Features/analytic views and table

tests/test_document_related.py

@@ -11,6 +11,9 @@
 from welearn_database.data.models.corpus_related import Category, Corpus
 from welearn_database.data.models.document_related import (
     ErrorDataQuality,
+    HistoricalQtyDocumentInQdrant,
+    HistoricalQtyDocumentInQdrantPerCorpus,
+    HistoricalQtyDocumentPerCorpus,
     ProcessState,
     WeLearnDocument,
 )
@@ -467,3 +470,66 @@ def test_error_data_quality(self):
         self.assertEqual(error_from_db.error_info, "Test Error")
         self.assertEqual(error_from_db.error_raiser, "welearn_database_test")
         self.assertEqual(error_from_db.document.id, doc_ids[0])
+
+    def test_historical_qty_document_per_corpus(self):
+        engine = create_engine("sqlite://")
+        s_maker = sessionmaker(engine)
+        handle_schema_with_sqlite(engine)
+
+        test_session = s_maker()
+        Base.metadata.create_all(test_session.get_bind())
+
+        test_hqdpc = HistoricalQtyDocumentPerCorpus(
+            id=uuid.uuid4(),
+            source_name="corpus_test",
+            quantity=100,
+        )
+        test_session.add(test_hqdpc)
+        test_session.commit()
+
+        hqpdc_from_db = test_session.query(HistoricalQtyDocumentPerCorpus).first()
+
+        self.assertEqual(hqpdc_from_db.source_name, "corpus_test")
+        self.assertEqual(hqpdc_from_db.quantity, 100)
+
+    def test_historical_qty_document_in_qdrant_per_corpus(self):
+        engine = create_engine("sqlite://")
+        s_maker = sessionmaker(engine)
+        handle_schema_with_sqlite(engine)
+
+        test_session = s_maker()
+        Base.metadata.create_all(test_session.get_bind())
+
+        test_hqdpc = HistoricalQtyDocumentInQdrantPerCorpus(
+            id=uuid.uuid4(),
+            source_name="corpus_test",
+            quantity=100,
+        )
+        test_session.add(test_hqdpc)
+        test_session.commit()
+
+        hqdiqpc_from_db = test_session.query(
+            HistoricalQtyDocumentInQdrantPerCorpus
+        ).first()
+
+        self.assertEqual(hqdiqpc_from_db.source_name, "corpus_test")
+        self.assertEqual(hqdiqpc_from_db.quantity, 100)
+
+    def test_historical_qty_document_in_qdrant(self):
+        engine = create_engine("sqlite://")
+        s_maker = sessionmaker(engine)
+        handle_schema_with_sqlite(engine)
+
+        test_session = s_maker()
+        Base.metadata.create_all(test_session.get_bind())
+
+        test_hqdpc = HistoricalQtyDocumentInQdrant(
+            id=uuid.uuid4(),
+            quantity=100,
+        )
+        test_session.add(test_hqdpc)
+        test_session.commit()
+
+        hqdiq_from_db = test_session.query(HistoricalQtyDocumentInQdrant).first()
+
+        self.assertEqual(hqdiq_from_db.quantity, 100)

welearn_database/alembic/versions/5aad97149044_add_histo_table_for_materialized_views.py

