Memory that AI Agents Love!
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Updated
May 22, 2026 - Python
Memory that AI Agents Love!
A MMORPS platform for persistent, branching AI stories using Gemini 3, LangGraph, and Firestore.
An AI agent that acts as a "Generative Historian," inspired by Isaac Asimov's Foundation, to simulate the emergent history of a civilization from the stone age to the stars.
GraphNews is a multi-agent system that acts as a self-correcting editorial team, generating newsletters
Stateful Telegram AI Assistant powered by Gemini 2.5 Flash & LangChain. Securely manages Google Calendar (CRUD) via custom tools. Features SQL-backed conversational memory for dynamic chats, zero-downtime error handling, strict access control, and cloud-ready architecture.
Complete hands-on Agentic AI bootcamp repository covering LangGraph, LangChain, AI Agents, multi-agent workflows, RAG pipelines, tool-augmented LLM systems, memory architectures, and production-grade AI application engineering for real-world intelligent systems.
EVM — Evolution Vector Memory: deterministic interaction-state continuity and bounded identity evolution framework for AI systems.
Agent Operating System running locally in the browser: a persistent, tool-driven AI that reasons in an agentic loop, executes skills, manages memory/state, and evolves over time with optional sync and strict governance.
Deterministic reflex-aware conversational middleware: tone tagging → deviation scoring → governance modes (Terminal + React demo, seeded replay, no external APIs).
An Experimental Cognitive Architecture with Persistent Memory for stateful LLM-agents
A laboratory for Java AI applications and agentic architectures. Focused on stateful multi-agent orchestration,LangChain4j, LangGraph4j workflows, and Spring Boot integrations. Practical, local-first LLM patterns using Ollama, and the Model Context Protocol (MCP).
A viewer whose perception evolves with each image—stateful, memory-carrying VLM reflections across a gallery.
đź“° Automate news research and curation with GraphNews, a multi-agent system that ensures high-quality, factual content through self-correction.
Stateful RAG with isolated user memory with history compression and semantic cache.
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