Weight Assignment

Enter the score for scalability (1-10): 7 Enter the score for security (1-10): 6 Enter the name of option 2: Option B Enter the score for cost (1-10): 7 Enter the score for scalability (1-10): 8 Enter the score for security (1-10): 9 Ente…

threshold = 0.10 return max(0, 1 - (cost / threshold)) # Example usage: criteria = ["accuracy", "latency", "cost"] weights = [2, 1, 1] # Example weights: accuracy is twice as important as latency and cost evaluator = LLMEv…

- You can easily add more criteria by extending the `criteria` list and implementing the corresponding normalization functions. ### Example Usage In the example usage, we define three criteria (`accuracy`, `latency`, `cost`) and assign…

2. **Normalization Function**: Implemented `_normalize_reliability` to normalize the reliability metric to a 0-1 scale. The threshold is set to 99.9%, which is a common target for enterprise systems. 3. **Updated Weights**: Adjusted the wei…

- **Description**: Coefficient for L2 norm of the weights. - **Range**: Typically between \(10^{-6}\) and \(10^{-2}\). - **Example Values**: \(1e-6\), \(1e-5\), \(1e-4\), \(1e-3\), \(1e-2\). - **Dropout Rate** - **De…

For each combination of weights, evaluate the performance using your test queries and measure the intent precision. ### Example Implementation Here's an example of how you might structure your experiments: ```python import itertools impo…

Identify the different components of your context and assign initial weights. For example: - `user_history` - `current_query` - `system_state` - `external_data_sources` ### Step 2: Generate Weight Combinations Use a systematic approach t…