chore(pkg-py): Update conventions in example apps

Author: gadenbuie

pkg-py/examples/app-database-sqlite.py

@@ -1,7 +1,7 @@
 from pathlib import Path
 
 import chatlas
-import querychat as qc
+import querychat
 from seaborn import load_dataset
 from shiny import App, render, ui
 from sqlalchemy import create_engine
@@ -29,7 +29,7 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
         system_prompt=system_prompt,
     )
 
-querychat_config = qc.init(
+qc_config = querychat.init(
     engine,
     "titanic",
     greeting=greeting,
@@ -40,7 +40,7 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
 # Create UI
 app_ui = ui.page_sidebar(
     # 2. Place the chat component in the sidebar
-    qc.sidebar("chat"),
+    querychat.sidebar("chat"),
     # Main panel with data viewer
     ui.card(
         ui.output_data_frame("data_table"),
@@ -55,13 +55,13 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
 # Define server logic
 def server(input, output, session):
     # 3. Initialize querychat server with the config from step 1
-    chat = qc.server("chat", querychat_config)
+    qc = querychat.server("chat", qc_config)
 
     # 4. Display the filtered dataframe
     @render.data_frame
     def data_table():
-        # Access filtered data via chat.df() reactive
-        return chat["df"]()
+        # Access filtered data via qc.df() reactive
+        return qc.df()
 
 
 # Create Shiny app

pkg-py/examples/app-dataframe-pandas.py

@@ -1,7 +1,7 @@
 from pathlib import Path
 
 import chatlas
-import querychat as qc
+import querychat
 from seaborn import load_dataset
 from shiny import App, render, ui
 
@@ -20,7 +20,7 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
         system_prompt=system_prompt,
     )
 
-querychat_config = qc.init(
+qc_config = querychat.init(
     titanic,
     "titanic",
     greeting=greeting,
@@ -31,7 +31,7 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
 # Create UI
 app_ui = ui.page_sidebar(
     # 2. Place the chat component in the sidebar
-    qc.sidebar("chat"),
+    querychat.sidebar("chat"),
     # Main panel with data viewer
     ui.card(
         ui.output_data_frame("data_table"),
@@ -46,13 +46,13 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
 # Define server logic
 def server(input, output, session):
     # 3. Initialize querychat server with the config from step 1
-    chat = qc.server("chat", querychat_config)
+    qc = querychat.server("chat", qc_config)
 
     # 4. Display the filtered dataframe
     @render.data_frame
     def data_table():
         # Access filtered data via chat.df() reactive
-        return chat.df()
+        return qc.df()
 
 
 # Create Shiny app

pkg-py/examples/app.py

@@ -2,7 +2,7 @@
 from seaborn import load_dataset
 from shiny import App, render, ui
 
-import querychat as qc
+import querychat
 
 titanic = load_dataset("titanic")
 
@@ -20,18 +20,18 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
     )
 
 
-querychat_config = qc.init(
+qc_config = querychat.init(
     data_source=titanic,
     table_name="titanic",
     client=use_github_models,
 )
 
 # Create UI
 app_ui = ui.page_sidebar(
-    # 2. Use qc.sidebar(id) in a ui.page_sidebar.
-    #    Alternatively, use qc.ui(id) elsewhere if you don't want your
+    # 2. Use querychat.sidebar(id) in a ui.page_sidebar.
+    #    Alternatively, use querychat.ui(id) elsewhere if you don't want your
     #    chat interface to live in a sidebar.
-    qc.sidebar("chat"),
+    querychat.sidebar("chat"),
     ui.card(
       ui.card_header("Titanic Data"),
       ui.output_data_frame("data_table"),
@@ -45,13 +45,13 @@ def use_github_models(system_prompt: str) -> chatlas.Chat:
 # Define server logic
 def server(input, output, session):
     # 3. Create a querychat object using the config from step 1.
-    chat = qc.server("chat", querychat_config)
+    qc = querychat.server("chat", qc_config)
 
     # 4. Use the filtered/sorted data frame anywhere you wish, via the
     #    chat.df() reactive.
     @render.data_frame
     def data_table():
-        return chat.df()
+        return qc.df()
 
 
 # Create Shiny app