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📸 Postman Examples for Image Processing Endpoints

🌅 Your iStock Image Example

Based on the image you provided: Family Sunset Photo

Extracted Content:

  • Title: "Family Enjoying a Sunny Day in a Field"
  • Description: "The image depicts a woman and two children in a sunlit field. The woman, wearing a pink sweater, is kneeling and facing the children, who are standing. The child on the left, a young girl, is wearing a pink top and has her hair in a ponytail. The child on the right, a young boy, is wearing a blue shirt. The sun is setting or rising in the background, casting a warm glow over the scene. The field is filled with tall, golden grass, and there are trees in the distance."
  • Text Found: "iStock Credit: kieferpix 1468298683"

🚀 Postman Setup for /transcribe-image-url

Method & URL

POST http://localhost:8000/transcribe-image-url

Headers

Content-Type: application/json
Accept: application/json

Body (JSON)

Example: Your iStock Image (Simplified)

{
  "url": "https://media.istockphoto.com/id/1468298683/pt/foto/mother-and-her-two-children-boy-and-girl-relaxing-in-nature-grass-field-watching-the-sunset.jpg?s=2048x2048&w=is&k=20&c=7wMm1zEerJCW3xDdm2gwovcdTBeU7DeayHEaYDNsJBI="
}

📝 Expected Response

{
  "file_id": "e5de9397-0431-4e8c-85e6-2ff1250210fe",
  "file_info": {
    "name": "family_sunset.jpg",
    "extension": ".jpg",
    "size_mb": 0.34,
    "mime_type": "image/jpeg",
    "duration": null,
    "chunks_processed": null,
    "url": "https://media.istockphoto.com/id/1468298683/pt/foto/mother-and-her-two-children-boy-and-girl-relaxing-in-nature-grass-field-watching-the-sunset.jpg?s=2048x2048&w=is&k=20&c=7wMm1zEerJCW3xDdm2gwovcdTBeU7DeayHEaYDNsJBI="
  },
  "success": true,
  "error": null,
  "title": "Family Enjoying a Sunny Day in a Field",
  "description": "The image depicts a woman and two children in a sunlit field. The woman, wearing a pink sweater, is kneeling and facing the children, who are standing. The child on the left, a young girl, is wearing a pink top and has her hair in a ponytail. The child on the right, a young boy, is wearing a blue shirt. The sun is setting or rising in the background, casting a warm glow over the scene. The field is filled with tall, golden grass, and there are trees in the distance.",
  "extracted_text": "iStock\nCredit: kieferpix\n1468298683",
  "processor_used": "OpenAI Vision",
  "processing_time": 4.228828,
  "timestamp": "2025-09-23T14:17:51.668013"
}

🔄 Alternative: File Upload Endpoint

If you want to upload the image file directly instead of using a URL:

Method & URL

POST http://localhost:8000/transcribe-image

Headers

Accept: application/json

Body (form-data)

Key: file
Type: File
Value: [Select your downloaded image file]

📋 More Postman Examples

Example 2: Other Image URLs

{
  "url": "https://picsum.photos/800/600"
}

Example 3: GitHub Image

{
  "url": "https://raw.githubusercontent.com/user/repo/main/image.png"
}

Example 4: Direct Image URL

{
  "url": "https://i.imgur.com/example.jpg"
}

🛠️ Postman Collection Setup

1. Create New Collection

  • Name: "AI Content Processing API"
  • Description: "Image processing and text extraction"

2. Add Environment Variables

api_base_url: http://localhost:8000

3. Add Request

  • Name: "Transcribe Image URL"
  • Method: POST
  • URL: {{api_base_url}}/transcribe-image-url

4. Pre-request Script (Optional)

// Log the request
console.log("Processing image URL:", pm.request.body.raw);

5. Tests Script

// Test successful response
pm.test("Status code is 200", function () {
    pm.response.to.have.status(200);
});

pm.test("Response has success field", function () {
    var jsonData = pm.response.json();
    pm.expect(jsonData).to.have.property('success');
});

pm.test("Processing was successful", function () {
    var jsonData = pm.response.json();
    pm.expect(jsonData.success).to.eql(true);
});

pm.test("Response has extracted content", function () {
    var jsonData = pm.response.json();
    pm.expect(jsonData).to.have.property('title');
    pm.expect(jsonData).to.have.property('description');
    pm.expect(jsonData).to.have.property('extracted_text');
});

// Log results
var response = pm.response.json();
if (response.success) {
    console.log("Title:", response.title);
    console.log("Description:", response.description);
    console.log("Extracted Text:", response.extracted_text);
    console.log("Processing Time:", response.processing_time + "s");
}

🔍 Postman Tips

1. Environment Setup

Create an environment with:

  • api_url: http://localhost:8000
  • image_url: https://media.istockphoto.com/id/1468298683/pt/foto/mother-and-her-two-children-boy-and-girl-relaxing-in-nature-grass-field-watching-the-sunset.jpg?s=2048x2048&w=is&k=20&c=7wMm1zEerJCW3xDdm2gwovcdTBeU7DeayHEaYDNsJBI=

2. Dynamic Variables

Use in your request body:

{
  "url": "{{image_url}}",
  "filename": "{{$randomFileName}}.jpg"
}

3. Save Response

Add to Tests script:

// Save response to environment
var response = pm.response.json();
pm.environment.set("last_extracted_text", response.extracted_text);
pm.environment.set("last_processing_time", response.processing_time);

🚨 Common Issues & Solutions

1. CORS Issues

Add to Headers:

Origin: http://localhost:3000

2. Long URLs

For very long URLs, encode them:

// Pre-request script
var encodedUrl = encodeURIComponent(pm.environment.get("image_url"));
pm.environment.set("encoded_image_url", encodedUrl);

3. Timeout for Large Images

Increase timeout in Settings > General > Request timeout

4. Authentication (if needed)

Add to Headers:

Authorization: Bearer your_api_token

📱 Mobile Testing

For mobile app development, test with:

{
  "url": "https://media.istockphoto.com/id/1468298683/pt/foto/mother-and-her-two-children-boy-and-girl-relaxing-in-nature-grass-field-watching-the-sunset.jpg?s=2048x2048&w=is&k=20&c=7wMm1zEerJCW3xDdm2gwovcdTBeU7DeayHEaYDNsJBI=",
  "filename": "mobile_upload.jpg"
}

🌐 Bulk Testing

Create multiple requests with different image URLs:

  1. Stock photos
  2. Screenshots
  3. Documents with text
  4. Handwritten notes
  5. Social media images

Each will return different extracted content based on what's visible in the image!