add direct run prompt

Author: lchen001

eureka_ml_insights/prompt_templates/aime_templates/Template_1direct.jinja

@@ -0,0 +1,5 @@
+You are a genius math graduate student solving math problems from the AIME competition. 
+
+Provide your final answer in the format: 'Final Answer: [numeric value]'. Dont box it, just provide the answer directly at the end.
+
+{{prompt}}

eureka_ml_insights/user_configs/__init__.py

@@ -4,9 +4,12 @@
     AIME_PIPELINE16Run,
     AIME_PIPELINE32Run,
     AIME_PIPELINE64Run,
+    AIME_PIPELINE128Run,
     AIME_PIPELINE256Run,
     AIME_PIPELINE512Run,
     AIME_PIPELINE1024Run,
+    AIME_PIPELINE5Run,
+    AIME_PIPELINEDirect5Run,
     AIME_PIPELINETag,
 )
 from .dna import DNA_PIPELINE

eureka_ml_insights/user_configs/aime.py

@@ -23,6 +23,7 @@
     MajorityVoteTransform,
     MultiplyTransform,
     SequenceTransform,
+    SamplerTransform
 )
 from eureka_ml_insights.data_utils.aime_utils import AIMEExtractAnswer
 from eureka_ml_insights.data_utils.data import DataLoader
@@ -78,7 +79,7 @@ def configure_pipeline(
             ),
             output_dir=os.path.join(self.log_dir, "inference_result"),
             resume_from=resume_from,
-            max_concurrent=10,
+            max_concurrent=1,
         )
         # post process the response to extract the answer
         self.data_post_processing = DataProcessingConfig(
@@ -215,6 +216,19 @@ def configure_pipeline(
         )
         return pipeline
 
+class AIME_PIPELINEDirect5Run(AIME_PIPELINE5Run):
+    """This class specifies the config for running AIME benchmark 5 repeated times"""
+
+    def configure_pipeline(
+        self, model_config: ModelConfig, resume_from: str = None, **kwargs: dict[str, Any]
+    ) -> PipelineConfig:
+        pipeline = super().configure_pipeline(model_config=model_config, resume_from=resume_from)
+        # data preprocessing
+        self.data_processing_comp.prompt_template_path=os.path.join(
+                os.path.dirname(__file__), "../prompt_templates/aime_templates/Template_1direct.jinja"
+            )
+        return pipeline
+
 
 class AIME_PIPELINE16Run(AIME_PIPELINE):
     """This class specifies the config for running AIME benchmark 5 repeated times"""