Repository: run-llama/llama_index
Pull request: Update DuckDB VectorStore
# Description

Bump to latest version.

1. Switch to Relational API where possible.
2. Setup DuckDB Client once
3. Add delete, delete_nodes, clear, get_nodes
4. Add unit tests

Fixes #19105

To-do:

- [x] Add additional metadata filter operators
- [x] Add additional tests

As for Full Text Search, DuckDB requires you to "refresh" the FTS index after every insert / delete so I'll hold off on Hybrid / FTS support for now.

## Version Bump?

Did I bump the version in the `pyproject.toml` file of the package I am updating? (Except for the `llama-index-core` package)

- [x] Yes
- [ ] No

## Type of Change

Please delete options that are not relevant.

- [x] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
- [ ] This change requires a documentation update

## How Has This Been Tested?

Your pull-request will likely not be merged unless it is covered by some form of impactful unit testing.

- [x] I added new unit tests to cover this change
- [ ] I believe this change is already covered by existing unit tests

## Suggested Checklist:

- [x] I have performed a self-review of my own code
- [x] I have commented my code, particularly in hard-to-understand areas
- [ ] I have made corresponding changes to the documentation
- [ ] I have added Google Colab support for the newly added notebooks.
- [x] My changes generate no new warnings
- [x] I have added tests that prove my fix is effective or that my feature works
- [x] New and existing unit tests pass locally with my changes
- [x] I ran `uv run make format; uv run make lint` to appease the lint gods


Problem statement:
[Feature Request]: DuckDB Vector Store Enhancements
### Feature Description

Hi, I'm interested in updating the DuckDB Vector Store integration.

I'd like to refactor it to:
1. Not re-initialize DuckDB from scratch for every query
2. Use the relational API instead of f-string to build SQL Queries
3. Add missing functionality like `get_nodes` and `delete_nodes`

Would ya'll be open to a PR to this effect?

### Reason

_No response_

### Value of Feature

_No response_

Hints from issue discussion:
Do it! 👏
Ok, draft up in 19106 -- will add more tests tomorrow and will run it in my environment for a bit

Commit message: Merge branch 'main' into update-duckdb-vectorstore

Patch to review:
diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py
index 8a8c13a81f..66c0accf2a 100644
--- a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py
+++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py
@@ -1,58 +1,100 @@
 """DuckDB vector store."""
 
+from ast import Expression
 import json
 import logging
-import os
-from typing import Any, List, Optional, cast
+import operator as py_operator
+from pathlib import Path
+from typing import Any
 
+import duckdb
+from duckdb import (
+    ColumnExpression,
+    ConstantExpression,
+    FunctionExpression,
+    StarExpression,
+    Expression,
+    CaseExpression,
+)
+from duckdb.typing import FLOAT, INTEGER, VARCHAR, SQLNULL
 from fsspec.utils import Sequence
-from llama_index.core.bridge.pydantic import PrivateAttr
+from llama_index.core.bridge.pydantic import (
+    PrivateAttr,
+    StrictInt,
+    StrictFloat,
+    StrictStr,
+)
 from llama_index.core.schema import BaseNode, MetadataMode
 from llama_index.core.vector_stores.types import (
     BasePydanticVectorStore,
     MetadataFilter,
     MetadataFilters,
+    FilterOperator,
     VectorStoreQuery,
     VectorStoreQueryResult,
+    FilterCondition,
 )
 from llama_index.core.vector_stores.utils import (
     metadata_dict_to_node,
     node_to_metadata_dict,
 )
 
-import duckdb
-
 logger = logging.getLogger(__name__)
-import_err_msg = "`duckdb` package not found, please run `pip install duckdb`"
-
 
-class DuckDBLocalContext:
-    def __init__(self, database_path: str):
-        self.database_path = database_path
-        self._conn = None
-        self._home_dir = os.path.expanduser("~")
-
-    def __enter__(self) -> "duckdb.DuckDBPyConnection":
-        if not os.path.exists(os.path.dirname(self.database_path)):
-            raise ValueError(
-                f"Directory {os.path.dirname(self.database_path)} does not exist."
-            )
+DEFAULT_TEXT_SEARCH_CONFIG = {
+    "stemmer": "english",
+    "stopwords": "english",
+    "ignore": "(\\.|[^a-z])+",
+    "strip_accents": True,
+    "lower": True,
+    "overwrite": False,
+}
+
+li_filter_to_py_operator = {
+    FilterOperator.GT: py_operator.gt,
+    FilterOperator.GTE: py_operator.ge,
+    FilterOperator.LT: py_operator.lt,
+    FilterOperator.LTE: py_operator.le,
+    FilterOperator.EQ: py_operator.eq,
+    FilterOperator.NE: py_operator.ne,
+}
+
+filter_value_type_to_duckdb_type = {
+    StrictInt: INTEGER,
+    StrictFloat: FLOAT,
+    StrictStr: VARCHAR,
+    int: INTEGER,
+    float: FLOAT,
+    str: VARCHAR,
+    None: SQLNULL,
+}
+
+
+class DuckDBInvalidConfigurationError(Exception):
+    def __init__(self, database_name: str, persist_dir: str):
+        self.database_name = database_name
+        self.persist_dir = persist_dir
+        super().__init__(
+            f"Invalid configuration for DuckDBVectorStore. database_name: {database_name}, persist_dir: {persist_dir}"
+        )
 
-        # if not os.path.isfile(self.database_path):
-        #     raise ValueError(f"Database path {self.database_path} is not a valid file.")
 
-        self._conn = duckdb.connect(self.database_path)
-        self._conn.execute(f"SET home_directory='{self._home_dir}';")
-        self._conn.install_extension("json")
-        self._conn.load_extension("json")
-        self._conn.install_extension("fts")
-        self._conn.load_extension("fts")
+class DuckDBTableNotInitializedError(Exception):
+    def __init__(self, table_name: str):
+        self.table_name = table_name
+        super().__init__(f"Table {table_name} is not initialized.")
 
-        return self._conn
 
-    def __exit__(self, exc_type, exc_val, exc_tb) -> None:
-        if self._conn:
-            self._conn.close()
+class DuckDBTableIncorrectColumnsError(Exception):
+    def __init__(
+        self, table_name: str, expected_columns: list[str], actual_columns: list[str]
+    ):
+        self.table_name = table_name
+        self.expected_columns = expected_columns
+        self.actual_columns = actual_columns
+        super().__init__(
+            f"Table {table_name} has incorrect columns. Expected {expected_columns}, got {actual_columns}."
+        )
 
 
 class DuckDBVectorStore(BasePydanticVectorStore):
@@ -82,62 +124,31 @@ class DuckDBVectorStore(BasePydanticVectorStore):
     stores_text: bool = True
     flat_metadata: bool = True
 
-    database_name: Optional[str]
+    database_name: str
     table_name: str
     # schema_name: Optional[str] # TODO: support schema name
-    embed_dim: Optional[int]
+    embed_dim: int | None
     # hybrid_search: Optional[bool] # TODO: support hybrid search
-    text_search_config: Optional[dict]
-    persist_dir: Optional[str]
+    text_search_config: dict | None
+    persist_dir: str
+
+    _conn: duckdb.DuckDBPyConnection = PrivateAttr()
+    _table: duckdb.DuckDBPyRelation | None = PrivateAttr(default=None)
 
