Captions API

Overview

The Captions API generates platform-optimized social media captions using the dolphin-mistral:7b model via Ollama. The model is specifically chosen for uncensored, creator-style content writing. Base Path: /api/captions Key Features:

Platform-specific style guides (OnlyFans, Fansly, X, Instagram, TikTok, etc.)
Tone customization (playful, professional, teasing, etc.)
Length control (short, medium, long)
Creator username personalization

POST /api/captions/generate

Generate a social media caption using AI. Authentication: Directus JWT (Bearer token)

Request Parameters

string

default:"onlyfans"

Target platform for the caption. Determines style guide and formatting.Supported values:

onlyfans - Intimate, teasing, personal (1-3 sentences, emojis OK)
fansly - Flirty, direct, confident (encourages subscription)
x - Punchy, under 280 chars, hook + value
reddit - Genuine, community-aware, conversational
tiktok - Energetic, with hashtags, max 150 chars
instagram - Visually descriptive, lifestyle tone, 3-5 hashtags
youtube - Keyword-rich, first 2 lines as hook, timestamps
snapchat - Very short, playful, max 30 chars

string

default:"playful"

Caption tone/voice. Examples: playful, professional, teasing, motivational, casual, confident

string

default:"new content drop"

Main topic or theme for the caption. Examples:

new photo set
behind the scenes
workout motivation
product announcement
Q&A session

string

default:"medium"

Desired caption length.Options:

short - 1-2 sentences, punchy
medium - 2-4 sentences, balanced detail
long - 4-8 sentences, detailed and engaging

string

Creator’s username on the platform (optional). Used to personalize the caption.

Response

boolean

Request success status

string

Generated caption text (trimmed, ready to post)

string

AI model used for generation (e.g., dolphin-mistral:7b)

string

Platform identifier (echoed from request)

Example Request

OnlyFans Caption:

curl -X POST http://localhost:3001/api/captions/generate \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..." \
  -H "Content-Type: application/json" \
  -d '{
    "platform": "onlyfans",
    "tone": "playful",
    "topic": "new lingerie photo set",
    "length": "medium",
    "platform_username": "fitcreator99"
  }'

Response:

{
  "ok": true,
  "caption": "Just dropped a new set that's been driving me wild all week 🔥 You know you wanna see what I've been hiding... link in bio babe 💋",
  "model": "dolphin-mistral:7b",
  "platform": "onlyfans"
}

Instagram Caption:

curl -X POST http://localhost:3001/api/captions/generate \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..." \
  -H "Content-Type: application/json" \
  -d '{
    "platform": "instagram",
    "tone": "motivational",
    "topic": "morning workout routine",
    "length": "long"
  }'

Response:

{
  "ok": true,
  "caption": "Starting the day strong with my favorite 30-minute HIIT circuit 💪 No excuses, just results. If you're struggling to stay consistent, remember: progress over perfection. Every rep counts, every day matters. Who else is getting after it this morning? Drop a 🔥 if you crushed your workout today! #FitnessMotivation #MorningWorkout #HIITTraining #ProgressNotPerfection #FitFam",
  "model": "dolphin-mistral:7b",
  "platform": "instagram"
}

X (Twitter) Post:

curl -X POST http://localhost:3001/api/captions/generate \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..." \
  -H "Content-Type: application/json" \
  -d '{
    "platform": "x",
    "tone": "confident",
    "topic": "content strategy tips",
    "length": "short"
  }'

Response:

{
  "ok": true,
  "caption": "Most creators fail because they post randomly. Winners batch content, analyze metrics, and double down on what works. Simple, not easy.",
  "model": "dolphin-mistral:7b",
  "platform": "x"
}

Platform Style Guides

The API uses platform-specific system prompts (from captions.js:18):

OnlyFans

Style: Intimate, teasing, personalFormat: 1-3 short sentencesGuidelines:

Emojis encouraged
No external links (platform restriction)
Direct, conversational tone
Encourage engagement/DMs

Fansly

Style: Flirty, direct, confidentFormat: 1-3 sentencesGuidelines:

Encourage subscription/tips
Bold, unapologetic tone
Call-to-action focused

X (Twitter)

Style: Punchy, under 280 charsFormat: Hook + valueGuidelines:

No fluff, direct value
Thread-starter friendly
High engagement potential

Instagram

Style: Visually descriptive, lifestyle toneFormat: 3-5 hashtags at endGuidelines:

First line is hook (visible in feed)
Storytelling encouraged
Hashtags for discoverability

TikTok

Style: Energetic, hashtag-richFormat: Max 150 chars for captionGuidelines:

Trending hashtags prioritized
CTA for watch/like/follow
Match video energy

YouTube

Style: Keyword-rich, SEO-optimizedFormat: First 2 lines as hook, timestamps if relevantGuidelines:

First 2 lines visible before “Show More”
Include chapters/timestamps
CTA to subscribe

Style: Genuine, community-aware, conversationalFormat: Natural, un-salesyGuidelines:

Match subreddit culture
No overt self-promotion
Value-first approach

Snapchat

Style: Very short, playfulFormat: Max 30 charsGuidelines:

Complements visual story
Emoji-heavy acceptable
Casual, spontaneous

Model Configuration

The caption generation uses Ollama’s /api/generate endpoint with optimized settings: From captions.js:88:

const ollamaRes = await fetch(`${OLLAMA_URL}/api/generate`, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    model: CAPTION_MODEL, // dolphin-mistral:7b
    system: systemPrompt,
    prompt: userPrompt,
    stream: false,
    options: { 
      temperature: 0.85,  // High creativity
      top_p: 0.9,         // Diverse token sampling
      num_predict: 300    // Max 300 tokens output
    },
  }),
});

Why dolphin-mistral:7b?

