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🎬 Story → Video Pipeline

A film director agent breaks a story into visual scenes. Each scene gets a script excerpt and a Stable Diffusion prompt. BatchSplitter separates the scenes for downstream image generation.

Nodes 12
Agents 1
Agent ID director@localhost
Key Feature BatchSplitter
Recall × 2 LLM BatchSplitter ToolParser

Pipeline Flow

Story concept → LLM writes scenes → ToolParser saves characters → BatchSplitter outputs individual scenes.

Identity
Setup
director@localhost
Context
Recall
query: "character"
Prompt
SystemPrompt
film director
Merge
TextCombine
story + characters
Generate
LLM
4096 tokens
Parse
ToolParser
save characters
Split
BatchSplitter
split on "## Scene"
Output
Scene 1
first_section
Output
All Scenes
all_sections
Story Input & Context Scene Generation Scene Breakdown & Memory

Key Features

BatchSplitter

Splits the LLM output on ## Scene headers. Returns the first scene individually plus a JSON array of all scenes — perfect for feeding into image generation loops.

🎨

Visual Bible

The director stores character descriptions and scene scripts in memory. Next time you run the workflow, new scenes reference existing character designs for visual consistency.

🎬

SD-Ready Prompts

Each scene comes with a script excerpt AND a Stable Diffusion prompt. Wire the scene outputs directly into your image generation pipeline.