GPTCache – Redis for LLMs

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Hey folks, As much as we love GPT-4, it's expensive and can be slow at times. That's why we built GPTCache - a semantic cache for autoregressive LMs - atop the vector database Milvus and SQLite. GPTCache provides several benefits: 1) reduced expenses due to minimizing the number of requests and tokens sent to the LLM service 2) enhanced performance by fetching cached query results directly 3) improved scalability and availability by avoiding rate limits, and 4) a flexible development environment that allows developers to verify their application's features without connecting to LLM APIs or network. Come check it out! https://github.com/zilliztech/gptcache

Visit product View on Hacker NewsApr 12, 2023

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

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% 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, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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