-    _conn: Any = PrivateAttr()
     _is_initialized: bool = PrivateAttr(default=False)
-    _database_path: Optional[str] = PrivateAttr()
+    _database_path: str | None = PrivateAttr()
 
     def __init__(
         self,
         database_name: str = ":memory:",
         table_name: str = "documents",
-        embed_dim: Optional[int] = None,
+        embed_dim: int | None = None,
         # https://duckdb.org/docs/extensions/full_text_search
-        text_search_config: Optional[dict] = {
-            "stemmer": "english",
-            "stopwords": "english",
-            "ignore": "(\\.|[^a-z])+",
-            "strip_accents": True,
-            "lower": True,
-            "overwrite": False,
-        },
+        text_search_config: dict | None = None,
         persist_dir: str = "./storage",
-        **kwargs: Any,
+        **kwargs: Any,  # noqa: ARG002
     ) -> None:
         """Init params."""
-        try:
-            import duckdb
-        except ImportError:
-            raise ImportError(import_err_msg)
-
-        database_path = None
-        if database_name == ":memory:":
-            _home_dir = os.path.expanduser("~")
-            conn = duckdb.connect(database_name)
-            conn.execute(f"SET home_directory='{_home_dir}';")
-            conn.install_extension("json")
-            conn.load_extension("json")
-            conn.install_extension("fts")
-            conn.load_extension("fts")
-        else:
-            # check if persist dir exists
-            if not os.path.exists(persist_dir):
-                os.makedirs(persist_dir)
-
-            database_path = os.path.join(persist_dir, database_name)
-
-            with DuckDBLocalContext(database_path) as _conn:
-                pass
-
-            conn = None
-
         fields = {
             "database_name": database_name,
             "table_name": table_name,
@@ -145,10 +156,11 @@ def __init__(
             "text_search_config": text_search_config,
             "persist_dir": persist_dir,
         }
+
         super().__init__(stores_text=True, **fields)
-        self._is_initialized = False
-        self._conn = conn
-        self._database_path = database_path
+
+        self._connect()
+        self._initialize()
 
     @classmethod
     def from_local(
@@ -156,44 +168,22 @@ def from_local(
         database_path: str,
         table_name: str = "documents",
         # schema_name: Optional[str] = "main",
-        embed_dim: Optional[int] = None,
+        embed_dim: int | None = None,
         # hybrid_search: Optional[bool] = False,
-        text_search_config: Optional[dict] = {
-            "stemmer": "english",
-            "stopwords": "english",
-            "ignore": "(\\.|[^a-z])+",
-            "strip_accents": True,
-            "lower": True,
-            "overwrite": False,
-        },
+        text_search_config: dict | None = DEFAULT_TEXT_SEARCH_CONFIG,
         **kwargs: Any,
     ) -> "DuckDBVectorStore":
         """Load a DuckDB vector store from a local file."""
-        with DuckDBLocalContext(database_path) as _conn:
-            try:
-                _table_info = _conn.execute(f"SHOW {table_name};").fetchall()
-            except Exception as e:
-                raise ValueError(f"Index table {table_name} not found in the database.")
-
-            # Not testing for the column type similarity only testing for the column names.
-            _std = {"text", "node_id", "embedding", "metadata_"}
-            _ti = {_i[0] for _i in _table_info}
-            if _std != _ti:
-                raise ValueError(
-                    f"Index table {table_name} does not have the correct schema."
-                )
+        db_path = Path(database_path)
 
-        _cls = cls(
-            database_name=os.path.basename(database_path),
+        return cls(
+            database_name=db_path.name,
             table_name=table_name,
             embed_dim=embed_dim,
             text_search_config=text_search_config,
-            persist_dir=os.path.dirname(database_path),
+            persist_dir=str(db_path.parent),
             **kwargs,
         )
-        _cls._is_initialized = True
-
-        return _cls
 
     @classmethod
     def from_params(
@@ -201,16 +191,9 @@ def from_params(
         database_name: str = ":memory:",
         table_name: str = "documents",
         # schema_name: Optional[str] = "main",
-        embed_dim: Optional[int] = None,
+        embed_dim: int | None = None,
         # hybrid_search: Optional[bool] = False,
-        text_search_config: Optional[dict] = {
-            "stemmer": "english",
-            "stopwords": "english",
-            "ignore": "(\\.|[^a-z])+",
-            "strip_accents": True,
-            "lower": True,
-            "overwrite": False,
-        },
+        text_search_config: dict | None = DEFAULT_TEXT_SEARCH_CONFIG,
         persist_dir: str = "./storage",
         **kwargs: Any,
     ) -> "DuckDBVectorStore":
@@ -234,37 +217,52 @@ def client(self) -> Any:
         """Return client."""
         return self._conn
 
+    def _connect(self) -> None:
+        """Connect to the DuckDB database -- create the data persistence directory if it doesn't exist."""
+        database_connection = self.database_name
+
+        if self.database_name != ":memory:":
+            persist_path = Path(self.persist_dir)
+
+            if not persist_path.exists():
+                persist_path.mkdir(parents=True, exist_ok=True)
+
+            database_connection = str(persist_path / self.database_name)
+
+        self._conn = duckdb.connect(database_connection)
+
     def _initialize(self) -> None:
-        if not self._is_initialized:
-            # TODO: schema.table also.
-            # Check if table and type is present
-            # if not, create table
-            if self.embed_dim is None:
-                _query = f"""
-                    CREATE TABLE {self.table_name} (
-                        node_id VARCHAR,
-                        text TEXT,
-                        embedding FLOAT[],
-                        metadata_ JSON
-                        );
-                    """
-            else:
-                _query = f"""
-                    CREATE TABLE {self.table_name} (
-                        node_id VARCHAR,
-                        text TEXT,
-                        embedding FLOAT[{self.embed_dim}],
-                        metadata_ JSON
-                        );
-                    """
-
-            if self.database_name == ":memory:":
-                self._conn.execute(_query)
-            elif self._database_path is not None:
-                with DuckDBLocalContext(self._database_path) as _conn:
-                    _conn.execute(_query)
-
-            self._is_initialized = True
+        """Initialize the DuckDB Database, extensions, and documents table."""
+        home_dir = Path.home()
+        self._conn.execute(f"SET home_directory='{home_dir}';")
+        self._conn.install_extension("json")
+        self._conn.load_extension("json")
+        self._conn.install_extension("fts")
+        self._conn.load_extension("fts")
+
+        embedding_type = (
+            f"FLOAT[{self.embed_dim}]" if self.embed_dim is not None else "FLOAT[]"
+        )
+
+        self._conn.execute(f"""
+            CREATE TABLE IF NOT EXISTS {self.table_name}  (
+                node_id VARCHAR,
+                text TEXT,
+                embedding {embedding_type},
+                metadata_ JSON
+            );
+        """)
+
+        self._table = self._conn.table(self.table_name)
+
+        required_columns = ["node_id", "text", "embedding", "metadata_"]
+        table_columns = self._table.describe().columns
+
+        for column in required_columns:
+            if column not in table_columns:
+                raise DuckDBTableIncorrectColumnsError(
+                    self.table_name, required_columns, table_columns
+                )
 
     def _node_to_table_row(self, node: BaseNode) -> Any:
         return (
@@ -281,35 +279,121 @@ def _node_to_table_row(self, node: BaseNode) -> Any:
     def _table_row_to_node(self, row: Any) -> BaseNode:
         return metadata_dict_to_node(json.loads(row[3]), row[1])
 
-    def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> List[str]:
-        """
-        Add nodes to index.
+    def _table_row_to_query_result(self, rows: list[Any]) -> VectorStoreQueryResult:
+        nodes = []
+        similarities = []
+        ids = []
 
-        Args:
-            nodes: List[BaseNode]: list of nodes with embeddings
+        for row in rows:
+            node = self._table_row_to_node(row)
+            nodes.append(node)
+            ids.append(row[0])
+            similarities.append(row[4])
 
