1. What is Qwen-Agent

Qwen-Agent is a framework specifically designed for developing applications based on large language models (LLM). It not only supports instruction following, tool usage, planning, and memory capabilities, but also can handle documents ranging from 8K to 1 million tokens, surpassing the limitations of traditional long-context models. This means developers can use Qwen-Agent to build intelligent agent applications that can understand and generate natural language and perform complex tasks.

Introduction to Qwen-Agent: An Open Source Agent Development Framework

2. Core Functions and Features

2.1 Function Calling

Function calling is a fundamental capability of Qwen-Agent, allowing the AI model to actively call predefined functions or tools when processing tasks. This feature enables Qwen-Agent to interact with external tools and APIs, thereby expanding the scope of AI applications. For example, developers can define a tool for generating images, and when users request an image of specific content, Qwen-Agent can call that tool and return the generated image link.

2.2 Code Interpreter

Qwen-Agent comes with a built-in code interpreter tool that can execute user-provided code snippets. This provides developers with great flexibility, allowing intelligent agents not only to understand and generate text but also to perform actual operations. For instance, when handling image generation tasks, Qwen-Agent can first call the image generation tool to generate an image, and then use the code interpreter to download the image and perform further processing, such as flipping the image.

2.3 Multimodal Processing

Qwen-Agent supports multimodal input and output, capable of understanding and generating various types of data such as text and images. This allows developers to build richer and more interactive applications. For example, an image understanding and text generation agent can first understand the content of the image provided by the user and then generate a text description or story related to the image.

2.4 Memory Capability

Qwen-Agent has memory capabilities, allowing it to remember previous dialogue content and operations performed. This enables the intelligent agent to better understand user intent and provide more coherent and personalized services. For instance, during multi-turn conversations with users, Qwen-Agent can provide more accurate answers and suggestions based on previous dialogue content.

3. Application Scenarios

The flexibility and powerful features of Qwen-Agent make it suitable for various application scenarios, including but not limited to:

Customer Service: As a chatbot, providing 24/7 customer consultation services, handling common questions and inquiries.
Personal Assistant: Helping users manage schedules, reminders, bookings, and other daily tasks.
Education and Learning: Serving as a virtual teaching assistant, providing personalized learning suggestions and answering student questions.
Content Creation: Assisting in writing, editing, and content generation, including articles, reports, and creative writing.
Technical Support: Providing solutions for technical issues, helping users resolve software or hardware problems.
Data Analysis: Assisting in analyzing and interpreting complex datasets, providing business insights.

4. Development and Usage

4.1 Installation

Install the stable version from PyPI:

pip install -U "qwen-agent[rag,code_interpreter,python_executor,gui]"# Or, use `pip install -U qwen-agent` to install minimal dependencies.# Optional dependencies can be specified as follows:#   [gui] for Gradio-based GUI support;#   [rag] for RAG support;#   [code_interpreter] for code interpreter related support;#   [python_executor] for Qwen2.5-Math tool-based reasoning support.

You can also install the latest development version from source:

git clone https://github.com/QwenLM/Qwen-Agent.gitcd Qwen-Agentpip install -e ./