feat(wren-ai-service): Consolidate SQL Pairs Service and Remove Redun…

…dant Code (#1268)

deployment/kustomizations/base/cm.yaml

@@ -165,9 +165,6 @@ data:
       - name: sql_pairs_indexing
         document_store: qdrant
         embedder: litellm_embedder.text-embedding-3-large
-      - name: sql_pairs_deletion
-        document_store: qdrant
-        embedder: litellm_embedder.text-embedding-3-large 
       - name: sql_pairs_retrieval
         document_store: qdrant
         embedder: litellm_embedder.text-embedding-3-large

docker/config.example.yaml

@@ -117,9 +117,6 @@ pipes:
   - name: sql_pairs_indexing
     document_store: qdrant
     embedder: litellm_embedder.text-embedding-3-large
-  - name: sql_pairs_deletion
-    document_store: qdrant
-    embedder: litellm_embedder.text-embedding-3-large 
   - name: sql_pairs_retrieval
     document_store: qdrant
     embedder: litellm_embedder.text-embedding-3-large

wren-ai-service/docs/config_examples/config.azure.yaml

@@ -101,9 +101,6 @@ pipes:
     document_store: qdrant
     embedder: litellm_embedder.azure/text-embedding-ada-002
     llm: litellm_llm.azure/gpt-4
-  - name: sql_pairs_deletion
-    document_store: qdrant
-    embedder: litellm_embedder.azure/text-embedding-ada-002 
   - name: sql_pairs_retrieval
     document_store: qdrant
     embedder: litellm_embedder.azure/text-embedding-ada-002

wren-ai-service/docs/config_examples/config.deepseek.yaml

@@ -125,9 +125,6 @@ pipes:
   - name: sql_pairs_indexing
     document_store: qdrant
     embedder: litellm_embedder.text-embedding-3-large
-  - name: sql_pairs_deletion
-    document_store: qdrant
-    embedder: litellm_embedder.text-embedding-3-large 
   - name: sql_pairs_retrieval
     document_store: qdrant
     embedder: litellm_embedder.text-embedding-3-large

wren-ai-service/docs/config_examples/config.google_ai_studio.yaml

@@ -107,9 +107,6 @@ pipes:
   - name: sql_pairs_indexing
     document_store: qdrant
     embedder: litellm_embedder.gemini/text-embedding-004
-  - name: sql_pairs_deletion
-    document_store: qdrant
-    embedder: litellm_embedder.gemini/text-embedding-004 
   - name: sql_pairs_retrieval
     document_store: qdrant
     embedder: litellm_embedder.gemini/text-embedding-004

wren-ai-service/docs/config_examples/config.groq.yaml

@@ -109,9 +109,6 @@ pipes:
   - name: sql_pairs_indexing
     document_store: qdrant
     embedder: litellm_embedder.text-embedding-3-large
-  - name: sql_pairs_deletion
-    document_store: qdrant
-    embedder: litellm_embedder.text-embedding-3-large 
   - name: sql_pairs_retrieval
     document_store: qdrant
     embedder: litellm_embedder.text-embedding-3-large

wren-ai-service/docs/config_examples/config.ollama.yaml

@@ -107,9 +107,6 @@ pipes:
   - name: sql_pairs_indexing
     document_store: qdrant
     embedder: litellm_embedder.openai/nomic-embed-text
-  - name: sql_pairs_deletion
-    document_store: qdrant
-    embedder: litellm_embedder.openai/nomic-embed-text 
   - name: sql_pairs_retrieval
     document_store: qdrant
     embedder: litellm_embedder.openai/nomic-embed-text

wren-ai-service/src/config.py

@@ -60,7 +60,7 @@ class Settings(BaseSettings):
     config_path: str = Field(default="config.yaml")
     _components: list[dict]
 
-    sql_pairs_path: str = Field(default="pairs.json")
+    sql_pairs_path: str = Field(default="sql_pairs.json")
 
     def __init__(self):
         load_dotenv(".env.dev", override=True)

wren-ai-service/src/globals.py

@@ -7,40 +7,27 @@
 from src.core.pipeline import PipelineComponent
 from src.core.provider import EmbedderProvider, LLMProvider
 from src.pipelines import generation, indexing, retrieval
-from src.web.v1.services.ask import AskService
-from src.web.v1.services.ask_details import AskDetailsService
-from src.web.v1.services.chart import ChartService
-from src.web.v1.services.chart_adjustment import ChartAdjustmentService
-from src.web.v1.services.question_recommendation import QuestionRecommendation
-from src.web.v1.services.relationship_recommendation import RelationshipRecommendation
-from src.web.v1.services.semantics_description import SemanticsDescription
-from src.web.v1.services.semantics_preparation import SemanticsPreparationService
-from src.web.v1.services.sql_answer import SqlAnswerService
-from src.web.v1.services.sql_expansion import SqlExpansionService
-from src.web.v1.services.sql_explanation import SqlExplanationService
-from src.web.v1.services.sql_pairs_preparation import SqlPairsPreparationService
-from src.web.v1.services.sql_question import SqlQuestionService
-from src.web.v1.services.sql_regeneration import SqlRegenerationService
+from src.web.v1 import services
 
 logger = logging.getLogger("wren-ai-service")
 
