Giselle
VerifiedOpen-source studio for building collaborative AI agent workflows.
What is Giselle?
Giselle is an open-source platform focused on agentic workflows that blend human input with AI capabilities for streamlined development tasks.
It operates via a drag-and-drop builder where agents are assembled from different models, GitHub data sources, and custom logic to handle sequential operations automatically.
Development teams and product groups benefit most, especially those wanting to automate routine processes without building infrastructure from scratch.
What you can build with Giselle
Research Assistant
Pulls relevant information from web sources and internal repositories to support ongoing projects.
Code Reviewer
Reviews pull requests and suggests improvements by integrating directly with GitHub workflows.
Document Generator
Produces specifications, release notes, and other documents based on existing codebase content.
Install Giselle
git clone https://github.com/giselles-ai/giselle.git && cd giselle && pnpm install# Clone the repository
git clone https://github.com/giselles-ai/giselle.git
cd giselle
# Install dependencies
pnpm install
# Create environment file
touch .env.local
# Add your API key (at least one required)
echo 'OPENAI_API_KEY="your_openai_api_key_here"' >> .env.local
# Start development server
pnpm turbo dev- 1Clone the repository from GitHub and navigate into the directory.
- 2Run pnpm install to set up all required dependencies.
- 3Create a .env.local file and add at least one supported AI provider key such as OpenAI.
- 4Execute pnpm turbo dev to launch the local development server.
- 5Open http://localhost:3000 in a browser to begin creating agents.
Giselle: pros & cons
Pros
- +Fully open source with Apache 2.0 license for customization and self-hosting.
- +Visual builder reduces the time needed to prototype and iterate on agents.
- +Supports composition across multiple providers including GPT, Claude, and Gemini.
- +Native GitHub integration enables direct automation of issues, PRs, and deployments.
Cons
- –Team collaboration and template features remain under development.
- –Requires separate API keys from at least one external model provider.
- –Initial setup involves manual environment configuration and dependency installation.
Frequently asked questions
The core platform is free and open source, but users must supply their own API keys from supported providers like OpenAI or Anthropic.
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