griptape vs declarative-agents
Python AI application frameworks compared
griptape and declarative-agents both help developers build tool-augmented LLM applications. griptape provides a modular Python framework with tasks, agents, pipelines, and workflows, while declarative-agents uses a Go runtime to interpret YAML-defined agent workflows.
griptape: Build AI Agents and Workflows in Python
Griptape is a modular Python framework for building generative AI applications with tasks, agents, pipelines, and workflows. It suits developers who want to combine language models with tools, memory, and retrieval components through swappable integrations.
declarative-agents: Define Tool-Augmented Agents in YAML
A Go runtime interprets YAML profiles that define agent tools, states, transitions, and budgets. It suits teams that want to change agent workflows through configuration, though the project is new, contributor-concentrated, and in bug-fix-only maintenance mode.
| griptape | declarative-agents | |
|---|---|---|
| Language | Python | Go |
| License | Apache-2.0 | BSD-3-Clause |
| Stars | 2.6k | 4 |
| Forks | 263 | 1 |
| Last analyzed | Oct 3, 2026 | Oct 11, 2026 |
Key differences
- griptape organizes applications with framework components such as tasks, memory, retrieval engines, and swappable drivers; declarative-agents defines tools, states, transitions, signals, and budgets in YAML profiles.
- griptape is written in Python, while declarative-agents is written in Go.
- griptape uses the Apache-2.0 license; declarative-agents uses the BSD-3-Clause license.
- griptape supports sequential and parallel workflows, while declarative-agents emphasizes changing state-machine workflows through configuration rather than rebuilding runtime code.
- griptape has 2.6k stars and 263 forks; declarative-agents has 4 stars and 1 fork, reports one contributor, and limits maintenance to bug fixes.
Choose griptape if you…
- need a Python framework for combining model providers, tools, memory, and retrieval.
- want reusable tasks, agents, pipelines, or parallel workflows in an application.
- are building RAG or multi-turn interactions using modular components.
Choose declarative-agents if you…
- want to define agent tools, states, transitions, and budgets in YAML.
- need to change workflows through configuration interpreted by a Go runtime.
- want reusable agent and tool blocks, runnable examples, or a declarative DSL specification.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.