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https://github.com/e2b-dev/ai-artifacts

Hackable open-source version of Anthropic's Claude Artifacts by E2B
https://github.com/e2b-dev/ai-artifacts

ai ai-code-generation anthropic claude claude-ai code-interpreter e2b javascript llm nextjs react sandbox typescript

Last synced: 4 months ago
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Hackable open-source version of Anthropic's Claude Artifacts by E2B

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README 

        
# E2B AI Artifacts



This is an open source version of [Anthropic's Claude Artifacts](https://www.anthropic.com/news/claude-3-5-sonnet) and Vercel [v0](https://v0.dev).



Powered by [E2B Sandbox SDK](https://github.com/e2b-dev/e2b) and [Code Interpreter SDK](https://github.com/e2b-dev/code-interpreter). Made by the [E2B](https://e2b.dev) team.



![Preview](preview.png)



[→ Try on artifacts.e2b.dev](https://artifacts.e2b.dev)



## Features



- Based on Next.js 14 (App Router), TailwindCSS, Vercel AI SDK.

- Uses [Code Interpreter SDK](https://github.com/e2b-dev/code-interpreter) from [E2B](https://e2b.dev) to securely execute code generated by AI.

- Streaming in the UI.

- Can install and use any package from npm, pip.

- Supported stacks ([add your own](#adding-custom-personas)):

  - 🔸 Python interpreter

  - 🔸 Next.js

  - 🔸 Vue.js

  - 🔸 Streamlit

  - 🔸 Gradio

- Supported LLM Providers ([add your own](#adding-custom-llm-models)):

  - 🔸 OpenAI

  - 🔸 Anthropic

  - 🔸 Google AI

  - 🔸 Mistral

  - 🔸 Groq

  - 🔸 Fireworks

  - 🔸 Together AI

  - 🔸 Ollama



**Make sure to give us a star!**



Screenshot 2024-04-20 at 22 13 32



## Get started



### Prerequisites



- [git](https://git-scm.com)

- Recent version of [Node.js](https://nodejs.org) and npm package manager

- [E2B API Key](https://e2b.dev)

- LLM Provider API Key



### 1. Clone the repository



In your terminal:



```

git clone https://github.com/e2b-dev/ai-artifacts.git

```



### 2. Install the dependencies



Enter the repository:



```

cd ai-artifacts

```



Run the following to install the required dependencies:



```

npm i

```



### 3. Set the environment variables



Create a `.env.local` file and set the following:



```sh

# Get your API key here - https://e2b.dev/

E2B_API_KEY="your-e2b-api-key"



# OpenAI API Key

OPENAI_API_KEY=



# Other providers

ANTHROPIC_API_KEY=

GROQ_API_KEY=

FIREWORKS_API_KEY=

TOGETHER_AI_API_KEY=

GOOGLE_AI_API_KEY=

MISTRAL_API_KEY=

```



### 4. Start the development server



```

npm run dev

```



### 5. Build the web app



```

npm run build

```



## Customize



### Adding custom personas



1. Make sure [E2B CLI](https://e2b.dev/docs/cli/installation) is installed and you're logged in.



2. Add a new folder under [sandbox-templates/](sandbox-templates/)



3. Initialize a new template using E2B CLI:



    ```

    e2b template init

    ```



    This will create a new file called `e2b.Dockerfile`.



4. Adjust the `e2b.Dockerfile`



    Here's an example streamlit template:



    ```Dockerfile

    # You can use most Debian-based base images

    FROM python:3.19-slim



    RUN pip3 install --no-cache-dir streamlit pandas numpy matplotlib requests seaborn plotly



    # Copy the code to the container

    WORKDIR /home/user

    COPY . /home/user

    ```



5. Specify a custom start command in `e2b.toml`:



    ```toml

    start_cmd = "cd /home/user && streamlit run app.py"

    ```



6. Deploy the template with the E2B CLI



    ```

    e2b template build --name 

    ```



    After the build has finished, you should get the following message:



    ```

    ✅ Building sandbox template   finished.

    ```



7. Open [lib/templates.json](lib/templates.json) in your code editor.



    Add your new template to the list. Here's an example for Streamlit:



    ```json

    "streamlit-developer": {

      "name": "Streamlit developer",

      "lib": [

        "streamlit",

        "pandas",

        "numpy",

        "matplotlib",

        "request",

        "seaborn",

        "plotly"

      ],

      "file": "app.py",

      "instructions": "A streamlit app that reloads automatically.",

      "port": 8501 // can be null

    },

    ```



    Provide a template id (as key), name, list of dependencies, entrypoint and a port (optional). You can also add additional instructions that will be given to the LLM.



4. Optionally, add a new logo under [public/thirdparty/templates](public/thirdparty/templates)



### Adding custom LLM models



1. Open [lib/models.json](lib/models.ts) in your code editor.



2. Add a new entry to the models list:



    ```json

    {

      "id": "mistral-large",

      "name": "Mistral Large",

      "provider": "Ollama",

      "providerId": "ollama"

    }

    ```



    Where id is the model id, name is the model name (visible in the UI), provider is the provider name and providerId is the provider tag (see [adding providers](#adding-custom-llm-providers) below).



### Adding custom LLM providers



1. Open [lib/models.ts](lib/models.ts) in your code editor.



2. Add a new entry to the `providerConfigs` list:



    Example for fireworks:



    ```ts

    fireworks: () => createOpenAI({ apiKey: apiKey || process.env.FIREWORKS_API_KEY, baseURL: baseURL || 'https://api.fireworks.ai/inference/v1' })(modelNameString),

    ```



3. Optionally, adjust the default structured output mode in the `getDefaultMode` function:



    ```ts

    if (providerId === 'fireworks') {

      return 'json'

    }

    ```



4. Optionally, add a new logo under [public/thirdparty/logos](public/thirdparty/logos)



## Contributing



As an open-source project, we welcome contributions from the community. If you are experiencing any bugs or want to add some improvements, please feel free to open an issue or pull request.