How I Constructed a Comedian Generator with OpenAI and Gemini

We’ve all loved comics in some unspecified time in the future, be it superhero comedian books, comics in newspapers, or manga from Japan. Comics are transient, expressive, and encapsulate storytelling inside only a few frames.  However what if there’s a new twist: what should you might use a comic book generator to show a brief video clip into a comic book strip of 4 panels with speech bubbles, expressive caricatures, and humour?

That is the thought behind Comedian Generator or Comedian Conflict, not simply one other content material generator. Nonetheless, a system I designed that takes a video clip and a brief, transient artistic concept and turns it right into a completed sketch picture. It’s greatest to consider it as an imaginative partnership between two minds: one “writing the screenplay” and the opposite “drawing the comedian.”

On this article, I’ll information you thru the journey of Comedian Conflict, explaining the way it works, what parts are required, which programming language to make use of for coding, the challenges I encountered through the course of, and the place the mission can go from right here.

The Idea of Comedian Conflict

All artistic functions hinge on a regular components:

• Enter: What the person provides.
• Transformation: How the system operates and furthers it.
• Output: The distillation of the expertise that feels full and polished.

For Comedian Conflict, the components seems like:

• Enter:
  • A brief video (like a YouTube brief).
  • A one-line artistic concept (“Exchange the combating within the clip with exams”).
• Transformation:
  • Systemically, the system analyzes the video, rewrites the thought right into a full comedian screenplay, and strictly enforces guidelines (layouts, fashion, humor).
• Output:
  • A 4-panel sketch in PNG format with dialogue balloons and captions. 

What makes this enjoyable? As a result of it’s customized. As an alternative of random comics, you’ll obtain a reinterpretation of the very clip you simply chosen, tailor-made round your one-line concept.

Think about a combat scene in a film, echoing a pupil morphed right into a goofy classroom battle about homework. This concoction of relatable visuals – acquainted usernames with a shocking, personalised comedian rewrite twist – is what makes Comedian Conflict addictive.

How Comedian Conflict Works

The pipeline is deconstructed as follows:

1. Inputs from the Person

The method begins with two easy inputs:

• Video URL: Your supply materials (ideally YouTube shorts of round 30-40 secs).
• Concept Textual content: Your twist or theme.

Instance:

Video URL: https://www.youtube.com/shorts/xQPAegqvFVs

Concept: As an alternative of violence, exchange it with exams, like Yash saying

“Violence, violence, I don’t like violence, I keep away from… however violence likes me.”

That is all of the person has to offer, no advanced settings, no sliders.

2. The Storyteller’s Job (Gemini)

The primary a part of the pipeline is what I confer with because the Storyteller. That is the place the uncooked enter of a YouTube video hyperlink and a short concept you typed in will get remodeled into one thing structured and usable.

Whenever you paste a video URL, Gemini seems on the clip and extracts particulars:

• What’s occurring within the scene?
• The temper (tense, dramatic, lighthearted).
• How the characters are transferring and interacting.

Then it takes your one-liner (for instance, “exchange violence with exams”) and expands it into a comic book script.

Now, this script isn’t simply random textual content. It’s a screenplay for 4 panels that follows a strict algorithm. These guidelines have been explicitly written into the system immediate that guides Gemini. They embody:

• At all times a 2×2 grid (so each comedian seems constant).
• Strictly a comic book e book fashion (no real looking rendering of characters).
• Dialogue written as meme-like speech bubbles.
• Captions added for additional punchlines or context.
• Nothing cropped, no cut-off textual content, and no dangerous references to copyrighted names.

By baking these constraints into the system immediate, I made positive the Storyteller all the time produces a clear, dependable screenplay. So as an alternative of asking the picture generator to “simply make a comic book,” Gemini prepares a totally structured plan that the following step can observe with out guesswork.

3. The Illustrator’s Job (OpenAI / Imagen)

As soon as the script is prepared, it’s handed on to the Illustrator.

This half doesn’t must interpret something; its single duty is to attract precisely what the Storyteller described.

The Illustrator perform is addressed by a picture technology mannequin. In my setup, I’ve OpenAI’s GPT-Picture-1 as my first selection, and Google’s Imagen as a secondary fallback if the primary device fails.

Here’s what it seems like in observe:

• The Illustrator receives the screenplay as one lengthy, detailed immediate.
• It then renders every panel with the characters, poses, background, and speech bubbles precisely as laid out.
• If OpenAI is unavailable, the identical immediate will get despatched to Imagen mechanically, so that you all the time get a completed comedian.

This separation is the important thing to creating Comedian Conflict dependable.

• Gemini thinks like a director: it writes the script and units the stage.
• GPT-Picture-1 or Imagen, they draw like artists, they observe the directions with out attempting to alter something.

That’s why the output doesn’t really feel messy or random. Every comedian comes out as a correct four-panel strip, styled like a meme, and matches your concept virtually one-to-one

4. Output: The Closing Comedian

The result’s a 4-panel sketch picture:

• Panels are clearly framed.
• Characters in the best poses.
• Speech bubbles with the best textual content.
• Humour intact.

And better of all, it looks like a completed comedian you may be revealed on-line.

Applied sciences Behind Comedian Conflict

Right here’s what powers the system:

• Language & Utilities
  • Python is the glue language.
  • dotenv for API key administration.
  • Pillow for picture dealing with.
  • base64 for processing picture knowledge.
• The Storyteller (Evaluation + Prompting)
  • Gemini (multimodal mannequin): reads video + expands person enter.
• The Illustrator (Picture Technology)
  • OpenAI GPT-Picture-1 (a DALL·E variant).
  • Fallback: Google Imagen (for resilience).

