Command-line chatbot featuring modular waifu personalities like deredere and tsundere. 🎀 Leverages an llm for dynamic conversation generation and optional user simulation. 💖 Offers interactive chat, automated llm-driven conversations, and direct llm prompt testing modes. ✨ Basic prompts configured via JSON. ✅ Includes pytest test suite. 👍

Classifies sentences as human (1) or machine (0) using an LLM via its API ✅. Features evaluation scripts calculating accuracy, precision, recall, F1, and confusion matrix 📊. Loads input data from TSV files 📂. Allows configuration of the target llm model and request delays ⚙️. Leverages scikit-learn for detailed performance analysis 📈.

Animated sprite waifu with TTS and emotion system for Hermes Agent

Generates random quantum circuit datasets with Cirq, including simulation and initial optimization steps ✨. Saves datasets in JSON Lines format for easy parsing 📊. Optimizes quantum circuits by prompting an LLM using in-context learning techniques 🚀. Includes a command-line interface for applying this LLM-based circuit optimization directly 💡.

Collection of interactive web apps focused on advanced topics. Includes simulations for tokenomics, bonding curves, quantum computing, AI agents, and the Orch-OR theory🎉. Features Solana ecosystem tools, and decentralized science applications✨. Also explores concepts like superintelligence, string theory, and consciousness💖.

Explores advanced concepts in quantum computing, tokenomics, and AI 🚀. Includes implementations of bonding curves, agent-based simulations 💸, dynamic pricing, and multimodal data handling 🧮, plus kinematic equations 💫, with an emphasis on formal mathematical models 🧪.

🔍 Analysis engine with 4-tier risk classification system (Real Yield/Systemic/Venture/Speculative) 🏗️ Rich library creates color-coded tables with ticker symbols, insider scores, tariff percentages, and exchange multipliers 📊 JSON data loader processes multiple files using Pydantic validation models for portfolio risk assessment 📈

compilation of original books

efficient benchmarks for ai performance

Generates llms-full.html files, improving documentation accessibility for Large Language Models. ✨ Aggregates full documentation and code examples into one structured HTML file. 👍 Leverages LLMs to generate concise content summaries, aiding AI ingestion. 📄 Helps overcome LLM context limitations by consolidating information. 🚀