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ChatJeepTea – A Voice-Based Conversational Telegram Chat Bot
Hacker NewsChatJeepTea – A Voice-Based Conversational Telegram Chat Bot
Hey HN! I'm excited to introduce ChatJeepTea, an Open Source Telegram chat bot that combines OpenAI's GPT API, Whisper ASR, and Google text-to-speech to enable voice-based conversations in near-realtime. It's written in Python and allows you to communicate with the bot using voice messages.
Share cardActual performance
5points
1comments
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: google, openai, using · Missing: mac, agents, macos84%84% 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: excited, open source, io · Missing: https docs, just released, exist72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListSuited for BetaList early-adopters · Strong signals: chat, introduce · Missing: web3, crypto, cryptocurrency53%53% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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