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I noticed a pattern: every LLM framework today lets the AI manage state and do math. Then we wonder why pipelines hallucinate numbers and break at 3 AM.I took a different approach and built Aura-State, an open-source Python framework that compiles LLM workflows into formally verified state machines.Instead of hoping the AI figures it out, I brought in real algorithms from hardware verification and statistical learning:CTL Model Checking: the same technique used to verify flight control systems, now applied to LLM workflow graphs. Proves safety properties before execution.Z3 Theorem Prover: every LLM extraction gets formally proven against business constraints. If the total ≠ price × quantity, Z3 catches it with a counterexample.Conformal Prediction: distribution-free 95% confidence intervals on every extracted field. Not just "the LLM said $450k" but "95% CI: [$448k, $452k]."MCTS Routing: Monte Carlo Tree Search (the algorithm behind AlphaGo) scores ambiguous state transitions mathematically.Sandboxed Math: English math rules compile to Python AST. Zero hallucination calculations.I ran a live benchmark against 10 real-estate sales transcripts using GPT-4o-mini:
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These orchestrated demonstrations climaxed on Aug. 19, 1953, when pro-shah forces and sympathetic leaders in the Iranian military – with CIA financial and logistical backing – seized key points of the country, confronted Mossadegh loyalists and helped topple his government. Estimates suggest around 200 to 300 people were killed in the chaotic fighting in Tehran.
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Ранее на квесте в Перми двух школьниц 11 и 14 лет избили плетками до травм. По словам матери одной из пострадавших, она предупредила организаторов, что участники являются несовершеннолетними.
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