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A Streamlit app that blends agent teamwork with agent-enabled routing and fallback, built entirely on AG2..
Learn how to build a governance layer that enforces deterministic policies on AI agents, preventing dangerous actions before they execute..
The AI Competitor Intelligence Agent Team is a powerful competitor analysis tool powered by Firecrawl and Agno's AI Agent framework. This app helps businesses analyze their competitors by extracting structured data from competitor...
A powerful business consultant powered by Google's Agent Development Kit that provides comprehensive market analysis, strategic planning, and actionable business recommendations with real-time web research.
An advanced AI research agent built using the Agno Agent framework, Together AI's Qwen model, and Composio tools. This agent helps users conduct comprehensive research on any topic by generating research questions, finding answers...
An intelligent, fully automated B2B outreach system that discovers companies, finds decision makers, researches company intelligence, and generates personalized cold emails using AI agents.
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.
A Streamlit application that simulates a full-service legal team using multiple AI agents to analyze legal documents and provide comprehensive legal insights. Each agent represents a different legal specialist role, from research and...
The AI Mental Wellbeing Agent Team is a supportive mental health assessment and guidance system powered by AG2(formerly AutoGen)'s AI Agent framework. This app provides personalized mental health support through the coordination of...
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.
A streamlined intelligence hub for Go-To-Market (GTM) & Product-Marketing teams. Built with Streamlit + Agno (GPT-4o) + Firecrawl, the app turns scattered public-web data into concise, actionable launch insights.
The AI Real Estate Agent Team is a sophisticated property search and analysis platform powered by specialized AI agents with Firecrawl's extract endpoint. This application provides comprehensive real estate insights, market analysis,...
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 streamlined multi-phase research agent built with Google's Interactions API that demonstrates stateful conversations, model mixing, background execution, and automatic infographic generation.
The AI SEO Audit Team is an autonomous, multi-agent workflow built with Google ADK. It takes a webpage URL, crawls the live page, researches real-time SERP competition, and produces a polished, prioritized SEO optimization report.
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...
AI Speech Trainer is an AI-powered multi-agent, multimodal public speaking coach that listens to how you speak, watches how you express, and evaluates what you say - helping you become a confident public speaker.
An advanced web extraction and analysis tool built using Firecrawl's FIRE-1 agent + extract v1 endpoint and the Agno Agent framework to get details of a new startup instantly! This application automatically extracts structured data from...
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.
The AQI Analysis Agent is a powerful air quality monitoring and health recommendation tool powered by Firecrawl and Agno's AI Agent framework. This app helps users make informed decisions about outdoor activities by analyzing real-time...
An AI-powered multi-agent codebase migration assistant built with LangGraph and Streamlit that plans file-by-file refactoring tasks, performs human-in-the-loop (HITL) risk review, fans out parallel refactoring workers, and aggregates...
A powerful research assistant that leverages OpenAI's Agents SDK and Firecrawl's deep research capabilities to perform comprehensive web research on any topic and any question.
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 Streamlit application that provides comprehensive design analysis using a team of specialized AI agents powered by Google's Gemini model. This application leverages multiple specialized AI agents to provide comprehensive analysis of...
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.
This app allows you to upload a Resume and a Job Description, then uses an LLM to: A great tool for job seekers to optimize resumes for each application.
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 .
TripCraft AI uses a sophisticated multi-agent system powered by Agno to create personalized travel experiences. This document explains the different agents and their roles in the system.
Build a multi-agent research pipeline where every AI agent must pass a trust verification before participating, and every action is recorded in a hash-chained audit trail that is independently verifiable.
This Streamlit app implements an AI-powered customer support agent for synthetic data generated using GPT-4o. The agent uses OpenAI's GPT-4o model and maintains a memory of past interactions using the Mem0 library with Qdrant as the...
An end-to-end, multi-agent Streamlit app that automates B2B outreach using GPT-5 and Exa. It discovers relevant companies, finds the right contacts (Founder's Office, GTM/Sales leadership, Partnerships/BD, Product Marketing), researches...
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 journalist agent that generates high-quality articles using OpenAI GPT-4o. It automates the process of researching, writing, and editing articles, allowing you to create compelling content on any...
This Streamlit application leverages multiple AI agents to create comprehensive meeting preparation materials. It uses OpenAI's GPT-4, Anthropic's Claude, and the Serper API for web searches to generate context analysis, industry...
