# griptape [](https://pypi.python.org/pypi/griptape) [](https://griptape.readthedocs.io) [](https://github.com/gitbucket/gitbucket/blob/master/LICENSE) [](https://discord.gg/gnWRz88eym) **griptape** is a modular Python framework for LLM workflows, tools, memory, and data. With **griptape**, you can: 1. 🚰 Build sequential **LLM pipelines** and sprawling **DAG workflows** for complex use cases. 2. 🧰️ Augment LLMs with **chain of thought** capabilities and integrate **external tools**, such as calculators, web search, spreadsheet editors, and API connectors. 3. 💾 Add **memory** to AI pipelines for context preservation and summarization. **griptape** consists of several core packages: - [griptape-flow](https://github.com/griptape-ai/griptape-flow): build LLM workflows and pipelines with memory, rules, and chain of thought reasoning. - [griptape-core](https://github.com/griptape-ai/griptape-core): integrate other services and functionality into LLMs as tools; run tools in any environment (local, containerized, cloud, etc.); convert tools into underlying middleware abstractions, such as ChatGPT Plugins, LangChain tools, and Fixie.ai agents. - [griptape-tools](https://github.com/griptape-ai/griptape-tools): official Griptape tools registry. griptape is in early 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 breaking features and patch versions (i.e., x.y.Z) for bug fixes. ## Documentation Please refer to [Griptape Docs](https://griptape.readthedocs.io) for: - Getting started guides. - Core concepts and design overviews. - Examples. - Contribution guidelines. ## Quick Start First, install griptape that includes all core modules: ``` pip install griptape -U ``` Second, configure an OpenAI client by [getting an API key](https://beta.openai.com/account/api-keys) and adding it to your environment as `OPENAI_API_KEY`. griptape uses [OpenAI Completions API](https://platform.openai.com/docs/guides/completion) to execute LLM prompts and to work with [LlamaIndex](https://gpt-index.readthedocs.io/en/latest/index.html) data structures. With griptape, you can create *structures*, such as `Pipelines` and `Workflows`, that are composed of different types of steps. You can also define structures as JSON objects and load them into griptape dynamically. Lets define a simple two-step pipeline that uses tools: ```python from decouple import config from griptape.tools import WebScraper, Calculator from griptape.flow import utils from griptape.flow.memory import PipelineMemory from griptape.flow.steps import PromptStep, ToolkitStep from griptape.flow.structures import Pipeline from griptape.flow.utils import ToolLoader scraper = WebScraper( openai_api_key=config(OPENAI_API_KEY) ) calculator = Calculator() pipeline = Pipeline( memory=PipelineMemory(), tool_loader=ToolLoader( tools=[calculator, scraper] ) ) pipeline.add_steps( ToolkitStep( tool_names=[calculator.name, scraper.name] ), PromptStep( Say the following like a pirate: {{ input }} ) ) pipeline.run(Give me a summary of https://en.wikipedia.org/w
