Qwen-Agent: Qwen2-Powered Multi-Agent Framework with Function Calling, Code Interpreter, and RAG!

Enhance Your AI Capabilities with Qwen-Agent: Advanced Function Calling, Code Interpretation, and RAG Integration

Alibaba recently launched the new Qwen 2 large language model and the upgraded Qwen Agent framework. This framework integrates the Qwen 2 model and supports functions like code interpretation, and RAG (Retrieval-Augmented Generation), and includes a Chrome extension.

The Qwen Agent handles documents ranging from 8K to 1 million tokens. It outperforms RAG and native long-context models and generates data for training new long-context models.

The Qwen Agent framework is useful for creating complex AI agents, showcasing its strong task-handling abilities.

The new framework uses a four-step development process: initial model development, agent development, data synthesis, and model fine-tuning.

By using the RAG algorithm, long documents are divided into smaller chunks, keeping only the most relevant parts to improve context processing.

The steps include retrieval-augmented generation, chunk-by-chunk reading, and step-by-step reasoning. The RAG algorithm optimizes document fragments to provide accurate context understanding and generation capabilities.

Experiments show that the Qwen Agent significantly improves context length and performance.