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Арсений Перельleft a comment
Hi Product Hunters! 👋 I’m Senya, and I built TRI·TFM Studio because I was tired of guessing how to write the "perfect prompt" for complex RAG pipelines. Most developers throw vague instructions at an LLM and hope for the best. When it hallucinates, they manually tweak words for hours. We decided to automate this. Under the hood is a 12-step Proposer-Critic-Arbiter (PCA) loop. You paste your...
TRI/TFM — Prompt Optimization EngineDeterministic Proposer-Critic-Arbiter loop for AI prompts
Stop writing bad prompts. TRI·TFM Studio uses a sophisticated Proposer-Critic-Arbiter (PCA) loop to automatically evaluate, enrich, and mathematically optimize your raw prompts across 5 dimensions (Emotion, Facts, Meaning, Nuance, Brevity).
TRI/TFM — Prompt Optimization EngineDeterministic Proposer-Critic-Arbiter loop for AI prompts
An open-source, mathematically proven evaluation pipeline for LLMs and RAG systems. We eliminate "metric hallucination" by locking T=0.0 and applying a dynamic weight matrix (Bal = 0.75F - 0.25B) to score Facts, Bias, and Narrative deterministically.
TRI·TFM v3.0 FrameworkDeterministic, LLM-as-a-Judge evaluation framework.
Арсений Перельleft a comment
Hi Product Hunters! 👋 Evaluating RAG pipelines and LLM agents in production is currently a nightmare. Most frameworks act as "black boxes" and average out metrics indiscriminately. Worse, they allow the Judge LLM to have a temperature > 0.0, turning your evaluation into a stochastic random number generator (the "Confident Idiot" problem). I built TRI·TFM v3.0 Framework to fix this. Over the...
TRI·TFM v3.0 FrameworkDeterministic, LLM-as-a-Judge evaluation framework.