Cyrano is an open-source Python framework and CLI for creating AI agents that orchestrate large language models and external tools through natural language prompts. Users can define custom tools (functions), configure memory and token limits, and handle callbacks. Cyrano handles parsing JSON responses from LLMs and executes specified tools in sequence. It emphasizes simplicity, modularity, and zero external dependencies, enabling developers to prototype chatbots, build automated workflows, and integrate AI capabilities into applications quickly.

EasyAgent provides a comprehensive framework for constructing autonomous AI agents in Python. It offers pluggable LLM backends such as OpenAI, Azure, and local models, customizable planning and reasoning modules, API tool integration, and persistent memory storage. Developers can define agent behaviors through simple YAML or code-based configurations, leverage built-in function calling for external data access, and orchestrate multiple agents for complex workflows. EasyAgent also includes features like logging, monitoring, error handling, and extension points for tailored implementations. Its modular architecture accelerates prototyping and deployment of specialized agents in domains like customer support, data analysis, automation, and research.

gpt-func-calling is a developer toolkit that showcases OpenAI’s function calling feature, allowing chat-based AI to interact with external services. By defining function signatures in JSON, developers guide GPT-3.5/4 to recognize when to call a function, automatically format arguments, and handle the response in a structured manner. This streamlines integration with weather APIs, database queries, or custom business logic, ensuring consistent, reliable outputs without manual parsing.

LLM Functions provides a simple framework to bridge large language model responses with real code execution. You define functions via JSON schemas, register them with the library, and the LLM will return structured function calls when appropriate. The library parses those responses, validates the parameters, and invokes the correct handler. It supports synchronous and asynchronous callbacks, custom error handling, and plugin extensions, making it ideal for applications that require dynamic data lookup, external API calls, or complex business logic within AI-driven conversations.

With AI Agents is a code-first framework in TypeScript that helps you define and orchestrate multiple AI Agents, each with distinct roles such as planner, executor, and memory. It provides built-in memory management to persist context, a function-calling subsystem to integrate external APIs, and a CLI interface for interactive sessions. By composing agents in pipelines or hierarchies, you can automate complex tasks—like data analysis pipelines or customer support flows—while ensuring modularity, scalability, and easy customization.