-        """
-        self._initialize()
+        return VectorStoreQueryResult(nodes=nodes, similarities=similarities, ids=ids)
 
-        ids = []
+    def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:  # noqa: ARG002
+        """Query the vector store for top k most similar nodes."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_metadata_filter_expressions(
+            metadata_filters=query.filters
+        )
+
+        inner_query = self._table.select(
+            StarExpression(),
+            FunctionExpression(
+                "list_cosine_similarity",
+                ColumnExpression("embedding"),
+                ConstantExpression(query.query_embedding),
+            ).alias("score"),
+        ).filter(filter_expression)
+
+        outer_query = (
+            inner_query.select(
+                ColumnExpression("node_id"),
+                ColumnExpression("text"),
+                ColumnExpression("embedding"),
+                ColumnExpression("metadata_"),
+                ColumnExpression("score"),
+            )
+            .filter(
+                ColumnExpression("score").isnotnull(),
+            )
+            .sort(
+                ColumnExpression("score").desc(),
+            )
+            .limit(
+                query.similarity_top_k,
+            )
+        )
+
+        command = outer_query.sql_query()
+
+        rows = self._conn.execute(command).fetchall()
 
-        if self.database_name == ":memory:":
-            _table = self._conn.table(self.table_name)
-            for node in nodes:
-                ids.append(node.node_id)
-                _row = self._node_to_table_row(node)
-                _table.insert(_row)
-        elif self._database_path is not None:
-            with DuckDBLocalContext(self._database_path) as _conn:
-                _table = _conn.table(self.table_name)
-                for node in nodes:
-                    ids.append(node.node_id)
-                    _row = self._node_to_table_row(node)
-                    _table.insert(_row)
-
-        return ids
-
-    def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
+        return self._table_row_to_query_result(rows)
+
+    def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> list[str]:  # noqa: ARG002
+        """Add nodes to the vector store."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        [self._table.insert(self._node_to_table_row(node)) for node in nodes]
+
+        return [node.node_id for node in nodes]
+
+    def get_nodes(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+        **get_kwargs: Any,
+    ) -> list[BaseNode]:  # noqa: ARG002
+        """Get nodes using node_ids and/or filters. If both are provided, both are considered."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_node_id_metadata_filter_expression(
+            node_ids=node_ids,
+            filters=filters,
+        )
+
+        command = self._table.filter(filter_expression).sql_query()
+
+        rows = self._conn.execute(command).fetchall()
+
+        return [self._table_row_to_node(row) for row in rows]
+
+    def delete_nodes(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+        **delete_kwargs: Any,
+    ) -> None:  # noqa: ARG002
+        """Delete nodes using node_ids and/or filters. If both are provided, both are considered."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_node_id_metadata_filter_expression(
+            node_ids=node_ids,
+            filters=filters,
+        )
+
+        command = f"DELETE FROM {self.table_name} WHERE {filter_expression}"
+
+        self._conn.execute(command)
+
+    def clear(self, **clear_kwargs: Any) -> None:  # noqa: ARG002
+        """Clear the vector store."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        command = f"DELETE FROM {self.table_name}"
+
+        self._conn.execute(command)
+
+    def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:  # noqa: ARG002
         """
         Delete nodes using with ref_doc_id.
 
@@ -317,116 +401,207 @@ def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
             ref_doc_id (str): The doc_id of the document to delete.
 
         """
-        _ddb_query = f"""
-            DELETE FROM {self.table_name}
-            WHERE json_extract_string(metadata_, '$.ref_doc_id') = ?;
-            """
-        if self.database_name == ":memory:":
-            self._conn.execute(_ddb_query, [ref_doc_id])
-        elif self._database_path is not None:
-            with DuckDBLocalContext(self._database_path) as _conn:
-                _conn.execute(_ddb_query, [ref_doc_id])
-
-    @staticmethod
-    def _build_metadata_filter_condition(
-        standard_filters: MetadataFilters,
-    ) -> str:
-        """Translate standard metadata filters to DuckDB SQL specification."""
-        filters_list = []
-        # condition = standard_filters.condition or "and"  ## and/or as strings.
-        condition = "AND"
-        _filters_condition_list = []
-
-        for filter in standard_filters.filters:
-            filter = cast(MetadataFilter, filter)
-            if filter.operator:
-                if filter.operator in [
-                    "<",
-                    ">",
-                    "<=",
-                    ">=",
-                    "<>",
-                    "!=",
-                ]:
-                    filters_list.append((filter.key, filter.operator, filter.value))
-                elif filter.operator in ["=="]:
-                    filters_list.append((filter.key, "=", filter.value))
-                else:
-                    raise ValueError(
-                        f"Filter operator {filter.operator} not supported."
-                    )
-            else:
-                filters_list.append((filter.key, "=", filter.value))
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        where_clause = self._build_metadata_filter_expression(
+            "ref_doc_id", ref_doc_id, FilterOperator.EQ
+        )
+
+        command = f"DELETE FROM {self.table_name} WHERE {where_clause}"
+
+        self._conn.execute(command)
+
+    def _build_node_id_metadata_filter_expression(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+    ) -> Expression:
+        filter_expression = Expression(True)
+
+        if filters is not None:
+            filter_expression = self._build_metadata_filter_expressions(
+                metadata_filters=filters
+            )
+
+        if node_ids is not None:
+            node_id_expression = FunctionExpression(
+                "list_contains",
+                ConstantExpression(node_ids),
+                ColumnExpression("node_id"),
+            )
+
+            filter_expression = filter_expression.__and__(node_id_expression)
+
+        return filter_expression
 
-        for _fc in filters_list:
-            if isinstance(_fc[2], str):
-                _filters_condition_list.append(
-                    f"json_extract_string(metadata_, '$.{_fc[0]}') {_fc[1]} '{_fc[2]}'"
+    def _build_metadata_filter_expression(
+        self, key: str, value: Any, operator: FilterOperator
+    ) -> Expression:
+        metadata_column = ColumnExpression(f"metadata_.{key}")
+
+        sample_value = value[0] if isinstance(value, list) else value
+        value_type = filter_value_type_to_duckdb_type.get(type(sample_value))
+
+        metadata_type_expression = FunctionExpression(
+            "json_type",
+            ColumnExpression("metadata_"),
+            ConstantExpression(f"$.{key}"),
+        )
+
+        if value_type is None:
+            # If the value is a JSON Null, we want to swap the 'Null' for an actual null
+            metadata_column = CaseExpression(
+                condition=metadata_type_expression.__eq__(ConstantExpression("NULL")),
+                value=ConstantExpression(None),
+            ).otherwise(metadata_column)
+
+        if value_type == VARCHAR:
+            # If the value is a string, it means the column is a JSON string
+            # and so we need to unpack it otherwise we'll get back a JSON string (a string wrapped in quotes)
+            # https://github.com/duckdb/duckdb/issues/17681
+            metadata_column = FunctionExpression(
+                "json_extract_string",
+                ColumnExpression("metadata_"),
+                ConstantExpression(f"$.{key}"),
+            )
+
+        metadata_value = ConstantExpression(value)
+
+        return self._build_filter_expression(metadata_column, metadata_value, operator)
+
+    def _build_filter_expression(
+        self, column: Expression, value: Expression, operator: FilterOperator
+    ) -> Expression:
+        # If our operator is IN or NIN we need to use a function expression
+        match operator:
+            case operator_func if operator_func := li_filter_to_py_operator.get(
+                operator
+            ):
+                # We have a straightforward operator, so we can just use the Python operator
+                # i.e. FilterOperator.EQ -> `==` (operator.eq)
+                # i.e. FilterOperator.GTE -> `>=` (operator.ge)
+                # ...
+                return operator_func(column, value)
+
+            # Less straightforward operators
+            case FilterOperator.IN:
+                # doclument value is in the filter list
+                return FunctionExpression(
+                    "list_contains",
+                    value,
+                    column,
                 )
-            else:
-                _filters_condition_list.append(
-                    f"json_extract(metadata_, '$.{_fc[0]}') {_fc[1]} {_fc[2]}"
+            case FilterOperator.NIN:
+                # document value is not in the filter list
+                return FunctionExpression(
+                    "list_contains",
+                    value,
+                    column,
+                ).__eq__(ConstantExpression(False))
+
+            case FilterOperator.CONTAINS:
+                # filter_value is in the document value
+                # This will never be true so long as the DuckDB vector store
+                # requires flat metadata
+                return FunctionExpression(
+                    "list_contains",
+                    value,
+                    column,
+                )
+            case FilterOperator.ANY:
+                # array of values has at least one element in common with the array of values in the column
+                return FunctionExpression(
+                    "list_has_any",
+                    column,
+                    value,
+                )
+            case FilterOperator.ALL:
+                # array of values is the same as the array of values in the column
+                return FunctionExpression(
+                    "list_has_all",
+                    column,
+                    value,
+                )
+            case FilterOperator.TEXT_MATCH:
+                return FunctionExpression(
+                    "contains",
+                    column,
+                    value,
+                )
+            case FilterOperator.TEXT_MATCH_INSENSITIVE:
+                return FunctionExpression(
+                    "contains",
+                    FunctionExpression(
+                        "lower",
+                        column,
+                    ),
+                    FunctionExpression(
+                        "lower",
+                        value,
+                    ),
+                )
+            case FilterOperator.IS_EMPTY:
+                # column is null or the array is empty
+                return column.isnull().__or__(
+                    CaseExpression(
+                        condition=FunctionExpression("typeof", column).__eq__(
+                            ConstantExpression("ARRAY")
+                        ),
+                        value=FunctionExpression("length", column).__eq__(
+                            ConstantExpression(0)
+                        ),
+                    )
                 )
 
