langchain-ai / open-canvas

šŸ“ƒ A better UX for chat, writing content, and coding with LLMs.
https://opencanvas.langchain.com/
MIT License
2.58k stars 378 forks source link

Open Canvas

TRY IT OUT HERE

Screenshot of app

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

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.

Diagram of the Open Canvas graph

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:

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:

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:

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.