Ti

TinyAgents – a Rust based recursive LLM harness

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TinyAgents – a Rust based recursive LLM harness

Hey Guys, I would like to showcase Tiny Agents, which is an entirely Rust-based RLM. RLMs are a recent and fantastic new innovation on how LLMs can be reimagined by designing the LLM agent itself to define how it will orchestrate or create its own sub-agent. I also could not find any good LLM harness workflow in Rust, so I built this one, taking massive inspiration from LangGraph and LangChain but also incorporating a Rust-based transpiler to build on-demand LLM graphs all in Rust following the RLM idea. This is the harness that we are currently using in production in openhuman.

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, new · Missing: mac, macos, cursor
90%90% 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.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
47%47% predicted probability of success on Indie Hackers, 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
44%44% 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
36%36% 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
31%31% 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
19%19% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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