Toonflow

1. Project Overview

A word to explain:

• * Toonflow tried to make the short play production link of "novel/script → story adaptation → mirror division → character/scene/prop → video clip → film" into a desktop AI workbench.**

2. Key Schematic

The following picture is from the screenshot of the official presentation of the project README, which has been downloaded to the '17-temporary attachments/Toonflow-app/'directory of the current Obsidian vault.

2.1 project management interface

! [[17-Interim Annex/Toonflow-app/screenshot-1.png]]

2.2 AI screenwriting and adaptation strategy

! [[17-Interim Annex/Toonflow-app/screenshot-2.png]]

Batch generation of 2.3 characters, scenes and props

! [[17-TEMPORARY ATTACHMENT/Toonflow-app/screenshot-4.png]]

2.4 Infinite Canvas, Mirror Table and Agent Process Status

! [[17-TEMPORARY ATTACHMENT/Toonflow-app/screenshot-7.png]]

2.5 Video Generation Prompt Words and Reference Materials

! [[17-TEMPORARY ATTACHMENT/Toonflow-app/screenshot-9.png]]

3. What can it mainly do

3.1 from novel/original to short play project

The core of the Toonflow is not a single point of video generation, but a process-oriented workbench for short drama production. The main flow described by the README is:

1. Create a new project and import the original.
2. Perform chapter event extraction.
3. Use ScriptAgent to generate story skeletons, adaptation strategies, and structured scripts.
4. Use ProductionAgent to organize mirror, footage, and video nodes in an infinite canvas.
5. Nodal fine adjustment of the sub-mirror graph.
6. Generate video clips, and finally splice and export.

Pre-sales value:

• * It expands "AI-generated content" from a one-time prompt to a traceable, modifiable, and traceable production pipeline, which is closer to team-based content production than simply calling Wensheng graph/Wensheng video tools.**

3.2 AI Screenwriting and Intelligent Adaptation

Toonflow provide ScriptAgent to do around the novel/story:

-Chapter event extraction.

-Story skeleton generation.

-Adapted strategy generation.

-Structured script generation.

-Conversational revision and feedback.

README emphasizes "chapter event graph-driven adaptation", that is, first structure the original chapter events, and then call the context according to the event graph to reduce the loss of long text information.

Suitable for pre-sales:

• * For long text content such as online articles, novels and IP adaptations, the Toonflow value lies in not directly letting the model "read the full text and write the script", but first structuring the story events and then driving the subsequent adaptation.**

3.3 character/scene/prop material generation

The Toonflow supports the generation and management of characters, scenes, props and other materials. In the screenshot you can see:

-Character, scene, prop type filtering.

-Model selection, e.g. GPT Image 2.

-Resolution configuration.

-Batch generate prompt words.

-Batch generate images.

-Material cards and status management.

This is suitable for the "asset library" part of short drama production: first unify the character image and scene style, and then use it for mirror splitting and video clips.

3.4 Infinite Canvas Production Workbench

README calls it the "Infinite Canvas Production Workbench" for organizing:

-The script.

-Role.

-Sub-mirror.

-Material.

-Video node.

-Agent task status.

The pre-sales value of this type of canvas workbench is that it is more suitable for creative production and mirror management than linear form processes. Content teams can work on footage, video, and revisions in parallel in the same space.

3.5 three-tier Agent collaboration system

README mentions that the Toonflow uses a three-tier Agent collaboration system:

This is the key narrative that distinguishes it from ordinary AI video tools: instead of generating a single model at a time, multi-Agent collaboration completes the production of a short play.

3.6 Persistence Agent Memory

Readme mentions that it does cross-session memory based on local ONNX vector retrieval, which supports:

-Short term news.

-Long-term summary.

-Semantic recall.

-Multi-round creation continuity.

Meaning of pre-sale:

• * Short/comic productions often span multiple rounds, days, and chapters. Agent memory helps maintain character setting, worldview, plot continuity, and style consistency.**

3.7 Programmable Supplier System

Toonflow, you can directly write vendor TypeScript logic in the setup center and it takes effect immediately without changing the source code or restarting.

This is very valuable for privatization and multi-model access:

-OpenAI, Anthropic, Google, DeepSeek, Wisdom Spectrum, MiniMax, Tongyi Thousand Questions, xAI, etc.

-Can be connected to Sora, bean bag, Seedance, Nano Banana Pro and other picture/video services.

-Can be connected to enterprise internal model gateway or third-party model API.

4. Applicable Scenario

4.1 Short Play/Short Video Content Factory

Suitable for teams that want to mass produce short plays, comic plays and short videos of plots:

-MCN.

-Short-play production companies.

-Novel/Web IP operators.

-Content marketing team.

-Education/Popular short video team.

Key Selling Points:

• * The previous process, which originally relied on screenwriting, mirror splitting, art and editing, was compressed into a batch executable process by AI workbench.**

4.2 Novel Film and Television and IP Adaptation Experiment

For customers with novels, web articles, scripts, comics IP, Toonflow can be used as a "low-cost test tool":

-Quickly verify if an IP is suitable for skit.

