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refactor: ai-agents (#12)
* refactor: ai-agents * docs: ai-agents * docs: fix * docs: fix link
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‎.github/workflows/build.yml

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pip install build
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python -m build --sdist
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cp dist/*.tar.gz my_server_extension.tar.gz
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pip uninstall -y "jupyter_ai_agent"
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rm -rf "jupyter_ai_agent"
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pip uninstall -y "jupyter_ai_agents"
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rm -rf "jupyter_ai_agents"
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- uses: actions/upload-artifact@v4
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if: startsWith(matrix.os, 'ubuntu')
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- name: Install and Test
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run: |
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pip install my_server_extension.tar.gz
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pip list 2>&1 | grep -ie "jupyter_ai_agent"
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python -c "import jupyter_ai_agent"
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pip list 2>&1 | grep -ie "jupyter_ai_agents"
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python -c "import jupyter_ai_agents"
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check_release:
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needs: test_sdist
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- name: Upload Distributions
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uses: actions/upload-artifact@v4
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with:
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name: jupyter_ai_agent-releaser-dist-${{ github.run_number }}
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name: jupyter_ai_agents-releaser-dist-${{ github.run_number }}
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path: .jupyter_releaser_checkout/dist

‎README.md

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[![Become a Sponsor](https://img.shields.io/static/v1?label=Become%20a%20Sponsor&message=%E2%9D%A4&logo=GitHub&style=flat&color=1ABC9C)](https://github.com/sponsors/datalayer)
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# 🪐 ✨ Jupyter AI Agent
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# 🪐 ✨ Jupyter AI Agents
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[![Github Actions Status](https://github.com/datalayer/jupyter-ai-agent/workflows/Build/badge.svg)](https://github.com/datalayer/jupyter-ai-agent/actions/workflows/build.yml)
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[![PyPI - Version](https://img.shields.io/pypi/v/jupyter-ai-agent)](https://pypi.org/project/jupyter-ai-agent)
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[![Github Actions Status](https://github.com/datalayer/jupyter-ai-agents/workflows/Build/badge.svg)](https://github.com/datalayer/jupyter-ai-agents/actions/workflows/build.yml)
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[![PyPI - Version](https://img.shields.io/pypi/v/jupyter-ai-agents)](https://pypi.org/project/jupyter-ai-agents)
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*Use Jupyter AI Agent, an AI Agent equipped with tools like 'execute', 'insert_cell', and more, to transform your Jupyter Notebooks into an intelligent, interactive workspace!*
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*The Jupyter AI Agents are equipped with tools like 'execute', 'insert_cell', and more, to transform your Jupyter Notebooks into an intelligent, interactive workspace!*
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![Jupyter AI Agent](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-prompt-demo-terminal.gif)
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![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agents/ai-agents-prompt-demo-terminal.gif)
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```
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Jupyter AI Agent <-----------> JupyterLab
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Jupyter AI Agents <-----------> JupyterLab
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|
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| (RTC Real Time Collaboration)
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|
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- JKC https://github.com/datalayer/jupyter-kernel-client
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```
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Jupyter AI Agent empowers **AI** models to **interact** with and **modify Jupyter Notebooks**. The agent is equipped with tools such as adding code cells, inserting markdown cells, executing code, enabling it to modify the notebook comprehensively based on user instructions or by reacting to notebook and kernel events.
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Jupyter AI Agents empowers **AI** models to **interact** with and **modify Jupyter Notebooks**. The agent is equipped with tools such as adding code cells, inserting markdown cells, executing code, enabling it to modify the notebook comprehensively based on user instructions or by reacting to notebook and kernel events.
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This agent is **innovative** as it is designed to **operate on the entire notebook**, not just at the cell level, enabling more comprehensive and seamless modifications.
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## Usage
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This library is documented on https://jupyter-ai-agent.datalayer.tech.
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This library is documented on https://jupyter-ai-agents.datalayer.tech.
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We put here a quick example for a Out-Kernel Stateless Agent helping your JupyterLab session.
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To install Jupyter AI Agent, run the following command.
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To install Jupyter AI Agents, run the following command.
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```bash
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pip install jupyter_ai_agent
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pip install jupyter_ai_agents
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```
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Or clone this repository and install it from source.
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```bash
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git clone https://github.com/datalayer/jupyter-ai-agent
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cd jupyter-ai-agent
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git clone https://github.com/datalayer/jupyter-ai-agents
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cd jupyter-ai-agents
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pip install -e .
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```
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The Jupyter AI Agent can directly interact with JupyterLab and the modifications made by the Jupyter AI Agent can be seen in real-time thanks to [Jupyter Real Time Collaboration](https://jupyterlab.readthedocs.io/en/stable/user/rtc.html). Make sure you have JupyterLab installed with the Collaboration extension.
