obsidian-copilot VS obsidian-omnisearch

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-...

Mobile Document Scanning using QuickScan iOS app and OCR search with Omnisearch and Text Extractor: I was a power user of the Scannable app by Evernote for capturing scans of receipts and documents, so moving on from this was going to be tough. But QuickScan has the same functionality (OCR scanning) and has quick outputs to where my scans are stored in my Obsidian folder. Using Omnisearch, searching my scans feels just as intuitive and snappy as what Evernote used to feel like for me.

In the past I have used Omnisearch which I have found to be an improvement.

https://github.com/scambier/obsidian-omnisearch

Combine this with my favorite Obsidian search plugin Omnisearch and you end up making this bunch of random chat threads useful - now I can link and tag across, and source them for new ideas.

The Omnisearch plugin might be what you need. No AI but weighted results depending on where your query words are found (filename, titles, frequency...). It works well for me, it's my primary way to find notes.

The tag system works well for GTD workflows and organization in general. Default search isn't the best but the Omnisearch plugin fixes that.

Also - and speaking about plugins in general - the best way to get an issue resolved is to ask it on the GitHub page. If the plugin is maintained, its developer will usually gladly help you solve your problem :) https://github.com/scambier/obsidian-omnisearch/issues

I think Obsidian Omnisearch can help you with that.

The Omnisearch plug-in for Obsidian does search in PDFs and images via OCR.

In my opinion it is absolutely possible. The developer of the Omnisearch plugin now works on PDF indexing - https://github.com/scambier/obsidian-omnisearch/releases/tag/1.6.5-beta.3.