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Lluminy – automate code comments for Python projects

Hacker News

Lluminy – automate code comments for Python projects

Hi everyone! I built lluminy to solve the pain of documenting Python code. It: - Uses LLama 3.3 to generate code comments - To avoid code hallucinations, it parses Python files into AST, and only modifies function docstrings - Integrates with GitHub (submits results as pull requests) - Handles projects of any size with minimal setup Try it out: https://lluminy.com Here's what I'm planning to work on next: - Automatic documentation suggestions on GitHub PRs - Sphinx integration - Support for more languages (JavaScript and others) - Alternative LLM options Looking forward to feedback from the HN community!

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Product HuntOn track for Day 1 leaderboard · Strong signals: code · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: llama, io · Missing: https docs, excited, just released
42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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