Uncensored: No content filters (critical for adult creator use cases)
Fast inference: 7B parameter model runs on CPU in less than 2 seconds
Style matching: Fine-tuned for conversational, creative writing
Consistency: Reliable output structure (no meta-commentary)

Environment Configuration

# .env
OLLAMA_URL=http://127.0.0.1:11434
CAPTION_MODEL=dolphin-mistral:7b

Error Handling

Unauthorized (no token):

{
  "ok": false,
  "error": "Authorization header required"
}

Invalid/expired token:

{
  "ok": false,
  "error": "Invalid or expired token"
}

Ollama service unavailable:

{
  "ok": false,
  "error": "Ollama error: connect ECONNREFUSED 127.0.0.1:11434"
}

Empty model response:

{
  "ok": false,
  "error": "Model returned empty response"
}

Best Practices

Caption Quality Tips

Be specific with topics: Instead of “new content”, use “new yoga tutorial series”
Match tone to platform: playful works for OnlyFans, professional for LinkedIn
Iterate on length: Start with medium, adjust based on platform engagement
Test multiple generations: Run 3-5 variations, pick the best

Integration Patterns

Client-side caching:

// Cache generated captions to avoid duplicate API calls
const cacheKey = `${platform}:${tone}:${topic}:${length}`;
const cached = localStorage.getItem(cacheKey);

if (cached) {
  return JSON.parse(cached);
}

const res = await fetch('/api/captions/generate', { ... });
const data = await res.json();

localStorage.setItem(cacheKey, JSON.stringify(data));
return data;

Batch generation:

// Generate captions for multiple platforms in parallel
const platforms = ['instagram', 'tiktok', 'x'];
const topic = 'new workout program launch';

const captions = await Promise.all(
  platforms.map(platform =>
    fetch('http://localhost:3001/api/captions/generate', {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${token}`,
        'Content-Type': 'application/json',
      },
      body: JSON.stringify({ platform, topic, tone: 'motivational', length: 'medium' }),
    }).then(r => r.json())
  )
);

console.log(captions);
// [
//   { ok: true, caption: "...", platform: "instagram" },
//   { ok: true, caption: "...", platform: "tiktok" },
//   { ok: true, caption: "...", platform: "x" }
// ]

Performance

Typical response times:

CPU inference (dolphin-mistral:7b): 1.5-3s
GPU inference (if available): 0.3-0.8s
Network overhead: Less than 100ms

Optimization tips:

Pre-warm Ollama: Run a dummy generation on server start to load model into memory
Use GPU: Set OLLAMA_GPU_LAYERS=-1 for full GPU offload
Adjust num_predict: Reduce to 150 for shorter captions (faster generation)
Connection pooling: Reuse HTTP connections to Ollama

Example Use Cases

Content Calendar Automation

Generate a week’s worth of captions for a creator:

const topics = [
  'Monday motivation workout',
  'New recipe video',
  'Behind the scenes photo shoot',
  'Q&A session announcement',
  'Weekend sale promo',
];

const captions = await Promise.all(
  topics.map(topic =>
    generateCaption({
      platform: 'instagram',
      tone: 'casual',
      topic,
      length: 'medium',
    })
  )
);

// Save to content calendar database
for (let i = 0; i < captions.length; i++) {
  await saveScheduledPost({
    platform: 'instagram',
    caption: captions[i].caption,
    scheduled_for: addDays(new Date(), i),
  });
}

A/B Testing Captions

Generate variations for split testing:

const tones = ['playful', 'confident', 'teasing'];
const variations = await Promise.all(
  tones.map(tone =>
    generateCaption({
      platform: 'onlyfans',
      tone,
      topic: 'new exclusive content drop',
      length: 'short',
    })
  )
);

// Show variations to creator for selection
console.log(variations.map(v => v.caption));
// [
//   "Just dropped something spicy 🌶️ Come see what I've been working on...",
//   "New exclusive content is live. You know you want it. 😏",
//   "Wanna see what I'm hiding? Check your DMs... 💋"
// ]

Endpoints

MCP Tools

Collections

Overview

POST /api/captions/generate

Request Parameters

Response

Example Request

Platform Style Guides

Model Configuration

Why dolphin-mistral:7b?

Environment Configuration

Error Handling

Best Practices

Caption Quality Tips

Integration Patterns

Performance

Example Use Cases

Content Calendar Automation

A/B Testing Captions

Next Steps

Queue API

Genie Chat

​Overview

​POST /api/captions/generate

​Request Parameters

​Response

​Example Request

​Platform Style Guides

​Model Configuration

​Why dolphin-mistral:7b?

​Environment Configuration

​Error Handling

​Best Practices

​Caption Quality Tips

​Integration Patterns

​Performance

​Example Use Cases

​Content Calendar Automation

​A/B Testing Captions

​Next Steps

Queue API

Genie Chat

Overview

POST /api/captions/generate

Request Parameters

Response

Example Request

Platform Style Guides

Model Configuration

Why dolphin-mistral:7b?

Environment Configuration

Error Handling

Best Practices

Caption Quality Tips

Integration Patterns

Performance

Example Use Cases

Content Calendar Automation

A/B Testing Captions

Next Steps