An agent to research a given topic by doing analytical and syntopic reading, summarizing and extracting main points, connecting them together, and forming new knowledge outputs such as zettels or evergreen notes.
Clone this repo and use poetry install
.
- Copy the
example.env
file to.env
and fill out your keys. - Run
load_knowledgebase
command to create and store your evergreen note embeddings.
- Create a textfile in this format for your article.
- Run
make_article --f FILE_LOCATION
and your source and evergreen notes will be added to the directories you specified in.env
- This is mostly a prototype to learn about building LLMs. With paid API access, this could get very costly very quickly and has not yet been optimized for cost-effectiveness.
- The current version is built for Obsidian-based knowledgebases, but there is an open issue for supporting additional tools for thought.
- This is also built around my own source and evergreen note templates. Feel free to rework the templates in
llm_knowledge_agent/obsidian_templates.py
to fit your templates. In the future this will be easier to configure.
TITLE
AUTHORS (separated by commas)
TAGS (#format separated by commas)
URL
TEXT