add reduce to pandas api

docetl/apis/pd_accessors.py

@@ -673,6 +673,68 @@ Record 2: {record_template.replace('input0', 'input2')}"""
 
         return self._record_operation(results, "reduce", reduce_config, reduce_cost)
 
+    def reduce(
+        self,
+        prompt: str,
+        output: dict[str, Any] | None = None,
+        *,
+        output_schema: dict[str, Any] | None = None,
+        reduce_keys: str | list[str] = ["_all"],
+        **kwargs,
+    ) -> pd.DataFrame:
+        """
+        Reduce/aggregate all rows using a language model.
+
+        This is a simplified wrapper around the agg() method for common reduce operations.
+
+        Documentation: https://ucbepic.github.io/docetl/operators/reduce/
+
+        Args:
+            prompt: Jinja template string for the reduction prompt. Use {% for item in inputs %}
+                   to iterate over input rows.
+            output: Output configuration with keys:
+                - "schema": Dictionary defining the expected output structure and types
+                - "mode": Optional output mode. Either "tools" (default) or "structured_output"
+            output_schema: DEPRECATED. Use 'output' parameter instead.
+            reduce_keys: Keys to group by for reduction (default: ["_all"] for all rows)
+            **kwargs: Additional configuration options passed to agg():
+                - model: LLM model to use
+                - validate: List of validation expressions
+                - num_retries_on_validate_failure: Number of retries
+                - timeout: Timeout in seconds (default: 120)
+                - max_retries_per_timeout: Max retries per timeout (default: 2)
+
+        Returns:
+            pd.DataFrame: Aggregated DataFrame with columns matching output['schema']
+
+        Examples:
+            >>> # Summarize all texts into one summary
+            >>> df.semantic.reduce(
+            ...     prompt=\"\"\"Summarize the following items:
+            ...     {% for item in inputs %}
+            ...     - {{ item.text }}
+            ...     {% endfor %}\"\"\",
+            ...     output={"schema": {"summary": "str"}}
+            ... )
+
+            >>> # Reduce by group
+            >>> df.semantic.reduce(
+            ...     prompt=\"\"\"Combine items for {{ reduce_key }}:
+            ...     {% for item in inputs %}
+            ...     - {{ item.description }}
+            ...     {% endfor %}\"\"\",
+            ...     output={"schema": {"combined": "str"}},
+            ...     reduce_keys=["category"]
+            ... )
+        """
+        return self.agg(
+            reduce_prompt=prompt,
+            output=output,
+            output_schema=output_schema,
+            reduce_keys=reduce_keys,
+            reduce_kwargs=kwargs,
+        )
+
     def filter(
         self,
         prompt: str,

docetl/operations/reduce.py

@@ -20,7 +20,6 @@ from jinja2 import Template
 from pydantic import Field, field_validator, model_validator
 
 from docetl.operations.base import BaseOperation
-from docetl.utils import has_jinja_syntax, prompt_user_for_non_jinja_confirmation
 from docetl.operations.clustering_utils import (
     cluster_documents,
     get_embeddings_for_clustering,
@@ -33,7 +32,11 @@ from docetl.operations.utils import (
 
 # Import OutputMode enum for structured output checks
 from docetl.operations.utils.api import OutputMode
-from docetl.utils import completion_cost
+from docetl.utils import (
+    completion_cost,
+    has_jinja_syntax,
+    prompt_user_for_non_jinja_confirmation,
+)
 
 
 class ReduceOperation(BaseOperation):
@@ -776,6 +779,7 @@ class ReduceOperation(BaseOperation):
 
         end_time = time.time()
         self._update_fold_time(end_time - start_time)
+        fold_cost = response.total_cost
 
         if response.validated:
             structured_mode = (
@@ -844,6 +848,7 @@ class ReduceOperation(BaseOperation):
 
         end_time = time.time()
         self._update_merge_time(end_time - start_time)
+        merge_cost = response.total_cost
 
         if response.validated:
             structured_mode = (