LLM-Blender-Agent enables developers to build modular, multi-agent AI systems by wrapping LLMs into collaborative agents. Each agent can access tools like Python execution, web scraping, SQL databases, and external APIs. The framework handles conversation memory, step-by-step reasoning, and tool orchestration, allowing tasks such as report generation, data analysis, automated research, and workflow automation. Built on top of LangChain, it’s lightweight, extensible, and works with GPT-3.5, GPT-4, and other LLMs.

BAML Agents is designed for developers and AI practitioners seeking a modular, extensible platform to build autonomous agents. It provides a plugin-based architecture for seamless integration of custom tools, a memory subsystem for maintaining conversational context, and built-in support for multi-step reasoning workflows. With BAML Agents, users can quickly configure agent behaviors, connect to external APIs, and orchestrate complex tasks without reinventing common agent patterns. Its lightweight design and clear abstractions make it ideal for prototyping, research, and production-grade deployments in various automation scenarios.