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Smolex – A code retrieval ChatGPT Plugin for Python

Hacker News

Smolex – A code retrieval ChatGPT Plugin for Python

The problem: We're chatting with ChatGPT about our code, right? And we've got to manually piece together a context to feed the AI, especially when that token limit comes into play. ;) Here's where Smolex jumps in. It allows ChatGPT to pull up context directly from your codebase (it's a plugin that just runs on localhost), making our back-and-forths about code more like a conversation and less like a chore. I find it's a real lifesaver when writing new tests based on old ones. Smolex can provide ChatGPT with the existing tests for context. Heads up, though, this tool's super experimental - basically, it's been cooked up to scratch my own itch.

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Actual performance

16points
4comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, context, chatgpt · Missing: mac, agents, macos
88%88% 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
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, real life · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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