PowerPoint Presentation Maker: Python, OpenAI, and Dezgo Teaming Up!

Generating a full presentation programmatically — outline, slide content, and images — takes three tools working together: an LLM for the content structure, an image generator for visuals, and python-pptx to assemble it all into an actual .pptx file. Here’s the working pipeline, end to end.

Step 1: Generate the Outline and Content

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY")

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{
        "role": "user",
        "content": """Create a 5-slide presentation outline about [YOUR TOPIC].
        For each slide, provide: a title, 3-4 bullet points, and a one-sentence
        image description for a relevant visual. Format as JSON with keys:
        title, bullets (list), image_prompt."""
    }],
    response_format={"type": "json_object"}
)

import json
slides_data = json.loads(response.choices[0].message.content)

Asking for structured JSON output directly (rather than parsing free-form text) makes the rest of the pipeline far more reliable — you’re not writing fragile regex to extract slide titles from prose.

Step 2: Generate Images for Each Slide

def generate_slide_image(prompt, filename):
    result = client.images.generate(
        model="dall-e-3",
        prompt=prompt,
        size="1024x1024",
        n=1
    )
    import requests
    img_data = requests.get(result.data[0].url).content
    with open(filename, "wb") as f:
        f.write(img_data)
    return filename

DALL-E 3 is the straightforward default here since you’re already using OpenAI for content generation — one API, one billing relationship. If you need a specific visual style or lower cost at higher volume, Stable Diffusion (self-hosted or via a provider like Replicate) is the usual alternative, at the cost of more setup.

Step 3: Assemble the .pptx File

from pptx import Presentation
from pptx.util import Inches, Pt

prs = Presentation()

for i, slide_data in enumerate(slides_data["slides"]):
    slide_layout = prs.slide_layouts[1]  # Title and Content layout
    slide = prs.slides.add_slide(slide_layout)

    slide.shapes.title.text = slide_data["title"]

    body = slide.placeholders[1].text_frame
    for bullet in slide_data["bullets"]:
        p = body.add_paragraph()
        p.text = bullet
        p.font.size = Pt(18)

    img_path = generate_slide_image(slide_data["image_prompt"], f"slide_{i}.png")
    slide.shapes.add_picture(img_path, Inches(5.5), Inches(1.5), width=Inches(4))

prs.save("generated_presentation.pptx")

Where This Approach Actually Helps

• Batch-generating first drafts for a recurring presentation format (weekly reports, standardized training decks) where the structure repeats but content changes.
• Rapid prototyping of a presentation’s structure and flow before investing design time in the final version.
• Programmatic pipelines where presentation generation is one step in a larger automated workflow, not a one-off manual task.

For a single, important, polished presentation, this pipeline gets you a strong first draft, not a finished product — plan on a manual design pass afterward for layout, spacing, and visual polish that automated generation doesn’t handle well.

Frequently Asked Questions

Do I need both OpenAI’s chat model and DALL-E, or can I use one provider for everything?
You can mix providers freely — the pipeline just needs something that returns structured text (any capable LLM) and something that returns images (DALL-E, Stable Diffusion, Midjourney’s API where available). Using one provider for both simplifies billing but isn’t required.

Is python-pptx able to handle complex slide layouts and animations?
It handles standard layouts, text, and images well, but has limited support for animations and highly custom designs — for those, treat the generated file as a content-complete draft to finish manually in PowerPoint or Google Slides.

Conclusion

A working AI-generated presentation pipeline is three straightforward pieces: an LLM for structured slide content, an image generator for visuals, and python-pptx to assemble the final file. It’s genuinely useful for drafts and repeatable formats — just plan on a manual polish pass for anything presentation-critical.