simply provide a numerical answer without any additional information or context. \n\nBased on these criteria, Response B is the better response.\n',     'value': 'B',     'score': 0}Methods‚ÄãThe pairwise string evaluator can be called using evaluate_string_pairs (or async aevaluate_string_pairs) methods, which accept:prediction (str) ‚Äì The predicted response of the first model, chain, or prompt.prediction_b (str) ‚Äì The predicted response of the second model, chain, or prompt.input (str) ‚Äì The input question, prompt, or other text.reference (str) ‚Äì (Only for the labeled_pairwise_string variant) The reference response.They return a dictionary with the following values:value: 'A' or 'B', indicating whether prediction or prediction_b is preferred, respectivelyscore: Integer 0 or 1 mapped from the 'value', where a score of 1 would mean that the first prediction is preferred, and a score of 0 would mean prediction_b is preferred.reasoning: String "chain of thought reasoning" from the LLM generated prior to creating the scoreWithout References‚ÄãWhen references aren't available, you can still predict the preferred response.
Open In Colab
Open In Colab ->: simply provide a numerical answer without any additional information or context. \n\nBased on these criteria, Response B is the better response.\n',     'value': 'B',     'score': 0}Methods‚ÄãThe pairwise string evaluator can be called using evaluate_string_pairs (or async aevaluate_string_pairs) methods, which accept:prediction (str) ‚Äì The predicted response of the first model, chain, or prompt.prediction_b (str) ‚Äì The predicted response of the second model, chain, or prompt.input (str) ‚Äì The input question, prompt, or other text.reference (str) ‚Äì (Only for the labeled_pairwise_string variant) The reference response.They return a dictionary with the following values:value: 'A' or 'B', indicating whether prediction or prediction_b is preferred, respectivelyscore: Integer 0 or 1 mapped from the 'value', where a score of 1 would mean that the first prediction is preferred, and a score of 0 would mean prediction_b is preferred.reasoning: String "chain of thought reasoning" from the LLM generated prior to creating the scoreWithout References‚ÄãWhen references aren't available, you can still predict the preferred response.