nema-lang 0.1.0

Agent-oriented programming language where emotion is a first-class citizen

Nema Language

NeuroState + Emilia — An agent-oriented programming language where emotion is a first-class citizen.

"Agents don't just compute. They feel."

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What is Nema?

Nema is a programming language where every agent has a NeuroState — a 6-dimensional emotional state based on neurotransmitters. Emotions gate function execution, propagate between agents, decay over time, and drive memory management.

@requires(dp > 0.6) compiles to a machine-level fcmp ogt instruction.
The world's first emotional conditional branch.

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Install

pip install nema-lang

Requires Python 3.10+ and LLVM (via llvmlite).

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Quick Start

# Run the REPL interpreter
nema hello.nema

# JIT compile and run benchmarks
python -m jit_run hello.nema

# Generate LLVM IR
nema hello.nema --compile
# → produces hello.ll

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Language Example

agent Neko {
  mood: NeuroState = {
    dp: 0.8, s: 0.5, ac: 0.7,
    ox: 0.6, gaba: 0.4, e: 0.6
  }

  // compiles to: fcmp ogt double %dp, 6.000000e-01
  @requires(dp > 0.6)
  fn explore(path) { }

  // multi-condition gate — both must be true
  @requires(gaba > 0.5 and s > 0.4)
  fn sleep() { }
}

agent Kernel {
  mood: NeuroState = {
    dp: 0.5, s: 0.7, ac: 0.9,
    ox: 0.4, gaba: 0.5, e: 0.5
  }

  // real malloc — gated by emotional focus
  @requires(ac > 0.8 and dp > 0.3)
  fn alloc(size: i64) -> ptr<i64> { }

  @requires(ac > 0.5)
  fn write(addr: ptr<i64>, val: i64) -> void { }

  @requires(dp > 0.3)
  fn read(addr: ptr<i64>) -> i64 { }

  fn free(addr: ptr<i64>) -> void { }
}

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Architecture

Nema source (.nema)
       ↓
   Lexer / Parser
       ↓
   Type Checker  ← validates NeuroState fields, ranges, always-fail gates
       ↓
      AST
       ↙        ↘
 Interpreter    LLVM Compiler
 (REPL mode)   (JIT / .ll output)
       ↓              ↓
  Runtime         Machine code
(emotion lives)  (emotion compiled)

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The 6 Dimensions

Symbol	Neurotransmitter	Meaning
dp	Dopamine	Curiosity, motivation
s	Serotonin	Stability, calm
ac	Acetylcholine	Focus, attention
ox	Oxytocin	Trust, empathy
gaba	GABA	Inhibition, composure
e	Endorphin	Joy, achievement

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REPL Commands

Command	Description
show <agent>	Display NeuroState + memory
call <agent> <fn> [args]	Call function (emotion-gated)
attract <A> <B> [strength]	Set symmetric attraction between agents
remember <agent> <key> <value>	Write to working memory
recall <agent> <key>	Retrieve from memory
introspect <agent>	Verbalize emotional state in Japanese
empathize <A> <B>	A absorbs 30% of B's emotional state
log <agent> <msg>	Log with emotional context
rand_mood <agent>	Randomize NeuroState
summarize <agent>	Swap working memory to long-term storage

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Core Features

Emotion Gates → Machine Code

@requires(dp > 0.6)
fn explore(path) { }

@requires(ac > 0.8 and dp > 0.3)
fn alloc(size: i64) -> ptr<i64> { }

Each condition compiles to fcmp ogt + and i1 + conditional branch in LLVM IR.
Gate-rejected functions return -1 (or null for pointer types).

Real Memory Operations

alloc, write, read, free compile to actual malloc/store/load/free instructions — not simulated, real machine code guarded by emotional state.

Static Type System

fn alloc(size: i64) -> ptr<i64> { }
fn write(addr: ptr<i64>, val: i64) -> void { }

Supported types: i64, i32, f64, bool, void, ptr<T>, NeuroState

Static Type Checker

Validates at parse time:

• Unknown NeuroState fields → error
• Values outside [0.0, 1.0] → error
• @requires(dp > 1.5) → warning (always fails)

Emotional Decay (background thread)

Every 5 seconds, all emotions decay at neurotransmitter-specific rates. Serotonin fades slowly; dopamine faster. Agents grow tired if left alone.

Agent Attraction

attract Neko Shii 0.5

Symmetric emotional pull — agents converge toward each other's state on every tick.
Compiles to (B[f] - A[f]) * strength * 0.1 delta applied symmetrically via LLVM fsub/fmul/fadd.

CPOS Memory Layer

Working memory (RAM, max 5 entries) + long-term storage (JSON).
When gaba ≥ 0.7, composure triggers automatic memory consolidation (swap to disk).

JIT Performance

Operation	Speedup over interpreter
tick (decay)	10.4×
gate check	6.3×
attract	9.6×

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LLVM IR Output

; NeuroState as double[6]
@"mood_Neko" = internal global [6 x double] [
  double 0x3fe999999999999a,  ; dp = 0.8
  double 0x3fe0000000000000,  ; s  = 0.5
  ...
]

; @requires(dp > 0.6) → fcmp ogt
define i32 @"fn_Neko_explore"() {
entry:
  %val_dp = load double, double* %dp_ptr
  %cmp_dp = fcmp ogt double %val_dp, 6.000000e-01
  br i1 %gate, label %exec, label %reject
exec:
  ret i32 0
reject:
  ret i32 -1
}

; alloc: real malloc gated by emotion
define i64* @"impl_Kernel_alloc"(i64 %size) {
entry:
  %cmp_ac = fcmp ogt double %ac, 8.000000e-01
  %cmp_dp = fcmp ogt double %dp, 3.000000e-01
  %gate = and i1 %cmp_ac, %cmp_dp
  br i1 %gate, label %exec, label %reject
exec:
  %nbytes = mul i64 %size, 8
  %raw = call i8* @malloc(i64 %nbytes)
  %ptr = bitcast i8* %raw to i64*
  ret i64* %ptr
reject:
  ret i64* null
}

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Files

File	Role
lexer.py	Tokenizer
parser.py	AST parser
ast_nodes.py	AST node definitions
typechecker.py	Static type checker
evaluator.py	Interpreter runtime
stdlib.py	Standard library
compiler.py	LLVM IR code generator
jit_run.py	JIT compiler + runner
nema.py	Entry point + REPL
hello.nema	Example: multi-agent with emotion
typed.nema	Example: typed memory ops
benchmark.py	JIT vs interpreter benchmarks

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Background

Nema is built on two original concepts:

• NeuroState — A 6-dimensional emotional model based on neurotransmitters, developed as part of the Emilia OS research project. [Zenodo DOI: 10.5281/zenodo.19734147]
• CPOS (Context Pointer OS) — A cognitive memory kernel for LLM agents. [github.com/kagioneko/context-pointer-os]

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Nema — where code has feelings.