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 app is an AI-powered personal finance planner that generates personalized financial plans using OpenAI GPT-4o. It automates the process of researching, planning, and creating tailored budgets, investment strategies, and...
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...
A open-source template for building local_ai_legal_agent_team within the Advanced AI Agents category, featuring modular AI integration and clean tool routing.
cd awesome-llm-apps/advancedtoolsframeworks/localchatgptclone 4. Expose the Llama-3 model as an OpenAI API by starting the server in LM Studio.
An open-source autonomous agent for controlling Windows desktop applications and GUI workflows using computer-use models.
This Streamlit app empowers you to research top stories and users on HackerNews using a team of AI assistants with GPT-4o. cd advancedaiagents/multiagentapps/multiagentresearcher.
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.
Dependency Doctor inspects one dependency manifest for surface-level, direct-manifest footguns. It catches unpinned versions, standard-library.
Every developer has the folder. Twenty-something dead projects, each abandoned for reasons nobody wrote down.
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>/.
Ramble at your agent by voice. Audit what it heard before it acts.
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 advanced handoff configuration including callbacks, structured inputs, and custom tool naming. cp ../env.example .env from agent import main.
Demonstrates advanced orchestration patterns where agents are used as tools by other agents. cp ../env.example .env from agents import Runner.
Demonstrates advanced orchestration patterns where specialized agents are used as function tools by orchestrator agents. cp ../env.example .env.
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.
Google ADK provides powerful pre-built tools that are optimized for performance and reliability. These tools integrate seamlessly with Gemini models and provide essential capabilities like web search and code execution.
Demonstrates using OpenAI Agents SDK built-in tools like WebSearchTool and CodeInterpreterTool. cp ../env.example .env from agents import Runner.
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.
cd 31customersupportticketagent 4. The response will be a structured JSON with all ticket details.
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.
This example demonstrates how to connect an ADK agent to a filesystem MCP server using the MCPToolset. The agent can perform file operations like reading, writing, and listing files through the Model Context Protocol.
Welcome to the Firecrawl MCP Agent! This powerful agent demonstrates how to integrate Firecrawl's advanced web scraping capabilities with Google ADK through the Model Context Protocol (MCP).
def calculatecompoundinterest(principal: float, rate: float, years: int) -> dict: Calculate compound interest for an investment. Use this function when users ask about investment growth.
Demonstrates custom function tools creation using the @functiontool decorator. cp ../env.example .env from agents import Runner from agent import rootagent.
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.
A sophisticated multi-agent system built with Google ADK that uses Firecrawl MCP tools for web scraping and coordinates between specialized research and summary agents.
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.
A basic realtime voice agent example using OpenAI's Realtime API. This demonstrates the core components for ultra-low latency voice conversations with minimal setup.
A complete voice interaction example using the OpenAI Agents SDK with pre-recorded audio input. This demonstrates the basic voice pipeline workflow with speech-to-text, agent processing, and text-to-speech capabilities.
A real-time voice interaction example using the OpenAI Agents SDK with continuous audio streaming. This demonstrates advanced voice pipeline capabilities with live speech detection, real-time processing, and turn-based conversation...
A structured output agent demonstrating Pydantic schema-based responses for customer support ticket creation. cp ../env.example .env from agents import Runner.
Third-party tools allow you to integrate existing tool ecosystems from frameworks like LangChain, CrewAI, and others. This dramatically expands your agent's capabilities by leveraging battle-tested tools from the broader AI community.
Voice agents combine the power of AI language models with speech processing to create natural conversational interfaces. Think of voice agents as AI assistants you can talk to naturally that.
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: ┌─────────────────────────────────────────────────────────────┐.
Tools are functions that your agent can call to perform specific tasks. Think of them as the agent's "hands" - they allow the agent to: ┌─────────────────────────────────────────────────────────────┐.
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.
Tool execution callbacks allow you to monitor when agents use tools, track their execution lifecycle, and analyze the results. This provides visibility into how agents interact with external systems and APIs.
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.
Plugins in Google ADK are custom code modules that can be executed at various stages of an agent workflow lifecycle using callback hooks. Unlike regular callbacks that are configured on individual agents or tools, plugins are registered...
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.
