From Chat to Image to Video: How to Design a Multimodal AI Character Experience

Delvin — Tue, 06 Oct 2026 11:51:23 +0000

Building an AI chat app is relatively straightforward today.

Send a conversation to an LLM, get a response back, render it in the UI.

But things get much more interesting when the same AI character needs to exist across chat, images, and video.

Imagine this flow:

Create Character
      ↓
Chat
      ↓
Generate Image
      ↓
Animate Image
      ↓
Generate Video

At first glance, these look like four separate AI features.

They shouldn't be.

When building an AI companion product, the real challenge is making all of these models feel like they are interacting with the same character.

I ran into this problem while working with Veline AI, an AI companion platform that connects character creation, conversation, image generation, and image-to-video generation.

Here are some of the design patterns that make this kind of workflow much easier to build.

The Wrong Approach: Treat Every AI Feature Separately

A simple architecture might look like this:

/chat
/image-generator
/video-generator
/character-creator

Technically, this works.

The problem is that each feature knows very little about the others.

A user creates a character named Emma in one screen.

Then the image generator asks them to describe Emma again.

Then the video generator asks for another prompt.

From the user's perspective, the product feels like four unrelated AI tools glued together.

A better architecture is:

             ┌── Chat
             │
Character ───┼── Image
             │
             └── Video

The character becomes the persistent object.

Everything else operates on it.

Step 1: Store a Structured Character Profile

Instead of storing the character as one giant prompt, use structured data.

For example:

const character = {
  id: "char_83fa",
  name: "Emma",
  visualStyle: "realistic",

  appearance: {
    hair: "long brown hair",
    eyes: "green",
    outfitStyle: "casual"
  },

  personality: {
    primary: "playful",
    secondary: "thoughtful",
    communicationStyle: "warm"
  },

  relationship: "girlfriend"
};

Structured attributes are much easier to reuse.

Your chat system might care mostly about:

character.personality
character.relationship

while your image pipeline might use:

character.visualStyle
character.appearance

Both are still referencing the same character.

Step 2: Build Prompts Dynamically

Users generally shouldn't have to understand prompt engineering.

Instead of showing them a giant textarea like:

Write the perfect Stable Diffusion prompt here...

you can let them make simple choices.

For example:

const generation = {
  scene: "coffee shop",
  outfit: "black dress",
  pose: "sitting by the window",
  mood: "romantic"
};

Then generate the final prompt internally:

function createImagePrompt(character, generation) {
  return `
    ${character.visualStyle} portrait of ${character.name},
    ${character.appearance.hair},
    ${character.appearance.eyes} eyes,
    wearing ${generation.outfit},
    ${generation.pose},
    inside a ${generation.scene},
    ${generation.mood} atmosphere,
    consistent character appearance,
    high detail
  `.trim();
}

Now the UI becomes much simpler.

Scene
[ Coffee Shop ▼ ]

Outfit
[ Black Dress ▼ ]

Pose
[ Sitting ▼ ]

Mood
[ Romantic ▼ ]

[ Generate ]

This is usually much easier for non-technical users than writing prompts manually.

Step 3: Keep Generation Attached to the Character

Every generated asset should reference its originating character.

For example:

const creation = {
  id: "img_f93e",
  characterId: "char_83fa",
  type: "image",
  prompt: "...",
  status: "completed",
  url: "https://cdn.example.com/image.webp"
};

That characterId becomes extremely useful later.

It allows you to build things like:

Emma
 ├── Conversation #1
 ├── Conversation #2
 ├── Image #1
 ├── Image #2
 └── Video #1

Instead of creating a generic gallery, you are creating a history for the character.

That changes the UX significantly.

Step 4: Treat Video Generation as an Async Job

Image generation is often fast enough that users are willing to wait on the page.

Video generation is different.

It can take significantly longer depending on the model.

Don't make your frontend wait for a single HTTP request like this:

const video = await fetch("/generate-video", {
  method: "POST",
  body: JSON.stringify(data)
});

If generation takes one or two minutes, that becomes fragile quickly.

A better pattern is asynchronous jobs.

Start the job

const response = await fetch("/api/videos", {
  method: "POST",
  headers: {
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    characterId: "char_83fa",
    imageId: "img_f93e"
  })
});

const { taskId } = await response.json();

The API immediately returns:

{
  "taskId": "video_task_1288",
  "status": "queued"
}

Poll the status

async function waitForVideo(taskId) {
  while (true) {
    const response = await fetch(`/api/videos/${taskId}`);
    const task = await response.json();

    if (task.status === "completed") {
      return task;
    }

    if (task.status === "failed") {
      throw new Error("Video generation failed");
    }

    await new Promise(resolve => setTimeout(resolve, 5000));
  }
}

For larger products, WebSockets, Server-Sent Events, or a queue system can improve this further.

The important idea is:

Generation should not depend on the browser session staying open.

The user should be able to leave the page and come back later.

Step 5: Build a Unified "My Creations" Layer

Once images and videos are asynchronous, users need one place to find them.

A simple API might be:

GET /api/characters/:id/creations

Returning:

[
  {
    "type": "image",
    "status": "completed",
    "createdAt": "2026-10-01T10:15:00Z"
  },
  {
    "type": "video",
    "status": "processing",
    "createdAt": "2026-10-01T10:17:00Z"
  }
]

The frontend can then render:

My Creations

Emma

┌─────────────┐
│   Image     │
│ Completed   │
└─────────────┘

┌─────────────┐
│   Video     │
│ Processing  │
└─────────────┘

This sounds like a small UX detail, but it's especially important for generative AI products where requests don't always finish immediately.

