Solution: Assemble the system using modular components
OxyGent enables a Lego-like development approach with standardized Oxy components in 4 key steps:
- environmental preparation: create a Python 3.10 environment using conda or uv and install the oxygent package (recommended for use with Node.js development environments)
- Defining Components: Declare intelligences (e.g., ReActAgent), tools (preset_tools), and LLM connection configurations (HttpLLM) in the oxy_space list
- Building collaborative relationships: Specify the master via the is_master parameter, and the sub_agents parameter sets the sub-smart associations.
- Starting services: Start the service using the start_web_service method of the MAS context manager
Typical application scenarios such as customer service system: through the main intelligent body to receive the user's question, coordinate the NLP intelligent body to analyze the intention, the database intelligent body to retrieve the information, and the output intelligent body to generate the response, the whole process automatically completes the dynamic task decomposition.
This answer comes from the articleOxyGent: Python open source framework for rapidly building intelligent systemsThe
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