A coordinator LlmAgent orchestrates three specialized agents in a sequential workflow: Research → Summarize → Critique. Each agent contributes to building a comprehensive research report.
Tracing provides comprehensive workflow monitoring that automatically captures every event during agent execution: ┌─────────────────────────────────────────────────────────────┐.
Business Topic → SequentialAgent → 4 Sub-agents (Sequential Execution) [Market Research + Web Search] → [SWOT Analysis] → [Strategy] → [Implementation].
Topic → LoopAgent → [Refine Plan] → [Increment Iteration] → [Check Completion] ↑ │ └──────────────────────────── Repeat until stop ─────────┘.
According to the ADK docs, Parallel Agents execute their sub-agents concurrently. Each child runs on its own invocation branch but shares the same session.state.
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.
AgentScout is an always-on Hacker News briefing agent built with Google ADK. It scans Hacker News for high-signal stories about AI agents, MCP, coding agents, workflow automation, and LLM apps, then turns a featured links into a concise...
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...
This Project demonstrates R1's code capabilities with a PyGame code generator and visualizer with browser use. The system uses DeepSeek for reasoning, OpenAI for code extraction, and browser automation agents to visualize the code on...
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.
4. Run the Streamlit App streamlit run chatpdf.py https://github.com/Shubhamsaboo/awesome-llm-apps/assets/31396011/12bdfc11-c877-4fc7-9e70-63f21d2eb977.
This Streamlit app enables you to engage in interactive conversations with arXiv, a vast repository of scholarly articles, using GPT-4o. With this RAG application, you can easily access and explore the wealth of knowledge contained...
Streamlit app that allows you to chat with a Substack newsletter using OpenAI's API and the Embedchain library. This app leverages GPT-4 to provide accurate answers to questions based on the content of the specified Substack newsletter.
LLM app with RAG to chat with YouTube Videos with OpenAI's gpt-4o, mem0/embedchain as memory and the youtube-transcript-api. The app uses Retrieval Augmented Generation (RAG) to provide accurate answers to questions based on the content...
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...
A deep research assistant that plans, searches the web, writes to a virtual filesystem, and renders each tool call as a live card in a workspace pane. Built with CopilotKit, Deep Agents, AG-UI, and Tavily on top of Next.js + LangGraph...
A multi-agent financial coach that analyzes your budget, plans your savings, and builds debt-payoff strategies — rendered as interactive UI cards in a separate report tab. Built with CopilotKit, AG-UI, and Google's ADK on top of Next.js.
Drop files — documents or source code — into a chatbot. The agent extracts entities, concepts, and relationships (or modules, classes, functions, and dependencies), then renders an interactive knowledge graph you can explore.
https://github.com/user-attachments/assets/b14bebd6-527a-48bd-94f5-d27fea8808aa Gen UI concept — schema-driven component composition. The full shadcn component schema is passed as agent context, so the model knows exactly which...
Interactive 3D scene renderer using Three.js. Demonstrates streaming code preview and full MCP App integration.
A chat-driven kanban board where you and the agent work the same task list. Built with CopilotKit, AG-UI, and LangGraph on top of Next.js.
https://github.com/user-attachments/assets/48eeab8d-7845-4d06-83ef-d518a807da03 Book flights, reserve hotels, manage portfolios, and run a kanban board — all inside the chat. Built with CopilotKit, AG-UI, and MCP Apps, showcasing the...
This is an MCP server project bootstrapped with create-mcp-use-app. First, run the development server.
A open-source template for building name within the Generative UI & Frontends category, featuring modular AI integration and clean tool routing.
This Streamlit app implements a multi-agent career coaching assistant built with Google's Agent Development Kit (ADK). A career orchestrator agent delegates each question to the right specialist sub-agent (resume, interview practice,...
This Streamlit app implements an AI-powered research assistant that helps users search for academic papers on arXiv while maintaining a memory of user interests and past interactions. It utilizes OpenAI's GPT-4o-mini model for...
This Streamlit app implements an AI-powered travel assistant that remembers user preferences and past interactions. It utilizes OpenAI's GPT-4o for generating responses and Mem0 with Qdrant for maintaining conversation history.
This Streamlit app is an AI-powered chatbot that uses OpenAI's GPT-4o model with a persistent memory feature. It allows users to have conversations with the AI while maintaining context across multiple interactions.
