griptape is a modular Python framework for LLM workflows, tools, memory, and data
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griptape offers developers the ability to build AI systems that operate across two dimensions: predictability and creativity. For predictability, software structures like sequential pipelines and directed acyclic graphs (DAGs) are enforced. Creativity, on the other hand, is facilitated by safely prompting LLMs with Griptape Tools that connect to external APIs and data sources. Developers can move between these two dimensions according to their use case.
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griptape nodes provides a powerful, visual, node-based interface for building and executing complex AI workflows. It combines a cloud-based IDE with a locally runnable engine, allowing for easy development, debugging, and execution of Griptape applications.
Please refer to the Griptape Docs for:
- Getting started guides.
- Core concepts and design overviews.
- Examples.
- Contribution guidelines.