-Adapted chapters into short video scripts.

-Generate character and scene visual references.

-Low-cost production of samples for investment, operation or platform evaluation.

4.3 AIGC Creator Tools Platform

If customers want to make their own AI creator tools, Toonflow can be used as open source reference:

-Desktop side web front end.

-Backend API SQLite data.

-Multi-model vendor configuration.

-Agent skill documentation configuration.

-Material management, task management and real-time communication.

4.4 Privatization AI Content Production Plan

Toonflow supports native installation, Docker, local source code build and server PM2 deployment, suitable for privatization demonstration:

-Customers do not want material and original content to go to public SaaS.

-The customer has an existing model API or internal model gateway.

-Customers want to control footage, scripts, and video production data.

5. Not suitable for the scene

5.1 professional film and television production with high quality requirements

Toonflow are better suited for short drama samples, low-cost bulk content, creative prototyping and process automation. For film and television production that requires film-level picture consistency, fine performance, complex lens scheduling and professional post-production, professional teams and tool chains are still needed.

5.2 customers without model resources or budgets

An example of the Demo cost of README shows:

This is an example cost of a Demo of about 2 minutes at a time. In real production, retries, scrap, resolution, model price, and concurrency can significantly affect costs.

5.3 items with unclear authorization for commercial distribution

Although GitHub marks Apache-2.0, LICENSE/README has a supplementary agreement: if the software or derivative version is distributed, sold or provided to two or more independent third parties in the form of products, HBAI-Ltd written commercial authorization is required.

Therefore, if customers want to package Toonflow into commercial products or external SaaS, they must first do legal and authorization confirmation.

5.4 requires a mature enterprise-level authority and audit system

The default account number in README is' admin/admin123', indicating that it is more standalone/lightweight. If the customer requires multi-tenancy, fine-grained permissions, audit logs, content compliance flow, enterprise SSO, etc., the secondary cost needs to be evaluated.

6. Core Competence List

7. Architecture, Deployment and Integration

7.1 Technical Architecture

7.2 Release Package

The latest Release 'v1.1.8 'offers:

-Windows x64 / ARM64 '.exe '.

-macOS Apple Silicon / Intel '.dmg'.

-Linux x86_64 / ARM64 '. AppImage '.

This shows that the project has a more complete cross-platform desktop distribution link.

7.3 Local Use Process

README gives a quick start:

1. Start the application and log in. The default account is 'admin' / 'admin123 '.
2. Complete model vendor configuration in the Settings Center, including text, image, and video models.
3. Create a new project and import the original work, and perform chapter event extraction.
4. Enter the ScriptAgent to generate story skeletons, adaptation strategies and structured scripts.
5. Switch to ProductionAgent and organize the mirror, material and video nodes in the infinite canvas.
6. Reflow the workbench after nodal fine adjustment of the sub-mirror diagram to complete video splicing and export.

7.4 Docker deployment

git clone https://github.com/HBAI-Ltd/Toonflow-app.git
cd Toonflow-app
yarn docker:local

Or build manually:

docker build -t toonflow .
docker run -d -p <本地端口>:10588 -v <本地数据路径>:/app/data toonflow

The default service port is '10588 '.

7.5 Cloud Deployment

README recommends server environments:

-Ubuntu 20.04 / CentOS 7.

-Node.js 24.x, minimum 23.11.1.

-Memory 2GB.

-Yarn, PM2.

Typical process:

git clone https://github.com/HBAI-Ltd/Toonflow-app.git
cd Toonflow-app
yarn install
yarn build
pm2 start pm2.json

8. Commercial Licensing and Compliance Attention

The Toonflow mandate needs to focus on:

Commercial Licensing Pricing (disclosed in README):

Pre-sales advice:

• * If it is only the customer's internal content production or PoC, it can be understood according to internal use. If you want to package it into an external commercial product or SaaS, you need to get authorization confirmation first, instead of just judging by Apache-2.0.**

9. What can I say before sales

9.1 Elevator

Toonflow is a one-stop open source workbench for AI skit production. It combines novel/script adaptation, character and scene generation, mirror table, video generation and editing export into a complete process, which is suitable for content teams to quickly verify IP, generate short drama samples in batches, and build a privatized AIGC content production line.

9.2 Value Points for Content Teams

-Upgrade from Single Build to Project Production ".

-Management of projects, scripts, materials, sub-mirrors and video nodes.

-Retain the authoring process for easy iteration and revision.

-Suitable for novel adaptation, short drama sample, plot short video and comic production.

-Reduce early coupon cost and cycle time.

9.3 Value Points for Technical Teams

-TypeScript/Node/Electron technology stack, easy to open two.

-SQLite local storage, lightweight deployment.

-Docker/PM2/desktop deployment methods.

