Discover open-source implementations addressing autonomous decision support with autonomous tool loops, retrieval augmented generation, and custom LLM reasoning.
Learn how to build a governance layer that enforces deterministic policies on AI agents, preventing dangerous actions before they execute..
The AI Financial Coach is a personalized financial advisor powered by Google's ADK (Agent Development Kit) framework. This app provides comprehensive financial analysis and recommendations based on user inputs including income,...
The AI Game Design Agent Team is a collaborative game design system powered by AG2(formerly AutoGen)'s AI Agent framework. This app generates comprehensive game concepts through the coordination of multiple specialized AI agents, each...
The AI Health & Fitness Planner is a personalized health and fitness Agent powered by Agno AI Agent framework. This app generates tailored dietary and fitness plans based on user inputs such as age, weight, height, activity level,...
A multi-agent system built with Google ADK that analyzes photos of your space, creates personalized renovation plans, and generates photorealistic renderings using Gemini 3 Flash and Gemini 3 Pro's multimodal capabilities.
Watch two AI agents battle it out in an epic used car negotiation! Built with Google ADK for the backend agents and AG-UI + CopilotKit for a jaw-dropping reactive frontend.
An intelligent meal planning agent built with Agno that helps you discover recipes, analyze nutrition, estimate costs, and create weekly meal plans based on your ingredients and dietary preferences.
A Streamlit application that simulates a full-service recruitment team using multiple AI agents to automate and streamline the hiring process. Each agent represents a different recruitment specialist role - from resume analysis and...
A multi-agent AI pipeline that generates competitive sales battle cards in real-time, built with Google ADK and Gemini.
An AI application that simulates a full-service digital agency using multiple AI agents to analyze and plan software projects. Each agent represents a different role in the project lifecycle, from strategic planning to technical...
An Agno agentic system that provides expert software architecture analysis and recommendations using a dual-model approach combining DeepSeek R1's Reasoning and Claude. The system provides detailed technical analysis, implementation...
A Streamlit application that brings together a team of specialized AI teaching agents who collaborate like a professional teaching faculty. Each agent acts as a specialized educator: a curriculum designer, learning path expert, resource...
A multi-agent AI pipeline for startup investment analysis, built with Google ADK, Gemini 3 Pro, Gemini 3 Flash and Nano Banana Pro.
A reference implementation demonstrating how to build a multi-agent pipeline that aggregates technical signals from multiple sources, scores them for relevance, assesses risks, and synthesizes an actionable intelligence digest.
An investor-grade earnings call companion that turns any YouTube earnings call into a playback-synced analyst workspace. Paste a call URL, watch the video, and let ADK agents surface the numbers, tone shifts, filing context, and...
A Streamlit app demonstrating the "Automatic Critique + Improvement Loop" pattern using GPT-OSS via Groq. This demo implements an iterative quality improvement process.
Learn how to build a trust layer for multi-agent systems that enables secure delegation, trust scoring, and policy enforcement between AI agents.
An AI Powered Streamlit application that serves as your personal coding assistant, powered by multiple Agents built on the new o3-mini model. You can also upload an image of a coding problem or describe it in text, and the AI agent will...
A sophisticated multi-agent system built with Google ADK that analyzes landing page designs, provides expert UI/UX feedback, and automatically generates improved versions using Gemini 2.5 Flash's multimodal capabilities.
A multi-agent app built on EvoAgentX that turns a single natural-language goal into a working program. It automatically generates a.
Strategic Thinking Assistant with Local LLM Integration Guided Responses Chatbot .
cd advancedaiagents/multiagentapps/agentteams/aifinanceagentteam 4. Run the team of AI Agents.
An AI-powered autonomous fraud investigation agent that cross-references childcare provider licensing records against physical building data to detect anomalies. The agent uses public data — Cook County property records, Illinois DCFS...
This AI-powered investment agent is built with Agno's AgentOS framework that analyzes stocks and generates detailed investment reports. By using GPT-5.2 with Yahoo Finance data, this app provides valuable insights to help you make...
This Streamlit app is an AI-powered movie production assistant that helps bring your movie ideas to life using Claude 3.5 Sonnet model. It automates the process of script writing and casting, allowing you to create compelling movie...
This Streamlit application demonstrates the use of RouteLLM, a system that intelligently routes queries between different language models based on the complexity of the task. It provides a chat interface where users can interact with AI...
An open-source autonomous agent for controlling Windows desktop applications and GUI workflows using computer-use models.
One model is a bottleneck. A team with one brain, twenty hands, and a board advisor is not.
git blame tells you who last changed a line. Commit Archaeologist reconstructs finds the introducing commit, orders later modifications, classifies commit.
Checks a working, staged, saved, or branch diff against a one-line intent. It flags unrelated paths, new dependencies, public API renames, config or CI.
Automatically optimize your agent skills using a multi-agent system built with Google ADK (Agent Development Kit) and Gemini. Upload a skill, let the agents generate test scenarios and evaluation criteria, then watch as three...
How this repo checks that its skills actually work — before they ship and on every change after. Layout: one folder per skill, evals/<skill-name>/.
61agentlifecyclecallbacks/ ├── agent.py # Agent with lifecycle callbacks ├── app.py # Streamlit web interface └── README.md # This file.
62llminteractioncallbacks/ ├── agent.py # Agent with LLM interaction callbacks ├── app.py # Streamlit web interface └── README.md # This file.
Demonstrates fundamental agent-to-agent task delegation using the OpenAI Agents SDK handoff system. cp ../env.example .env from agent import main.
