Docs

config_examples/application_specific_commands.jl

@@ -0,0 +1,47 @@
+# To run this do in the Julia REPL `include("path-to-file")` or simply copy paste it inside.
+using JustSayIt
+
+# 1) Define reusable commands shared by several application contexts.
+base_commands = Dict(
+    "sentence"     => Keyboard.type_sentence,
+    "continuation" => Keyboard.type_sentence_lowercase,
+    "spell"        => Keyboard.type_letters,
+    "type summary" => LLM.type_summary,
+    "answer"       => LLM.read_text_answer,
+    "followup"     => LLM.read_followup,
+    "read this"    => TTS.read,
+    "pause"        => TTS.pause,
+    "stop"         => TTS.stop,
+)
+
+# 2) Extend the base dictionary with browser-specific commands.
+browser_commands = merge(
+    base_commands,
+    Dict(
+        "new tab"      => (Key.ctrl, 't'),
+        "close tab"    => (Key.ctrl, 'w'),
+        "jump address" => (Key.ctrl, 'l'),
+        "search web"   => [(Key.ctrl, 'l'), Keyboard.type_lowercase, Key.enter],
+    ),
+)
+
+# 3) Extend the base dictionary with coding-specific commands.
+coding_commands = merge(
+    base_commands,
+    Dict(
+        "comment"          => (Key.ctrl, '/'),
+        "format selection" => [(Key.ctrl, 'k'), (Key.ctrl, 'f')],
+        "workspace search" => (Key.ctrl, Key.shift, 'f'),
+        "jump line"        => [(Key.ctrl, 'g'), Keyboard.type_digits, Key.enter],
+    ),
+)
+
+# 4) Assemble top-level commands that activate nested application contexts.
+commands = Dict(
+    "help"    => Help.help,
+    "browser" => [`firefox`, browser_commands],
+    "coding"  => [`code`, coding_commands],
+)
+
+# 5) Start JustSayIt with the application-specific command dictionaries.
+start(commands=commands)

config_examples/config_custom_function.jl

@@ -1,6 +1,6 @@
 # To run this do in the Julia REPL `include("path-to-file")` or simply copy paste it inside.
 using JustSayIt
-using JustSayIt.API       # Import JustSayIt API to write @voicearg functions
+using JustSayIt.API       # Import JustSayIt API to write @voiceargs functions
 using DefaultApplication  # To install type: `]` and then `add DefaultApplication`
 
 # 1) Define a custom weather forecast search function.
@@ -15,10 +15,10 @@ weather
     DefaultApplication.open("https://www.google.com/search?q=weather+$day")
 end
 
-# 2) Define command name to function mapping, calling custom function
-commands = Dict("help"      => Help.help,
-                "weather"   => weather,
-                );
+# 2) Define command name to function mapping, calling the custom function.
+commands = Dict("help"    => Help.help,
+                "weather" => weather,
+                )
 
 # 3) Start JustSayIt with the custom commands.
 start(commands=commands)  # If you say "help weather", it will show the documentation written above in the Julia REPL.

config_examples/jupyter_llm_commands.jl

@@ -0,0 +1,24 @@
+# To run this do in the Julia REPL `include("path-to-file")` or simply copy paste it inside.
+using JustSayIt
+
+# 1) Define the Jupyter notebook LLM-assisted commands shown in the JuliaCon 2025 slides.
+jupyter_llm_commands = Dict(
+    "generate magic" => () -> LLM.type_answer(
+        instruction_prefix="Generate the appropriate IPython magic command for the following task using proper syntax (%line magic or %%cell magic) with necessary options:"
+    ),
+    "explain cell" => () -> LLM.type_text_answer_to(
+        "Explain what the selected cell code does in simple terms. Include key functions, algorithms, and data transformations. Format as markdown with clear section headings."
+    ),
+    "parallelize code" => () -> LLM.type_text_answer_to(
+        "Convert the selected code to use parallel processing. Use appropriate IPython magic commands (%%px, %%parallel) and add necessary setup. Return only the parallelized code with essential comments."
+    ),
+    "visualize data" => () -> LLM.type_text_answer_to(
+        "Generate visualization code for the selected data/variables. Choose appropriate plotting libraries and create informative visualizations. Use %matplotlib inline for display. Return only executable code."
+    ),
+)
+
+# 2) Combine them with the top-level help command.
+commands = merge(Dict("help" => Help.help), jupyter_llm_commands)
+
+# 3) Start JustSayIt with the Jupyter notebook LLM-assisted commands.
+start(commands=commands)