Workflow Configuration Workflow Configuration Workflow Configuration Workflow Configuration Workflow Configuration Workflow Configuration
In the web interface of theWorkflow Modulein which configuring multi-model collaboration is divided into three key steps:
- Model Registration: first inmodel managementAdd each AI provider in (e.g. DeepSeek needs to fill in parameters such as API_KEY, temperature, etc.)
- Process Design: Define the order of execution via JSON, for example:
{"name": "写作增强流","steps": [{"model_id": "gemini","step_type": "大纲生成","step_order": 1},{"model_id": "claude","step_type": "内容扩写","step_order": 2}]} - API encapsulation: Saving can be done through the
/v1/chat/completionsinterface call, specify themodelThe parameter is the workflow name
Typical Application Scenarios::
- Analyze-Execute Model: Logical Reasoning with DeepSeek, then Generate Natural Language Results with Claude
- Creative workflow: Gemini for brainstorming, GPT-4 for optimizing expression
- Calibration process: cross-validation of answer consistency across multiple models
Note that the browser interface is only for configuration, the actual use needs to be called through the API.
This answer comes from the articleDeepGemini: Multi-model orchestration of tasks and encapsulation into an API interfaceThe
May not be reproduced without permission:AI productivity tools " How exactly is DeepGemini's multi-model orchestration feature configured? Please provide an example
