Blender AI 插件如何闭环执行代码

项目转向

过去几个月，我一直在开发一个本地多 Agent CLI 代码生成器：planner → coder → tester → executor → reviewer，通过 Ollama 运行开放模型。它形成了完整闭环：编写代码、运行代码、测试代码，再修复代码。

它确实能用。而这恰恰就是问题所在：它解决的并不是我自己的需求。为磁盘上的文件编写代码，已经是一个有成熟解决方案的细分领域。我是在和其他所有代码生成工具竞争，而目标用户手里早就有了同类工具。

我真正每天都在做的事情是 3D。于是，这个项目转向了另一个方向：让 AI 助手住进 Blender，真正掌握处理模型的工具，而不只是一个输出代码的文本框。

目前已经能做什么

这个 add-on 叫 Game Asset Assistant，面向 Blender 4.2+，以规范的扩展 zip 包形式分发。

• 停靠在 3D Viewport 的侧边栏中（N → AI 标签页）。
• 也可以通过 Ctrl+Alt+A 打开独立的浮动窗口。
• 支持流式响应、消息历史，以及停止和清空按钮。

它了解你的场景

每次请求都会携带一份精简的场景快照，注入 system prompt：

Blender 4.2.0 场景：Scene | fps=24 | units=METRIC | render=CYCLES 对象数：12

Cube [MESH] loc=(0.00, 0.00, 0.00) rot_deg=(0.0, 0.0, 0.0) scale=(1.00, 1.00, 1.00) verts=8 edges=12 faces=6 | uv=UVMap | materials=Steel | modifiers=SUBSURF 已选中：Cube 活动对象：Cube | mode=OBJECT

所以，当你问“活动对象有多少个多边形？”时，模型回答的是你场景中的那个对象，而且会直接说出它的名字。

从回答到执行，只需一次点击

当回复中包含一个

python block, it appears in a box with two buttons:

Run code - executes it in the current scene on the main thread, captures print() output and tracebacks, and pushes both back into the chat. That closes the loop: the model writes, Blender executes, the model sees the error and fixes it.
To Text Editor - saves it as a text datablock for manual review.
Backends

Local (Ollama, e.g. qwen2.5-coder:7b) or any OpenAI-compatible API - switchable in preferences, no code changes.

The part that broke my brain: Blender forbids threads
Here's the non-obvious bit worth the whole post.

Blender's API docs say it plainly: Python threads that outlive the script cause hard-to-diagnose crashes in Blender's own drawing code. So the obvious approach - "spawn a thread, call the LLM API, update the UI when it returns" - is off the table.

The add-on therefore never blocks and never spawns a thread. Instead:

Blender (main thread)              worker process            network
┌────────────────────────┐         ┌──────────────┐
│ operator appends a     │commands │              │
│ JSON line ─────────────┼────────→│  worker.py   │──HTTP──→ Ollama / API
│                        │         │              │
│ bpy.app.timers,        │events   │              │
│ every 0.1s, reads new  │←────────┤              │
│ lines ─────────────────┤         └──────────────┘
└────────────────────────┘
Commands are just JSON objects appended to commands.jsonl.
Events (chunk, done, error) are appended to events.jsonl.
A bpy.app.timers callback pumps events every 0.1 s - and a timer is not a thread, it's a callback Blender invokes on the main thread between frames. That's the only legal way to do background work.
Side effect: the whole add-on ships without any third-party dependency, and the protocol already has room for tool-call requests in a later phase.

What's not there yet
Being honest about the gaps:

No structured tool-calling - the model emits a code block and we exec() it
No confirmation for destructive operations (the prompt asks the model to warn; that's a request, not a guarantee)
No undo grouping - one Ctrl+Z won't roll back a whole script
UV, rigging and texturing exist only as chat advice, not as one-click tools
Scene snapshot is blind to UV islands, texel density, weights and armature pose
Roadmap
Phase   What    Why first
0   Richer snapshot, undo-push, destructive-op confirmation Cheap, unlocks everything after
1   Tool-calling over the JSONL channel, executed on the main thread with a registry + JSON schemas The reliability jump: from "80 lines of text that may fail" to named calls
2   Texturing: PBR material presets, texture assignment, packing, bake helpers  Stable API, high daily value
3   UV: quick unwrap/pack/texel-density, seam-by-angle, and a UV diagnostics report (overlaps, density) Most repetitive work; the report lets the model read the result and propose fixes
4   Auto-rig: metarig → Rigify, auto-weights, weight validation, export checks    Hardest - errors are silent, so diagnostics matter more than generation
5   One-click pipelines: GBC Prep, Char Prep, PBR Bake, Game Export Combines 2–4 into buttons
6   Teach the model: tool catalog in the prompt, domain recipes, few-shot examples  Ongoing, parallel
Integration with other Blender add-ons (delegating to UV packers, for example) is on the list - but the final roadmap is still open. I'd rather ship phases 0–3 and let real usage decide what phase 4 looks like.

The plan from here
Post progress as it lands. If you're working on AI × 3D pipelines, or you've wrapped a DCC tool for an LLM - I'd love to compare notes.

Repo link in the comments.

#blender #ai #python #gamedev #3d #showdev

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