> For the complete documentation index, see [llms.txt](https://docs.trymito.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.trymito.io/mito-ai/data-copilot.md). # Mito AI Core Concepts Make your Python environment intelligent. **Installing Data Copilot** Start by [creating a virtual environment](/getting-started/installing-mito/setting-up-a-virtual-environment.md), then run: ``` pip install mito-ai mitosheet ``` Then, follow these instructions to [create a mitosheet](/how-to/creating-a-mitosheet.md) and [use AI](/mito-ai/chat.md). ## Features Mito AI is a suite of context-aware AI Chat and error debugging tools to help you get the most from LLMs. No more copying and pasting between Jupyter and ChatGPT/Claude, or wasting time looking up Python syntax. Data Copilot integrates all of the tools you need directly into Jupyter.
Agent can build and edit full notebooks for you!ezgif-598f02527a6177.gifAgent
Chat is like collaborating with a colleague who sees your code, knows your data, and is a Python expert.Screenshot 2025-01-27 at 7.23.02 PM.pngChat
Smart Debugging identifies and fixes your errors so you can focus on your data and code, not the typos.Screenshot 2025-01-27 at 7.06.28 PM.pngSmart Debugging
--- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.trymito.io/mito-ai/data-copilot.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.