Spaces:
Running on Zero
Running on Zero
| license: mit | |
| language: | |
| - en | |
| tags: | |
| - 3d-printing | |
| - additive-manufacturing | |
| - llm | |
| - retrieval | |
| - build-small-hackathon | |
| pretty_name: "Microfactory Node: Lesson Ledger" | |
| size_categories: | |
| - n<1K | |
| # Microfactory Node: 3D Printer (Lesson Ledger) | |
| The compounding memory of **Microfactory Node: 3D Printer**, a small local Gemma that learns 3D | |
| printing job by job. Each row is one durable lesson keyed to the conditions it was learned in. | |
| The node retrieves from this ledger before every print, so job N+1 starts smarter than job N. | |
| This is the knowledge that usually lives in one maker's head and dies with the shop. Here it | |
| persists, and anyone can read it. | |
| Project: [Live](https://node.microfactory.space) · | |
| [Code](https://github.com/kylebrodeur/microfactory-node). | |
| ## Schema (one JSON object per line) | |
| ```json | |
| {"job_id": "seed-004", "material": "PLA", "geometry_type": "overhang", | |
| "env_temp": 28.0, "env_humidity": 50.0, "outcome": "failed_sag", | |
| "lesson": "PLA overhang sagged at 28C with the fan low; raise cooling, drop nozzle ~10C.", | |
| "source": "seed", "timestamp": "2026-05-20T09:00:00Z"} | |
| ``` | |
| | Field | Meaning | | |
| |---|---| | |
| | `material` | PLA, PETG, ABS, TPU | | |
| | `geometry_type` | overhang, bridge, stringing, adhesion, vase (the failure-mode class) | | |
| | `env_temp` / `env_humidity` | room conditions the lesson was learned in | | |
| | `outcome` | success, failed_sag, failed_stringing | | |
| | `lesson` | one durable, directional sentence (the transferable craft) | | |
| | `source` | `seed` (curated start), `ingested` (from real configs/prints), `earned` (a real reported outcome), `sim` (the deterministic world) | | |
| ## How the knowledge is sourced | |
| Lessons are grounded, never invented. Seed lessons are hand-curated starters. Ingested lessons | |
| come from real slicer/firmware profiles and real print history. Earned and simulated lessons come | |
| from outcomes reported outside the model: the model proposes, a deterministic world or a human | |
| reports what happened, and only then is a lesson written. The model never grades its own work. | |
| ## Honest limits | |
| Small and deliberately so. The simulated outcomes are a physics-lite stand-in for a printer, used | |
| to run the closed loop on camera; they are labeled as such. Treat the lessons as a maker's | |
| notebook: directionally true, condition-keyed, and meant to be checked against your own machine. | |