# AI is just syntax
think "What should I build today?"

# Chain AI agents with ->
"Nigerian fintech trends" -> researcher -> analyst -> writer

# Neural pipeline
pipeline market_analysis:
    collect "African tech ecosystem"
    process with ai
    generate report
    save to database

run pipeline market_analysis

model "gemini"
think "Using Gemini now"

model "openai"
think "Using GPT now"

model "claude"
think "Using Claude now"

name = "Emmanuel"
show "Hello {name}!"
show "Welcome to NEKOVA — where AI is syntax."

# Standalone think
think "What is the capital of Nigeria?"

# Captured think
idea = think "Give me one startup idea in one sentence"
show "AI said: {idea}"

# Think with variables
topic = "African fintech"
result = think "Analyze {topic} in 2025"
show result

# Chain agents — output flows left to right
"Analyze Nigerian tech ecosystem" -> researcher -> marketer -> reporter

# Captured result
report = "Future of AI in Africa" -> analyst -> writer
show report

pipeline market_research:
    collect "Nigerian startup ecosystem 2025"
    process with ai
    generate report
    save to database

run pipeline market_research
result = run pipeline market_research
show result

# All three run simultaneously
autonomous parallel:
    think "Capital of Nigeria?"
    think "Capital of Ghana?"
    think "Capital of Kenya?"

# Captured results
results = autonomous parallel:
    think "Name one African unicorn"
    think "Name one Nigerian founder"

use vision
use voice

# Analyze an image
description = vision_scan("photo.png")
show "AI sees: {description}"

# Speak the result
voice_speak("Analysis complete!")

# Listen for input
transcript = voice_listen()
show "You said: {transcript}"

memory user_profile:
    name = "Emmanuel"
    language = "NEKOVA"
    run_count = 0

show user_profile["name"]
show user_profile["language"]

sandbox strict:
    show "Running in secure mode"
    think "What is 2 + 2?"

sandbox relaxed:
    use files
    data = read_file("input.txt")
    show data

# Variables
name = "Emmanuel"
age  = 20
items = [1, 2, 3]

# Conditions
if age >= 18:
    show "Adult"
else:
    show "Minor"

# Loops
repeat 5:
    show "NEKOVA!"

for item in items:
    show item

# Tasks (functions)
task greet(name):
    show "Hello {name}!"
    return "Done"

result = greet("World")
show result

use math
use text
use database
use web

show sqrt(144)
show upper("hello nekova")

db_connect("myapp.db")
db_create("users", "name text, age integer")
db_insert("users", "Emmanuel, 20")
results = db_find("users", "all")
show results

nekova/
├── main.py              ← Entry point
├── runner.py            ← Pipeline orchestrator
├── config.py            ← Version & constants
├── repl.py              ← Interactive shell
├── nekova_cli.py        ← pip CLI entry point
├── lexer/               ← Tokenizer
├── parser/              ← AST builder
├── interpreter/         ← Execution engine
├── compiler/            ← Bytecode compiler + VM
├── stdlib/              ← Standard library
├── ai/                  ← AI runtime + providers
├── web/                 ← Web framework
├── database/            ← Database system
├── ui/                  ← UI framework
├── web_ide/             ← Browser-based IDE
├── deploy/              ← Deployment tools
├── examples/            ← Example programs (.nk)
└── tests/               ← Test suite (147 tests)