viscribe 1.0.2

ViscribeAI SDK

🌐 ViscribeAI - Python SDK

Official Python SDK for ViscribeAI - AI-powered image understanding and analysis.

🎁 Get started with free credits! Visit dashboard.viscribe.ai to sign up and get your API key.

📦 Installation

pip install viscribe

🚀 Features

• 🖼️ AI-powered image description, extraction, classification, VQA (Visual Question Answering), and comparison
• 🔄 Both sync and async clients
• 📊 Structured output with Pydantic schemas
• 🔍 Detailed logging
• ⚡ Automatic retries
• 🔐 Secure authentication

🎯 Quick Start

from viscribe import Client

client = Client(api_key="your-api-key-here")

Note: You can set the VISCRIBE_API_KEY environment variable and initialize the client without parameters: client = Client()

📚 Image Endpoints

1. Describe Image

Generate a natural language description of an image, optionally with tags.

from viscribe import Client
client = Client(api_key="your-api-key-here")

resp = client.describe_image(
    image_url="https://img.com/cat.jpg",
    generate_tags=True
)
print(resp)

2. Classify Image

Classify an image into one or more categories.

resp = client.classify_image(
    image_url="https://img.com/cat.jpg",
    classes=["cat", "dog"]
)
print(resp)

3. Visual Question Answering (VQA)

Ask a question about the content of an image and get an answer.

resp = client.ask_image(
    image_url="https://img.com/car.jpg",
    question="What color is the car?"
)
print(resp)

4. Extract Structured Data from Image

Extract structured data from an image using either simple fields or an advanced schema.

Simple Fields (Recommended for basic extraction)

Use simple fields for straightforward data extraction (max 10 fields):

resp = client.extract_image(
    image_url="https://img.com/prod.jpg",
    fields=[
        {"name": "product_name", "type": "text", "description": "Name of the product"},
        {"name": "price", "type": "number", "description": "Product price"},
        {"name": "tags", "type": "array_text", "description": "Product tags"},
    ]
)
print(resp.extracted_data)

Field Types:

• text: Single text value
• number: Single numeric value
• array_text: Array of text values (max 5 items)
• array_number: Array of numeric values (max 5 items)

Advanced Schema (For complex/nested structures)

Use advanced schema for complex nested structures or when you need more control:

from pydantic import BaseModel

class Product(BaseModel):
    product_name: str
    price: float
    specifications: dict

resp = client.extract_image(
    image_url="https://img.com/prod.jpg",
    advanced_schema=Product  # Pass the class directly
)
print(resp.extracted_data)

Note: Either fields or advanced_schema must be provided, not both.

5. Compare Images

Compare two images and get a description of their similarities and differences.

resp = client.compare_images(
    image1_url="https://img.com/cat1.jpg",
    image2_url="https://img.com/cat2.jpg"
)
print(resp)

👤 User Endpoints

Check credits and submit feedback.

Get Credits

credits = client.get_credits()
print(credits)

Submit Feedback

feedback_response = client.submit_feedback(
    request_id="your-request-id",
    rating=5,  # Rating from 1-5
    feedback_text="Perfect image description!",
)
print(feedback_response)

⚡ Async Usage

All endpoints support async operations:

import asyncio
from viscribe import AsyncClient

async def main():
    client = AsyncClient(api_key="your-api-key-here")
    resp = await client.describe_image({"image_url": "https://img.com/cat.jpg"})
    print(resp)
    # ... use other endpoints as above

asyncio.run(main())

📖 Documentation

For detailed documentation, visit docs.viscribe.ai

🛠️ Development

For information about setting up the development environment and contributing to the project, see our Contributing Guide.

💬 Support & Feedback

• 📧 Email: [e-mail]
• 💻 GitHub Issues: Create an issue
• 🌟 Feature Requests: Request a feature
• ⭐ API Feedback: You can also submit feedback programmatically using the feedback endpoint:

  from viscribe import Client
  
  client = Client(api_key="your-api-key-here")
  
  client.submit_feedback(
      request_id="your-request-id",
      rating=5,
      feedback_text="Great results!"
  )
  

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Links

• Website
• Documentation
• GitHub

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🎁 Get started with free credits! Visit dashboard.viscribe.ai to sign up and get your API key.

Made with ❤️ by ViscribeAI