posit-dev
diff --git a/‎pkg-py/CHANGELOG.md‎
Lines changed: 13 additions & 3 deletions b/‎pkg-py/CHANGELOG.md‎
Lines changed: 13 additions & 3 deletions
diff --git a/‎pkg-py/examples/07-gradio-custom-app.py‎
Lines changed: 1 addition & 2 deletions b/‎pkg-py/examples/07-gradio-custom-app.py‎
Lines changed: 1 addition & 2 deletions
diff --git a/‎pkg-py/src/querychat/_dash.py‎
Lines changed: 53 additions & 6 deletions b/‎pkg-py/src/querychat/_dash.py‎
Lines changed: 53 additions & 6 deletions
@@ -9,14 +9,24 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### New features
 
-* Added `PolarsLazySource` to support Polars LazyFrames as data sources. Data stays lazy until the render boundary, enabling efficient handling of large datasets. Pass a `polars.LazyFrame` directly to `QueryChat()` and queries will be executed lazily via Polars' SQLContext.
-
 * Added support for Gradio, Dash, and Streamlit web frameworks in addition to Shiny. Import from the new submodules:
   * `from querychat.gradio import QueryChat`
   * `from querychat.dash import QueryChat`
   * `from querychat.streamlit import QueryChat`
 
-Each framework's `QueryChat` provides `.app()` for quick standalone apps and `.ui()` for custom layouts. Install framework dependencies with pip extras: `pip install querychat[gradio]`, `pip install querychat[dash]`, or `pip install querychat[streamlit]`.
+Each framework's `QueryChat` provides `.app()` for quick standalone apps and `.ui()` for custom layouts. Install framework dependencies with pip extras: `pip install querychat[gradio]`, `pip install querychat[dash]`, or `pip install querychat[streamlit]`. (#190)
+
+* `QueryChat()` gains support for more data sources:
+  * `polars.LazyFrame`: queries execute lazily via `polars.SQLContext`. In this case, `.df()` et al. methods will return a `polars.LazyFrame`. (#191)
+  * `pyarrow.Table`: queries execute in-memory via `duckdb`. In this case, `.df()` et al. methods will return a `pyarrow.Table`. (#196)
+
+### Improvements
+
+* Improved typing support for return types on `.df()` et al. (#196)
+
+### Changes
+
+* `DataFrameSource` methods now (once again) return the input DataFrame type (e.g., `pandas.DataFrame`) instead of `nw.DataFrame`. (#196)
 
 ## [0.4.0] - 2026-01-14
 
 
@@ -47,8 +47,7 @@ def update_display(state_dict: AppStateDict):
         sql = qc.sql(state_dict)
         title = qc.title(state_dict)
 
-        # Convert narwhals DataFrame to native (pandas) for Gradio compatibility
-        display_df = df.head(100).to_native()
+        display_df = df.head(100)
         return (
             f"### {title or 'Full Dataset'}",
             sql or "SELECT * FROM titanic",
 
@@ -2,10 +2,11 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Literal, Optional, cast
+from typing import TYPE_CHECKING, Literal, Optional, cast, overload
 
 import narwhals.stable.v1 as nw
 from chatlas import Turn
+from narwhals.stable.v1.typing import IntoDataFrameT, IntoFrameT, IntoLazyFrameT
 
 from ._dash_ui import IDs, card_ui, chat_container_ui, chat_messages_ui
 from ._querychat_base import TOOL_GROUPS, QueryChatBase
@@ -31,7 +32,7 @@
     from dash import html
 
 
-class QueryChat(QueryChatBase, StateDictAccessorMixin):
+class QueryChat(QueryChatBase[IntoFrameT], StateDictAccessorMixin[IntoFrameT]):
     """
     QueryChat for Dash applications.
 
@@ -86,6 +87,54 @@ def update_sql(state):
 
     """
 
+    @overload
+    def __init__(
+        self: QueryChat[IntoLazyFrameT],
+        data_source: IntoLazyFrameT,
+        table_name: str,
+        *,
+        greeting: Optional[str | PathType] = None,
+        client: Optional[str | chatlas.Chat] = None,
+        tools: TOOL_GROUPS | tuple[TOOL_GROUPS, ...] | None = ("update", "query"),
+        data_description: Optional[str | PathType] = None,
+        categorical_threshold: int = 20,
+        extra_instructions: Optional[str | PathType] = None,
+        prompt_template: Optional[str | PathType] = None,
+        storage_type: Literal["memory", "session", "local"] = "memory",
+    ) -> None: ...
+
+    @overload
+    def __init__(
+        self: QueryChat[IntoDataFrameT],
+        data_source: IntoDataFrameT,
+        table_name: str,
+        *,
+        greeting: Optional[str | PathType] = None,
+        client: Optional[str | chatlas.Chat] = None,
+        tools: TOOL_GROUPS | tuple[TOOL_GROUPS, ...] | None = ("update", "query"),
+        data_description: Optional[str | PathType] = None,
+        categorical_threshold: int = 20,
+        extra_instructions: Optional[str | PathType] = None,
+        prompt_template: Optional[str | PathType] = None,
+        storage_type: Literal["memory", "session", "local"] = "memory",
+    ) -> None: ...
+
+    @overload
+    def __init__(
+        self: QueryChat[nw.DataFrame],
+        data_source: sqlalchemy.Engine,
+        table_name: str,
+        *,
+        greeting: Optional[str | PathType] = None,
+        client: Optional[str | chatlas.Chat] = None,
+        tools: TOOL_GROUPS | tuple[TOOL_GROUPS, ...] | None = ("update", "query"),
+        data_description: Optional[str | PathType] = None,
+        categorical_threshold: int = 20,
+        extra_instructions: Optional[str | PathType] = None,
+        prompt_template: Optional[str | PathType] = None,
+        storage_type: Literal["memory", "session", "local"] = "memory",
+    ) -> None: ...
+
     def __init__(
         self,
         data_source: IntoFrame | sqlalchemy.Engine,
@@ -374,8 +423,7 @@ def update_display(state_data: AppStateDict, reset_clicks):
         sql_title = state.title or "SQL Query"
         sql_code = f"```sql\n{state.get_display_sql()}\n```"
 
-        df = state.get_current_data()
-        # Collect if lazy before accessing .to_pandas() or .shape
+        df = nw.from_native(state.get_current_data())
         if isinstance(df, nw.LazyFrame):
             df = df.collect()
 
@@ -408,8 +456,7 @@ def update_display(state_data: AppStateDict, reset_clicks):
     )
     def export_csv(n_clicks: int, state_data: AppStateDict):
         state = deserialize_state(state_data)
-        df = state.get_current_data()
-        # Collect if lazy before converting to pandas
+        df = nw.from_native(state.get_current_data())
         if isinstance(df, nw.LazyFrame):
             df = df.collect()
         return send_data_frame(df.to_pandas().to_csv, "querychat_data.csv", index=False)