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The Jupyter AI Agents can directly interact with JupyterLab. The modifications made by the Jupyter AI Agents can be seen in real-time thanks to [Jupyter Real Time Collaboration](https://jupyterlab.readthedocs.io/en/stable/user/rtc.html). Make sure you have JupyterLab installed with the Collaboration extension.
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```bash
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pip install jupyterlab jupyter-collaboration ipykernel
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EOF
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```
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To use the Jupyter AI Agent, an easy way is to launch a CLI (update the Azure deployment name based on your setup).
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To use the Jupyter AI Agents, an easy way is to launch a CLI (update the Azure deployment name based on your setup).
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```bash
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# Prompt agent example.
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jupyter-ai-agent prompt \
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jupyter-ai-agents prompt \
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--url http://localhost:8888 \
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--token MY_TOKEN \
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--azure-ai-deployment-name gpt-40-mini \
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--path test.ipynb \
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--input "Create a matplotlib example"
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```
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![Jupyter AI Agent](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-prompt-demo-terminal.gif)
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![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agents/ai-agents-prompt-demo-terminal.gif)
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```bash
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# Explain Error agent example.
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jupyter-ai-agent explain-error \
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jupyter-ai-agents explain-error \
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--url http://localhost:8888 \
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--token MY_TOKEN \
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--azure-ai-deployment-name gpt-40-mini \
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--path test.ipynb
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```
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![Jupyter AI Agent](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-explainerror-demo-terminal.gif)
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![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agents/ai-agents-explainerror-demo-terminal.gif)
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## Uninstall
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To uninstall the agent, execute.
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```bash
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pip uninstall jupyter_ai_agent
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pip uninstall jupyter_ai_agents
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```
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## Contributing
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```bash
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# Clone the repo to your local environment
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# Change directory to the jupyter_ai_agent directory
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# Change directory to the jupyter_ai_agents directory
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# Install package in development mode - will automatically enable
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# The server extension.
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pip install -e ".[test,lint,typing]"
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### Development uninstall
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```bash
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pip uninstall jupyter_ai_agents
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```
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### Packaging the library

‎RELEASE.md

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~ BSD 3-Clause License
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-->
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# Making a new release of jupyter_ai_agent
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# Making a new release of jupyter_ai_agents
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The extension can be published to `PyPI` manually or using the [Jupyter Releaser](https://github.com/jupyter-server/jupyter_releaser).
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‎docs/Makefile

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publish: build ## publish
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($(CONDA_ACTIVATE) ${ENV_NAME}; \
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aws s3 rm \
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s3://datalayer-jupyter-ai-agent/ \
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s3://datalayer-jupyter-ai-agents/ \
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--recursive \
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--profile datalayer && \
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aws s3 cp \
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./build \
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s3://datalayer-jupyter-ai-agent/ \
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s3://datalayer-jupyter-ai-agents/ \
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--recursive \
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--profile datalayer && \
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aws cloudfront create-invalidation \
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--distribution-id E2U9KIMWUI2OHQ \
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--paths "/*" \
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--profile datalayer && \
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echo open ✨ https://jupyter-ai-agent.datalayer.tech )
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echo open ✨ https://jupyter-ai-agents.datalayer.tech )

‎docs/README.md

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[![Become a Sponsor](https://img.shields.io/static/v1?label=Become%20a%20Sponsor&message=%E2%9D%A4&logo=GitHub&style=flat&color=1ABC9C)](https://github.com/sponsors/datalayer)
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# Jupyter AI Agent Docs
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# Jupyter AI Agents Docs
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> Source code for the [Jupyter AI Agent Documentation](https://datalayer.io), built with [Docusaurus](https://docusaurus.io).
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> Source code for the [Jupyter AI Agents Documentation](https://datalayer.io), built with [Docusaurus](https://docusaurus.io).
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```bash
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# Install the dependencies.