This Streamlit application implements a fully local ChatGPT-like experience using Llama 3.1, featuring personalized memory storage for each user. All components, including the language model, embeddings, and vector store, run locally...
This Streamlit application demonstrates a multi-LLM system with a shared memory layer, allowing users to interact with different language models while maintaining conversation history and context across sessions.
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.
Reduce LLM API costs by 50-90% through intelligent context compression. Tool outputs are 70-95% redundant boilerplate—Headroom compresses that away while preserving accuracy.
Reduce LLM API costs by 30-60% using TOON (Token-Oriented Object Notation) format for structured data serialization. This app demonstrates how to use Toonify to dramatically reduce token usage when passing structured data to Large...
https://github.com/user-attachments/assets/a01e09fa-131b-479a-8df3-2d1a61fd80f3 A Streamlit application that allows you to browse and interact with websites using natural language commands through the Model Context Protocol (MCP) and...
A Streamlit application that allows you to explore and analyze GitHub repositories using natural language queries through the Model Context Protocol (MCP).
A Streamlit app that demonstrates the multi-agent + MCP pattern: specialized AI agents that each connect to different MCP servers to handle domain-specific tasks.
The Multi-MCP Intelligent Assistant is a powerful productivity tool that integrates multiple Model Context Protocol (MCP) servers to provide seamless access to GitHub, Perplexity, Calendar, and Gmail services through natural language...
A terminal-based Notion Agent for interacting with your Notion pages using natural language through the Notion MCP (Model Context Protocol) server.
Learn how to connect a plain OpenAI function-calling loop to a hosted Streamable HTTP MCP server—without an agent framework. The script keeps the complete bridge visible.
A sophisticated Streamlit-based AI travel planning application that creates extremely detailed, personalized travel itineraries using multiple MCP servers and Google Maps integration. The app uses Airbnb MCP for real accommodation data...
An agentic RAG application built with the Agno framework, featuring GPT-5 and LanceDB for efficient knowledge retrieval and question answering.
A RAG Agentic system built with the new Gemini 2.0 Flash Thinking model and gemini-exp-1206, Qdrant for vector storage, and Agno (phidata prev) for agent orchestration. This application features intelligent query rewriting, document...
AI Blog Search is an Agentic RAG application designed to enhance information retrieval from AI-related blog posts. This system leverages LangChain, LangGraph, and Google's Gemini model to fetch, process, and analyze blog content,...
You'll need the following API keys: streamlit run ragreasoningagent.py 4. Configure API Keys:.
This Streamlit application implements an Autonomous Retrieval-Augmented Generation (RAG) system using OpenAI's GPT-4o model and PgVector database. It allows users to upload PDF documents, add them to a knowledge base, and query the AI...
A Streamlit app that integrates Contextual AI's managed RAG platform. Create a datastore, ingest documents, spin up an agent, and chat grounded on your data.
A sophisticated Retrieval-Augmented Generation (RAG) system that implements a corrective multi-stage workflow using LangGraph. This system combines document retrieval, relevance grading, query transformation, and web search to provide...
A powerful reasoning agent that combines local Deepseek models with RAG capabilities. Built using Deepseek (via Ollama), Snowflake for embeddings, Qdrant for vector storage, and Agno for agent orchestration, this application offers both...
A Streamlit application demonstrating how Knowledge Graph-based Retrieval-Augmented Generation (RAG) provides multi-hop reasoning with fully verifiable source attribution.
A powerful document Q&A application that leverages Hybrid Search (RAG) and local LLMs for comprehensive answers. Built with RAGLite for robust document processing and retrieval, and Streamlit for an intuitive chat interface, this system...
An open-source agentic RAG system for mathematical problem solving and symbolic reasoning using LLMs and calculation tools.
This is a multimodal RAG app built with Gemini Embedding 2 and Google ADK. Add text, URLs, PDFs, images, audio, or video; ask a question; and get a grounded answer with clear citations.
PharmaQuery is an advanced Pharmaceutical Insight Retrieval System designed to help users gain meaningful insights from research papers and documents in the pharmaceutical domain.
This RAG Application demonstrates how to build a powerful Retrieval-Augmented Generation (RAG) system using locally running Qwen 3 and Gemma 3 models via Ollama. It combines document processing, vector search, and web search...
