Evaluation: Upload Dataset Improvements

backend/app/api/routes/evaluation.py

@@ -17,7 +17,7 @@
     list_datasets,
     start_evaluation_batch,
     upload_csv_to_object_store,
-    upload_dataset_to_langfuse_from_csv,
+    upload_dataset_to_langfuse,
 )
 from app.crud.evaluations import list_evaluation_runs as list_evaluation_runs_crud
 from app.crud.evaluations.dataset import delete_dataset as delete_dataset_crud
@@ -41,6 +41,19 @@
 router = APIRouter(tags=["evaluation"])
 
 
+def _dataset_to_response(dataset) -> DatasetUploadResponse:
+    """Convert a dataset model to a DatasetUploadResponse."""
+    return DatasetUploadResponse(
+        dataset_id=dataset.id,
+        dataset_name=dataset.name,
+        total_items=dataset.dataset_metadata.get("total_items_count", 0),
+        original_items=dataset.dataset_metadata.get("original_items_count", 0),
+        duplication_factor=dataset.dataset_metadata.get("duplication_factor", 1),
+        langfuse_dataset_id=dataset.langfuse_dataset_id,
+        object_store_url=dataset.object_store_url,
+    )
+
+
 def sanitize_dataset_name(name: str) -> str:
     """
     Sanitize dataset name for Langfuse compatibility.
@@ -164,24 +177,32 @@ async def upload_dataset(
     try:
         csv_text = csv_content.decode("utf-8")
         csv_reader = csv.DictReader(io.StringIO(csv_text))
-        csv_reader.fieldnames = [name.strip() for name in csv_reader.fieldnames]
 
-        # Validate headers
-        if (
-            "question" not in csv_reader.fieldnames
-            or "answer" not in csv_reader.fieldnames
-        ):
+        if not csv_reader.fieldnames:
+            raise HTTPException(status_code=422, detail="CSV file has no headers")
+
+        # Normalize headers for case-insensitive matching
+        clean_headers = {
+            field.strip().lower(): field for field in csv_reader.fieldnames
+        }
+
+        # Validate required headers (case-insensitive)
+        if "question" not in clean_headers or "answer" not in clean_headers:
             raise HTTPException(
                 status_code=422,
-                detail=f"CSV must contain 'question' and 'answer' columns. "
+                detail=f"CSV must contain 'question' and 'answer' columns "
                 f"Found columns: {csv_reader.fieldnames}",
             )
 
+        # Get the actual column names from the CSV
+        question_col = clean_headers["question"]
+        answer_col = clean_headers["answer"]
+
         # Count original items
         original_items = []
         for row in csv_reader:
-            question = row.get("question", "").strip()
-            answer = row.get("answer", "").strip()
+            question = row.get(question_col, "").strip()
+            answer = row.get(answer_col, "").strip()
             if question and answer:
                 original_items.append({"question": question, "answer": answer})
 
@@ -237,9 +258,9 @@ async def upload_dataset(
         )
 
         # Upload to Langfuse
-        langfuse_dataset_id, _ = upload_dataset_to_langfuse_from_csv(
+        langfuse_dataset_id, _ = upload_dataset_to_langfuse(
             langfuse=langfuse,
-            csv_content=csv_content,
+            items=original_items,
             dataset_name=dataset_name,
             duplication_factor=duplication_factor,
         )
@@ -316,24 +337,7 @@ def list_datasets_endpoint(
         offset=offset,
     )
 
-    # Convert to response format
-    response = []
-    for dataset in datasets:
-        response.append(
-            DatasetUploadResponse(
-                dataset_id=dataset.id,
-                dataset_name=dataset.name,
-                total_items=dataset.dataset_metadata.get("total_items_count", 0),
-                original_items=dataset.dataset_metadata.get("original_items_count", 0),
-                duplication_factor=dataset.dataset_metadata.get(
-                    "duplication_factor", 1
-                ),
-                langfuse_dataset_id=dataset.langfuse_dataset_id,
-                object_store_url=dataset.object_store_url,
-            )
-        )
-
-    return response
+    return [_dataset_to_response(dataset) for dataset in datasets]
 
 
 @router.get(
@@ -364,15 +368,7 @@ def get_dataset(
             status_code=404, detail=f"Dataset {dataset_id} not found or not accessible"
         )
 
-    return DatasetUploadResponse(
-        dataset_id=dataset.id,
-        dataset_name=dataset.name,
-        total_items=dataset.dataset_metadata.get("total_items_count", 0),
-        original_items=dataset.dataset_metadata.get("original_items_count", 0),
-        duplication_factor=dataset.dataset_metadata.get("duplication_factor", 1),
-        langfuse_dataset_id=dataset.langfuse_dataset_id,
-        object_store_url=dataset.object_store_url,
-    )
+    return _dataset_to_response(dataset)
 
 
 @router.delete(

backend/app/crud/evaluations/__init__.py

@@ -25,7 +25,7 @@
 from app.crud.evaluations.langfuse import (
     create_langfuse_dataset_run,
     update_traces_with_cosine_scores,
-    upload_dataset_to_langfuse_from_csv,
+    upload_dataset_to_langfuse,
 )
 from app.crud.evaluations.processing import (
     check_and_process_evaluation,
@@ -62,5 +62,5 @@
     # Langfuse
     "create_langfuse_dataset_run",
     "update_traces_with_cosine_scores",
-    "upload_dataset_to_langfuse_from_csv",
+    "upload_dataset_to_langfuse",
 ]

backend/app/crud/evaluations/core.py

@@ -1,138 +1,13 @@
-import csv
-import io
 import logging
 
-from fastapi import HTTPException
 from sqlmodel import Session, select
 
 from app.core.util import now
-from app.models import EvaluationRun, UserProjectOrg
-from app.models.evaluation import DatasetUploadResponse
-from app.utils import get_langfuse_client
+from app.models import EvaluationRun
 
 logger = logging.getLogger(__name__)
 