Demonstrates fundamental session memory management with SQLiteSession for automatic conversation history. cp ../env.example .env from agent import inmemorysessionexample, persistentsessionexample.
Demonstrates manual conversation threading with toinputlist() and automatic management with Sessions. cp ../env.example .env from agent import manualconversationexample, sessionconversationexample.
Demonstrates advanced tracing patterns including custom traces, spans, and workflow organization for complex multi-agent systems. cp ../env.example .env.
Demonstrates the built-in automatic tracing system that captures all agent workflow events without any setup required. cp ../env.example .env.
4. The response will be a structured JSON with subject and body fields.
Demonstrates the three execution methods available in the OpenAI Agents SDK: sync, async, and streaming. cp ../env.example .env from agents import Runner.
Demonstrates advanced session memory operations including item manipulation, conversation corrections, and session management. cp ../env.example .env.
Demonstrates managing multiple concurrent sessions for different users, contexts, and conversation types. cp ../env.example .env from agent import multiusersessions, contextbasedsessions.
Demonstrates running multiple agents simultaneously using asyncio.gather() for improved performance and quality through diversity. cp ../env.example .env.
A basic personal assistant agent demonstrating the fundamental concepts of agent creation with the OpenAI Agents SDK. cp ../env.example .env from agents import Runner.
A complex structured output agent demonstrating advanced Pydantic schemas for product review analysis. cp ../env.example .env from agents import Runner.
An ADK agent is a programmable AI assistant that can: Think of it as creating a smart function that uses AI to handle complex tasks. The main building block for creating AI agents in ADK.
An OpenAI agent is a programmable AI assistant that can: Think of it as creating a smart function that uses AI to handle complex tasks.
Learn how to create agents that work with different AI models using OpenRouter. This example shows how ADK can use OpenAI and Anthropic models through separate agent implementations.
Traditional AI responses are unstructured text, making them difficult to process programmatically. Structured outputs solve this by: ┌─────────────────────────────────────────────────────────────┐.
When you call any Runner method, the SDK executes a sophisticated loop that handles the complete agent workflow: ┌─────────────────────────────────────────────────────────────┐.
InMemorySessionService stores session data in your computer's RAM (memory). This means: from google.adk.sessions import InMemorySessionService.
DatabaseSessionService stores session data in a SQLite database file. This means: from google.adk.sessions import DatabaseSessionService ┌─────────────────────────────────────────────────────────────┐.
Context management allows you to pass custom data structures to your agents that persist throughout the entire agent execution. Think of context as a shared state container that.
Guardrails are automated safety mechanisms that validate inputs and outputs to ensure AI agents operate within acceptable boundaries. Think of guardrails as safety checkpoints that.
Sessions provide automatic conversation memory that eliminates the need to manually handle .toinputlist() between turns. Think of sessions as a smart conversation database that.
Handoffs enable agent specialization and delegation where agents can transfer tasks to other agents with specific expertise. Think of handoffs as a smart routing system that.
Tracing provides comprehensive workflow monitoring that automatically captures every event during agent execution: ┌─────────────────────────────────────────────────────────────┐.
Topic → LoopAgent → [Refine Plan] → [Increment Iteration] → [Check Completion] ↑ │ └──────────────────────────── Repeat until stop ─────────┘.
Multi-agent orchestration enables coordinated AI workflows where multiple specialized agents work together to solve complex problems. Think of orchestration as a conductor leading an orchestra where.
Release Radar is an always-on dependency briefing agent built with Google ADK. It reads requirements.txt or package.json, checks mapped dependencies against GitHub releases, and reports only changes that need attention: breaking...
An advanced Chess game system where two AI agents play chess against each other using Autogen in a streamlit app. It is built with robust move validation and game state management.
An interactive Tic-Tac-Toe game where two AI agents powered by different language models compete against each other built on Agno Agent Framework and Streamlit as UI.
A minimal example demonstrating real-time AI streaming and conversation state management using the Motia framework. streaming-ai-chatbot/.
Welcome to The Magician IA Reader! This project presents a unique application combining the power of Artificial Intelligence with the mystique of tarot reading.
4. Get your GitHub Access Token.
4. Get your OpenAI API Key.
https://github.com/user-attachments/assets/9201d528-573f-43cc-9d31-571c362318a7 An agent that populates live charts, metrics, and real-time data into a Canvas dashboard instead of just streaming text. Built with CopilotKit, AG-UI, and...
This script demonstrates how to finetune the Llama 3.2 model using the Unsloth library, which makes the process easy and fast. You can run this example to finetune Llama 3.1 1B and 3B models for free in Google Colab.
Minimal example to finetune Google's Gemma 3 Instruct models with Unsloth using 4-bit loading + LoRA. Small, readable, and runnable on a CUDA GPU.
An AI data analysis Agent built using the Agno Agent framework and Openai's gpt-4o model. This agent helps users analyze their data - csv, excel files through natural language queries, powered by OpenAI's language models and DuckDB for...
A Streamlit application that acts as your personal data visualization expert, powered by LLMs. Simply upload your dataset and ask questions in natural language - the AI agent will analyze your data, generate appropriate visualizations,...
An AI agent with its own crypto wallet that pays for the data it needs — no API keys, no subscriptions, no signup. Ask a question in plain English.
A Medical Imaging Diagnosis Agent build on agno powered by Gemini 2.0 Flash that provides AI-assisted analysis of medical images of various scans. The agent acts as a medical imaging diagnosis expert to analyze various types of medical...
This is a Streamlit-based application that allows users to generate music using the ModelsLab API and OpenAI's GPT-4 model. Users can input a prompt describing the type of music they want to generate, and the application will generate a...
