From 9f5e25811e79f41488056a16da673230a5464961 Mon Sep 17 00:00:00 2001
From: Maximilian Kimmich <maximilian.kimmich@ims.uni-stuttgart.de>
Date: Tue, 1 Oct 2024 16:14:53 +0200
Subject: [PATCH] Update sample selection for base prompt generation and
temporarily disable bsae prompt generation
---
evoprompt/task/base_prompts_mixin.py | 13 +++++++++++--
1 file changed, 11 insertions(+), 2 deletions(-)
diff --git a/evoprompt/task/base_prompts_mixin.py b/evoprompt/task/base_prompts_mixin.py
index 5c31c50..c4d00cd 100644
--- a/evoprompt/task/base_prompts_mixin.py
+++ b/evoprompt/task/base_prompts_mixin.py
@@ -5,6 +5,7 @@ import re
from datasets import Dataset
from evoprompt.models import LLMModel
+from evoprompt.utils import get_rng
class BasePromptsFromJsonMixin:
@@ -35,17 +36,25 @@ class BasePromptsFromGeneration:
self, num_prompts: int, patience: int = 10, allow_duplicates: bool = False
) -> str:
self.validation_dataset: Dataset
- samples = self.validation_dataset._select_contiguous(0, 5)
+ samples = self.validation_dataset.shuffle(42).select(
+ get_rng().choice(len(self.validation_dataset), 5, replace=False)
+ )
prompt = "I gave a friend an instruction and five inputs. The friend read the instruction and wrote an output for every one of the inputs. Here are the input-output pairs:\n"
+ raise NotImplementedError(
+ "The prompt needs to be adapted for the model taking into account the correct format."
+ )
prompt = self.build_demonstration_prompt(samples, prompt=prompt)
prompt += "\nThe instruction was "
+ system_message = "You are a helpful assistant. Please provide the instruction wrapped within tags <instruction> and </instruction> that belongs to the given input-output pairs."
+ input(prompt)
generated_prompts = []
while len(generated_prompts) < num_prompts:
response, _, _, _ = self.evolution_model.create_completion(
- system_message=f"You are a helpful assistant. Please provide the instruction wrapped within tags <instruction> and </instruction> that belongs to the given input-output pairs.",
+ system_message=system_message,
prompt=prompt,
)
+ input(response)
matches = re.findall(
# regex that extracts anything within tags <instruction> and optional </instruction>
rf"<instruction>(.+?)(?:(?=</instruction>)|$)",
--
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