@@ -0,0 +1,71 @@
+"""add_histo_table_for_materialized_views
+
+Revision ID: 5aad97149044
+Revises: b84462ca3800
+Create Date: 2026-06-17 11:31:55.292978
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy import text
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision: str = "5aad97149044"
+down_revision: Union[str, None] = "b84462ca3800"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.create_table(
+        "historical_qty_document_per_corpus",
+        sa.Column(
+            "id", sa.Uuid(), server_default=text("gen_random_uuid()"), nullable=False
+        ),
+        sa.Column("source_name", sa.String(), nullable=False),
+        sa.Column("quantity", sa.Integer(), nullable=False),
+        sa.Column(
+            "created_at", postgresql.TIMESTAMP(), server_default="NOW()", nullable=False
+        ),
+        sa.PrimaryKeyConstraint("id"),
+        schema="document_related",
+    )
+
+    op.create_table(
+        "historical_qty_document_in_qdrant_per_corpus",
+        sa.Column(
+            "id", sa.Uuid(), server_default=text("gen_random_uuid()"), nullable=False
+        ),
+        sa.Column("source_name", sa.String(), nullable=False),
+        sa.Column("quantity", sa.Integer(), nullable=False),
+        sa.Column(
+            "created_at", postgresql.TIMESTAMP(), server_default="NOW()", nullable=False
+        ),
+        sa.PrimaryKeyConstraint("id"),
+        schema="document_related",
+    )
+
+    op.create_table(
+        "historical_qty_document_in_qdrant",
+        sa.Column(
+            "id", sa.Uuid(), server_default=text("gen_random_uuid()"), nullable=False
+        ),
+        sa.Column("quantity", sa.Integer(), nullable=False),
+        sa.Column(
+            "created_at", postgresql.TIMESTAMP(), server_default="NOW()", nullable=False
+        ),
+        sa.PrimaryKeyConstraint("id"),
+        schema="document_related",
+    )
+
+
+def downgrade() -> None:
+    op.drop_table("historical_qty_document_per_corpus", schema="document_related")
+    op.drop_table(
+        "historical_qty_document_in_qdrant_per_corpus", schema="document_related"
+    )
+    op.drop_table("historical_qty_document_in_qdrant", schema="document_related")

welearn_database/alembic/versions/6d4346fad6f4_view_used_feature_per_session.py

@@ -0,0 +1,88 @@
+"""view_used_feature_per_session
+
+Revision ID: 6d4346fad6f4
+Revises: 5aad97149044
+Create Date: 2026-06-17 11:54:52.441998
+
+"""
+
+from typing import Sequence, Union
+
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = "6d4346fad6f4"
+down_revision: Union[str, None] = "5aad97149044"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.execute("""
+        CREATE OR REPLACE VIEW grafana.used_feature_per_session
+        AS WITH matching_features_endpoint AS (
+SELECT
+	endpoint_name,
+	feature_name
+FROM
+	(
+VALUES
+	('/api/v1/search/by_document', 'search'),
+	('/api/v1/qna/chat/answer', 'chat'),
+	('/api/v1/qna/chat/agent', 'chat'),
+	('/api/v1/tutor/syllabus', 'syllabus'),
+	('/api/v1/user/bookmarks/:document_id', 'bookmark'),
+	('/api/v1/user/:user_id/bookmarks/:document_id', 'bookmark')
+	) AS t(endpoint_name, feature_name)
+),
+session_feature_pair AS (
+SELECT
+	DISTINCT
+	er.session_id,
+	mfe.feature_name
+FROM
+	user_related.endpoint_request er
+CROSS JOIN matching_features_endpoint mfe
+ORDER BY
+	er.session_id
+),
+actual_count AS (
+SELECT
+	er.session_id,
+	mfe.feature_name,
+	COUNT(1) AS cnt
+FROM
+	user_related.endpoint_request er
+INNER JOIN
+	user_related."session" s ON
+	s.id = er.session_id
+INNER JOIN
+	matching_features_endpoint mfe ON
+	mfe.endpoint_name = er.endpoint_name
+GROUP BY
+	er.session_id,
+	mfe.feature_name 
+)
+SELECT 
+	s.inferred_user_id,
+	sfp.session_id,
+	sfp.feature_name,
+	COALESCE(ac.cnt, 0) AS cnt,
+	COALESCE(ac.cnt, 0) > 0 AS is_feature_used,
+	s.created_at AS session_created_at
+FROM
+	session_feature_pair sfp
+LEFT JOIN actual_count ac ON
+	ac.feature_name = sfp.feature_name
+	AND ac.session_id = sfp.session_id
+INNER JOIN user_related."session" s ON
+	s.id = sfp.session_id
+ORDER BY
+	session_created_at
+        """)
+
+
+def downgrade() -> None:
+    op.execute("""
+    DROP VIEW IF EXISTS grafana.used_feature_per_session;
+    """)

