MINIMAX H3 prompt studio (story mode update)
Built a local tool that turns reference images into a full MiniMax H3 video prompt storyboard — no cloud, no API keys
https://github.com/lololerigolo60/Minimax-H3-prompt-studio
I've been building H3 Prompt Studio, a desktop app (CustomTkinter) that writes MiniMax H3's rigid structured prompts for you, using a local LLM (Ollama / LM Studio / llama.cpp — pick your poison).
The part I'm most excited about is the Story → Sequences mode:
- Drop in your reference images (characters, settings, whatever) with a quick role/description each.
- Hit "Generate story" — the LLM writes a short narrative that actually uses all your references, invents connective tissue if your premise is thin.
- Pick how many sequences you want, hit "Break into sequences" — the LLM splits the story into N beats, and for each one it decides on its own which references apply, whether there's dialogue, and what camera move fits best.
- Hit generate, and it spits out one fully-formed, isolated H3 Ref2VA prompt per sequence — ready to feed straight into your video pipeline.
No more manually writing 6-section H3 prompts by hand for every single shot of a sequence. You just curate references and a premise, and let the model handle the structure/labeling grunt work (subject definitions, retention analysis, camera vocab, dialogue tags, the works).
Everything's local, everything's saveable — you can dump a whole session (refs + story + sequences) to a JSON file and reload it later.
Still very much a personal tool, sharing in case it's useful to anyone else building on H3 locally. Happy to answer questions about the pipeline if anyone's curious.
u/lololerigolo60 — 3 days ago
▲ 3 r/ollama
RAG-art: Build Your Own Art Expert with ollama
I built myself a personal AI art history assistant
https://github.com/lololerigolo60/RAG-art/tree/main
I love art history but I have way too many books, PDFs, and notes scattered everywhere. So I built myself a little app to help me actually use all of it.
Here's what it can do:
- Reads my library for me. I feed it PDFs and text files (art history books, articles, notes), and it organizes everything so I can search and ask questions about it later.
- I can chat with it. I can ask things like "what do we know about this painter's use of color" and it digs through everything I've fed it to answer, remembering our conversation as we go.
- It looks at paintings and describes them. I can show it a picture of an artwork and it writes up an art-critical analysis — style, composition, technique — which then gets added to its memory too.
- It searches the web when needed. It can pull info from Wikipedia and the Met Museum's collection, show me what it found, and I decide what's worth keeping.
- It helps me write image prompts. For a creative project of mine, it turns everything it has learned into structured prompts I can use to generate new artwork inspired by real art history.
The best part: it all runs on my own computer, nothing gets sent to the cloud. It's basically a private research assistant that grows smarter about art the more I use it.
Still a work in progress, but it's already become a genuinely useful tool for my art research. Happy to answer questions!
u/lololerigolo60 — 10 days ago
▲ 36 r/StableDiffusion
Prompt Architect
Prompt Architect Pro — a heavy-duty Python/CustomTkinter desktop suite designed to ingest massive text files (novels, scripts), extract structured visual prompts via multi-pass semantic segmentation, analyze local image folders (Vision model batching), and manage everything inside a WAL-optimized SQLite database with built-in anti-corruption filters! 💡✨
https://github.com/lololerigolo60/Prompt-architect
🔥 Key Features Under the Hood:
🔹 Hardware VRAM Profiles: Instant switching between pre-configured presets (8GB, 12GB, 16GB, 24GB, 32GB+ like RTX 5090) or custom manual parameters to fine-tune num_ctx & num_predict safely without crashing Ollama.
🔹 Pass 1 & Pass 2 Text Segmentation: Intelligently groups raw lines based on core location changes rather than blind line breaks.
🔹 Vision Batch Analysis: Automatically normalizes WebPs, PNGs, and JPEGs via Pillow and extracts rich structured prompts (Subject, Environment, Style, Lighting, Technical).
🔹 Smart Gap-Fill & Anti-Degeneration: Prevents repetitive loops, foreign script drift, and empty fields using intelligent semantic safeguards.
🔹 Integrated DB Editor: Search, edit, reset IDs, delete ranges, and generate missing fields on the fly with live LLM assistance.
🔹two ComfyUI nodes : one that can use the database created by Prompt Architect . The second one can take a prompt and transform it to store it in the database created by Prompt Architect. You can find them on Prompt Architect's GitHub.
#GenerativeAI #Ollama #PromptEngineering #Python #CustomTkinter #LocalAI #AIArt
u/lololerigolo60 — 25 days ago
Prompt Architect
Prompt Architect Pro — a heavy-duty Python/CustomTkinter desktop suite designed to ingest massive text files (novels, scripts), extract structured visual prompts via multi-pass semantic segmentation, analyze local image folders (Vision model batching), and manage everything inside a WAL-optimized SQLite database with built-in anti-corruption filters! 💡✨
https://github.com/lololerigolo60/Prompt-architect
🔥 Key Features Under the Hood:
🔹 Hardware VRAM Profiles: Instant switching between pre-configured presets (8GB, 12GB, 16GB, 24GB, 32GB+ like RTX 5090) or custom manual parameters to fine-tune num_ctx & num_predict safely without crashing Ollama.
🔹 Pass 1 & Pass 2 Text Segmentation: Intelligently groups raw lines based on core location changes rather than blind line breaks.
🔹 Vision Batch Analysis: Automatically normalizes WebPs, PNGs, and JPEGs via Pillow and extracts rich structured prompts (Subject, Environment, Style, Lighting, Technical).
🔹 Smart Gap-Fill & Anti-Degeneration: Prevents repetitive loops, foreign script drift, and empty fields using intelligent semantic safeguards.
🔹 Integrated DB Editor: Search, edit, reset IDs, delete ranges, and generate missing fields on the fly with live LLM assistance.
🔹two ComfyUI nodes : one that can use the database created by Prompt Architect . The second one can take a prompt and transform it to store it in the database created by Prompt Architect. You can find them on Prompt Architect's GitHub.
#GenerativeAI #Ollama #PromptEngineering #Python #CustomTkinter #LocalAI #AIArt
u/lololerigolo60 — 26 days ago