Qwen-Agent
Agent framework and applications built upon Qwen>=3.0, featuring Function Calling, MCP, Code Interpreter, RAG, Chrome extension, etc.
Qwen-Agent is an agent framework developed by QwenLM for building LLM applications on top of Qwen models (version 3.0 and later). It provides core capabilities including function calling, MCP integration, code interpretation, retrieval-augmented generation (RAG), and multi-step planning. The framework offers both low-level building blocks (LLMs, tools) and high-level agent implementations like Assistant, enabling developers to create custom AI agents with tool usage, file reading, and web browsing capabilities. It powers the backend of Qwen Chat and includes example applications such as Browser Assistant and Code Interpreter.
Key Features
Use Cases
- 01Building custom AI assistants with tool access for tasks like image generation, web search, and data processing
- 02Creating code-generating agents that write, execute, and debug Python code autonomously in sandboxed environments
- 03Implementing RAG systems for document question-answering over technical manuals, research papers, or long-form content
- 04Developing browser automation assistants using the BrowserQwen extension for web scraping and form filling
- 05Building conversational agents with multi-step reasoning and planning capabilities using QwQ-32B
- 06Deploying visual reasoning agents with Qwen3-VL for image analysis, zoom, and web-based image search
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Qwen-Agent — FAQ
What is Qwen-Agent?+
Qwen-Agent is an agent framework for developing LLM applications based on Qwen models (≥3.0), providing instruction following, tool usage, planning, and memory capabilities. It includes both reusable components (LLMs, tools) and pre-built agent implementations like Assistant, and powers the Qwen Chat backend.
How do I install Qwen-Agent?+
Install from PyPI using 'pip install -U "qwen-agent[gui,rag,code_interpreter,mcp]"' for full features, or 'pip install -U qwen-agent' for minimal requirements. Alternatively, clone the GitHub repository and install from source with 'pip install -e ./"[gui,rag,code_interpreter,mcp]"'.
What API key or model service does Qwen-Agent require?+
Qwen-Agent works with Alibaba Cloud's DashScope API (requires DASHSCOPE_API_KEY environment variable) or self-hosted OpenAI-compatible services. You can deploy Qwen models locally using vLLM for GPU or Ollama for CPU+GPU, eliminating the need for cloud API keys.
Does Qwen-Agent support function calling and tool usage?+
Yes, all LLM classes provide native function calling capabilities with support for parallel function calls. Agent implementations like Assistant and ReActChat are built on this capability and can use both custom tools and built-in tools like code_interpreter.
How do I use the Code Interpreter feature?+
The code interpreter requires Docker installed and running locally. Enable it by adding 'code_interpreter' to your agent's function_list. The first run will build a container image, and code executes safely in an isolated Docker sandbox environment.
Is Qwen-Agent free and open source?+
Yes, Qwen-Agent is open source under the Apache License 2.0. The framework itself is free to use, though you'll need either a DashScope API account (which may have usage costs) or self-hosted Qwen models to run agents.
How do I install Qwen-Agent?+
Open the source repository on GitHub and follow its README. Qwen-Agent is a agent — MCP Agents Market links you directly to the official repo.
Is Qwen-Agent free?+
Qwen-Agent is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.