Add /api/predict REST endpoint with CORS support for Postman testing

POSTMAN_EXAMPLE.md

@@ -0,0 +1,131 @@
+# Postman API Testing Guide
+
+## Endpoint: `/api/predict`
+
+### Request Configuration
+
+**Method:** `POST`  
+**URL:** `https://saifisvibin-volaris-pdf-tool.hf.space/api/predict`  
+**Headers:** None required (multipart/form-data is set automatically)
+
+### Body Configuration
+
+1. Select **Body** tab
+2. Select **form-data** (not raw)
+3. Add a key named `file`
+4. Change the type from "Text" to **"File"** (dropdown on the right)
+5. Click **"Select Files"** and choose a PDF file
+
+### Example Request in Postman
+
+```
+POST https://saifisvibin-volaris-pdf-tool.hf.space/api/predict
+Content-Type: multipart/form-data
+
+Body (form-data):
+  file: [Select PDF file]
+```
+
+### Expected Response
+
+```json
+{
+  "status": "success",
+  "filename": "document.pdf",
+  "text": "# Document Title\n\nThis is the extracted markdown text...",
+  "tables": [
+    {
+      "page": 1,
+      "bbox": [100, 200, 500, 400],
+      "confidence": 0.95,
+      "width": 400,
+      "height": 200,
+      "image_base64": "data:image/png;base64,iVBORw0KGgoAAAANS...",
+      "image_path": "tables/page_1_tab_0.png"
+    }
+  ],
+  "figures": [
+    {
+      "page": 2,
+      "bbox": [150, 250, 550, 650],
+      "confidence": 0.92,
+      "width": 400,
+      "height": 400,
+      "image_base64": "data:image/png;base64,iVBORw0KGgoAAAANS...",
+      "image_path": "figures/page_2_fig_0.png"
+    }
+  ],
+  "summary": {
+    "total_pages": 42,
+    "figures_count": 5,
+    "tables_count": 3,
+    "elements_count": 8
+  }
+}
+```
+
+### Error Response
+
+```json
+{
+  "status": "error",
+  "error": "Error message here"
+}
+```
+
+### cURL Example
+
+```bash
+curl -X POST https://saifisvibin-volaris-pdf-tool.hf.space/api/predict \
+  -F "file=@/path/to/your/document.pdf"
+```
+
+### Python Example
+
+```python
+import requests
+
+url = "https://saifisvibin-volaris-pdf-tool.hf.space/api/predict"
+
+with open("document.pdf", "rb") as f:
+    files = {"file": f}
+    response = requests.post(url, files=files)
+
+result = response.json()
+print(f"Status: {result['status']}")
+print(f"Figures: {result['summary']['figures_count']}")
+print(f"Tables: {result['summary']['tables_count']}")
+print(f"Text length: {len(result['text'])} characters")
+```
+
+### JavaScript/Fetch Example
+
+```javascript
+const formData = new FormData();
+formData.append('file', fileInput.files[0]);
+
+fetch('https://saifisvibin-volaris-pdf-tool.hf.space/api/predict', {
+  method: 'POST',
+  body: formData
+})
+.then(response => response.json())
+.then(data => {
+  console.log('Status:', data.status);
+  console.log('Figures:', data.summary.figures_count);
+  console.log('Tables:', data.summary.tables_count);
+  console.log('Text:', data.text);
+})
+.catch(error => console.error('Error:', error));
+```
+
+### Testing Checklist
+
+- [ ] Upload a PDF file
+- [ ] Verify response status is "success"
+- [ ] Check that "text" field contains extracted markdown
+- [ ] Verify "tables" array contains table data with base64 images
+- [ ] Verify "figures" array contains figure data with base64 images
+- [ ] Check "summary" contains correct counts
+- [ ] Test with invalid file type (should return error)
+- [ ] Test without file (should return error)
+

app.py

@@ -6,13 +6,17 @@ import uuid
 from pathlib import Path
 from typing import Dict, List, Optional
 from flask import Flask, render_template, request, jsonify, send_file, send_from_directory
+from flask_cors import CORS
 from werkzeug.utils import secure_filename
 import torch
+import base64
 
 import main as extractor
 from loguru import logger
 
 app = Flask(__name__)
+# Enable CORS for all routes
+CORS(app, resources={r"/api/*": {"origins": "*"}})
 app.config['MAX_CONTENT_LENGTH'] = 500 * 1024 * 1024  # 500MB max file size
 app.config['UPLOAD_FOLDER'] = './uploads'
 app.config['OUTPUT_FOLDER'] = './output'

requirements.txt

@@ -10,3 +10,4 @@ loguru==0.7.3
 numpy==1.26.4
 flask==3.0.0
 werkzeug==3.0.1
+flask-cors==4.0.0