Multimodal LLM Patterns Skill

Multimodal LLM Patterns

Integrate vision, audio, and video generation capabilities from leading multimodal models. Covers image analysis, document understanding, real-time voice agents, speech-to-text, text-to-speech, and AI video generation (Kling 3.0, Sora 2, Veo 3.1, Runway Gen-4.5).

Quick Reference

| Category | Rules | Impact | When to Use | |----------|-------|--------|-------------| | Vision: Image Analysis | 1 | HIGH | Image captioning, VQA, multi-image comparison, object detection | | Vision: Document Understanding | 1 | HIGH | OCR, chart/diagram analysis, PDF processing, table extraction | | Vision: Model Selection | 1 | MEDIUM | Choosing provider, cost optimization, image size limits | | Audio: Speech-to-Text | 1 | HIGH | Transcription, speaker diarization, long-form audio | | Audio: Text-to-Speech | 1 | MEDIUM | Voice synthesis, expressive TTS, multi-speaker dialogue | | Audio: Model Selection | 1 | MEDIUM | Real-time voice agents, provider comparison, pricing | | Video: Model Selection | 1 | HIGH | Choosing video gen provider (Kling, Sora, Veo, Runway) | | Video: API Patterns | 1 | HIGH | Async task polling, SDK integration, webhook callbacks | | Video: Multi-Shot | 1 | HIGH | Storyboarding, character elements, scene consistency |

Total: 9 rules across 3 categories (Vision, Audio, Video Generation)

Vision: Image Analysis

Send images to multimodal LLMs for captioning, visual QA, and object detection. Always set max_tokens and resize images before encoding.

| Rule | File | Key Pattern | |------|------|-------------| | Image Analysis | rules/vision-image-analysis.md | Base64 encoding, multi-image, bounding boxes |

Vision: Document Understanding

Extract structured data from documents, charts, and PDFs using vision models.

| Rule | File | Key Pattern | |------|------|-------------| | Document Vision | rules/vision-document.md | PDF page ranges, detail levels, OCR strategies |

Vision: Model Selection

Choose the right vision provider based on accuracy, cost, and context window needs.

| Rule | File | Key Pattern | |------|------|-------------| | Vision Models | rules/vision-models.md | Provider comparison, token costs, image limits |

Audio: Speech-to-Text

Convert audio to text with speaker diarization, timestamps, and sentiment analysis.

| Rule | File | Key Pattern | |------|------|-------------| | Speech-to-Text | rules/audio-speech-to-text.md | Gemini long-form, GPT-4o-Transcribe, AssemblyAI features |

Audio: Text-to-Speech

Generate natural speech from text with voice selection and expressive cues.

| Rule | File | Key Pattern | |------|------|-------------| | Text-to-Speech | rules/audio-text-to-speech.md | Gemini TTS, voice config, auditory cues |

Audio: Model Selection

Select the right audio/voice provider for real-time, transcription, or TTS use cases.

| Rule | File | Key Pattern | |------|------|-------------| | Audio Models | rules/audio-models.md | Real-time voice comparison, STT benchmarks, pricing |

Video: Model Selection

Choose the right video generation provider based on use case, duration, and budget.

| Rule | File | Key Pattern | |------|------|-------------| | Video Models | rules/video-generation-models.md | Kling vs Sora vs Veo vs Runway, pricing, capabilities |

Video: API Patterns

Integrate video generation APIs with proper async polling, SDKs, and webhook callbacks.

| Rule | File | Key Pattern | |------|------|-------------| | API Integration | rules/video-generation-patterns.md | Kling REST, fal.ai SDK, Vercel AI SDK, task polling |

Video: Multi-Shot

Generate multi-scene videos with consistent characters using storyboarding and character elements.

| Rule | File | Key Pattern | |------|------|-------------| | Multi-Shot | rules/video-multi-shot.md | Kling 3.0 character elements, 6-shot storyboards, identity binding |

Key Decisions

| Decision | Recommendation | |----------|----------------| | High accuracy vision | Claude Opus 4.6 or GPT-5 | | Long documents | Gemini 2.5 Pro (1M context) | | Cost-efficient vision | Gemini 2.5 Flash ($0.15/M tokens) | | Video analysis | Gemini 2.5/3 Pro (native video) | | Voice assistant | Grok Voice Agent (fastest, <1s) | | Emotional voice AI | Gemini Live API | | Long audio transcription | Gemini 2.5 Pro (9.5hr) | | Speaker diarization | AssemblyAI or Gemini | | Self-hosted STT | Whisper Large V3 | | Character-consistent video | Kling 3.0 (Character Elements 3.0) | | Narrative video / storytelling | Sora 2 (best cause-and-effect coherence) | | Cinematic B-roll | Veo 3.1 (camera control + polished motion) | | Professional VFX | Runway Gen-4.5 (Act-Two motion transfer) | | High-volume social video | Kling 3.0 Standard ($0.20/video) | | Open-source video gen | Wan 2.6 or LTX-2 | | Lip-sync / avatar video | Kling 3.0 (native lip-sync API) |

Example

import anthropic, base64

client = anthropic.Anthropic()
with open("image.png", "rb") as f:
    b64 = base64.standard_b64encode(f.read()).decode("utf-8")

response = client.messages.create(
    model="claude-opus-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": [
        {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": b64}},
        {"type": "text", "text": "Describe this image"}
    ]}]
)

Common Mistakes

Not setting max_tokens on vision requests (responses truncated)
Sending oversized images without resizing (>2048px)
Using high detail level for simple yes/no classification
Using STT+LLM+TTS pipeline instead of native speech-to-speech
Not leveraging barge-in support for natural voice conversations
Using deprecated models (GPT-4V, Whisper-1)
Ignoring rate limits on vision and audio endpoints
Calling video generation APIs synchronously (they're async — poll or use callbacks)
Generating separate clips without character elements (characters look different each time)
Using Sora for high-volume social content (expensive, slow — use Kling Standard instead)

Related Skills

ork:rag-retrieval - Multimodal RAG with image + text retrieval
ork:llm-integration - General LLM function calling patterns
streaming-api-patterns - WebSocket patterns for real-time audio
ork:demo-producer - Terminal demo videos (VHS, asciinema) — not AI video gen

Agent Skills: Multimodal LLM Patterns

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