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FunPack Story Writer

This node generates up to 5 sequential prompts for video shots based on a user request, optional per-shot instructions, and an LLM.

It is built around LLaMA-style chat models and is intended for story-driven multi-shot generation workflows.

Parameters

user_prompt: Main instruction describing the overall story, scene, or video idea.

prompt1, prompt2, prompt3, prompt4, prompt5: Optional extra instructions for specific sequence slots. Leave them empty if you want the node to decide each shot from the main request alone.

story_system_prompt: System instruction used when the node first generates a hidden story outline.

sequence_system_prompt: System instruction used when generating the actual sequence prompts.

model_path_type: Choose between a local .safetensors LLM file and a HuggingFace pretrained model.

model_path: HuggingFace repository path used when model_path_type is set to pretrained.

llm_safetensors_file: Local .safetensors model file from your ComfyUI models/clip folder.

prompt_count: Number of sequence prompts to generate, from 1 to 5.

top_p, top_k, min_p, temperature, max_new_tokens, repetition_penalty: Text generation settings that affect variety, strictness, and output length.

mode: Sequences from story first creates a hidden story and then expands it into shots. Sequences from user prompt skips the hidden story step and generates shots directly from the user request.

vision_input: Optional text from a vision-language model describing the starting image so the generated shots can stay aligned with it.

sanity_check: If enabled, each generated sequence is reviewed by the same model and corrected if it breaks the requested rules.

sanity_check_system_prompt: System instruction used for the sanity-check pass.

disable_continuity: If enabled, later sequences are generated without feeding the previously generated shot history back into the model.

provide_current_id: When continuity is disabled, this controls whether the current sequence number is still provided to the model.

Outputs

prompt1, prompt2, prompt3, prompt4, prompt5: Generated sequence prompts. Outputs beyond prompt_count are returned as empty strings.

Purpose

Use this node when you want one LLM pass to turn a high-level idea into a short sequence of video prompts that still feel connected from shot to shot.