‎docs/docs/agents/explain_error/index.mdx

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- Error Explanation: Explain the error encountered in the code cell.
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- Error Resolution: Provide potential solutions to resolve the error.
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![Jupyter AI Agent](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-explainerror-demo-terminal.gif)
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![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agents/ai-agent-explainerror-demo-terminal.gif)
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```bash
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jupyter-ai-agent explain-error \
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jupyter-ai-agents explain-error \
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--url http://localhost:8888 \
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--token MY_TOKEN \
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--azure-ai-deployment-name gpt-40-mini \

‎docs/docs/agents/index.mdx

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Make sure the you understand the [**Deployment Modes**](/docs/deployments) referring to where the agent is running, and the [**Interactions Modes**](/docs/interactions) referring to how the agent is used.
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Jupyter AI Agent currently provides the following agents.
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Jupyter AI Agents currently provides the following agents.
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<DocCardList />
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## Create your own Agent
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More Jupyter AI Agent like `Code Refactor Agent`, `Documentation Agent`... can be created by extending the base class.
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More Jupyter AI Agents like `Code Refactor Agent`, `Documentation Agent`... can be created by extending the base class.
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:::info
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‎docs/docs/agents/prompt/index.mdx

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- Code Generation: Generate cells code based on natural language input.
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- Notebook Modification: Add new cells based on existing one.
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![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agents/ai-agent-prompt-demo-terminal.gif)
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To use the Jupyter AI Agent, an easy way is to launch a CLI (update the Azure deployment based on your setup).
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To use the Jupyter AI Agents, an easy way is to launch a CLI (update the Azure deployment based on your setup).
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```bash
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jupyter-ai-agent prompt \
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jupyter-ai-agents prompt \
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--url http://localhost:8888 \
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--token MY_TOKEN \
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--azure-ai-deployment-name gpt-40-mini \

‎docs/docs/deployments/in-kernel/index.mdx

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:::
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To install Jupyter AI Agents, run the following command.
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```bash
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pip install jupyter_ai_agents
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```
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The Jupyter AI Agent can directly interact with JupyterLab and the modifications made by the Jupyter AI Agent can be seen in real-time thanks to [Jupyter Real Time Collaboration](https://jupyterlab.readthedocs.io/en/stable/user/rtc.html).
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The Jupyter AI Agents can directly interact with JupyterLab and the modifications made by the Jupyter AI Agents can be seen in real-time thanks to [Jupyter Real Time Collaboration](https://jupyterlab.readthedocs.io/en/stable/user/rtc.html).
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‎docs/docs/index.mdx

