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A better UI for ChatGPT, Claude with text search, saved chats and more

Hacker News

A better UI for ChatGPT, Claude with text search, saved chats and more

Video introduction: https://www.youtube.com/watch?v=o9UwZcM62Dc Link: https://www.teletyped.com/ Hey HN! My brother and I worked on this UI for ChatGPT, Claude, LLama 3, and Mistral models. Our features: - Full text search across all your chats - Saved chats - Switch models mid-chat - Edit model outputs and continue generating, or save model responses for longer prompt engineering - Temporary chats - Edit model creativity (temperature) - Different color themes On our roadmap: - Upload pdf files + photos (we know this an important one and plan to support in coming weeks) - Web search + RAG for all models as a toggle Really curious what you guys think!

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Actual performance

23points
21comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, model, models · Missing: mac, agents, macos
85%85% 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.
Hacker NewsStrong engagement from HN community · Strong signals: llama, ide, io · Missing: https docs, excited, just released
54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
44%44% 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
20%20% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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