Step 6: Don't Couple the Product to One AI Model

AI models change incredibly fast.

Today's best image model might not be the best option six months from now.

So instead of doing this:

generateWithModelX(prompt);

introduce a provider layer:

async function generateImage({
  provider,
  prompt,
  character
}) {
  switch (provider) {
    case "providerA":
      return providerA.generate(prompt);

    case "providerB":
      return providerB.generate(prompt);

    default:
      throw new Error("Unsupported provider");
  }
}

Eventually, the provider can even be selected dynamically.

Generation Request
        ↓
   Model Router
     ↙     ↘
 Fast      Quality
 Model      Model

For example:

function selectImageModel(request) {
  if (request.priority === "speed") {
    return "fast-model";
  }

  if (request.priority === "quality") {
    return "premium-model";
  }

  return "balanced-model";
}

This gives you much more flexibility around:

generation quality
latency
API reliability
model availability
cost per generation

For AI products, model abstraction is becoming increasingly similar to database abstraction: you usually don't want your entire application coupled tightly to one vendor.

The Bigger Lesson

When building multimodal AI products, it is tempting to think in terms of models:

LLM
Image Model
Video Model
Voice Model

But users don't care which model produced something.

They care about the experience.

For an AI character application, a better mental model is:

                    ┌── Conversation
                    │
                    ├── Images
User ── Character ──┼── Videos
                    │
                    └── Memories

The character is the product abstraction.

The AI models are implementation details underneath it.

That is the approach we're exploring with Veline AI: instead of treating chat, image generation, and video generation as isolated tools, connect them around a persistent fictional character.

If you're building something similar, I'd strongly recommend designing the character/data layer first and adding individual AI models afterward.

It makes replacing models much easier — and, more importantly, creates a much more coherent experience for users.

Is Veline AI Worth Trying? A Closer Look at This Affordable AI Girlfriend Platform

Delvin — Thu, 23 Jul 2026 02:30:06 +0000

The AI girlfriend market is becoming crowded. Most platforms promise realistic conversations and attractive characters, but many end up offering the same experience: repetitive replies, expensive credit systems, and creative features spread across several different tools.

After spending time with Veline AI, what stood out was how naturally it brings storytelling, chat, image generation, video, and voice into one place—without making regular use unnecessarily expensive.

Characters With More Than a Profile Picture

A visually appealing character may grab your attention, but personality is what keeps a conversation interesting.
The platform gives its characters distinct backgrounds, personalities, and evolving storylines. Conversations feel closer to interactive fiction or long-form AI roleplay than a basic chatbot exchange. Instead of starting over each time, users can gradually develop a story and relationship with the same character.
Support for the Tavern ecosystem is another useful addition. Users familiar with Tavern characters can bring their favorite creations into the platform and continue building stories around them.

Free Chat With More Ways to Interact

Text remains the foundation of most AI companion services, but Veline AI goes beyond messaging.
The platform combines free AI girlfriend chat with image generation, AI video creation, and voice interaction. A conversation can move from text to a custom picture, short video, or spoken response without requiring several unrelated services.
Users looking for an AI NSFW image generator can also create detailed images directly from prompts or existing photos, making the creative workflow much smoother than switching between multiple tools.

Creative Freedom for Adult Users

People use AI companions for different reasons. Some want casual conversation, while others prefer romance, fantasy scenarios, character-driven stories, or adult roleplay.
The platform includes NSFW tools designed for adult users. Besides generating images, it also supports AI image-to-video generation for NSFW content, allowing users to transform still images into dynamic videos as part of the same creative experience.
Because these tools are connected to the character and chat experience, they feel like part of a continuing story rather than isolated generation tools.

Pricing That Makes Longer Conversations Possible

Token pricing is one of the biggest frustrations in the AI girlfriend category.
On many platforms, every message, image, and video consumes separate credits. Users quickly begin monitoring their balance instead of enjoying the interaction.
Veline AI is priced at roughly half the cost of many comparable AI companion services. Its lower pricing makes it easier to have longer conversations and experiment with images or videos without constantly worrying about token consumption.

Final Verdict

Veline AI offers a well-rounded experience for users who want more than a simple chatbot. Its story-driven characters, Tavern compatibility, free chat, voice interaction, image and video generation, NSFW features, and affordable pricing cover most of what regular AI companion users actually need.
For anyone who values ongoing AI roleplay and wants more freedom to chat and create, it is an option worth exploring.

DEV Community: Delvin

From Chat to Image to Video: How to Design a Multimodal AI Character Experience

The Wrong Approach: Treat Every AI Feature Separately

Step 1: Store a Structured Character Profile

Step 2: Build Prompts Dynamically

Step 3: Keep Generation Attached to the Character

Step 4: Treat Video Generation as an Async Job

Start the job

Poll the status

Step 5: Build a Unified "My Creations" Layer

Step 6: Don't Couple the Product to One AI Model

The Bigger Lesson

Is Veline AI Worth Trying? A Closer Look at This Affordable AI Girlfriend Platform

Characters With More Than a Profile Picture

Free Chat With More Ways to Interact

Creative Freedom for Adult Users

Pricing That Makes Longer Conversations Possible

Final Verdict