Merge branch 'dev' into restructure-folders

* dev:
  feat: genericizing data source using DataSource protocol: Supports SQLAlchemy and Pandas
  fix: No longer need to manually calls `session$ns()` with shinychat (#10)
  Remove website routine, no pkgdown site intended (#18)

Author: schloerke

.github/workflows/R-CMD-check.yml

@@ -12,10 +12,10 @@ on:
 name: Package checks
 
 jobs:
-  website:
-    uses: rstudio/shiny-workflows/.github/workflows/website.yaml@v1
-    with:
-      working-directory: ./pkg-r
+  # website:
+  #   uses: rstudio/shiny-workflows/.github/workflows/website.yaml@v1
+  #   with:
+  #     working-directory: ./pkg-r
   routine:
     uses: rstudio/shiny-workflows/.github/workflows/routine.yaml@v1
     with:

.gitignore

@@ -2,6 +2,8 @@ __pycache__/
 animation.screenflow/
 README_files/
 README.html
+.DS_Store
+python-package/examples/titanic.db
 .quarto
 
 # Byte-compiled / optimized / DLL files

pkg-py/README.md

@@ -56,7 +56,7 @@ def server(input, output, session):
     #    chat["df"]() reactive.
     @render.data_frame
     def data_table():
-        return chat["df"]()
+        return chat.df()
 
 
 # Create Shiny app
@@ -171,8 +171,8 @@ which you can then pass via:
 
 ```python
 querychat_config = querychat.init(
-    df=titanic,
-    table_name="titanic",
+    titanic,
+    "titanic",
     data_description=Path("data_description.md").read_text()
 )
 ```
@@ -185,8 +185,8 @@ You can add additional instructions of your own to the end of the system prompt,
 
 ```python
 querychat_config = querychat.init(
-    df=titanic,
-    table_name="titanic",
+    titanic,
+    "titanic",
     extra_instructions=[
         "You're speaking to a British audience--please use appropriate spelling conventions.",
         "Use lots of emojis! 😃 Emojis everywhere, 🌍 emojis forever. ♾️",
@@ -218,8 +218,8 @@ def my_chat_func(system_prompt: str) -> chatlas.Chat:
 my_chat_func = partial(chatlas.ChatAnthropic, model="claude-3-7-sonnet-latest")
 
 querychat_config = querychat.init(
-    df=titanic,
-    table_name="titanic",
+    titanic,
+    "titanic",
     create_chat_callback=my_chat_func
 )
 ```

pkg-py/examples/app-database.py

@@ -0,0 +1,57 @@
+from pathlib import Path
+
+from seaborn import load_dataset
+from shiny import App, render, ui
+from sqlalchemy import create_engine
+
+import querychat
+
+# Load titanic data and create SQLite database
+db_path = Path(__file__).parent / "titanic.db"
+engine = create_engine("sqlite:///" + str(db_path))
+
+if not db_path.exists():
+    # For example purposes, we'll create the database if it doesn't exist. Don't
+    # do this in your app!
+    titanic = load_dataset("titanic")
+    titanic.to_sql("titanic", engine, if_exists="replace", index=False)
+
+greeting = (Path(__file__).parent / "greeting.md").read_text()
+data_desc = (Path(__file__).parent / "data_description.md").read_text()
+
+# 1. Configure querychat
+querychat_config = querychat.init(
+    engine,
+    "titanic",
+    greeting=greeting,
+    data_description=data_desc,
+)
+
+# Create UI
+app_ui = ui.page_sidebar(
+    # 2. Place the chat component in the sidebar
+    querychat.sidebar("chat"),
+    # Main panel with data viewer
+    ui.card(
+        ui.output_data_frame("data_table"),
+        fill=True,
+    ),
+    title="querychat with Python (SQLite)",
+    fillable=True,
+)
+
+
+# Define server logic
+def server(input, output, session):
+    # 3. Initialize querychat server with the config from step 1
+    chat = querychat.server("chat", querychat_config)
+
+    # 4. Display the filtered dataframe
+    @render.data_frame
+    def data_table():
+        # Access filtered data via chat.df() reactive
+        return chat["df"]()
+
+
+# Create Shiny app
+app = App(app_ui, server)

pkg-py/examples/app.py renamed to pkg-py/examples/app-dataframe.py

@@ -7,10 +7,8 @@
 
 titanic = load_dataset("titanic")
 
-with open(Path(__file__).parent / "greeting.md", "r") as f:
-    greeting = f.read()
-with open(Path(__file__).parent / "data_description.md", "r") as f:
-    data_desc = f.read()
+greeting = (Path(__file__).parent / "greeting.md").read_text()
+data_desc = (Path(__file__).parent / "data_description.md").read_text()
 
 # 1. Configure querychat
 querychat_config = querychat.init(
@@ -43,7 +41,7 @@ def server(input, output, session):
     @render.data_frame
     def data_table():
         # Access filtered data via chat.df() reactive
-        return chat["df"]()
+        return chat.df()
 
 
 # Create Shiny app