obsidian-copilot VS obsidian-smart-connections

hadn't seen your repo yet [1] - adding it to my list right now.

Your blog post is really neat on top - thanks for sharing

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

Um... can someone explain what this actually does?

In the video the user chooses the 'Copilot: Draft' action, and wow, it generates code...

...but, the 'draft' action [1] calls `/get_chunks` and then runs 'queryLLM' [2] which then just invokes 'https://api.openai.com/v1/chat/completions' directly.

So, generating text this way is 100% not interesting or relevant.

What's interesting here is how it's building the prompt to send to the openai-api.

So... can anyone shed some light on what the actual code [3] in get_chunks() does, and why you would... hm... I guess, do a lookup and pass the results to the openai api, instead of just the raw text?

The repo says: "You write a section header and the copilot retrieves relevant notes & docs to draft that section for you.", and you can see in the linked post [4], this is basically what the OP is trying to implement here; you write 'I want X', and the plugin (a bit like copilot) does a lookup of related documents, crafts a meta-prompt and passes the prompt to the openai api.

...but, it doesn't seem to do that. It seems to ignore your actual prompt, lookup related documents by embedding similarity... and then... pass those documents in as the prompt?

I'm pretty confused as to why you would want that.

It basically requires that you write your prompt separately before hand, so you can invoke it magically with a one-line prompt later. Did I misunderstand how this works?

[1] - https://github.com/eugeneyan/obsidian-copilot/blob/bdabdc422...

[2] - https://github.com/eugeneyan/obsidian-copilot/blob/bdabdc422...

[3] - https://github.com/eugeneyan/obsidian-copilot/blob/main/src/...

[4] - https://eugeneyan.com/writing/llm-experiments/#shortcomings-...

For my personal notes, I use Smart Connections[1] with Obsidian. I am considering devising my own solution using LlamaIndex[2] in the near future.

For coding, I use Copilot[3]. While it's been great for writing boilerplate code, it falls short in every other regard. I also had the opportunity to try the new version of Copilot as well, but it feels like a glorified ChatGPT inside VSCode.

For everything else, I use a tiny tool I made[4] which enables me to invoke my own prompts in basically any application that allows me to select text.

[1] https://github.com/brianpetro/obsidian-smart-connections

[2] https://gpt-index.readthedocs.io/en/latest/getting_started/s...

[3] https://github.com/features/copilot

[4] https://github.com/overflowy/chat-key

Adding options to us local LLM's like GPT4all, or alpaca #141

Smart Connections allows you to search using embeddings[1].

[1] https://github.com/brianpetro/obsidian-smart-connections

There is actually a plugin that leverages AI to do it. I haven't used it yet plus there might also be a concern over giving a third party AI access to your notes but if you are interested here is the link. https://github.com/brianpetro/obsidian-smart-connections

The "smart connection" plugin is ideal for your search needs. This plugin allows you to search using semantics rather than keywords, just like Google. https://github.com/brianpetro/obsidian-smart-connections

Here is the Obsidian plugin I was referring to: https://github.com/brianpetro/obsidian-smart-connections

I am very attracted to the Smart Connections plugin, which would implement Obsidian with the only real feature I envy other centralized PKMs (such as Mem X): that of finding and connecting to similar notes. The point is this: the price (paid after each use) due to Open AI for using the GPT engine.

I'm using Obsidian with the Smart Connections plugin. I then used chatGPT (4) to write a python script that chatGPT summarized this way:

Smart Connections