agniiva/griptape

Modular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory. Griptape is an enterprise grade alternative to LangChain.

griptape

Griptape is a modular Python framework for building AI-powered applications that connect securely to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step.

Build AI Apps: Easily compose apps in Python with modular structures and ready-made tools. Use built-in drivers to connect to whichever LLMs and data stores you choose.

Control Data Access: Connect securely to data sources with granular access controls, ensuring LLMs stay focused on the information that matters.

Scale With Your Workload: Easily deploy and run apps in the cloud, where your data lives. Process data ahead of time or vectorize it on the fly.

Using Griptape, you can securely integrate with your internal data stores and APIs. You get to control what data goes into the prompt, and what the LLM is allowed to do with it.

Documentation

Please refer to Griptape Docs for:

• Getting started guides.
• Core concepts and design overviews.
• Examples.
• Contribution guidelines.

Please check out Griptape Trade School for free online courses.

Quick Start

First, install griptape:

pip install griptape -U

Second, configure an OpenAI client by getting an API key and adding it to your environment as OPENAI_API_KEY. By default, Griptape uses OpenAI Completions API to execute LLM prompts.

With Griptape, you can create structures, such as Agents, Pipelines, and Workflows, that are composed of different types of tasks. Let's build a simple creative agent that dynamically uses two tools with shared short-term memory.

from griptape.structures import Agent
from griptape.tools import WebScraper

agent = Agent(
    tools=[WebScraper()]
)

agent.run(
    "based on https://www.griptape.ai/, tell me what Griptape is"
)

And here is the output:

Q: based on https://www.griptape.ai/, tell me what Griptape is
A: Griptape is an opinionated Python framework that enables developers to fully harness the potential of LLMs while enforcing strict trust boundaries, schema validation, and activity-level permissions. It offers developers the ability to build AI systems that operate across two dimensions: predictability and creativity. Griptape can be used to create conversational and autonomous agents.

During the run, the Griptape agent loaded a webpage with a tool, stored its full content in the short-term memory, and finally queried it to answer the original question. The important thing to note here is that no matter how big the webpage is it can never blow up the prompt token limit because the full content never goes back to the main prompt.

Check out our docs to learn more about how to use Griptape with other LLM providers like Anthropic, Claude, Hugging Face, and Azure.

Versioning

Griptape is in constant development and its APIs and documentation are subject to change. Until we stabilize the API and release version 1.0.0, we will use minor versions (i.e., x.Y.z) to introduce features and breaking features, and patch versions (i.e., x.y.Z) for bug fixes.

Contributing

Contributions in the form of bug reports, feature ideas, or pull requests are super welcome! Take a look at the current issues and if you'd like to help please submit a pull request with some tests.

License

Griptape is available under the Apache 2.0 License.