A guide to building long-term compounding knowledge infrastructure. See details on GitHub .

Qwen-Agent

Qwen-Agent is an open-source agent framework that provides tool calling, RAG, code interpreter and deployment examples to quickly build intelligent assistants and applications.

Qwen-Agent is an open-source framework for building LLM applications. It supports instruction following, tool calling, planning and memory, and ships with example apps such as Browser Assistant and Code Interpreter for rapid prototyping of interactive assistants and RAG-enabled services.

Key features

  • Modular agent components: class-based LLMs, tools and agent abstractions for extensibility.
  • Integrated capabilities: built-in RAG, function/tool calling, code interpreter and Gradio GUI examples.
  • Deployment flexibility: compatible with various model services (vLLM, Ollama, DashScope) for local or cloud deployment.

Use cases

  • Document QA and knowledge assistants: convert documents into queryable knowledge and build contextual Q&A.
  • Automated workflows: orchestrate multi-step tasks using tool calls and planning features.
  • Prototyping & education: examples and notebooks help quickly validate ideas and teach concepts.

Technical notes

  • Implementation & language: primarily Python, with clear project structure and extensive examples.
  • Configurable pipelines: combine retrieval and generation strategies through config and examples.
  • Community & license: active contributors, published on PyPI, Apache-2.0 licensed, docs at qwen.readthedocs.io.

Comments

Qwen-Agent
Resource Info
Author QwenLM
Added Date 2025-09-27
Tags
OSS Agent Framework Dev Tools RAG