welearn_database/data/models/document_related.py

@@ -44,7 +44,7 @@ class WeLearnDocument(Base):
     """
     This class represents a document in the WeLearn system.
     :cvar id: The unique identifier of the document.
-    :cvar doi: The unique DOI identifier if it exist for this document
+    :cvar doi: The unique DOI identifier if it exists for this document
     :cvar external_id: ID use by the document provider for identify it (ex: PubMed ID, ArXiv ID, OAI PMH identifier etc.)
     :cvar external_id_type: The type of the external ID, represented as an enumeration
     :cvar url: The URL of the document.
@@ -478,6 +478,65 @@ class ContextDocument(Base):
     )
 
 
+class HistoricalQtyDocumentPerCorpus(Base):
+    __tablename__ = "historical_qty_document_per_corpus"
+    __table_args__ = {"schema": schema_name}
+
+    id = mapped_column(
+        types.Uuid,
+        primary_key=True,
+        server_default=GEN_RANDOM_UUID,
+        nullable=False,
+    )
+    source_name: Mapped[str] = mapped_column()
+    quantity: Mapped[int]
+    created_at: Mapped[datetime] = mapped_column(
+        TIMESTAMP(timezone=False),
+        nullable=False,
+        default=func.localtimestamp(),
+        server_default=NOW,
+    )
+
+
+class HistoricalQtyDocumentInQdrantPerCorpus(Base):
+    __tablename__ = "historical_qty_document_in_qdrant_per_corpus"
+    __table_args__ = {"schema": schema_name}
+
+    id = mapped_column(
+        types.Uuid,
+        primary_key=True,
+        server_default=GEN_RANDOM_UUID,
+        nullable=False,
+    )
+    source_name: Mapped[str] = mapped_column()
+    quantity: Mapped[int]
+    created_at: Mapped[datetime] = mapped_column(
+        TIMESTAMP(timezone=False),
+        nullable=False,
+        default=func.localtimestamp(),
+        server_default=NOW,
+    )
+
+
+class HistoricalQtyDocumentInQdrant(Base):
+    __tablename__ = "historical_qty_document_in_qdrant"
+    __table_args__ = {"schema": schema_name}
+
+    id = mapped_column(
+        types.Uuid,
+        primary_key=True,
+        server_default=GEN_RANDOM_UUID,
+        nullable=False,
+    )
+    quantity: Mapped[int]
+    created_at: Mapped[datetime] = mapped_column(
+        TIMESTAMP(timezone=False),
+        nullable=False,
+        default=func.localtimestamp(),
+        server_default=NOW,
+    )
+
+
 # Views
 class QtyDocumentInQdrant(Base):
     __tablename__ = "qty_document_in_qdrant"

welearn_database/data/models/grafana.py

@@ -136,3 +136,18 @@ class Session(Base):
     created_at: Mapped[datetime] = mapped_column()
     end_at: Mapped[datetime | None] = mapped_column(nullable=True)
     host: Mapped[str | None] = mapped_column(nullable=True)
+
+
+class UsedFeaturePerSession(Base):
+    __tablename__ = "used_feature_per_session"
+    __table_args__ = {"schema": schema_name}
+    __read_only__ = True
+
+    inferred_user_id: Mapped[uuid.UUID] = mapped_column(
+        UUID(as_uuid=True), primary_key=True
+    )
+    session_id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True)
+    feature_name: Mapped[str] = mapped_column(primary_key=True)
+    cnt: Mapped[int] = mapped_column()
+    is_feature_used: Mapped[bool] = mapped_column()
+    session_created_at: Mapped[datetime] = mapped_column()