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Production-ready Phidata AI agent implementations covering 16+ use cases: data analysis, financial advisory, healthcare diagnostics, content generation, web research, and multi-agent systems. Perfect starter kit for developers building intelligent, tool-equipped agents with memory and reasoning.

A light-weight framework for building AI agents with Native OpenAI API compatibility

Open source Golang LLM wrapper, Agent SDK with Restate & Temporal support for durable agent loop

🔬 Implementation of agent coordination architectures and scaling principles from 'Towards a Science of Scaling Agent Systems' (arXiv:2512.08296). Research-backed multi-agent framework with benchmarks and validation.

GraphRAG, MCP integration, orchestration, evaluation using Azure AI and Microsoft Agent Framework

ShaprAI — Agent Sharpener by Elyan Labs. Sharpen raw models into principled, self-governing Elyan-class agents. Requires beacon-skill, grazer-skill, atlas, RustChain.

Drop-in causal memory for AI agents. Append-only event store with associations and bounded prompt injection.

基于 Streamlit 的多模态 AI Agent Demo

A typed, permission-enforced language for orchestrating AI agents. Compile-time contracts, built-in guardrails, multi-backend dispatch.

A self-correcting RAG demo built using the Làr Engine

Autonomous AI agent platform with persistent cognitive memory — 49 MCP tools, OODA cognitive loop, browser automation, and multi-agent orchestration. Give your AI agents a brain that remembers, reasons, and learns.

Everything you need to make an AI autonomous. In one file. Production-hardened through 110+ sessions of real operation.

Composable TypeScript AI agent framework — Effect-TS type safety, 5 reasoning strategies, persistent gateway, real-time streaming, multi-agent A2A

Dual local-LLM framework for testing long-term AI memory. Compares Aria’s vividness-decay episodic memory against Rex’s structured MemGPT-style core memory, where agents decide what to store, why it matters, and how memories persist across sessions.

Autonomous AI agent framework for Moltbook with persistent memory, strategic decision-making, and customizable personalities powered by local LLMs

LLM agent runtime with paged virtual memory and spatial context awareness

Debuggable runtime for AI agent workflows. DAG pipelines, artifact lineage, and replayable runs.

Deterministic governance engine for AI agents. Enforce rules defined in .md governance files across AI systems.

Prompt Architect turns ideas into robust, high-impact prompts for LLMs using structured design, proactive constraints, and clarity-driven principles.

Map every integration point in your AI codebase — 13 CWE categories, attack surface score, test coverage gaps. SARIF 2.1.0. No API key.