-- A full RAG ingestion pipeline in ONE expression
let doc be Document("notes.txt", "MOL is built for IntraMind pipelines.")

let index be doc |> chunk(30) |> embed |> store("my_index")

show index

  ┌─ Pipeline Trace ──────────────────────────────────────
  │ 0.  input                   ─  <Document:a3f2 "notes.txt" 39B>
  │ 1.  chunk(..)           0.1ms  → List<2 Chunks>
  │ 2.  embed               0.2ms  → List<2 Embeddings>
  │ 3.  store(..)           0.0ms  → <VectorStore:b7c1 "my_index" 2 vectors>
  └─ 3 steps · 0.3ms total ───────────────────────────
<VectorStore:b7c1 "my_index" 2 vectors>

-- Inferred type
let name be "IntraMind"
let count be 42

-- Explicit type annotation (mismatch = compile error)
let x : Number be 10
let msg : Text be "hello"
let flag : Bool be true

-- Reassignment
set count to count + 1

if score > 90 then
  show "excellent"
elif score > 70 then
  show "good"
else
  show "needs work"
end

while count < 10 do
  set count to count + 1
end

for item in range(5) do
  show to_text(item)
end

define greet(name)
  return "Hello, " + name + "!"
end

show greet("Mounesh")

-- This is a comment
show "code"  -- inline comment

-- Single stage
"hello world" |> upper              -- "HELLO WORLD"

-- With arguments
"a,b,c" |> split(",")              -- ["a", "b", "c"]

-- Multi-stage chain (auto-traced when 3+ stages)
"  HELLO  " |> trim |> lower |> split(" ")

-- With custom functions
define double(x)
  return x * 2
end

5 |> double |> add_ten |> double    -- 40

pipeline preprocess(data)
  return data |> trim |> lower
end

let clean be "  RAW INPUT  " |> preprocess
show clean   -- "raw input"

  ┌─ Pipeline Trace ──────────────────────────────────────
  │ 0.  input                   ─  Text("  HELLO  ")
  │ 1.  trim                0.0ms  → Text("HELLO")
  │ 2.  lower               0.0ms  → Text("hello")
  │ 3.  split(..)           0.0ms  → List<1 strs>
  └─ 3 steps · 0.0ms total ───────────────────────────

trigger "event_name"           -- Fire an event
listen "event_name" do ... end -- Listen for events
link nodeA to nodeB            -- Connect nodes
process node with 0.3          -- Activate & adjust
evolve node                    -- Next generation
access "mind_core"             -- Request resource (checked!)
sync stream                    -- Synchronize data
emit "data"                    -- Emit to stream

guard confidence > 0.8 : "Confidence too low for production"
guard len(data) > 0 : "Empty dataset"
guard answer |> assert_not_null

-- 1. Create a document
let doc be Document("kb.txt", "Machine learning enables computers to learn. Deep learning uses neural networks.")

-- 2. Ingest: chunk → embed → store (ONE expression)
doc |> chunk(50) |> embed |> store("knowledge")

-- 3. Query
let results be retrieve("What is deep learning?", "knowledge", 3)

-- 4. Synthesize answer
let answer be results |> think("answer the question")

-- 5. Validate quality
guard answer.confidence > 0.5 : "Low confidence"

show answer.content

access "mind_core"      -- ✅ Allowed
access "memory_bank"    -- ✅ Allowed
access "secret_vault"   -- 🔒 DENIED — MOLSecurityError

let x : Number be "hello"   -- 🚫 MOLTypeError at declaration

-- MOL
"hello" |> upper |> split(" ")

-- Import everything
use std

-- Import specific functions
use math : sqrt, pi

-- Alias
use text as T

let task be spawn do
  sleep(1000)
  "result"
end
show "main continues..."
let result be await task

let results be parallel(items, fn(x) -> process(x))

let ch be channel()
spawn do
  send(ch, "hello")
end
let msg be receive(ch)

let winner be race([task1, task2])    -- first to finish
let all be wait_all([task1, task2])   -- wait for all

let double be fn(x) -> x * 2
let result be [1, 2, 3] |> map(fn(x) -> x * x)

let grade be match score with
  | s when s >= 90 -> "A"
  | s when s >= 80 -> "B"
  | [x, y] -> f"pair({x}, {y})"
  | _ -> "default"
end

let timeout be config ?? 30         -- fallback if null

let msg be f"Hello {name}, you have {count} items"

let [first, ...rest] be [1, 2, 3, 4]
let {x, y} be {"x": 10, "y": 20}

try
  let data be risky_operation()
rescue e
  show f"Error: {e}"
ensure
  cleanup()
end

define greet(name, greeting be "Hello")
  show f"{greeting}, {name}!"
end
greet("World")          -- Hello, World!
greet("MOL", "Welcome") -- Welcome, MOL!

test "arithmetic" do
  assert_eq(2 + 2, 4)
  assert_true(10 > 5)
end

MOL/
├── mol/                        # Language implementation
│   ├── __init__.py             # Package metadata (v0.5.0)
│   ├── grammar.lark            # Lark EBNF grammar specification
│   ├── parser.py               # LALR parser + AST transformer
│   ├── ast_nodes.py            # 45+ AST node dataclasses
│   ├── interpreter.py          # Visitor-pattern interpreter with auto-tracing
│   ├── types.py                # Domain types (8 types)
│   ├── stdlib.py               # 90+ built-in functions
│   ├── transpiler.py           # Python & JavaScript transpiler
│   ├── lsp_server.py           # Language Server Protocol (LSP) server
│   ├── package_manager.py      # Package manager (init/install/publish)
│   ├── wasm_builder.py         # Browser/JS compilation
│   ├── runtime.js              # JavaScript runtime (90+ functions)
│   └── cli.py                  # CLI interface
├── docs/                       # MkDocs Material documentation source
├── examples/                   # 16 example programs
├── tutorial/                   # 6 tutorial files + cheatsheet
├── tests/test_mol.py           # 68 tests (all passing)
├── mol-vscode/                 # VS Code extension + LSP client
├── mkdocs.yml                  # MkDocs configuration
├── pyproject.toml              # Python project config
├── Dockerfile                  # Docker image (144 MB)
├── LANGUAGE_SPEC.md            # Formal language specification
├── CHANGELOG.md                # Version history
├── ROADMAP.md                  # Development roadmap
└── LICENSE                     # License

┌─────────────┐     ┌──────────────┐     ┌─────────────┐     ┌──────────────┐
│  .mol file  │ ──▶ │  Lark LALR   │ ──▶ │     AST     │ ──▶ │ Interpreter  │
│  (source)   │     │  Parser      │     │  (35+ node  │     │  (Visitor +  │
│             │     │              │     │   types)    │     │  Auto-Trace) │
└─────────────┘     └──────────────┘     └──────┬──────┘     └──────────────┘
                                                │
                                    ┌───────────┼───────────┐
                                    ▼           ▼           ▼
                              ┌──────────┐ ┌──────────┐ ┌──────────┐
                              │  Python  │ │   JS     │ │  (more)  │
                              │  Output  │ │  Output  │ │          │
                              └──────────┘ └──────────┘ └──────────┘