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# Overview
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**Jupyter AI Agent** is a flexible and powerful solution for using and creating **✨ AI Agents** to interact with **📓 Jupyter Notebooks**
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**Jupyter AI Agents** is a flexible and powerful solution for using and creating **✨ AI Agents** to interact with **📓 Jupyter Notebooks**
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with tools like `insert_cell`, `execute_cell`...
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:::info
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**Jupyter AI Agent** empowers **AI models** to **interact** with and **modify** Jupyter Notebooks.
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**Jupyter AI Agents** empowers **AI models** to **interact** with and **modify** Jupyter Notebooks.
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:::
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![Jupyter AI Agent](https://assets.datalayer.tech/jupyter-ai-agent/ai-agent-prompt-demo-terminal.gif)
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![Jupyter AI Agents](https://assets.datalayer.tech/jupyter-ai-agents/ai-agent-prompt-demo-terminal.gif)
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The Agent is equipped with [Tools](/docs/tools) such as adding Code Cells, inserting Markdown Cells, executing Code, enabling it to modify the Notebook comprehensively based on user instructions or by reacting to Notebook and Kernel events.
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## What is an AI Agent?
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## What is an AI Agents?
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An artificial intelligence (AI) agent is a system that **autonomously performs tasks** by designing workflows and **using tools**.
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Leveraging Large Manguage Models (LLMs), AI agents process user inputs step-by-step and call external tools as needed to tackle
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complex tasks effectively.
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## What Makes Jupyter AI Agent Unique?
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## What Makes Jupyter AI Agents Unique?
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This agent is **innovative** as it is designed to **operate on the entire Notebook**, not just at the Cell level, enabling more comprehensive and seamless modifications.
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```
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Jupyter AI Agent <-----------> JupyterLab
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Jupyter AI Agents <-----------> JupyterLab
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|
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| (RTC Real Time Collaboration)
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**We value your feedback!**
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If you encounter any issues or have suggestions for improvement, please open a [GitHub issue](https://github.com/datalayer/jupyter-ai-agent/issues).
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If you encounter any issues or have suggestions for improvement, please open a [GitHub issue](https://github.com/datalayer/jupyter-ai-agents/issues).
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:::

‎docs/docs/models/azure/index.mdx

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# Azure OpenAI
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Jupyter AI Agent supports models from [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service).
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Jupyter AI Agents supports models from [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service).
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Read the [Azure Documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai) to get the needed credentials and make sure you define them in the following environment variables.
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‎docs/docs/use-cases/index.mdx

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We are working on UI to easily interact with the Agents and plan on building new Agents to support more use cases.
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- **Creating a UI for Chatting with the Agent in JupyterLab** - Developing an interactive interface within JupyterLab
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where users can directly communicate with the Jupyter AI Agent, issuing commands and receiving real-time responses
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where users can directly communicate with the Jupyter AI Agents, issuing commands and receiving real-time responses
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in a conversational format.
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- **Building a Code Refactoring Agent** - Developing an agent that can automatically refactor code in Jupyter Notebooks,
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improving code quality, readability, and maintainability.

‎docs/docusaurus.config.js

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/** @type {import('@docusaurus/types').DocusaurusConfig} */
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title: '🪐 ✨ Jupyter AI Agent documentation',
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title: '🪐 ✨ Jupyter AI Agents documentation',
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tagline: 'Tansform your Notebooks into an interactive, AI-powered workspace that adapts to your needs!',
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url: 'https://datalayer.io',
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baseUrl: '/',
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onBrokenLinks: 'throw',
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onBrokenMarkdownLinks: 'warn',
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favicon: 'img/favicon.ico',
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organizationName: 'datalayer', // Usually your GitHub org/user name.
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projectName: 'jupyter-ai-agent', // Usually your repo name.
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projectName: 'jupyter-ai-agents', // Usually your repo name.
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title: 'Jupyter AI Agents Docs',
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href: 'https://github.com/datalayer/jupyter-ai-agents',
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items: [
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editUrl: 'https://github.com/datalayer/jupyter-ai-agents/edit/main/',
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‎docs/package.json

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{
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"name": "@datalayer/jupyter-ai-agent-docs",
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"name": "@datalayer/jupyter-ai-agents-docs",
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"version": "0.0.1",
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"private": true,
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"scripts": {

‎docs/src/components/HomepageProducts.js

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const ProductList = [
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/*
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{
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title: 'Jupyter AI Agents',
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Svg: require('../../static/img/product_1.svg').default,
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description: (
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<>
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Get started by creating a Jupyter platform in the cloud with Jupyter AI Agent. You will get Jupyter on Kubernetes with a cloud database and storage bucket to persist your notebooks and datasets.
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Get started by creating a Jupyter platform in the cloud with Jupyter AI Agents. You will get Jupyter on Kubernetes with a cloud database and storage bucket to persist your notebooks and datasets.
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</>
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),
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},

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