Venice Video Harness

Documentation Index

Fetch the complete documentation index at: https://docs.venice.ai/llms.txt

Use this file to discover all available pages before exploring further.

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What this is

• Orchestration rules in CLAUDE.md
• Reusable playbooks in .claude/commands/ (19 workflow commands)
• Specialized agents in .claude/agents/ (art-director, prompt-engineer, cut-qa, and more)
• Venice production skills in .claude/skills/ (compatible with the Agent Skills format)
• TypeScript execution layer in src/
• Comprehensive model registry covering 50+ Venice video, image, audio, and music models

• Character-consistent video projects (any genre, any length)
• Visual-style-locked series or campaigns
• Storyboard-to-video workflows
• Short-form and long-form narrative content
• Branded cinematic sequences, trailers, and teasers
• Recurring-character social series

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Getting started

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Requirements

brew install whisper-cpp
mkdir -p ~/.cache/whisper.cpp
curl -L -o ~/.cache/whisper.cpp/ggml-base.en.bin \
  https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin

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Setup

git clone https://github.com/jordanurbs/venice-video-harness.git
cd venice-video-harness

cp .env.example .env
# Add VENICE_API_KEY to .env

npm install
npm run build

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What’s Venice-optimized about it

• Image prompts tuned for Venice image models like seedream-v5-lite, nano-banana-pro, flux-2-pro/max, and more
• Two-pass panel generation with Venice multi-edit refinement for character correction
• Model-routing logic for action, atmosphere, and character-consistency tiers
• Reference-aware video generation that uses elements, reference_image_urls, and scene_image_urls correctly per model
• Environment-aware prompt adaptation for daytime vs night scene handling
• Venice-native audio paths for TTS (Kokoro, Qwen3, ElevenLabs), SFX, and music
• Cost estimation before generation via /video/quote and /audio/quote
• Model-aware parameter building that auto-skips parameters the target model doesn’t support

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Model routing defaults

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Supported Venice models

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Video (April 2026)

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Image, audio, and music

• Image (22+ models): nano-banana-pro/2, gpt-image-2, flux-2-pro/max, grok-imagine, qwen-image-2-pro, recraft-v4-pro, seedream-v4 / v5-lite, lustify-sdxl/v7, wai-Illustrious, and more
• Multi-edit: qwen-edit, flux-2-max-edit, nano-banana-pro-edit, seedream-v5-lite-edit, gpt-image-2-edit, and more
• TTS: tts-kokoro (50+ voices), tts-qwen3-0-6b/1-7b, elevenlabs-tts-v3, elevenlabs-tts-multilingual-v2
• Music: elevenlabs-music, minimax-music-v2, ace-step-15, stable-audio-25
• SFX: elevenlabs-sound-effects-v2, mmaudio-v2-text-to-audio

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Production pipelines

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Generation pipeline

npm run dev -- produce-episode -p output/my-series -e 1

• Series / character / episode management
• LLM-powered script workshopping
• Two-pass storyboard generation (generate + multi-edit refine)
• Vision-based panel QA
• Video generation with frame chaining
• Layered audio post-production
• Subtitle burn-in and final assembly

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Editing pipeline

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Commands, agents, and skills

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NLE round-trip

mini-drama export-timeline -p output/<project> -e 1 --format fcpxml      # Final Cut Pro X
mini-drama export-timeline -p output/<project> -e 1 --format premiere    # Premiere Pro
mini-drama export-timeline -p output/<project> -e 1 --format davinci     # DaVinci Resolve

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Programmatic usage

import { VeniceClient } from './src/venice/client.js';
import { generateVideo, quoteVideo } from './src/venice/video.js';
import { listVideoModels } from './src/venice/models.js';

const client = new VeniceClient();

const quote = await quoteVideo(client, {
  model: 'kling-v3-pro-image-to-video',
  duration: '8s',
  audio: true,
});
console.log(`Estimated cost: $${quote.quote}`);

const result = await generateVideo(client, {
  model: 'kling-v3-pro-image-to-video',
  prompt: 'A slow dolly shot pushes forward...',
  duration: '8s',
  imageUrl: 'data:image/png;base64,...',
  audio: true,
  outputPath: 'output/shot-001.mp4',
});

const longModels = listVideoModels({ minDurationSec: 20 });

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Resources