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eugeneyan
obsidian-copilot
Python2023–2024
eugeneyan / obsidian-copilot

obsidian-copilot

🤖 A prototype assistant for writing and thinking

AI & Machine LearningProductivity
Explore on GitHubRead Hacker News discussions
2Distinct people
2Mentions
0Explicit recommenders
561GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

🤖 A prototype assistant for writing and thinking

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month2 dated mentions

Observed mentions: 2023-06-13 15:50:07 UTC to 2024-04-04 10:13:13 UTC.

012023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJun 20232023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsNov 20232023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsApr 2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC101
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC000
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC000
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC000
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC000
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC000
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC000
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC000
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC101

What Hacker News says

2 sources
wokwokwok·Jun 13, 2023
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 tryi
Read the rest
ng 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-...
In Obsidian-Copilot: A Prototype Assistant for Writing and Thinking

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