e2e-chainlit-chatbot is a sample project demonstrating the complete development lifecycle of a conversational AI agent using Chainlit. The repository includes end-to-end code for launching a local web server that hosts an interactive chat interface, integrating with large language models for responses, and managing conversation context across messages. It features customizable prompt templates, multi-agent workflows, and real-time streaming of responses. Developers can configure API keys, adjust model parameters, and extend the system with custom logic or integrations. With minimal dependencies and clear documentation, this project accelerates experimentation with AI-driven chatbots and provides a solid foundation for production-grade conversational assistants. It also includes examples for customizing front-end components, logging, and error handling. Designed for seamless integration with cloud platforms, it supports both prototype and production use cases.

Notte is a developer-centric Python framework designed for orchestrating AI agents powered by large language models. It provides built-in memory modules to store and retrieve conversational context, flexible tool integration for external APIs or custom functions, and a planning engine that sequences tasks. With Notte, you can rapidly prototype conversational assistants, data analysis bots, or automated workflows, while benefiting from open-source extensibility and cross-platform support.

rag-services is an extensible platform that breaks down RAG pipelines into discrete microservices. It offers a document store service, a vector index service, an embedder service, multiple LLM inference services, and an orchestrator service to coordinate workflows. Each component exposes REST APIs, allowing you to mix and match databases and model providers. With Docker and Docker Compose support, you can deploy locally or in Kubernetes clusters. The framework enables scalable, fault-tolerant RAG solutions for chatbots, knowledge bases, and automated document Q&A.

SonAgent is an extensible open-source framework designed for building, organizing, and running AI agents in Python. It provides core modules for memory storage, tool wrappers, planning logic, and asynchronous event handling. Developers can register custom tools, integrate language models, manage long-term agent memory, and orchestrate multiple agents to collaborate on complex tasks. SonAgent’s modular design accelerates the development of conversational bots, workflow automations, and distributed agent systems.

Agentle provides a structured framework for developers to build custom AI agents with minimal boilerplate. It supports defining agent workflows as sequences of tasks, seamless integration with external APIs and tools, conversational memory management for context preservation, and built-in logging for auditability. The library also offers plugin hooks to extend functionality, multi-agent coordination for complex pipelines, and a unified interface to run agents locally or deploy via HTTP APIs.

Crayon empowers developers to build autonomous AI agents in JavaScript/Node.js that can call external APIs, maintain conversation history, plan multi-step tasks, and handle asynchronous processes. At its core, Crayon implements a planning-execution loop that breaks down high-level goals into discrete actions, integrates with custom toolkits, and utilizes memory modules to store and recall information across sessions. The framework supports multiple memory backends, plugin-based tool integration, and comprehensive logging for debugging. Developers can configure agent behavior through prompts and YAML-based pipelines, enabling complex workflows like data scraping, report generation, and interactive chatbots. Crayon's architecture promotes extensibility, allowing teams to integrate domain-specific tools and tailor agents to unique business requirements.