# Ltx 2.3 Reframe Video To Video > AI model for generating video content ## Overview - **Model ID**: `ltx-2-3-pro-v2v` - **Category**: video - **Provider**: ltx - **Source Type**: Closed Source Model - **Status**: model_ready - **Screenshot**: `https://assets.modelslab.ai/generations/23c6b495-2abc-4c07-a62b-33302c5e6ccd.webp` ## API Information This model can be used via our HTTP API. See the API documentation and usage examples below. ### Endpoint - **URL**: `https://modelslab.com/api/v7/video-fusion/video-to-video` - **Method**: POST ### Parameters - **`init_video`** (required): Upload the reference video. Accepted format MP4, webm, mov, Ogg. All videos are limited to 16MB - Type: file - **`model_id`** (optional): - Type: text - **`resolution`** (required): Select the resolution - Type: select (options: 1:1 (square) 720P, 1:1 (square) 1080P, 4:5 (portrait) 720P, 4:5 (portrait) 1080P, 5:4 (landscape) 720P, 5:4 (landscape) 1080P, 9:16 (portrait) 720P, 9:16 (portrait) 1080P, 16:9 (landscape) 720P, 16:9 (landscape) 1080P) ## Usage Examples ### cURL ```bash curl --request POST \ --url https://modelslab.com/api/v7/video-fusion/video-to-video \ --header "Content-Type: application/json" \ --data '{ "key": "YOUR_API_KEY", "model_id": "ltx-2-3-pro-v2v", "init_video": "https://assets.modelslab.ai/generations/069b5d64-3699-4bc5-98bd-46e30ded661a.mp4", "resolution": "720x720" }' ``` ### Python ```python import requests response = requests.post( "https://modelslab.com/api/v7/video-fusion/video-to-video", headers={ "Content-Type": "application/json" }, json={ "key": "YOUR_API_KEY", "model_id": "ltx-2-3-pro-v2v", "init_video": "https://assets.modelslab.ai/generations/069b5d64-3699-4bc5-98bd-46e30ded661a.mp4", "resolution": "720x720" } ) print(response.json()) ``` ### JavaScript ```javascript fetch("https://modelslab.com/api/v7/video-fusion/video-to-video", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ "key": "YOUR_API_KEY", "model_id": "ltx-2-3-pro-v2v", "init_video": "https://assets.modelslab.ai/generations/069b5d64-3699-4bc5-98bd-46e30ded661a.mp4", "resolution": "720x720" }) }) .then(response => response.json()) .then(data => console.log(data)); ``` ## Integration Options ### CLI Install: `curl -fsSL https://modelslab.sh/install.sh | sh` or `brew install modelslab/tap/modelslab` ```bash modelslab auth login # Authenticate modelslab models search "ltx-2-3-pro-v2v" # Find this model modelslab models detail --id ltx-2-3-pro-v2v # Get model details modelslab generate image --prompt "..." --model ltx-2-3-pro-v2v # Generate with model modelslab config set generation.default_model ltx-2-3-pro-v2v # Set as default ``` - Website: https://modelslab.sh - GitHub: https://github.com/ModelsLab/modelslab-cli ### MCP Servers (Model Context Protocol) For Claude Code, Cursor, VS Code, Windsurf, and any MCP-compatible agent. - Generation: `https://modelslab.com/mcp/v7` (API key auth, 23 tools) - Agent Control Plane: `https://modelslab.com/mcp/agents` (Bearer token auth, 10 tools) Claude Code config (`~/.claude/settings.json`): ```json { "mcpServers": { "modelslab-v7": { "url": "https://modelslab.com/mcp/v7", "headers": { "Authorization": "Bearer YOUR_API_KEY" } } } } ``` - Documentation: https://docs.modelslab.com/mcp-web-api/overview ### Agent Skills Install skill files directly into AI coding agents: ```bash npx skills add modelslab/skills --all # All skills npx skills add modelslab/skills --skill image-generation # Specific skill npx skills add modelslab/skills --all -a claude-code -a cursor # Target agents ``` - GitHub: https://github.com/ModelsLab/skills - Documentation: https://docs.modelslab.com/agent-skills ### SDKs - Python: `pip install modelslab` - TypeScript: `npm install modelslab` - PHP: `composer require modelslab/modelslab` - Go: `go get github.com/modelslab/modelslab-go` - Dart: `dart pub add modelslab` ## Links - [Model Playground](https://modelslab.com/models/ltx/ltx-2-3-pro-v2v) - [API Documentation](https://docs.modelslab.com) - [ModelsLab Platform](https://modelslab.com)