 
 @dataclass
 class ServiceContainer:
-    ask_service: AskService
-    ask_details_service: AskDetailsService
-    question_recommendation: QuestionRecommendation
-    relationship_recommendation: RelationshipRecommendation
-    semantics_description: SemanticsDescription
-    semantics_preparation_service: SemanticsPreparationService
-    chart_service: ChartService
-    chart_adjustment_service: ChartAdjustmentService
-    sql_answer_service: SqlAnswerService
-    sql_expansion_service: SqlExpansionService
-    sql_explanation_service: SqlExplanationService
-    sql_regeneration_service: SqlRegenerationService
-    sql_pairs_preparation_service: SqlPairsPreparationService
-    sql_question_service: SqlQuestionService
+    ask_service: services.AskService
+    ask_details_service: services.AskDetailsService
+    question_recommendation: services.QuestionRecommendation
+    relationship_recommendation: services.RelationshipRecommendation
+    semantics_description: services.SemanticsDescription
+    semantics_preparation_service: services.SemanticsPreparationService
+    chart_service: services.ChartService
+    chart_adjustment_service: services.ChartAdjustmentService
+    sql_answer_service: services.SqlAnswerService
+    sql_expansion_service: services.SqlExpansionService
+    sql_explanation_service: services.SqlExplanationService
+    sql_regeneration_service: services.SqlRegenerationService
+    sql_pairs_service: services.SqlPairsService
+    sql_question_service: services.SqlQuestionService
 
 
 @dataclass
@@ -58,15 +45,15 @@ def create_service_container(
         "ttl": settings.query_cache_ttl,
     }
     return ServiceContainer(
-        semantics_description=SemanticsDescription(
+        semantics_description=services.SemanticsDescription(
             pipelines={
                 "semantics_description": generation.SemanticsDescription(
                     **pipe_components["semantics_description"],
                 )
             },
             **query_cache,
         ),
-        semantics_preparation_service=SemanticsPreparationService(
+        semantics_preparation_service=services.SemanticsPreparationService(
             pipelines={
                 "db_schema": indexing.DBSchema(
                     **pipe_components["db_schema_indexing"],
@@ -85,7 +72,7 @@ def create_service_container(
             },
             **query_cache,
         ),
-        ask_service=AskService(
+        ask_service=services.AskService(
             pipelines={
                 "intent_classification": generation.IntentClassification(
                     **pipe_components["intent_classification"],
@@ -127,7 +114,7 @@ def create_service_container(
             allow_sql_generation_reasoning=settings.allow_sql_generation_reasoning,
             **query_cache,
         ),
-        chart_service=ChartService(
+        chart_service=services.ChartService(
             pipelines={
                 "sql_executor": retrieval.SQLExecutor(
                     **pipe_components["sql_executor"],
@@ -139,7 +126,7 @@ def create_service_container(
             },
             **query_cache,
         ),
-        chart_adjustment_service=ChartAdjustmentService(
+        chart_adjustment_service=services.ChartAdjustmentService(
             pipelines={
                 "sql_executor": retrieval.SQLExecutor(
                     **pipe_components["sql_executor"],
@@ -151,7 +138,7 @@ def create_service_container(
             },
             **query_cache,
         ),
-        sql_answer_service=SqlAnswerService(
+        sql_answer_service=services.SqlAnswerService(
             pipelines={
                 "preprocess_sql_data": retrieval.PreprocessSqlData(
                     **pipe_components["preprocess_sql_data"],
@@ -163,7 +150,7 @@ def create_service_container(
             },
             **query_cache,
         ),
-        ask_details_service=AskDetailsService(
+        ask_details_service=services.AskDetailsService(
             pipelines={
                 "sql_breakdown": generation.SQLBreakdown(
                     **pipe_components["sql_breakdown"],
@@ -175,7 +162,7 @@ def create_service_container(
             },
             **query_cache,
         ),
-        sql_expansion_service=SqlExpansionService(
+        sql_expansion_service=services.SqlExpansionService(
             pipelines={
                 "retrieval": retrieval.Retrieval(
                     **pipe_components["db_schema_retrieval"],
@@ -196,23 +183,23 @@ def create_service_container(
             },
             **query_cache,
         ),
-        sql_explanation_service=SqlExplanationService(
+        sql_explanation_service=services.SqlExplanationService(
             pipelines={
                 "sql_explanation": generation.SQLExplanation(
                     **pipe_components["sql_explanation"],
                 )
             },
             **query_cache,
         ),
-        sql_regeneration_service=SqlRegenerationService(
+        sql_regeneration_service=services.SqlRegenerationService(
             pipelines={
                 "sql_regeneration": generation.SQLRegeneration(
                     **pipe_components["sql_regeneration"],
                 )
             },
             **query_cache,
         ),
-        relationship_recommendation=RelationshipRecommendation(
+        relationship_recommendation=services.RelationshipRecommendation(
             pipelines={
                 "relationship_recommendation": generation.RelationshipRecommendation(
                     **pipe_components["relationship_recommendation"],
@@ -221,7 +208,7 @@ def create_service_container(
             },
             **query_cache,
         ),
-        question_recommendation=QuestionRecommendation(
+        question_recommendation=services.QuestionRecommendation(
             pipelines={
                 "question_recommendation": generation.QuestionRecommendation(
                     **pipe_components["question_recommendation"],
@@ -242,18 +229,16 @@ def create_service_container(
             },
             **query_cache,
         ),
-        sql_pairs_preparation_service=SqlPairsPreparationService(
+        sql_pairs_service=services.SqlPairsService(
             pipelines={
-                "sql_pairs_preparation": indexing.SqlPairs(
+                "sql_pairs": indexing.SqlPairs(
                     **pipe_components["sql_pairs_indexing"],
-                ),
-                "sql_pairs_deletion": indexing.SqlPairsDeletion(
-                    **pipe_components["sql_pairs_deletion"],
-                ),
+                    sql_pairs_path=settings.sql_pairs_path,
+                )
             },
             **query_cache,
         ),
-        sql_question_service=SqlQuestionService(
+        sql_question_service=services.SqlQuestionService(
             pipelines={
                 "sql_question_generation": generation.SQLQuestion(
                     **pipe_components["sql_question_generation"],