-Programmable vendor system suitable for docking internal model gateways.

-Agent prompt/Skill documentation for easy tuning and version management.

Differences between 9.4 and Generic Video Generation Tools

10. Frequently Asked Customer Questions

Q: Can Toonflow turn a novel into a complete and releasable short play with one click?

A: To be more precise, it provides a process tool from the novel to the production of short plays, but the quality of the film still depends on the quality of the original work, the ability of the model, the tuning of the prompt words, the manual revision and the later selection. Don't promise to be completely unattended before sale.

Q: Is it SaaS?

A: It's not just SaaS. It is an open source desktop/server application that supports native installation, Docker and server deployment, and also has an official website portal and distribution package.

Q: What models are needed?

A: At least a large language model interface, an image generation model, and a video generation model are required. README mentions Sora/Bean video service, Nano Banana Pro image generation model, and the use of Seedance 2.0, GPT Image 2, Claude Opus 4.6 in Demo.

Q: Can it be privatized?

A: From a technical point of view, it can be deployed locally and on servers, and it also supports multi-model vendor configuration. However, if you want to distribute products externally, you need to pay attention to supplementary commercial licenses.

Q: How much does it cost to generate a video?

A: The Demo example of README is filmed in about 2 minutes, totaling about ¥ 130, of which the video model is about ¥ 120. But the true cost depends on the model, the resolution, the number of retries, the proportion of scrap and the length of the piece.

Q: Is it suitable for internal use?

A: Suitable for content production PoC, creative samples, IP adaptation experiments, internal training/marketing video prototypes. However, it should be supplemented with enterprise rights, content review, copyright regulations and asset management processes.

Q: Can we pick up our own model?

A:README refers to a programmable supplier system that can write TypeScript supplier logic in the setup center and take effect immediately. In theory, it is suitable for internal model gateway, but it needs technical verification.

11. PoC Recommendations

11.1 PoC Target

It is recommended to verify the following issues:

-Whether a usable story skeleton can be generated from the client's existing novel/script text.

-Whether the chapter event extraction can maintain the main line and character relationship.

-Whether the characters, scenes and props are generated in a consistent style.

-Whether the split mirror table can meet the needs of short play production.

-Whether the video generation prompt words and reference materials can improve the consistency of the film.

-Whether the model call cost, time consumption and manual revision amount are acceptable.

-Customer on-premises and model vendor access is feasible.

11.2 PoC data

Recommended preparations:

11.3 PoC Metrics

11.4 Demo Route

Recommended Pre-Sales Demo:

1. Import a short story or a plot outline provided by the customer.
2. Demonstrate chapter event extraction and ScriptAgent adaptation strategies.
3. Show the batch generation of characters/scenes/props.
4. Show the mirror table and production nodes in the infinite canvas.
5. Show the binding of video generation prompt words and reference materials.
6. Output 30-60 seconds sample or segment.
7. Summarize time, cost and manual revision points.

12. Risks and Considerations

- Project is still relatively new : warehouse was created in 2026-01, latest version v1.1.8, production maturity needs to be verified by customer scenarios.

-Strong model dependency: The quality of the film is affected by the LLM, image model, video model, and vendor stability.

-Cost Uncertain: Video generation costs may become a major cost, and retries and scrap films will enlarge the budget.

- Copyright compliance is complex : novel IP, generated pictures, video model service terms, and distribution of the film platform are all subject to review.

-Commercial authorization needs to be confirmed: Third parties to external products or services should pay attention to supplementary commercial agreements.

-Security and permissions need to be enhanced: The default account password and lightweight SQLite form are suitable for PoC, but enterprise deployment requires additional permissions, audit, and key management.

- Material consistency still needs to be checked manually :AI character/scene/shot consistency is a common problem in the industry and cannot rely solely on tool commitments.

- official website is a front-end single-page application : official website has less static HTML information, and the main information is still subject to GitHub README/Release/LICENSE.

13. My Pre-Sales Judgment

Toonflow is a very suitable project for pre-sales display, because it pulls AIGC content production from "flashy single point generation" back to "managed production process":

-There is project management.

-There are AI screenwriters.

-There are material assets.

-There are unlimited canvases.

-There are split mirror and video nodes.

-There are model vendor configurations.

-There are desktop side and Docker deployment.

It is best suited for pre-sales positioning is:

AI the short production workbench/content production pipeline PoC instead of the pure video generation model.

When communicating with customers, it is suggested to emphasize "process, privatization, multi-model, suitable for IP adaptation and short play samples", and actively prompt "commercial authorization, model cost, copyright compliance, enterprise authority and film quality need PoC verification". This will not only speak product imagination, but also not over-promise.

14. REFERENCE

-HBAI-Ltd/Toonflow-app GitHub repository

-Toonflow README

-Toonflow v1.1.8 Release

-Toonflow LICENSE

-Toonflow-web front-end warehouse

-Toonflow official website

-Bilibili 12-minute quick-start video