 
-async def upload_dataset_to_langfuse(
-    csv_content: bytes,
-    dataset_name: str,
-    dataset_id: int,
-    duplication_factor: int,
-    _session: Session,
-    _current_user: UserProjectOrg,
-) -> tuple[bool, DatasetUploadResponse | None, str | None]:
-    """
-    Upload a CSV dataset to Langfuse with duplication for flakiness testing.
-
-    Args:
-        csv_content: Raw CSV file content as bytes
-        dataset_name: Name for the dataset in Langfuse
-        dataset_id: Database ID of the created dataset
-        duplication_factor: Number of times to duplicate each item (default 5)
-        _session: Database session
-        _current_user: Current user organization
-
-    Returns:
-        Tuple of (success, dataset_response, error_message)
-    """
-    try:
-        # Get Langfuse client
-        try:
-            langfuse = get_langfuse_client(
-                session=_session,
-                org_id=_current_user.organization_id,
-                project_id=_current_user.project_id,
-            )
-        except HTTPException as http_exc:
-            return False, None, http_exc.detail
-
-        # Parse CSV content
-        csv_text = csv_content.decode("utf-8")
-        csv_reader = csv.DictReader(io.StringIO(csv_text))
-
-        # Validate CSV headers
-        if (
-            "question" not in csv_reader.fieldnames
-            or "answer" not in csv_reader.fieldnames
-        ):
-            return (
-                False,
-                None,
-                "CSV must contain 'question' and 'answer' columns. "
-                f"Found columns: {csv_reader.fieldnames}",
-            )
-
-        # Read all rows from CSV
-        original_items = []
-        for row in csv_reader:
-            question = row.get("question", "").strip()
-            answer = row.get("answer", "").strip()
-
-            if not question or not answer:
-                logger.warning(f"Skipping row with empty question or answer: {row}")
-                continue
-
-            original_items.append({"question": question, "answer": answer})
-
-        if not original_items:
-            return False, None, "No valid items found in CSV file."
-
-        logger.info(
-            f"Parsed {len(original_items)} items from CSV. "
-            f"Will duplicate {duplication_factor}x for a total of {len(original_items) * duplication_factor} items."
-        )
-
-        # Create or get dataset in Langfuse
-        dataset = langfuse.create_dataset(name=dataset_name)
-
-        # Upload items with duplication
-        total_uploaded = 0
-        for item in original_items:
-            # Duplicate each item N times
-            for duplicate_num in range(duplication_factor):
-                try:
-                    langfuse.create_dataset_item(
-                        dataset_name=dataset_name,
-                        input={"question": item["question"]},
-                        expected_output={"answer": item["answer"]},
-                        metadata={
-                            "original_question": item["question"],
-                            "duplicate_number": duplicate_num + 1,
-                            "duplication_factor": duplication_factor,
-                        },
-                    )
-                    total_uploaded += 1
-                except Exception as e:
-                    logger.error(
-                        f"Failed to upload item (duplicate {duplicate_num + 1}): {item['question'][:50]}... Error: {e}"
-                    )
-
-        # Flush to ensure all items are uploaded
-        langfuse.flush()
-
-        logger.info(
-            f"Successfully uploaded {total_uploaded} items to dataset '{dataset_name}' "
-            f"({len(original_items)} original × {duplication_factor} duplicates)"
-        )
-
-        return (
-            True,
-            DatasetUploadResponse(
-                dataset_id=dataset_id,
-                dataset_name=dataset_name,
-                total_items=total_uploaded,
-                original_items=len(original_items),
-                duplication_factor=duplication_factor,
-                langfuse_dataset_id=dataset.id if hasattr(dataset, "id") else None,
-            ),
-            None,
-        )
-
-    except Exception as e:
-        logger.error(f"Error uploading dataset: {str(e)}", exc_info=True)
-        return False, None, f"Failed to upload dataset: {str(e)}"
-
-
 def create_evaluation_run(
     session: Session,
     run_name: str,
@@ -170,8 +45,13 @@ def create_evaluation_run(
     )
 
     session.add(eval_run)
-    session.commit()
-    session.refresh(eval_run)
+    try:
+        session.commit()
+        session.refresh(eval_run)
+    except Exception as e:
+        session.rollback()
+        logger.error(f"Failed to create EvaluationRun: {e}", exc_info=True)
+        raise
 
     logger.info(f"Created EvaluationRun record: id={eval_run.id}, run_name={run_name}")
 
@@ -214,7 +94,7 @@ def list_evaluation_runs(
         f"project_id={project_id}"
     )
 
-    return list(runs)
+    return runs
 
 
 def get_evaluation_run_by_id(
@@ -302,7 +182,12 @@ def update_evaluation_run(
 
     # Persist to database
     session.add(eval_run)
-    session.commit()
-    session.refresh(eval_run)
+    try:
+        session.commit()
+        session.refresh(eval_run)
+    except Exception as e:
+        session.rollback()
+        logger.error(f"Failed to update EvaluationRun: {e}", exc_info=True)
+        raise
 
     return eval_run