-        return f" {condition} ".join(_filters_condition_list)
+            case _:
+                raise NotImplementedError(f"Unsupported operator: {operator}")
 
-    def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:
-        """
-        Query index for top k most similar nodes.
+    def _build_metadata_filter_expressions(
+        self, metadata_filters: MetadataFilters | None = None
+    ) -> Expression:
+        expressions: list[Expression] = []
 
-        Args:
-            query.query_embedding (List[float]): query embedding
-            query.similarity_top_k (int): top k most similar nodes
+        if metadata_filters is None or len(metadata_filters.filters) == 0:
+            return Expression(True)
 
-        """
-        nodes = []
-        similarities = []
-        ids = []
+        for metadata_filter in metadata_filters.filters:
+            if isinstance(metadata_filter, MetadataFilter):
+                expressions.append(
+                    self._build_metadata_filter_expression(
+                        metadata_filter.key,
+                        metadata_filter.value,
+                        metadata_filter.operator,
+                    )
+                )
+            elif isinstance(metadata_filter, MetadataFilters):
+                expressions.append(
+                    self._build_metadata_filter_expressions(metadata_filter)
+                )
+            else:
+                raise NotImplementedError(
+                    f"Unsupported metadata filter: {metadata_filter}"
+                )
 
-        if query.filters is not None:
-            # TODO: results from the metadata filter query
-            _filter_string = self._build_metadata_filter_condition(query.filters)
-            _ddb_query = f"""
-            SELECT node_id, text, embedding, metadata_, score
-            FROM (
-                SELECT *, list_cosine_similarity(embedding, ?) AS score
-                FROM {self.table_name}
-                WHERE ?
-            ) sq
-            WHERE score IS NOT NULL
-            ORDER BY score DESC LIMIT ?;
-            """
-            query_params = [
-                query.query_embedding,
-                _filter_string,
-                query.similarity_top_k,
-            ]
-        else:
-            _ddb_query = f"""
-            SELECT node_id, text, embedding, metadata_, score
-            FROM (
-                SELECT *, list_cosine_similarity(embedding, ?) AS score
-                FROM {self.table_name}
-            ) sq
-            WHERE score IS NOT NULL
-            ORDER BY score DESC LIMIT ?;
-            """
-            query_params = [
-                query.query_embedding,
-                query.similarity_top_k,
-            ]
+        final_expression: Expression = expressions[0]
 
-        _final_results = []
-        if self.database_name == ":memory:":
-            _final_results = self._conn.execute(_ddb_query, query_params).fetchall()
-        elif self._database_path is not None:
-            with DuckDBLocalContext(self._database_path) as _conn:
-                _final_results = _conn.execute(_ddb_query, query_params).fetchall()
+        for expression in expressions[1:]:
+            if metadata_filters.condition == FilterCondition.AND:
+                final_expression = final_expression.__and__(expression)
+                continue
 
-        for _row in _final_results:
-            node = self._table_row_to_node(_row)
-            nodes.append(node)
-            similarities.append(_row[4])
-            ids.append(_row[0])
+            if metadata_filters.condition == FilterCondition.OR:
+                final_expression = final_expression.__or__(expression)
+                continue
 
-        return VectorStoreQueryResult(nodes=nodes, similarities=similarities, ids=ids)
+            # I dont know what NOT means in this context
+            # https://github.com/run-llama/llama_index/discussions/19112
+            # if metadata_filters.condition == FilterCondition.NOT:
+            #     final_expression = Expression(py_operator.not_(expressions))
+            #     continue
+            else:
+                raise NotImplementedError(
+                    f"Unsupported condition: {metadata_filters.condition}"
+                )
+
+        return final_expression
diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/pyproject.toml b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/pyproject.toml
index 48dce9e396..a2fb1fcef5 100644
--- a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/pyproject.toml
+++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/pyproject.toml
@@ -26,7 +26,7 @@ dev = [
 
 [project]
 name = "llama-index-vector-stores-duckdb"
-version = "0.3.1"
+version = "0.4.0"
 description = "llama-index vector_stores duckdb integration"
 authors = [{name = "Adithya Krishnan", email = "me@krishadi.com"}]
 requires-python = ">=3.9,<4.0"
@@ -34,7 +34,7 @@ readme = "README.md"
 license = "MIT"
 maintainers = [{name = "krish-adi"}]
 dependencies = [
-    "duckdb>=0.10.1,<0.11",
+    "duckdb>=0.10.1,<1.3.1",
     "llama-index-core>=0.12.0,<0.13",
 ]
 
diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/tests/test_duckdb.py b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/tests/test_duckdb.py
index 29a2119977..1f686a4231 100644
--- a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/tests/test_duckdb.py
+++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/tests/test_duckdb.py
@@ -3,9 +3,15 @@
 import importlib.util
 
 from llama_index.core.schema import NodeRelationship, RelatedNodeInfo, TextNode
-from llama_index.core.vector_stores.types import VectorStoreQuery
+from llama_index.core.vector_stores.types import VectorStoreQuery, FilterOperator
 from llama_index.vector_stores.duckdb import DuckDBVectorStore
 from llama_index.vector_stores.duckdb import DuckDBVectorStore
+from llama_index.core.vector_stores.types import (
+    MetadataFilter,
+    MetadataFilters,
+    FilterCondition,
+)
+from llama_index.vector_stores.duckdb.base import DuckDBTableNotInitializedError
 
 
 def test_duckdb_installed():
@@ -119,6 +125,9 @@ def test_duckdb_add_and_query(
 ) -> None:
     vector_store.add(text_node_list)
 
