ChatGPT History Explorer

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Hey HN, As a heavy ChatGPT user, I often want to explore my chat history, look for things I've already asked, keep favorite chats, and much more. ChatGPT doesn't even offer search capability (except in mobile version). So I decided to build one myself. It runs locally, so no sensitive data leaks. You only need to export your ChatGPT conversations, and put it in the `data` folder. Optionally setup OpenAI API key and it will create embeddings for semantic search. *Important* - it's not a desktop app (at least, not yet) - it's a python code with a browser interface that I've only tested on MacOS so far. Minimal dev skills are required to set it up. Current functionality: - Github-style activity graph and some other statistics - Browse and read your conversations - Quick filters by conversation title and time period - Search (semantic and simple "strict") - Add chats to favorites - Open conversations on the ChatGPT site to continue working My plans for new features: https://github.com/mirableio/chat-history/issues Hope it will be useful to people. Would love to hear your feedback.

Visit product View on Hacker NewsSep 14, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, user · Missing: agents, agent, cursor

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best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

35%35% 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

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 · 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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