openclaw - 💡(How to fix) Fix [Feature]:智能模型路由（Intelligent Model Routing） [1 comments, 2 participants]

Fix Plan

To implement the intelligent model routing feature, we will introduce a routing mechanism that considers task type, context length, complexity, and time to select the most suitable model.

Step-by-Step Solution:

1. Define a routing strategy: Create a function that takes task type, context length, complexity, and time as inputs and returns the preferred model (local or API).
2. Implement model selection logic: Use a decision tree or a simple if-else statement to determine the best model based on the input factors.
3. Integrate with existing routing: Modify the existing primary + fallbacks routing to incorporate the new intelligent routing mechanism.

Example Code (Python):

def select_model(task_type, context_length, complexity, time):
    if task_type == "simple" and context_length < 100:
        return "local_model"
    elif complexity > 0.5 and time < 1000:
        return "api_model"
    else:
        return "fallback_model"

def route_request(task_type, context_length, complexity, time):
    preferred_model = select_model(task_type, context_length, complexity, time)
    if preferred_model == "local_model":
        # Use local model
        return local_model_response
    elif preferred_model == "api_model":
        # Use API model
        return api_model_response
    else:
        # Use fallback model
        return fallback_model_response

Verification

To verify the fix, test the routing mechanism with different input scenarios and ensure that the correct model is selected. Monitor API costs, response times, and privacy protection to confirm the expected benefits.

Extra Tips

• Continuously monitor and update the routing strategy to adapt to changing task types and model performance.
• Consider using machine learning algorithms to optimize the routing decision-making process.
• Ensure proper error handling and fallback mechanisms to maintain high availability.