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Setting up SpecForge on Linux

This guide will walk you through setting up SpecForge on Linux using the standalone executable.

1. Download the Executable

Download specforge-x.y.z-Linux-X64.tar.bz2 from the SpecForge releases page and extract it to a directory of your choice.

2. Install Dependencies

The SpecForge executable requires Z3 to be installed. rsvg-converter is optional but recommended for SVG-to-PNG conversion used by the animation feature.

Use your distribution’s package manager:

Ubuntu/Debian:

sudo apt install z3 librsvg2-bin

Fedora/RHEL:

sudo dnf install z3 librsvg2-tools

Arch Linux:

sudo pacman -S z3 librsvg

Note: The librsvg2-bin / librsvg2-tools / librsvg package provides the rsvg-convert command. Without it, the animate() feature in the Python SDK will not be able to render PNG frames from SVG visualizations. All other SpecForge features work without it.

3. Configure Your Edition and License

SpecForge defaults to the Community Edition when no tier or license is configured. The commercial tier runs the Essential Edition with project-size limits unless a valid license enables the Enterprise Edition. See Editions, usage tiers, and licenses for details and instructions for changing tiers.

To run the Enterprise Edition, place your license.json file in one of the following locations:

SpecForge also searches for *-license.json in the standard configuration and current directories before these license.json paths. If SPECFORGE_LICENSE_FILE is set, only that file is searched.

  • Standard Configuration Directory (recommended):

    • ~/.config/specforge/license.json

  • Environment Variable (for custom locations):

    export SPECFORGE_LICENSE_FILE=/path/to/license.json

  • Current Directory: ./license.json

Create the directory if it doesn’t exist:

mkdir -p ~/.config/specforge
cp /path/to/your/license.json ~/.config/specforge/

4. Configure LLM Provider (Optional)

To use LLM-based features such as natural-language spec generation and error explanation, configure an LLM provider by setting environment variables before starting the server.

For OpenAI (recommended):

export SPECFORGE_LLM_PROVIDER=openai
export SPECFORGE_LLM_MODEL=gpt-5-nano-2025-08-07
export OPENAI_API_KEY=your-api-key-here

Get an API key from platform.openai.com/api-keys.

For other providers (Gemini, Anthropic, Ollama), see the LLM Provider Configuration guide.

5. Start the Server

Navigate to the directory where you extracted the SpecForge executable and run:

./specforge serve

The server will start on http://localhost:8080. You can verify it’s running by navigating to http://localhost:8080/health, which should show version information.

6. Install the VSCode Extension

Install the SpecForge VSCode extension from the Visual Studio Marketplace or see the VSCode Extension setup guide.

7. Install the Python SDK (Optional)

The Python SDK enables interaction with the SpecForge server programmatically from Python. This can be used to embed SpecForge analyses in Python notebooks and directly feed and retrieve data using Pandas Dataframes. See the Python SDK setup guide for instructions on how to set it up.

Further Reading