Magic Platform's Multi-Model Unified Access Solution
Magic solves the problem of multi-model compatibility through standardized interface design:
- Unified Configuration::
- Set 'LLM_API_TYPE=openai' in .env file (compatible with all OpenAI format API models)
- Support for various private deployment models via 'LLM_API_BASE=Interface Address'
- thermal cutover mechanism::
- Business Scenario: Configure different models for different business modules (e.g. GPT-4 for customer service dialog, Claude-3 for data analysis)
- Failover: automatically switch to the standby model when the primary model is unavailable to ensure service continuity
- Advanced Configuration::
- Modify config/model_router.json to implement smart routing based on query content
- Setting the model load balancing policy with parameters such as 'system_performance=80'
Practical advice: Enterprise users should first conduct model performance benchmarking to determine the optimal model configuration scheme for different business scenarios, and then realize optimal resource allocation through Magic's flexible routing mechanism.
This answer comes from the articleMagic: Open Source AI Productivity Platform to Help Enterprises Efficiently Build Intelligent ApplicationsThe
May not be reproduced without permission:AI productivity tools " How to overcome the system compatibility issues arising from multi-model switching?
