Model Forge

EXPERIMENTAL — This plugin is a work in progress. APIs, features, and UI may change without notice. External links and documentation may become outdated or broken.

What is Model Forge?

Model Forge is a QGIS plugin that generates editable geoprocessing models from plain-language descriptions. It bridges AI language models with QGIS Processing Framework, transforming natural language workflow descriptions into visual models ready for editing, refinement, and execution.

Gallery

Generate Tab	Model Tab	Settings Tab	History Tab

Generated Result

Architecture

User Description --> LLM Backend --> QGIS Processing Model
(e.g. "Buffer    (OpenAI,         (.model3 file,
 then clip...")  Ollama, any     editable in Designer)
                  OpenAI-compatible)

Key Capabilities

• Natural language to model — Describe workflows like "Buffer input points by 500m, clip with city boundary, compute mean population"
• Multi-LLM support — Works with any OpenAI-compatible API (OpenAI, Ollama, Anthropic, local models, custom endpoints). Not locked to a single provider unlike IntelliGeo
• Visual model generation — Opens directly in QGIS Model Designer with pre-computed layouts
• Iterative refinement — Use repair prompts to fix or extend generated models
• Layout algorithms — Sugiyama, topological, axis pack, radial shell, ancestor weighted

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Known Issues

• External links may become outdated or broken
• Experimental features may change without notice
• Generated model quality depends on LLM capability
• Custom step registration does not persist across sessions

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User Guide

Installation

1. Install via QGIS Plugin Manager (Plugins -> Manage and Install Plugins -> search "Model Forge")
2. Open panel: Plugins -> Model Forge -> Open Model Forge
3. Configure LLM backend in Settings tab

Generate a Model

1. Go to Generate tab
2. Enter workflow description:

   "Buffer input points by 500 m, clip with the city boundary, then compute mean population per buffer."

3. Optional: set Name/Group, select Context layers, choose Layout profile/organisation/algorithm
4. Click Generate Model
5. View result in Model tab

Model Tab Functions

Action	Purpose
Model JSON (editable)	View/edit workflow JSON
Rebuild model from JSON	Apply manual edits to QGIS model
Save .model3	Export to file loadable in Processing Model Designer
Open in Designer	Launch Model Designer with pre-computed layout
Auto-wire model steps	Auto-connect missing parameter connections
Re-layout current JSON	Re-apply layout without regeneration
Auto-layout (Model Forge)	In-Designer re-layout

History

• History tab stores recent generation attempts
• Load, rename, delete, or clear past entries
• Restores saved model JSON and layout controls

Repair Mode

• Auto-Repair — validates JSON structure and sends repair request to LLM if issues found
• Send repair prompt — describe fixes (e.g., "add dissolve after clip", "rename field to pop_2020")

Settings

• Provider selection (OpenAI, Ollama, custom)
• API URL, key, temperature
• Algorithm catalog configuration

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Developer Notes

Repository Structure

Model Forge/
├── model_forge/                    # Canonical stitched plugin
│   ├── model_forge.py             # Plugin entry point
│   ├── forge_dock.py              # Dock widget wrapper
│   ├── forge_widget.py            # Main UI (Generate/Model/Settings)
│   ├── forge_generate_worker.py   # Background generation thread
│   ├── legacy_base/               # Original LLM->JSON workflow
│   └── compiler_core/             # MCP compiler pipeline
├── model_forge_initial/           # Legacy variant (deprecated)
└── modelforge_arch/               # Architecture variant (deprecated)

Key Modules

Module	Purpose
model_forge.py	Plugin registration, toolbar, menu
forge_dock.py	Embeds ForgeWidget into QGIS dock
forge_widget.py	UI logic, tab management, LLM wiring
llm_backend.py	LLM abstraction layer
context_collector.py	Gathers project/algorithm context
model_builder.py	JSON -> QingProcessingModelAlgorithm
model_layout.py	DAG layout computation

Concurrency

• LLM calls run in background QThread
• GenerateWorker emits finished(dict) or error(str)
• RepairWorker follows identical pattern

Persistence

• QSettings with prefix ModelForge/
• Stores: backend config, URL, API key, temperature, algorithm catalog

Model JSON Schema

{
  "inputs": [{ "id": "input_points", "type": "vector", "geometry": "point" }],
  "algorithms": [
    {
      "id": "buffer_step",
      "algorithm_id": "native:buffer",
      "parameters": {
        "INPUT": { "type": "child_output", "child_id": "input_points" },
        "DISTANCE": 500
      }
    }
  ]
}

Child outputs use { "type": "child_output", "child_id": "step_id" }. Validation performed by _validate_model() in forge_widget.py.

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Support

• Report issues: https://github.com/Wolren/ModelForge/issues
• Verify all external links before relying on them

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Last updated: 05.2026