-
-1. Install dependencies:
-```bash
-pip install -r requirements.txt
-```
-
-2. Set environment variables:
-```bash
-export MONGODB_URI="mongodb://expenseuser:Kem_6o%3F%3F@165.227.69.221:27017/expense?authSource=admin"
-# optional
-export OPENAI_API_KEY="your_openai_key"
-```
-
-3. Run the application:
-```bash
-uvicorn app.main:app --reload
-```
-
-The API will be available at `http://localhost:8000`
-
-## Docker Deployment
-
-### Build Docker Image
-```bash
-docker build -t smart-budget-recommendation .
-```
-
-### Run Docker Container
-```bash
-docker run -p 7860:7860 -e MONGODB_URI="your_mongodb_uri" smart-budget-recommendation
-```
-
-## Hugging Face Deployment
-
-### Prerequisites
-1. Hugging Face account
-2. Docker installed
-3. MongoDB connection string stored as a secret in Hugging Face
-
-### Steps
-
-1. **Store secrets in Hugging Face**:
-   - Go to your Hugging Face Space settings
-   - Navigate to "Variables and secrets"
-   - Add `MONGODB_URI` with your MongoDB connection string
-   - *(Optional)* Add `OPENAI_API_KEY` if you want GPT-powered recommendations
-
-2. **Create Hugging Face Space**:
-   - Create a new Space on Hugging Face
-   - Choose "Docker" as the SDK
-
-3. **Upload Files**:
-   - Upload all files from this repository to your Space
-   - Ensure `Dockerfile` is in the root directory
-
-4. **Configure Space**:
-   - The Dockerfile will automatically build and run the application
-   - The app will use the `MONGODB_URI` secret from Hugging Face environment variables
-
-### Hugging Face Space Configuration
-
-The Dockerfile is configured to:
-- Use Python 3.11
-- Install all dependencies
-- Expose port 7860 (Hugging Face default)
-- Run the FastAPI application with Uvicorn
-
-Hugging Face will automatically:
-- Build the Docker image
-- Set environment variables from secrets
-- Deploy the container
-- Provide a public URL
-
-## API Documentation
-
-Once deployed, access interactive API documentation at:
-- Swagger UI: `http://your-url/docs`
-- ReDoc: `http://your-url/redoc`
-
-## Algorithm Details
-
-The Smart Budget Recommendation engine:
-
-1. **Data Collection**: Analyzes expenses from the past 6 months
-2. **Category Analysis**: Groups expenses by category and calculates:
-   - Average monthly spending
-   - Standard deviation (variability)
-   - Number of transactions
-   - Months of data available
-3. **Budget Calculation**: 
-   - Base: Average monthly expense
-   - Buffer: 5-10% based on spending variability
-   - Rounding: Rounds to nearest 100 for cleaner numbers
-4. **Confidence Scoring**: 
-   - Based on data quality (months analyzed, transaction count, consistency)
-   - Returns score from 0-1
-5. **(Optional) GPT Refinement**:
-   - If `OPENAI_API_KEY` is set, GPT reviews the history and suggests increase/decrease/keep along with a natural-language reason.
-
-## Environment Variables
-
-- `MONGODB_URI`: MongoDB connection string (required)
-- `OPENAI_API_KEY`: Optional. If set, GPT-based recommendations augment the rule-based engine.
-
-## License
-
-Copyright © 2025 WalletSync. All Rights Reserved