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Obsidian-copilot

How would a copilot for writing and thinking look like?

Here's a possible implementation: You write a section header and the copilot retrieves relevant notes & docs to draft that section for you. This pattern of retrieval-augmented generation can also be extended to other use cases. Here's an example where the copilot helps you reflect on your week based on your daily journal entries.

copilot-v2.mp4

Currently, copilot helps you:

  • Draft sections based on your notes
  • Reflect on your week based on your daily journal entries

More technical details on how it works here: Obsidian-Copilot: A Prototype Assistant for Writing & Thinking

Quick start

Clone and update the path to your obsidian-vault and huggingface hub cache

git clone https://github.com/eugeneyan/obsidian-copilot.git

# Open Makefile and update the following paths
export OBSIDIAN_PATH = /Users/eugene/obsidian-vault/
export TRANSFORMER_CACHE = /Users/eugene/.cache/huggingface/hub

Build the OpenSearch and semantic indices

# Build the docker image
make build

# Start the opensearch container and wait for it to start. 
# You should see something like this: [c6587bf83572] Node 'c6587bf83572' initialized
make opensearch

# In ANOTHER terminal, build your artifacts (this can take a while)
make build-artifacts

Running the retrieval app

# First, stop the opensearch container (CTRL + C). Then, start the retrieval app. 
# You should see this: Uvicorn running on http://0.0.0.0:8000
make run

Install the copilot-plugin, enable it in community plugin settings, and update the API key in copilot

make install-plugin

How does it work?

At a high level, when you type a section header, it'll:

  • Retrieve relevant documents/snippets from the your obsidian vault via:
  • The retrieved context is then used to generate paragraphs for the section
  • It is also displayed in a new tab for info

TODOs

  • Add support for using anthrophic claude (100k context)
  • Assess sending in entire documents instead of chunks

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  • Python 53.2%
  • TypeScript 34.1%
  • Makefile 7.2%
  • JavaScript 3.6%
  • Dockerfile 1.2%
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