AgentIn is a Python-based AI agent framework designed to accelerate the development of conversational and task-driven agents. It offers built-in memory modules to persist context, dynamic tool integration to call external APIs or local functions, and a flexible prompt templating system for customized interactions. Multi-agent orchestration enables parallel workflows, while logging and caching improve reliability and auditability. Easily configurable via YAML or Python code, AgentIn supports major LLM providers and can be extended with custom plugins for domain-specific capabilities.

AiChat offers a versatile toolkit for creating intelligent chat agents by providing role-based prompt management, memory handling, and streaming response capabilities. Users can set up multiple conversational roles, such as system, assistant, and user, to shape dialogue context and behavior. The framework supports plugin integrations for external APIs, data retrieval, or custom logic, enabling seamless extension of functionalities. AiChat's modular design allows easy swapping of language models and configuration of feedback loops to refine responses. Built-in memory features provide context persistence across sessions, while streaming API support delivers low-latency interactions. Developers benefit from clear documentation and sample projects to accelerate deployment of chatbots across web, desktop, or server environments.

bedrock-agent is a versatile AI agent framework that integrates with AWS Bedrock’s suite of large language models to orchestrate complex, task-driven workflows. It offers a plugin architecture for registering custom tools, memory modules for context persistence, and a chain-of-thought mechanism for improved reasoning. Through a simple Python API and command-line interface, it enables developers to define agents that can call external services, process documents, generate code, or interact with users via chat. Agents can be configured to automatically select relevant tools based on user prompts and maintain conversational state across sessions. This framework is open-source, extensible, and optimized for rapid prototyping and deployment of AI-powered assistants on local or AWS cloud environments.