+    nodes = vector_store.get_nodes(node_ids=["c330d77f-90bd-4c51-9ed2-57d8d693b3b0"])
+    assert len(nodes) == 1
+
     res = vector_store.query(
         VectorStoreQuery(query_embedding=[1.1, 0.0, 0.0], similarity_top_k=1)
     )
@@ -127,8 +136,10 @@ def test_duckdb_add_and_query(
     assert res.nodes[0].get_content() == "lorem ipsum"
     assert res.nodes[0].metadata.get("author") == "Stephen King"
     assert res.nodes[0].metadata.get("theme") == "Friendship"
+
     assert res.nodes[0].excluded_embed_metadata_keys == []
     assert res.nodes[0].excluded_llm_metadata_keys == []
+    assert res.nodes[0].source_node is not None
     assert res.nodes[0].source_node.node_id == "test-0"
 
     res = vector_store.query(
@@ -147,4 +158,302 @@ def test_duckdb_add_and_query(
         "metadata",
         "keys",
     ]
+    assert res.nodes[0].source_node is not None
     assert res.nodes[0].source_node.node_id == "test-7"
+
+
+def test_duckdb_from_local_and_params():
+    store1 = DuckDBVectorStore.from_local(database_path=":memory:", embed_dim=3)
+    assert isinstance(store1, DuckDBVectorStore)
+    store2 = DuckDBVectorStore.from_params(embed_dim=3)
+    assert isinstance(store2, DuckDBVectorStore)
+
+
+def test_delete_nodes(vector_store: DuckDBVectorStore, text_node_list: List[TextNode]):
+    vector_store.clear()
+    vector_store.add(text_node_list[:2])
+    node_ids = [n.node_id for n in text_node_list[:2]]
+    assert len(vector_store.get_nodes(node_ids=node_ids)) == 2
+    vector_store.delete_nodes(node_ids=[node_ids[0]])
+    nodes = vector_store.get_nodes(node_ids=node_ids)
+    assert len(nodes) == 1
+    assert nodes[0].node_id == node_ids[1]
+
+
+def test_clear(vector_store: DuckDBVectorStore, text_node_list: List[TextNode]):
+    vector_store.add(text_node_list[:2])
+    assert len(vector_store.get_nodes()) >= 2
+    vector_store.clear()
+    assert len(vector_store.get_nodes()) == 0
+
+
+def test_delete_by_ref_doc_id(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    test_node = text_node_list[0]
+    test_node_id = test_node.node_id
+    assert test_node.source_node is not None
+
+    test_node_source_document = test_node.source_node
+    test_node_source_document_id = test_node_source_document.node_id
+
+    vector_store.add([test_node])
+    nodes = vector_store.get_nodes()
+    assert vector_store.get_nodes(node_ids=[test_node_id])
+    vector_store.delete(ref_doc_id=test_node_source_document_id)
+    assert not vector_store.get_nodes(node_ids=[test_node_id])
+
+
+def test_get_nodes_with_metadata_filters(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list[:2])
+
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="author", value="Stephen King", operator=FilterOperator.EQ
+            ),
+        ],
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 1
+    assert nodes[0].metadata.get("author") == "Stephen King"
+
+
+def test_error_on_uninitialized_table():
+    store = DuckDBVectorStore(embed_dim=3)
+    # Manually break table
+    store._table = None
+
+    with pytest.raises(DuckDBTableNotInitializedError):
+        store.get_nodes(node_ids=["any"])
+
+
+def test_filter_operator_ne(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="author", value="Stephen King", operator=FilterOperator.NE
+            )
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 5
+    # Only the second node has a different author
+    assert all(n.metadata.get("author") != "Stephen King" for n in nodes)
+
+
+def test_filter_operator_in(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="author",
+                value=["Marie Curie", "Stephen King"],
+                operator=FilterOperator.IN,
+            )
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 2
+    assert any(n.metadata.get("author") == "Stephen King" for n in nodes)
+    assert any(n.metadata.get("author") == "Marie Curie" for n in nodes)
+
+
+def test_filter_operator_nin(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="author", value=["Stephen King"], operator=FilterOperator.NIN
+            )
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 5
+    assert all(n.metadata.get("author") != "Stephen King" for n in nodes)
+
+
+def test_filter_text_match(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="theme", value="Friend", operator=FilterOperator.TEXT_MATCH
+            )
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 1
+    assert any("Friend" in n.metadata.get("theme", "") for n in nodes)
+
+
+def test_filter_text_match_insensitive(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="theme",
+                value="friendship",
+                operator=FilterOperator.TEXT_MATCH_INSENSITIVE,
+            )
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 1
+    assert any(n.metadata.get("theme", "").lower() == "friendship" for n in nodes)
+
+
+def test_filter_is_empty_on_none(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    # Add a node with an empty field
+    node = TextNode(
+        text="empty test",
+        id_="empty-node",
+        relationships={},
+        metadata={"empty_field": None},
+        embedding=[0.1, 0.2, 0.3],
+    )
+    vector_store.add([node])
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="empty_field", value=None, operator=FilterOperator.IS_EMPTY
+            )
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 1
+    assert any(n.node_id == "empty-node" for n in nodes)
+
+
+def test_filter_is_empty_on_missing_key(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    # Add a node with an empty field
+    node = TextNode(
+        text="empty test",
+        id_="empty-node",
+        relationships={},
+        metadata={},
+        embedding=[0.1, 0.2, 0.3],
+    )
+    vector_store.add([node])
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="empty_field", value=None, operator=FilterOperator.IS_EMPTY
+            )
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 1
+    assert any(n.node_id == "empty-node" for n in nodes)
+
+
+def test_filter_and_condition(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="author", value="Stephen King", operator=FilterOperator.EQ
+            ),
+            MetadataFilter(key="theme", value="Friendship", operator=FilterOperator.EQ),
+        ],
+        condition=FilterCondition.AND,
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 1
+    assert nodes[0].metadata.get("author") == "Stephen King"
+    assert nodes[0].metadata.get("theme") == "Friendship"
+
+
+def test_filter_or_condition(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="author", value="Stephen King", operator=FilterOperator.EQ
+            ),
+            MetadataFilter(key="theme", value="Mafia", operator=FilterOperator.EQ),
+        ],
+        condition=FilterCondition.OR,
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 2
+    # Should match either author or theme
+    assert any(n.metadata.get("author") == "Stephen King" for n in nodes)
+    assert any(n.metadata.get("theme") == "Mafia" for n in nodes)
+
+
+def test_filter_nested_and_or_condition(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(
+                key="author", value="Stephen King", operator=FilterOperator.EQ
+            ),
+            MetadataFilters(
+                filters=[
+                    MetadataFilter(
+                        key="theme", value="Mafia", operator=FilterOperator.EQ
+                    ),
+                    MetadataFilter(
+                        key="theme", value="Friendship", operator=FilterOperator.EQ
+                    ),
+                ],
+                condition=FilterCondition.OR,
+            ),
+        ],
+        condition=FilterCondition.AND,
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 1
+    # Should match either author or theme
+    assert any(n.metadata.get("author") == "Stephen King" for n in nodes)
+    assert any(n.metadata.get("theme") == "Friendship" for n in nodes)
+
+
+def test_filter_missing_key(
+    vector_store: DuckDBVectorStore, text_node_list: List[TextNode]
+):
+    vector_store.clear()
+    vector_store.add(text_node_list)
+    filters = MetadataFilters(
+        filters=[
+            MetadataFilter(key="not_a_key", value="foo", operator=FilterOperator.EQ)
+        ]
+    )
+    nodes = vector_store.get_nodes(filters=filters)
+    assert len(nodes) == 0
diff --git a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/uv.lock b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/uv.lock
index 5f82a09e57..ab57ecc9ae 100644
--- a/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/uv.lock
+++ b/llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/uv.lock
@@ -4,8 +4,7 @@ requires-python = ">=3.9, <4.0"
 resolution-markers = [
     "python_full_version >= '3.11'",
     "python_full_version == '3.10.*'",
-    "python_full_version >= '3.9.17' and python_full_version < '3.10'",
-    "python_full_version < '3.9.17'",
+    "python_full_version < '3.10'",
 ]
 