This twin strategy ensures each creativity (from the storyteller) and visible consistency (from the illustrator).

Implementation

Now, let’s look into the precise implementation.

1. Configuration

@dataclass

class ComicGenerationConfig:

    primary_service: str = "openai"

    fallback_service: str = "imagen"

    output_filename: str = "photographs/generated_comic.png"

    openai_model: str = "gpt-image-1"

    imagen_model: str = "imagen-4.0-generate-preview-06-06"

    gemini_model: str = "gemini-2.0-flash"

The place the fashions have been used within the following method:

• OpenAI is the default illustrator.
• Imagen is the backup.
• Gemini is the storyteller.

2. Constructing the Screenplay

def extract_comic_prompt_and_enhance(video_url, user_input):

    response = gemini_client.fashions.generate_content(

        mannequin="gemini-2.0-flash",

        contents=[

            Part(text=enhancement_prompt),

            Part(file_data={"file_uri": video_url, "mime_type": "video/mp4"})

        ]

    )

    return response.textual content

This step rewrites a obscure enter into an in depth comedian immediate.

3. Producing the Picture

OpenAI (main):

outcome = openai_client.photographs.generate(

    mannequin="gpt-image-1",

    immediate=enhanced_prompt,

)

image_bytes = base64.b64decode(outcome.knowledge[0].b64_json)

Imagen (fallback):

response = gemini_client.fashions.generate_images(

    mannequin="imagen-4.0-generate-preview-06-06",

    immediate=enhanced_prompt,

)

image_data = response.generated_images[0].picture

Fallback ensures reliability; if one illustrator fails, the opposite takes over.

4. Saving the Comedian

def save_image(image_data, filename="generated_comic.png"):

    img = PILImage.open(BytesIO(image_data))

    img.save(filename)

    return filename

This methodology writes the sketch to disk in PNG format.

5. Orchestration

def generate_comic(video_url, user_input):

    enhanced_prompt = extract_comic_prompt_and_enhance(video_url, user_input)

    image_data = generate_image_with_fallback(enhanced_prompt)

    return save_image(image_data)

All of the steps tie collectively right here:

• Extract screenplay to Generate comedian to Save output.

Demo Instance

Let’s see this in motion.

Enter:

• Concept: “Exchange violence with exams.”

Generated screenplay:

• Panel 1: Hero slumped at a desk:  “Exams, exams, exams…”
• Panel 2: Slams e book shut: “I don’t like exams!”
• Panel 3: Sneaks away quietly: “I keep away from them…”
• Panel 4: A large e book monster named Finals: “…however exams like me!”

Output:

Challenges in Constructing Comedian Conflict

No mission is with out hurdles. Listed here are some I confronted:

• Obscure Inputs: Customers have a tendency to provide brief concepts. With out enhancement, outputs look bland or obscure resulting from restricted data. Answer: strict screenplay enlargement.
• Picture Failures: Generally picture technology stalls. Answer: automated fallback to a backup service.
• Cropping Points: Speech bubbles bought lower off. Answer: specific composition guidelines in prompts.
• Copyright Dangers: Some clips reference well-known motion pictures. Answer: auto-removal of film names/manufacturers within the screenplay.

Past Comedian Conflict

Comedian Conflict is only one use case. The identical engine can energy:

• Meme Turbines: Auto-generate viral memes from trending clips.
• Instructional Comics: Flip boring lectures into 4-panel explainers.
• Advertising and marketing Instruments: Generate branded storyboards for campaigns.
• Interactive Storytelling: Let customers information tales panel by panel.

Briefly, something that mixes humor, visuals, and personalization may benefit from this strategy.

My DHS Expertise

Comedian Conflict began as one in all our proposals throughout DHS, and it’s one thing very private to me. I labored with my colleagues, Mounish and Badri, and we spent hours considering collectively, tossing concepts and ideas on the market, rejecting concepts, and laughing at issues we got here up with, till we lastly discovered an concept we thought we might actually do something with: “How about we take a brief video and make a comic book strip?”

We submitted our concept, incognizant of what would occur… and we have been shocked when it bought chosen. Finally, we needed to create it, each bit by piece. It entailed many lengthy nights, plenty of debugging, and loads of pleasure each time one thing ‘labored’ the way in which we needed it to. Seeing our concept transfer from simply an concept to one thing actual was truthfully top-of-the-line emotions ever.

Response from People

What we witnessed, after we let it free, was effectively price it, as all of the responses have been constructive. Folks saved telling me it was nice, and that they have been intrigued by the thought and the method of how we arrived on the concept after which made it occur. 

Maybe probably the most shocking half for me was how individuals started to make use of it in methods I by no means thought-about. Mother and father started to make comics for his or her kids, actually turning mundane little tales into one thing particular and visible. Others began exploring and experimenting, considering of probably the most superb prompts after which seeing what occurred subsequent. 

For me, that was probably the most thrilling half, seeing individuals get enthusiastic about one thing we created after which go and create one thing even cooler, and to see this little concept second flip into one thing like Comedian Conflict was superb.

Conclusion

Constructing Comedian Conflict was a lesson in orchestration, splitting the job between a storyteller and an illustrator.

As an alternative of hoping a single mannequin “figures all the things out,” we gave every half a transparent function:

• One expands and buildings the thought
• One attracts faithfully

The result’s one thing that feels polished, private, and enjoyable.

And that’s the purpose: with only a brief video and a foolish concept, anybody can create a comic book that appears prefer it belongs on the web’s entrance web page.

Steadily Requested Questions

Hello, I’m Janvi, a passionate knowledge science fanatic presently working at Analytics Vidhya. My journey into the world of knowledge started with a deep curiosity about how we will extract significant insights from advanced datasets.