Unlock AI-Powered Summarization: Use Vision Instruct Models on DigitalOcean

Want to create concise presentation notes without the tedious manual work? Discover how DigitalOcean's Vision Instruct models, paired with Hugging Face, can automate slide summarization and boost your productivity. Dive into this guide to learn how to effortlessly integrate advanced multi-modal AI into your projects.

What are Vision Instruct Models?

Vision Instruct models are AI powerhouses capable of processing both images and text simultaneously. They’re perfect for tasks requiring visual data analysis alongside textual context, opening doors to AI-driven automation for developers and data scientists.

Think of Vision Instruct models as your AI assistants, simplifying complex tasks like:

• Analyzing images and Videos
• Creating accurate image captions.
• Answering questions about visual content.
• Powering intelligent chatbots.

Why Use Vision Instruct for Slide Summaries?

Manually summarizing slides is time-consuming. Vision Instruct models streamline this process by interpreting slide images and presentation abstracts, saving you valuable time! This is a game-changer for educators, professionals, and anyone who wants polished presentations without the extra effort.

Vision Instruct models offer versatility beyond slide summarization. Consider these use cases:

• Generating alt-text, improving accessibility.
• Automating content tagging in digital libraries.
• Creating quick previews for image-rich reports.
• Automatically labeling objects inside of assets.

Hands-On: Automate Slide Note Generation with DigitalOcean and Vision Instruct

Here’s a step-by-step guide to automating slide summarization using Vision Instruct models hosted on DigitalOcean:

Prerequisites:

• A Linux or Mac-based developer laptop (Windows users can use a VM or cloud instance).
• Python 3.10+ (using a virtual environment is highly recommended).
• Installed Libraries: pip install huggingface_hub.
• ImageMagick installed for PDF-to-image conversion.
• A PDF presentation (like this NVIDIA GTC session: Crack the AI Black Box).

Step 1: Deploy Your Vision Instruct Model on DigitalOcean

Simplify deployment with DigitalOcean's one-click GPU Droplets:

1. Create a GPU Droplet.
2. Select the Vision Instruct model in the Marketplace.
3. Done!

Step 2: Convert Your Slides to Images with ImageMagick

Turn your presentation into individual slide images:

1. Download your presentation (or use the example NVIDIA GTC session).
2. Open your terminal and use ImageMagick: magick your_presentation.pdf slide_%03d.png
3. Create a subfolder called slides_images and move converted images into it.
4. Upload the slides_images folder to a DigitalOcean Spaces bucket and grant public access. This allows your Python script to access the images.

Step 3: Generate Summaries with Python and Vision Instruct

Use the following Python script to interact with your DigitalOcean-hosted Vision Instruct model and generate summaries:

#!/usr/bin/env python3
import os
from huggingface_hub import InferenceClient

# Configuration
BASE_URL = "http://<REPLACE WITH YOUR 1-CLICK MODEL IP>/v1"
API_KEY = "<REPLACE WITH YOUR BEARER_TOKEN>"
IMAGES_DIR = "./slides_images"
IMAGE_URL_PREFIX = "<YOUR UNIQUE DIGITALOCEAN BUCKET NAME>/slides_images"
ABSTRACT_TEXT = "<REPLACE WITH A SESSION ABSTRACT FOR YOUR SLIDES>"

# Initialize the inference client
client = InferenceClient(base_url=BASE_URL, api_key=API_KEY)

def generate_slide_summary(slide_file: str, slide_number: int, abstract_text: str) -> str:
    """Sends the abstract text and an image URL to the InferenceClient's chat endpoint."""
    slide_url = f"{IMAGE_URL_PREFIX}/{slide_file}"
    messages = [
        {"role": "user", "content": [{"type": "text", "text": f"Presentation Abstract: {abstract_text}"}]},
        {"role": "user", "content": [{"type": "image_url", "image_url": {"url": slide_url}},
                                     {"type": "text", "text": f"Slide number {slide_number}. Please summarize this slide based on the context of the abstract."}]}
    ]
    response = client.chat.completions.create(messages=messages, temperature=0.7, top_p=0.95, max_tokens=150)
    return response["choices"][0]["message"]["content"]

def main():
    slide_images = sorted([f for f in os.listdir(IMAGES_DIR) if f.lower().endswith(".png")])
    if not slide_images:
        print("No slide images found in the specified directory.")
        return
    for idx, slide_file in enumerate(slide_images, start=1):
        print(f"\n--- Generating summary for {slide_file} ---")
        slide_summary = generate_slide_summary(slide_file, idx, ABSTRACT_TEXT)
        print(f"Summary:\n{slide_summary}")

if __name__ == "__main__":
    main()

Important! Replace the placeholders in the script with your:

• Droplet's IP Address.
• Bearer Token (found on your Droplet).
• DigitalOcean Spaces Bucket FQDN.
• Presentation Abstract.

Example output using the XAI presentation:

--- Generating summary for slide_004.png ---
Summary:
Slide 5 illustrates flawed data, which is a key challenge in AI/ML.  The slides features examples such as biased data leading to disriminatory outcomes.

--- Generating summary for slide_005.png ---
Summary:
This slide introduces the topic of Explainable AI ( XAI) by highlighting the importance of trust, transparency, debugging, improvement, compliance, and ethics...

Vision Instruct Model (FAQs)

1. What can Vision Instruct models do?

Vision Instruct models can do more than generating summaries. They handle multi-modal tasks integrating visuals and text for image captioning, visual question answering, and image-text retrieval.

2. How do I convert PDFs to images?

Use ImageMagick! It's an open-source tool designed for image manipulation. Refer to ImageMagick's documentation for detailed instructions.

3. What's the InferenceClient's job?

The Hugging Face InferenceClient bridges communication with the remotely hosted Vision Instruct model. It generates slide summaries, making integration seamless and efficient.

4. How do I align talking points with visuals?

Vision Instruct models generate concise and context-aware summaries, guiding your talking points to make them relevant and accurate.

5. What else can I do with Vision Instruct models?

Think beyond summaries! Use them for generating alt-text, automating content tagging, or creating image-heavy report previews.

6. How do I deploy the Models on DigitalOcean?

Create a GPU Droplet, choose the Model, and DigitalOcean sets up everything automatically.

7. What are the main benefits in summariation?

Summaries will be more accurate, are more time efficient because the need for manual effort reduces and it also increases productivity.