Open Agent Leaderboard offers a complete evaluation pipeline for open-source AI agents. It includes a curated task suite covering reasoning, planning, question answering, and tool usage, an automated harness to run agents in isolated environments, and scripts to collect performance metrics such as success rate, runtime, and resource consumption. Results are aggregated and displayed on a web-based leaderboard with filters, charts, and historical comparisons. The framework supports Docker for reproducible setups, integration templates for popular agent architectures, and extensible configurations to add new tasks or metrics easily.

Agent Forge streamlines the entire lifecycle of AI agent development by offering CLI scaffold commands to generate boilerplate code, conversation templates, and configuration settings. Developers can define agent roles, attach LLM providers, and integrate external tools such as vector databases, REST APIs, and custom plugins using YAML or JSON descriptors. The framework enables local execution, interactive testing, and packaging agents as Docker images or serverless functions for easy deployment. Built-in logging, environment profiles, and VCS hooks simplify debugging, collaboration, and CI/CD pipelines. This flexible architecture supports creating chatbots, autonomous research assistants, customer support bots, and automated data processing workflows with minimal setup.

FastAPI LangGraph Agent Template offers a comprehensive foundation for developing LLM-driven agents within a FastAPI application. It includes predefined LangGraph nodes for common tasks like text completion, embedding, and vector similarity search while allowing developers to create custom nodes and pipelines. The template manages conversation history via memory modules that persist context across sessions and supports environment-based configuration for different deployment stages. Built-in Docker files and CI/CD-friendly structure ensure seamless containerization and deployment. Logging and error-handling middleware enhance observability, while the modular codebase simplifies extending functionality. By combining FastAPI's high-performance web framework with LangGraph's orchestration capabilities, this template streamlines the agent development lifecycle from prototyping to production.

Defang is an AI-enabled cloud deployment tool that allows developers to easily and securely deploy applications to their cloud of choice using a single command. It transforms any Docker Compose-compatible project into a live deployment instantly, provides AI-guided debugging, and supports any programming language or framework. Whether you use AWS, GCP, or DigitalOcean, Defang ensures your deployments are secure, scalable, and cost-efficient. The platform supports various environments like development, staging, and production, making it ideal for projects of any scale.