Comprehensive stateful conversations Tools for Every Need

Get access to stateful conversations solutions that address multiple requirements. One-stop resources for streamlined workflows.

stateful conversations

  • A JavaScript library that lets you define and run AI agents with custom tools, memory and OpenAI models.
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    What is OpenAI Agents JS?
    OpenAI Agents JS enables developers to construct AI agents by combining OpenAI models with custom toolsets. Agents can process user input, call external APIs, manage stateful conversations with memory modules, and perform tasks like web scraping, code generation, or data lookup. The framework offers a plugin system for registering tools, a standardized Agent class for orchestration, built-in memory abstractions, and support for both chat-based and completion-based models. Features include error recovery, multi-tool orchestration, and customizable middleware. By defining tools and feeding them into the agent instance, you can deploy sophisticated AI-driven workflows in Node.js or browser contexts with minimal boilerplate. Additionally, it simplifies API key management and supports asynchronous operations, allowing agents to execute long-running tasks or integrate with databases and messaging queues effortlessly.
    OpenAI Agents JS Core Features
    • Agent orchestration
    • Tool registration
    • Conversational memory
    • OpenAI chat and completion integration
    • Error handling and recovery
    • Customizable middleware
    OpenAI Agents JS Pro & Cons

    The Cons

    Requires OpenAI API key and associated costs
    Limited to JavaScript/TypeScript environment
    No standalone pricing or hosted service information available
    Potentially requires familiarity with LLM concepts

    The Pros

    Lightweight and easy to learn with minimal primitives
    Enables building complex agentic interactions
    Built-in tracing and debugging tools
    Supports agent delegation via handoffs
    TypeScript-first design for seamless integration with existing codebases
    Open source with community access
  • A minimal Python framework to create autonomous GPT-powered AI agents with tool integration and memory.
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    What is TinyAgent?
    TinyAgent provides a lightweight agent framework for orchestrating complex tasks with OpenAI GPT models. Developers install via pip, configure an API key, define tools or plugins, and leverage in-memory context to maintain multi-step conversations. TinyAgent supports chaining tasks, integrating external APIs, and persisting user or system memories. Its simple Pythonic API lets you prototype autonomous data analysis workflows, customer service chatbots, code generation assistants, or any use case requiring an intelligent, stateful agent. The library remains fully open-source, extensible, and platform-agnostic.
  • Goat is a Go SDK for building modular AI agents with integrated LLMs, tools management, memory, and publisher components.
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    What is Goat?
    Goat SDK is designed to simplify the creation and orchestration of AI agents in Go. It provides pluggable LLM integrations (OpenAI, Anthropic, Azure, local models), a tool registry for custom actions, and memory stores for stateful conversations. Developers can define chains, representer strategies, and publishers to output interactions via CLI, WebSocket, REST endpoints, or a built-in Web UI. Goat supports streaming responses, customizable logging, and easy error handling. By combining these components, you can develop chatbots, automation workflows, and decision-support systems in Go with minimal boilerplate, while maintaining flexibility to swap or extend providers and tools as needed.
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