Open Canvas

TRY IT OUT HERE

Open Canvas is an open source web application for collaborating with agents to better write documents. It is inspired by OpenAI's "Canvas", but with a few key differences.

1. Open Source: All the code, from the frontend, to the content generation agent, to the reflection agent is open source and MIT licensed.
2. Built in memory: Open Canvas ships out of the box with a reflection agent which stores style rules and user insights in a shared memory store. This allows Open Canvas to remember facts about you across sessions.
3. Start from existing documents: Open Canvas allows users to start with a blank text, or code editor in the language of their choice, allowing you to start the session with your existing content, instead of being forced to start with a chat interaction. We believe this is an ideal UX because many times you will already have some content to start with, and want to iterate on-top of it.

Features

• Memory: Open Canvas has a built in memory system which will automatically generate reflections and memories on you, and your chat history. These are then included in subsequent chat interactions to give a more personalized experience.
• Custom quick actions: Custom quick actions allow you to define your own prompts which are tied to your user, and persist across sessions. These then can be easily invoked through a single click, and apply to the artifact you're currently viewing.
• Pre-built quick actions: There are also a series of pre-built quick actions for common writing and coding tasks that are always available.
• Artifact versioning: All artifacts have a "version" tied to them, allowing you to travel back in time and see previous versions of your artifact.
• Code, Markdown, or both: The artifact view allows for viewing and editing both code, and markdown. You can even have chats which generate code, and markdown artifacts, and switch between them.
• Live markdown rendering & editing: Open Canvas's markdown editor allows you to view the rendered markdown while you're editing, without having to toggle back and fourth.

How to use

You can use our deployed version for free by visiting opencanvas.langchain.com

or

You can clone this repository and run locally/deploy to your own cloud. See the next section for steps on how to do this.

Development

Running or developing Open Canvas is easy. Start by cloning this repository and navigating into the directory.

git clone https://github.com/langchain-ai/open-canvas.git

cd open-canvas

Next, install the dependencies via Yarn:

yarn install

Then install LangGraph Studio which is required to run the graphs locally, or create a LangSmith account to deploy to production on LangGraph Cloud.

After that, copy the .env.example file contents into .env and set the required values:

# LangSmith tracing
LANGCHAIN_TRACING_V2=true
LANGCHAIN_API_KEY=

# LLM API keys
# Anthropic used for reflection
ANTHROPIC_API_KEY=
# OpenAI used for content generation
OPENAI_API_KEY=

# LangGraph Deployment, or local development server via LangGraph Studio.
# If running locally, this URL should be set in the `constants.ts` file.
# LANGGRAPH_API_URL=

# Supabase for authentication
# Public keys
NEXT_PUBLIC_SUPABASE_URL=
NEXT_PUBLIC_SUPABASE_ANON_KEY=

Finally, start the development server:

yarn dev

Then, open localhost:3000 with your browser and start interacting!

You can also watch a short (2 min) video walkthrough on how to setup Open Canvas locally here.

LLM Models

Open Canvas is designed to be compatible with any LLM model. The current deployment has the following models configured:

• Anthropic Claude 3 Haiku 👤: Haiku is Anthropic's fastest model, great for quick tasks like making edits to your document. Sign up for an Anthropic account here.
• Fireworks Llama 3 70B 🦙: Llama 3 is a SOTA open source model from Meta, powered by Fireworks AI. You can sign up for an account here.
• OpenAI GPT 4o Mini 💨: GPT 4o Mini is OpenAI's newest, smallest model. You can sign up for an API key here.

If you'd like to add a new model, follow these simple steps:

1. Add to or update the model provider variables in constants.ts.
2. Install the necessary package for the provider (e.g. @langchain/anthropic).
3. Update the getModelNameAndProviderFromConfig function in src/agent/utils.ts to include your new model name and provider.
4. Manually test by checking you can:

• 4a. Generate a new artifact

• 4b. Generate a followup message (happens automatically after generating an artifact)

• 4c. Update an artifact via a message in chat

• 4d. Update an artifact via a quick action

• 4e. Repeat for text/code (ensure both work)

Roadmap

Features

Below is a list of features we'd like to add to Open Canvas in the near future:

• Render React in the editor: Ideally, if you have Open Canvas generate React (or HTML) code, we should be able to render it live in the editor. Edit: This is in the planning stage now!
• Multiple assistants: Users should be able to create multiple assistants, each having their own memory store.
• Give assistants custom 'tools': Once we've implemented RemoteGraph in LangGraph.js, users should be able to give assistants access to call their own graphs as tools. This means you could customize your assistant to have access to current events, your own personal knowledge graph, etc.

Do you have a feature request? Please open an issue!

Contributing

We'd like to continue developing and improving Open Canvas, and want your help!

To start, there are a handful of GitHub issues with feature requests outlining improvements and additions to make the app's UX even better. There are three main labels:

• frontend: This label is added to issues which are UI focused, and do not require much if any work on the agent(s).
• ai: This label is added to issues which are focused on improving the LLM agent(s).
• fullstack: This label is added to issues which require touching both the frontend and agent code.

If you have questions about contributing, please reach out to me via email: brace(at)langchain(dot)dev. For general bugs/issues with the code, please open an issue on GitHub.