 [[package]]
@@ -19,7 +18,7 @@ wheels = [
 
 [[package]]
 name = "aiohttp"
-version = "3.11.18"
+version = "3.12.13"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -31,88 +30,93 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/63/e7/fa1a8c00e2c54b05dc8cb5d1439f627f7c267874e3f7bb047146116020f9/aiohttp-3.11.18.tar.gz", hash = "sha256:ae856e1138612b7e412db63b7708735cff4d38d0399f6a5435d3dac2669f558a", size = 7678653, upload_time = "2025-04-21T09:43:09.191Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/c7/c3/e5f64af7e97a02f547020e6ff861595766bb5ecb37c7492fac9fe3c14f6c/aiohttp-3.11.18-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:96264854fedbea933a9ca4b7e0c745728f01380691687b7365d18d9e977179c4", size = 711703, upload_time = "2025-04-21T09:40:25.487Z" },
-    { url = "https://files.pythonhosted.org/packages/5f/2f/53c26e96efa5fd01ebcfe1fefdfb7811f482bb21f4fa103d85eca4dcf888/aiohttp-3.11.18-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9602044ff047043430452bc3a2089743fa85da829e6fc9ee0025351d66c332b6", size = 471348, upload_time = "2025-04-21T09:40:27.569Z" },
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Code review comments:
diff_hunk: @@ -281,152 +279,329 @@ def _node_to_table_row(self, node: BaseNode) -> Any:
     def _table_row_to_node(self, row: Any) -> BaseNode:
         return metadata_dict_to_node(json.loads(row[3]), row[1])
 
-    def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> List[str]:
-        """
-        Add nodes to index.
+    def _table_row_to_query_result(self, rows: list[Any]) -> VectorStoreQueryResult:
+        nodes = []
+        similarities = []
+        ids = []
 
-        Args:
-            nodes: List[BaseNode]: list of nodes with embeddings
+        for row in rows:
+            node = self._table_row_to_node(row)
+            nodes.append(node)
+            ids.append(row[0])
+            similarities.append(row[4])
 
-        """
-        self._initialize()
+        return VectorStoreQueryResult(nodes=nodes, similarities=similarities, ids=ids)
 
-        ids = []
+    def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:  # noqa: ARG002
+        """Query the vector store for top k most similar nodes."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_metadata_filter_expressions(
+            metadata_filters=query.filters
+        )
+
+        inner_query = self._table.select(
+            StarExpression(),
+            FunctionExpression(
+                "list_cosine_similarity",
+                ColumnExpression("embedding"),
+                ConstantExpression(query.query_embedding),
+            ).alias("score"),
+        ).filter(filter_expression)
+
+        outer_query = (
+            inner_query.select(
+                ColumnExpression("node_id"),
+                ColumnExpression("text"),
+                ColumnExpression("embedding"),
+                ColumnExpression("metadata_"),
+                ColumnExpression("score"),
+            )
+            .filter(
+                ColumnExpression("score").isnotnull(),
+            )
+            .sort(
+                ColumnExpression("score").desc(),
+            )
+            .limit(
+                query.similarity_top_k,
+            )
+        )
+
+        command = outer_query.sql_query()
+
+        rows = self._conn.execute(command).fetchall()
 
-        if self.database_name == ":memory:":
-            _table = self._conn.table(self.table_name)
-            for node in nodes:
-                ids.append(node.node_id)
-                _row = self._node_to_table_row(node)
-                _table.insert(_row)
-        elif self._database_path is not None:
-            with DuckDBLocalContext(self._database_path) as _conn:
-                _table = _conn.table(self.table_name)
-                for node in nodes:
-                    ids.append(node.node_id)
-                    _row = self._node_to_table_row(node)
-                    _table.insert(_row)
-
-        return ids
-
-    def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
+        return self._table_row_to_query_result(rows)
+
+    def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> list[str]:  # noqa: ARG002
+        """Add nodes to the vector store."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        [self._table.insert(self._node_to_table_row(node)) for node in nodes]
+
+        return [node.node_id for node in nodes]
+
+    def get_nodes(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+        **get_kwargs: Any,
+    ) -> list[BaseNode]:  # noqa: ARG002
+        """Get nodes using node_ids and/or filters. If both are provided, both are considered."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_node_id_metadata_filter_expression(
+            node_ids=node_ids,
+            filters=filters,
+        )
+
+        command = self._table.filter(filter_expression).sql_query()
+
+        rows = self._conn.execute(command).fetchall()
+
+        return [self._table_row_to_node(row) for row in rows]
+
+    def delete_nodes(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+        **delete_kwargs: Any,
+    ) -> None:  # noqa: ARG002
+        """Delete nodes using node_ids and/or filters. If both are provided, both are considered."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_node_id_metadata_filter_expression(
+            node_ids=node_ids,
+            filters=filters,
+        )
+
+        command = f"DELETE FROM {self.table_name} WHERE {filter_expression}"
+
+        self._conn.execute(command)
+
+    def clear(self, **clear_kwargs: Any) -> None:  # noqa: ARG002
+        """Clear the vector store."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        command = f"DELETE FROM {self.table_name}"
+
+        self._conn.execute(command)
+
+    def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:  # noqa: ARG002
         """
         Delete nodes using with ref_doc_id.
 
         Args:
             ref_doc_id (str): The doc_id of the document to delete.
 
         """
-        _ddb_query = f"""
-            DELETE FROM {self.table_name}
-            WHERE json_extract_string(metadata_, '$.ref_doc_id') = ?;
-            """
-        if self.database_name == ":memory:":
-            self._conn.execute(_ddb_query, [ref_doc_id])
-        elif self._database_path is not None:
-            with DuckDBLocalContext(self._database_path) as _conn:
-                _conn.execute(_ddb_query, [ref_doc_id])
-
-    @staticmethod
-    def _build_metadata_filter_condition(
-        standard_filters: MetadataFilters,
-    ) -> str:
-        """Translate standard metadata filters to DuckDB SQL specification."""
-        filters_list = []
-        # condition = standard_filters.condition or "and"  ## and/or as strings.
-        condition = "AND"
-        _filters_condition_list = []
-
-        for filter in standard_filters.filters:
-            filter = cast(MetadataFilter, filter)
-            if filter.operator:
-                if filter.operator in [
-                    "<",
-                    ">",
-                    "<=",
-                    ">=",
-                    "<>",
-                    "!=",
-                ]:
-                    filters_list.append((filter.key, filter.operator, filter.value))
-                elif filter.operator in ["=="]:
-                    filters_list.append((filter.key, "=", filter.value))
-                else:
-                    raise ValueError(
-                        f"Filter operator {filter.operator} not supported."
-                    )
-            else:
-                filters_list.append((filter.key, "=", filter.value))
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        where_clause = self._build_metadata_filter_expression(
+            "ref_doc_id", ref_doc_id, FilterOperator.EQ
+        )
+
+        command = f"DELETE FROM {self.table_name} WHERE {where_clause}"
+
+        self._conn.execute(command)
+
+    def _build_node_id_metadata_filter_expression(
+        self,
+        node_ids: list[str] | None = None,
path: llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py
text: @user1:
I would prefer python3.9 friendly typing (I think our eval-backport package in core catches this/supports this, but imo better safe than sorry)

diff_hunk: @@ -281,152 +279,329 @@ def _node_to_table_row(self, node: BaseNode) -> Any:
     def _table_row_to_node(self, row: Any) -> BaseNode:
         return metadata_dict_to_node(json.loads(row[3]), row[1])
 