wren-ai-service/src/pipelines/common.py

@@ -33,21 +33,26 @@ def build_table_ddl(
     ), has_calculated_field
 
 
-def dry_run_pipeline(pipeline_cls: BasicPipeline, pipeline_name: str, **kwargs):
+def dry_run_pipeline(
+    pipeline_cls: BasicPipeline,
+    pipeline_name: str,
+    method: str = "run",
+    **kwargs,
+):
     from langfuse.decorators import langfuse_context
 
     from src.config import settings
     from src.core.pipeline import async_validate
     from src.providers import generate_components
     from src.utils import init_langfuse, setup_custom_logger
 
-    setup_custom_logger("wren-ai-service", level_str=settings.logging_level)
+    setup_custom_logger("wren-ai-service", level_str=settings.logging_level, is_dev=True)
 
     pipe_components = generate_components(settings.components)
     pipeline = pipeline_cls(**pipe_components[pipeline_name])
     init_langfuse(settings)
 
-    async_validate(lambda: pipeline.run(**kwargs))
+    async_validate(lambda: getattr(pipeline, method)(**kwargs))
 
     langfuse_context.flush()
 

wren-ai-service/src/pipelines/indexing/__init__.py

@@ -87,41 +87,15 @@ async def run(
         return {"documents_written": documents_written}
 
 
-@component
-class SqlPairsCleaner:
-    def __init__(self, sql_pairs_store: DocumentStore) -> None:
-        self._sql_pairs_store = sql_pairs_store
-
-    @component.output_types()
-    async def run(
-        self, sql_pair_ids: List[str], project_id: Optional[str] = None
-    ) -> None:
-        filters = {
-            "operator": "AND",
-            "conditions": [
-                {"field": "sql_pair_id", "operator": "in", "value": sql_pair_ids},
-            ],
-        }
-
-        if project_id:
-            filters["conditions"].append(
-                {"field": "project_id", "operator": "==", "value": project_id}
-            )
-
-        return await self._sql_pairs_store.delete_documents(filters)
-
-
 # Put the pipelines imports here to avoid circular imports and make them accessible directly to the rest of packages
 from .db_schema import DBSchema  # noqa: E402
 from .historical_question import HistoricalQuestion  # noqa: E402
 from .sql_pairs import SqlPairs  # noqa: E402
-from .sql_pairs_deletion import SqlPairsDeletion  # noqa: E402
 from .table_description import TableDescription  # noqa: E402
 
 __all__ = [
     "DBSchema",
     "TableDescription",
     "HistoricalQuestion",
-    "SqlPairsDeletion",
     "SqlPairs",
 ]