A RAG Agentic system built with Cohere's new model Command-r7b-12-2024, Qdrant for vector storage, Langchain for RAG and LangGraph for orchestration. This application allows users to upload documents, ask questions about them, and get...
A Streamlit application that demonstrates an advanced implementation of RAG Agent with intelligent query routing. The system combines multiple specialized databases with smart fallback mechanisms to ensure reliable and accurate...
A powerful document Q&A application that leverages Hybrid Search (RAG) and Claude's advanced language capabilities to provide comprehensive answers. Built with RAGLite for robust document processing and retrieval, and Streamlit for an...
A small, framework-agnostic RAG failure diagnostics clinic. You paste a real bug description from your LLM + RAG pipeline.
This Streamlit app answers questions from uploaded PDFs or a documentation URL. Every response is a validated Answer object with exact source quotes, chunk IDs.
A powerful visual Retrieval-Augmented Generation (RAG) system that utilizes Cohere's modern Embed-4 model for multimodal embedding and Google's efficient Gemini 2.5 Flash model for answering questions about images and PDF pages.
This Streamlit app demonstrates an agentic Retrieval-Augmented Generation (RAG) Agent using Google's EmbeddingGemma for embeddings and Llama 3.2 as the language model, all running locally via Ollama.
Streamlit app that allows you to chat with any webpage using local Llama-3.1 and Retrieval Augmented Generation (RAG). This app runs entirely on your computer, making it 100% free and without the need for an internet connection.
This application implements a Retrieval-Augmented Generation (RAG) system using Llama 3.2 via Ollama, with Qdrant as the vector database. Built with Agno v2.0.
4. Run the Streamlit app streamlit run ragapp.py.
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,...
The AI Meme Generator Agent is a powerful browser automation tool that creates memes using AI agents. This app combines multi-LLM capabilities with automated browser interactions to generate memes based on text prompts through direct...
This is an AI-powered application designed to help users emotionally recover from breakups by providing support, guidance, and emotional outlet messages from a team of specialized AI agents. The app is built using Streamlit and Agno,...
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 Streamlit application that helps users estimate the amount of term life insurance they may need and surfaces currently available policy options. The app is powered by the Agno agent framework, uses OpenAI GPT-5 as the LLM, the E2B...
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...
A multi-agent research application built with OpenAI's Agents SDK and Streamlit. This application enables users to conduct comprehensive research on any topic by leveraging multiple specialized AI agents.
AI-powered web scraping using ScrapeGraphAI - extract structured data from websites using natural language prompts. This agent runs locally with the open-source scrapegraphai library.
This is a Streamlit-based application that allows users to convert any blog post into a podcast. The app uses OpenAI's GPT-4 model for summarization, Firecrawl for scraping blog content, and ElevenLabs API for generating audio.
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...
The AI Reasoning Agent leverages advanced AI models to provide insightful reasoning and decision-making capabilities. This agent is designed to assist users in various analytical tasks by processing information and generating structured...
The AI Startup Trend Analysis Agent is tool for budding entrepreneurs that generates actionable insights by identifying nascent trends, potential market gaps, and growth opportunities in specific sectors. Entrepreneurs can use these...
A Streamlit application that combines video analysis and web search capabilities using Google's Gemini 2.5 model. This agent can analyze uploaded videos and answer questions by combining visual understanding with web-search.
This application creates a financial analysis agent powered by xAI's Grok model, combining real-time stock data with web search capabilities. It provides structured financial insights through an interactive playground interface.
An OpenAI SDK powered customer support agent application that delivers voice-powered responses to questions about your knowledge base using OpenAI's GPT-4o and TTS capabilities. The system crawls through documentation websites with...
A voice-first insurance claim intake app that lets a claimant talk naturally while the agent builds a structured claim packet in real time. The UI shows the live conversation, extracted claim facts, operator guidance, missing items, and...
A conversational voice agent system that generates immersive, self-guided audio tours based on the user’s location, areas of interest, and tour duration. Built on a multi-agent architecture using OpenAI Agents SDK, real-time information...
This script demonstrates how to build a voice-enabled Retrieval-Augmented Generation (RAG) system using OpenAI's SDK and Streamlit. The application allows users to upload PDF documents, ask questions, and receive both text and voice...
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