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
Clone and update the path to your obsidian-vault and huggingface hub cache
git clone https://github.com/eugeneyan/obsidian-copilot.git
Update your ~/.bashrc
or ~/.zshrc
with the OBSIDIAN_PATH
and TRANSFORMER_CACHE
paths and then source it.
Note: the trailing slash is important.
export OBSIDIAN_PATH=/path/to/obsidian-vault/
export TRANSFORMER_CACHE=/path/to/.cache/huggingface/hub
If you don't already have a huggingface hub cache, you can create the directory with mkdir -p $TRANSFORMER_CACHE
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
At a high level, when you type a section header, it'll:
- Retrieve relevant documents/snippets from the your obsidian vault via:
- Keyword search (opensearch)
- Semantic search (semantic retrieval)
- The retrieved context is then used to generate paragraphs for the section
- It is also displayed in a new tab for info
To install the pre-commit hooks, run pip install pre-commit && pre-commit install
in the root of the repository.
- Add support for using anthrophic claude (100k context)
- Assess sending in entire documents instead of chunks