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CodeRabbit325 resources
Template workflow for Agentic AI Services hackathon. Contains kodosumi node implementation: a hello-world crewAI crew and correct node pre-configured scaffold.
Extended Crew AI Tools for Agentic Workflows and Operations
This repository implements a Cybersecurity Threat agentic workflow that generates a report for cybersecurity professionals using the CrewAI framework and Streamlit for the user interface.
CLI and Flask‑based web application that transforms plain‑English prompts into production‑ready, multi‑agent AI workflows. It generates native YAML for IBM WatsonX Orchestrate, Python code for CrewAI, CrewAI Flow, LangGraph, or ReAct, and includes a built‑in FastAPI MCP server wrapper for seamless deployment to the MCP Gateway.
Automate complex business workflows with our Multi-AI-Agent Systems using crewAI. This framework leverages autonomous, role-specific AI agents to collaboratively perform multi-step tasks, enhancing efficiency and accuracy across various domains. Ideal for applications in resume tailoring, website design, research, customer support, and more.
Manage Notion tasks efficiently with CrewAI using an agent-driven workflow.
A go-to repository for building web search agents and multi-agent systems using LangChain, LangGraph, Phidata/Agno, Pydantic, and CrewAI. It includes a multi-agent email response agent, LLaMA OCR, and a multi-agent travel planner, enabling autonomous and intelligent workflows. 🚀
Agentic RAG pipeline where autonomous agents collaborate for document-grounded responses.Using CrewAI, the agents operate in a structured, multi-step workflow to ensure accurate and controlled outputs. 🚀
Developed with Panel, this project facilitates enhanced human-agent interactions within CrewAI applications, featuring a dynamic UI that supports real-time communication and workflow management between users and AI agents.
An AI-powered platform that uses an agentic workflow to automatically generate Project Requirement Documents (PRDs).
🚀 Build AI Agent Teams as Production-Ready APIs. Orchestrate CrewAI agents with FastAPI for enterprise-grade AI services. Leverage Groq's lightning-fast LLMs to deploy collaborative AI workflows at scale.
This repository contains a ready-to-use boilerplate for quickly setting up and working with crewai. It provides essential configurations and code examples to help you integrate and start using crewai efficiently in your projects. Ideal for AI developers looking to streamline their workflow with minimal setup.
DataRobot Agentic Workflow Templates
An autonomous agent to automate your code review workflow made using crewAI
Using ComfyUI to develop crews without any code. As easy as you are working with visual workflow system.
CrewAI-Agentic-Jira: Enhance your Jira workflows with intelligent agent-driven automation. Powered by the CrewAI framework, this project enables seamless integration of GenAI agents to Jira
A showcase of companies and platforms leveraging CrewAI to power their AI solutions and workflows.
Developed an Intelligent AutoML Assistant using PyCaret, TensorFlow, and CrewAI that analyzes tabular datasets, compares ML and DL models, and recommends the best algorithm. A multi-agent workflow handles analysis, training, evaluation, and decision-making, with a Streamlit UI for easy dataset upload and clear, explainable results.
Implementing a scalable content team using AI involves creating a framework that blends the strengths of AI technologies with the creative and supervisory capabilities of human team members. This strategy aims to enhance efficiency, creativity, and content output quality.
The Smart Marketing Assistant is an innovative project that leverages AI agents to automate tasks within an Instagram marketing workflow. This project aims to streamline and optimize various marketing activities, providing users with a powerful tool to enhance their social media strategies.
MCP Crew AI Server is a lightweight Python-based server designed to run, manage and create CrewAI workflows.
Run CrewAI agent workflows on local LLM models with Llamafile and Ollama
This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.
Automate complex business workflows with our Multi-AI-Agent Systems using crewAI. This framework leverages autonomous, role-specific AI agents to collaboratively perform multi-step tasks, enhancing efficiency and accuracy across various domains. Ideal for applications in resume tailoring, website design, research, customer support, and more.
A Node-Based Frontend for CrewAI: Revolutionizing AI Workflow Creation
A collection of notebooks, cookbooks, and recipes showcasing fun and effective ways to use CrewAI's agentic workflow implementations and tools.
Flock is a workflow-based low-code platform for rapidly building chatbots, RAG, and coordinating multi-agent teams, powered by LangGraph, Langchain, FastAPI, and NextJS.（Flock 是一个基于workflow工作流的低代码平台，用于快速构建聊天机器人、RAG、Agent和Muti-Agent应用，采用 LangGraph、Langchain、FastAPI 和 NextJS 构建。）
A collection of examples that show how to use CrewAI framework to automate workflows.
An AI research assistant that automates knowledge gathering by deploying multiple analyst personas. These agents conduct interviews, search for information, and collaborate to produce comprehensive reports with proper citations on any topic. Built with LangGraph for orchestrating the multi-agent workflow.
This repository offers modular projects on agent-driven reasoning, iterative content refinement, and retrieval-augmented generation (RAG). It showcases progressive workflows for building intelligent, self-improving AI assistants, from simple reasoning agents to adaptive, self-correcting systems.
This repository serves as a personal study archive, practical notebook, and portfolio of implementations, covering the foundations and advanced topics of building agentic workflows with LangGraph.
This project demonstrates how to build a simple LLM-powered chatbot using **LangGraph**, a library that enables building stateful, agentic workflows on top of Language Models. It integrates the power of Large Language Models (LLMs) with a graph-based workflow design to allow controlled and modular interactions.
A beginner-friendly LangGraph demo showcasing multi-node workflows, branching (math vs non-math queries), and OpenAI integration. Includes input/output logging, preprocessing, postprocessing, and conditional edges for dynamic flow control.
This project is a simple research and podcast generation workflow that uses LangGraph with the unique capabilities of Google's Gemini 2.5 model family
Welcome to the LangGraph Project Series — a curated collection of beginner-friendly projects designed to help you learn and build with LangGraph, a powerful framework for building agentic workflows using natural language and AI.
An Agentic Workflow built with LangGraph and LangChain that implements AI Orchestration via Conditional State Graphs, using Semantic Routing and Persistent Memory to deterministically triage user queries
Learn to build real-world AI agents, multi-agent workflows, and autonomous apps with LangGraph and LangChain
Getting started with workflows and agents using lang-graph
This repository contains an interactive Jupyter Notebook demonstrating how to build **Agentic RAG (Retrieval-Augmented Generation)** workflows using **LangGraph**, **LangChain**, and **LLM tools**. It integrates memory, graph-based control flow, TypedDict state management, and tool usage.
Use for learning LangGraph, LangGraph is a LangChain library designed to create agent and LLM workflows based on graphs, rather than linear chains.
Antigravity workflow template from A-LangGraph-based-conditional-workflow-demo-with-visual-output
Features a stateful, multi-segment LangGraph architecture that decouples SQL generation, validation, and execution into autonomous, self-correcting workflows.
Utilizing LangGraph workflows to develop a WhatsApp bot tailored for a dental clinic.
A collection of workflow automation examples using LangGraph, demonstrating node-based execution, data flow, and visualization.
An end-to-end AI-powered B2B lead generation workflow using **LangGraph**, automating prospect discovery, enrichment, scoring, outreach, response tracking, and feedback improvement.
Antigravity workflow template from LangGraph-LangChain-Agentic-Workflows
A medical multiagent system using LangGraph and RAG
POCs on Pydantic and LangGraph for agentic workflows
Antigravity workflow template from Agentic-workflow-using-LangGraph
Antigravity workflow template from LangGraph-Agentic-Workflow