-    def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> List[str]:
-        """
-        Add nodes to index.
+    def _table_row_to_query_result(self, rows: list[Any]) -> VectorStoreQueryResult:
+        nodes = []
+        similarities = []
+        ids = []
 
-        Args:
-            nodes: List[BaseNode]: list of nodes with embeddings
+        for row in rows:
+            node = self._table_row_to_node(row)
+            nodes.append(node)
+            ids.append(row[0])
+            similarities.append(row[4])
 
-        """
-        self._initialize()
+        return VectorStoreQueryResult(nodes=nodes, similarities=similarities, ids=ids)
 
-        ids = []
+    def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:  # noqa: ARG002
+        """Query the vector store for top k most similar nodes."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_metadata_filter_expressions(
+            metadata_filters=query.filters
+        )
+
+        inner_query = self._table.select(
+            StarExpression(),
+            FunctionExpression(
+                "list_cosine_similarity",
+                ColumnExpression("embedding"),
+                ConstantExpression(query.query_embedding),
+            ).alias("score"),
+        ).filter(filter_expression)
+
+        outer_query = (
+            inner_query.select(
+                ColumnExpression("node_id"),
+                ColumnExpression("text"),
+                ColumnExpression("embedding"),
+                ColumnExpression("metadata_"),
+                ColumnExpression("score"),
+            )
+            .filter(
+                ColumnExpression("score").isnotnull(),
+            )
+            .sort(
+                ColumnExpression("score").desc(),
+            )
+            .limit(
+                query.similarity_top_k,
+            )
+        )
+
+        command = outer_query.sql_query()
+
+        rows = self._conn.execute(command).fetchall()
 
-        if self.database_name == ":memory:":
-            _table = self._conn.table(self.table_name)
-            for node in nodes:
-                ids.append(node.node_id)
-                _row = self._node_to_table_row(node)
-                _table.insert(_row)
-        elif self._database_path is not None:
-            with DuckDBLocalContext(self._database_path) as _conn:
-                _table = _conn.table(self.table_name)
-                for node in nodes:
-                    ids.append(node.node_id)
-                    _row = self._node_to_table_row(node)
-                    _table.insert(_row)
-
-        return ids
-
-    def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
+        return self._table_row_to_query_result(rows)
+
+    def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> list[str]:  # noqa: ARG002
+        """Add nodes to the vector store."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        [self._table.insert(self._node_to_table_row(node)) for node in nodes]
+
+        return [node.node_id for node in nodes]
+
+    def get_nodes(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+        **get_kwargs: Any,
+    ) -> list[BaseNode]:  # noqa: ARG002
+        """Get nodes using node_ids and/or filters. If both are provided, both are considered."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_node_id_metadata_filter_expression(
+            node_ids=node_ids,
+            filters=filters,
+        )
+
+        command = self._table.filter(filter_expression).sql_query()
+
+        rows = self._conn.execute(command).fetchall()
+
+        return [self._table_row_to_node(row) for row in rows]
+
+    def delete_nodes(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+        **delete_kwargs: Any,
+    ) -> None:  # noqa: ARG002
+        """Delete nodes using node_ids and/or filters. If both are provided, both are considered."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        filter_expression = self._build_node_id_metadata_filter_expression(
+            node_ids=node_ids,
+            filters=filters,
+        )
+
+        command = f"DELETE FROM {self.table_name} WHERE {filter_expression}"
+
+        self._conn.execute(command)
+
+    def clear(self, **clear_kwargs: Any) -> None:  # noqa: ARG002
+        """Clear the vector store."""
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        command = f"DELETE FROM {self.table_name}"
+
+        self._conn.execute(command)
+
+    def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:  # noqa: ARG002
         """
         Delete nodes using with ref_doc_id.
 
         Args:
             ref_doc_id (str): The doc_id of the document to delete.
 
         """
-        _ddb_query = f"""
-            DELETE FROM {self.table_name}
-            WHERE json_extract_string(metadata_, '$.ref_doc_id') = ?;
-            """
-        if self.database_name == ":memory:":
-            self._conn.execute(_ddb_query, [ref_doc_id])
-        elif self._database_path is not None:
-            with DuckDBLocalContext(self._database_path) as _conn:
-                _conn.execute(_ddb_query, [ref_doc_id])
-
-    @staticmethod
-    def _build_metadata_filter_condition(
-        standard_filters: MetadataFilters,
-    ) -> str:
-        """Translate standard metadata filters to DuckDB SQL specification."""
-        filters_list = []
-        # condition = standard_filters.condition or "and"  ## and/or as strings.
-        condition = "AND"
-        _filters_condition_list = []
-
-        for filter in standard_filters.filters:
-            filter = cast(MetadataFilter, filter)
-            if filter.operator:
-                if filter.operator in [
-                    "<",
-                    ">",
-                    "<=",
-                    ">=",
-                    "<>",
-                    "!=",
-                ]:
-                    filters_list.append((filter.key, filter.operator, filter.value))
-                elif filter.operator in ["=="]:
-                    filters_list.append((filter.key, "=", filter.value))
-                else:
-                    raise ValueError(
-                        f"Filter operator {filter.operator} not supported."
-                    )
-            else:
-                filters_list.append((filter.key, "=", filter.value))
+        if self._table is None:
+            raise DuckDBTableNotInitializedError(self.table_name)
+
+        where_clause = self._build_metadata_filter_expression(
+            "ref_doc_id", ref_doc_id, FilterOperator.EQ
+        )
+
+        command = f"DELETE FROM {self.table_name} WHERE {where_clause}"
+
+        self._conn.execute(command)
+
+    def _build_node_id_metadata_filter_expression(
+        self,
+        node_ids: list[str] | None = None,
+        filters: MetadataFilters | None = None,
+    ) -> Expression:
+        filter_expression = Expression(True)
+
+        if filters is not None:
+            filter_expression = self._build_metadata_filter_expressions(
+                metadata_filters=filters
+            )
+
+        if node_ids is not None:
+            node_id_expression = FunctionExpression(
+                "list_contains",
+                ConstantExpression(node_ids),
+                ColumnExpression("node_id"),
+            )
+
+            filter_expression = filter_expression.__and__(node_id_expression)
+
+        return filter_expression
 
-        for _fc in filters_list:
-            if isinstance(_fc[2], str):
-                _filters_condition_list.append(
-                    f"json_extract_string(metadata_, '$.{_fc[0]}') {_fc[1]} '{_fc[2]}'"
+    def _build_metadata_filter_expression(
+        self, key: str, value: Any, operator: FilterOperator
+    ) -> Expression:
+        metadata_column = ColumnExpression(f"metadata_.{key}")
+
+        sample_value = value[0] if isinstance(value, list) else value
+        value_type = filter_value_type_to_duckdb_type.get(type(sample_value))
+
+        metadata_type_expression = FunctionExpression(
+            "json_type",
+            ColumnExpression("metadata_"),
+            ConstantExpression(f"$.{key}"),
+        )
+
+        if value_type is None:
+            # If the value is a JSON Null, we want to swap the 'Null' for an actual null
+            metadata_column = CaseExpression(
+                condition=metadata_type_expression.__eq__(ConstantExpression("NULL")),
+                value=ConstantExpression(None),
+            ).otherwise(metadata_column)
+
+        if value_type == VARCHAR:
+            # If the value is a string, it means the column is a JSON string
+            # and so we need to unpack it otherwise we'll get back a JSON string (a string wrapped in quotes)
+            # https://github.com/duckdb/duckdb/issues/17681
+            metadata_column = FunctionExpression(
+                "json_extract_string",
+                ColumnExpression("metadata_"),
+                ConstantExpression(f"$.{key}"),
+            )
+
+        metadata_value = ConstantExpression(value)
+
+        return self._build_filter_expression(metadata_column, metadata_value, operator)
+
+    def _build_filter_expression(
+        self, column: Expression, value: Expression, operator: FilterOperator
+    ) -> Expression:
+        # If our operator is IN or NIN we need to use a function expression
+        match operator:
path: llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py
text: @user1:
This is not available in python3.9

