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The vision for Reor is for it to become the self-organising knowledge base that runs LLM workflows and is backed by a knowledge graph.
What does that mean?
Reor provides a core set of API functions like search and filesystem functions which LLMs will use as tools.
Users can then define an LLM workflow which could combine any number of steps, inputs and tools.
That LLM workflow can run anywhere in the app: in chat, within the writing assistant, as a cron job that runs daily or something that summarises a webpage every time a link is pasted, etc.
Ultimately, every note will be a node in a knowledge graph with a set of properties and relationships to other notes. Really powerful things can then be done like automatically linking notes and easily querying notes via the natural language->LLM->SQL flow.
Improve reliability around large files (files get automatically embedded even if they are very big)
Migrate from transformers.js to ollama for embeddings
Improve electron store interface
Rename file should not overwrite content if it already exists
Show api name under model dropdown
Fix content security bug
Allow for editing of custom llm apis
Update app automatically
Customise dialog implementation for shadcn so it works seabed from context
minimize and close buttons on linux
date filters in search tool should allow both date created and date modified
If search tool is available, force search tool rather than 'initial knowledge base search'
Fix/investigate bug with duplicate search entries for each note
Show search tool query arguments
To allow easy prompt reuse, we can just proactively store prompts for users that they often use and just predict them
Fix object has been destroyed bug
Allow cancel generation
Of course, the above is not set in stone. We are very keen for contributors to propose ideas to work on. Check out our contributors guide to get started 😄
The text was updated successfully, but these errors were encountered:
The vision for Reor is for it to become the self-organising knowledge base that runs LLM workflows and is backed by a knowledge graph.
What does that mean?
Ultimately, every note will be a node in a knowledge graph with a set of properties and relationships to other notes. Really powerful things can then be done like automatically linking notes and easily querying notes via the natural language->LLM->SQL flow.
Key upcoming tasks:
Other important tasks:
Of course, the above is not set in stone. We are very keen for contributors to propose ideas to work on. Check out our contributors guide to get started 😄
The text was updated successfully, but these errors were encountered: