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Private RAG with Mistral, Ollama and Pathway
Hacker NewsPrivate RAG with Mistral, Ollama and Pathway
We’re excited to share our fully local RAG setup, which has received great feedback from the community. Full app: https://github.com/pathwaycom/llm-app/tree/main/examples/pip... We also feature tools and parsers for various RAG use cases, including document parsing with local vision LMs and some other cool stuff.
Share cardActual performance
5points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: excited, llama, io · Missing: https docs, just released, exist69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: including · Missing: supports, reddit linkedin, podcasting34%34% 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, revenue13%13% 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, crypto4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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