@author:
I'll switch to 3.9 and remove any other items that aren't compatible

diff_hunk: @@ -82,135 +124,76 @@ class DuckDBVectorStore(BasePydanticVectorStore):
     stores_text: bool = True
     flat_metadata: bool = True
 
-    database_name: Optional[str]
+    database_name: str
     table_name: str
     # schema_name: Optional[str] # TODO: support schema name
-    embed_dim: Optional[int]
+    embed_dim: int | None
     # hybrid_search: Optional[bool] # TODO: support hybrid search
-    text_search_config: Optional[dict]
-    persist_dir: Optional[str]
+    text_search_config: dict | None
+    persist_dir: str
+
+    _conn: duckdb.DuckDBPyConnection = PrivateAttr()
+    _table: duckdb.DuckDBPyRelation | None = PrivateAttr(default=None)
 
-    _conn: Any = PrivateAttr()
     _is_initialized: bool = PrivateAttr(default=False)
-    _database_path: Optional[str] = PrivateAttr()
+    _database_path: str | None = PrivateAttr()
 
     def __init__(
         self,
         database_name: str = ":memory:",
         table_name: str = "documents",
-        embed_dim: Optional[int] = None,
+        embed_dim: int | None = None,
         # https://duckdb.org/docs/extensions/full_text_search
-        text_search_config: Optional[dict] = {
-            "stemmer": "english",
-            "stopwords": "english",
-            "ignore": "(\\.|[^a-z])+",
-            "strip_accents": True,
-            "lower": True,
-            "overwrite": False,
-        },
+        text_search_config: dict | None = None,
         persist_dir: str = "./storage",
-        **kwargs: Any,
+        **kwargs: Any,  # noqa: ARG002
     ) -> None:
         """Init params."""
-        try:
-            import duckdb
-        except ImportError:
-            raise ImportError(import_err_msg)
-
-        database_path = None
-        if database_name == ":memory:":
-            _home_dir = os.path.expanduser("~")
-            conn = duckdb.connect(database_name)
-            conn.execute(f"SET home_directory='{_home_dir}';")
-            conn.install_extension("json")
-            conn.load_extension("json")
-            conn.install_extension("fts")
-            conn.load_extension("fts")
-        else:
-            # check if persist dir exists
-            if not os.path.exists(persist_dir):
-                os.makedirs(persist_dir)
-
-            database_path = os.path.join(persist_dir, database_name)
-
-            with DuckDBLocalContext(database_path) as _conn:
-                pass
-
-            conn = None
-
         fields = {
             "database_name": database_name,
             "table_name": table_name,
             "embed_dim": embed_dim,
             "text_search_config": text_search_config,
             "persist_dir": persist_dir,
         }
+
         super().__init__(stores_text=True, **fields)
-        self._is_initialized = False
-        self._conn = conn
-        self._database_path = database_path
+
+        self._connect()
+        self._initialize()
 
     @classmethod
     def from_local(
         cls,
         database_path: str,
         table_name: str = "documents",
         # schema_name: Optional[str] = "main",
-        embed_dim: Optional[int] = None,
+        embed_dim: int | None = None,
         # hybrid_search: Optional[bool] = False,
-        text_search_config: Optional[dict] = {
-            "stemmer": "english",
-            "stopwords": "english",
-            "ignore": "(\\.|[^a-z])+",
-            "strip_accents": True,
-            "lower": True,
-            "overwrite": False,
-        },
+        text_search_config: dict | None = DEFAULT_TEXT_SEARCH_CONFIG,
path: llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py
text: @user1:
I think I'd prefer not have dicts as defaults

Can we do `text_search_config: dict | None = None` and then later on `text_search_config = text_search_config or DEFAULT_TEXT_SEARCH_CONFIG` ?

@author:
I don't like dicts as defaults either! Will do

diff_hunk: @@ -82,135 +124,76 @@ class DuckDBVectorStore(BasePydanticVectorStore):
     stores_text: bool = True
     flat_metadata: bool = True
 
-    database_name: Optional[str]
+    database_name: str
     table_name: str
     # schema_name: Optional[str] # TODO: support schema name
-    embed_dim: Optional[int]
+    embed_dim: int | None
     # hybrid_search: Optional[bool] # TODO: support hybrid search
-    text_search_config: Optional[dict]
-    persist_dir: Optional[str]
+    text_search_config: dict | None
+    persist_dir: str
+
+    _conn: duckdb.DuckDBPyConnection = PrivateAttr()
+    _table: duckdb.DuckDBPyRelation | None = PrivateAttr(default=None)
 
-    _conn: Any = PrivateAttr()
     _is_initialized: bool = PrivateAttr(default=False)
-    _database_path: Optional[str] = PrivateAttr()
+    _database_path: str | None = PrivateAttr()
 
     def __init__(
         self,
         database_name: str = ":memory:",
         table_name: str = "documents",
-        embed_dim: Optional[int] = None,
+        embed_dim: int | None = None,
         # https://duckdb.org/docs/extensions/full_text_search
-        text_search_config: Optional[dict] = {
-            "stemmer": "english",
-            "stopwords": "english",
-            "ignore": "(\\.|[^a-z])+",
-            "strip_accents": True,
-            "lower": True,
-            "overwrite": False,
-        },
+        text_search_config: dict | None = None,
         persist_dir: str = "./storage",
-        **kwargs: Any,
+        **kwargs: Any,  # noqa: ARG002
     ) -> None:
         """Init params."""
-        try:
-            import duckdb
-        except ImportError:
-            raise ImportError(import_err_msg)
-
-        database_path = None
-        if database_name == ":memory:":
-            _home_dir = os.path.expanduser("~")
-            conn = duckdb.connect(database_name)
-            conn.execute(f"SET home_directory='{_home_dir}';")
-            conn.install_extension("json")
-            conn.load_extension("json")
-            conn.install_extension("fts")
-            conn.load_extension("fts")
-        else:
-            # check if persist dir exists
-            if not os.path.exists(persist_dir):
-                os.makedirs(persist_dir)
-
-            database_path = os.path.join(persist_dir, database_name)
-
-            with DuckDBLocalContext(database_path) as _conn:
-                pass
-
-            conn = None
-
         fields = {
             "database_name": database_name,
             "table_name": table_name,
             "embed_dim": embed_dim,
             "text_search_config": text_search_config,
             "persist_dir": persist_dir,
         }
+
         super().__init__(stores_text=True, **fields)
-        self._is_initialized = False
-        self._conn = conn
-        self._database_path = database_path
+
+        self._connect()
+        self._initialize()
path: llama-index-integrations/vector_stores/llama-index-vector-stores-duckdb/llama_index/vector_stores/duckdb/base.py
text: @user1:
Normally I would say this should be lazily initialized instead of in the constructor, but since this isn't actually making API/network calls, I think this is ok 

@author:
I need to check if it's initialized in every call anyway so I can switch to lazy init no problem

The old code did an init in the constructor, I guess to make sure the configuration is correct and fail fast vs failing later