small updates to llama model class

eureka_ml_insights/configs/model_configs.py

@@ -186,6 +186,28 @@
     },
 )
 
+AIF_NT_LLAMA3_2_90B_VISION_INSTRUCT_CONFIG = ModelConfig(
+    LlamaServerlessAzureRestEndpointModel,
+    {
+        "url": "https://Llama-3-2-90B-Vision-Instruct-ev.eastus2.models.ai.azure.com/chat/completions",
+        "secret_key_params": {
+            "key_name": "aif-nt-meta-llama-3-2-90b-Instruct-1",
+            "local_keys_path": "keys/aifeval-vault-azure-net.json",
+        },
+    },
+)
+
+AIF_NT_LLAMA3_2_90B_VISION_INSTRUCT_CONFIG_2 = ModelConfig(
+    LlamaServerlessAzureRestEndpointModel,
+    {
+        "url": "https://Llama-3-2-90B-Vision-Instruct-2.eastus2.models.ai.azure.com/chat/completions",
+        "secret_key_params": {
+            "key_name": "aif-nt-meta-llama-3-2-90b-Instruct-2",
+            "local_keys_path": "keys/aifeval-vault-azure-net.json",
+        },
+    },
+)
+
 # Mistral Endpoints
 AIF_NT_MISTRAL_LARGE_2_2407_CONFIG = ModelConfig(
     MistralServerlessAzureRestEndpointModel,

eureka_ml_insights/data_utils/__init__.py

@@ -1,3 +1,4 @@
+from .aime_utils import AIMEExtractAnswer
 from .data import (
     AzureDataReader,
     AzureJsonReader,
@@ -41,6 +42,7 @@
 )
 
 __all__ = [
+    AIMEExtractAnswer,
     JsonLinesWriter,
     JsonReader,
     HFJsonReader,

eureka_ml_insights/data_utils/aime_utils.py

@@ -3,7 +3,7 @@
 
 import pandas as pd
 
-from eureka_ml_insights.data_utils import DFTransformBase
+from .transform import DFTransformBase
 
 
 @dataclass
@@ -12,32 +12,32 @@ class AIMEExtractAnswer(DFTransformBase):
     model_answer_column: str
 
     def transform(self, df: pd.DataFrame) -> pd.DataFrame:
-        df[self.model_answer_column] = df[self.model_output_column].apply(parse_output_answer)
+        df[self.model_answer_column] = df[self.model_output_column].apply(self.parse_output_answer)
         return df
 
-
-def parse_output_answer(response):
-    """
-    Parse the input string to extract answer of a given AIME question.
-    Parameters:
-        response (str): Input string containing answer X in the form of "Final Answer: X".
-    Returns: 
-        numerical_value (float): A numeric value representing the model's answer.
-    """
-    numerical_value = None
-
-    # Try to find an answer in the "Final Answer: X" format
-    match = re.search(r"Final Answer:\s*([\$]?-?[\d,]+(?:\.\d+)?%?)", response)
-    if match:
-        answer_str = match.group(1)
-        # Remove $ and commas, handle percentages for numerical comparison
-        answer_str = answer_str.replace("$", "").replace(",", "")
-        if answer_str.endswith("%"):
-            numerical_value = float(answer_str[:-1]) / 100  # Convert percentage to decimal
-        else:
-            try:
-                numerical_value = float(answer_str)
-            except ValueError as e:
-                numerical_value = None
-
-    return numerical_value
+    @staticmethod
+    def parse_output_answer(response):
+        """
+        Parse the input string to extract answer of a given AIME question.
+        Parameters:
+            response (str): Input string containing answer X in the form of "Final Answer: X".
+        Returns: 
+            numerical_value (float): A numeric value representing the model's answer.
+        """
+        numerical_value = None
+
+        # Try to find an answer in the "Final Answer: X" format
+        match = re.search(r"Final Answer:\s*([\$]?-?[\d,]+(?:\.\d+)?%?)", response)
+        if match:
+            answer_str = match.group(1)
+            # Remove $ and commas, handle percentages for numerical comparison
+            answer_str = answer_str.replace("$", "").replace(",", "")
+            if answer_str.endswith("%"):
+                numerical_value = float(answer_str[:-1]) / 100  # Convert percentage to decimal
+            else:
+                try:
+                    numerical_value = float(answer_str)
+                except ValueError as e:
+                    numerical_value = None
+
+        return numerical_value

eureka_ml_insights/data_utils/dna_utils.py

@@ -2,7 +2,7 @@
 
 import pandas as pd
 
-from eureka_ml_insights.data_utils import DFTransformBase
+from .transform import DFTransformBase
 
 
 @dataclass

eureka_ml_insights/data_utils/flenqa_utils.py

@@ -5,7 +5,7 @@
 import numpy as np
 import pandas as pd
 
-from eureka_ml_insights.data_utils import DFTransformBase
+from .transform import DFTransformBase
 
 
 @dataclass

eureka_ml_insights/data_utils/kitab_utils.py

@@ -9,7 +9,7 @@
 
 import pandas as pd
 
-from eureka_ml_insights.data_utils import DFTransformBase
+from .transform import DFTransformBase
 
 
 @dataclass

eureka_ml_insights/data_utils/mmmu_utils.py

@@ -2,7 +2,7 @@
 
 import pandas as pd
 
-from eureka_ml_insights.data_utils import DFTransformBase
+from .transform import DFTransformBase
 
 MMMUCategories = {
     "Art and Design": ["Art", "Art_Theory", "Design", "Music"],

eureka_ml_insights/data_utils/spatial_utils.py

@@ -5,10 +5,7 @@
 
 import pandas as pd
 
-from eureka_ml_insights.data_utils.transform import (
-    DFTransformBase,
-    MultiColumnTransform,
-)
+from .transform import DFTransformBase, MultiColumnTransform
 
 
 @dataclass

eureka_ml_insights/data_utils/toxigen_utils.py

@@ -3,7 +3,7 @@
 
 import pandas as pd
 
-from eureka_ml_insights.data_utils import DFTransformBase
+from .transform import DFTransformBase
 
 delimiters = [
     "Toxic score",