/- Copyright (c) 2026 Sovereign Research Stack. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Research Stack Team

NextGenAgentDesign.lean — Swarm-Designed Next-Generation Agent Architecture

Replaces scripts/swarm_design_nextgen_agents.py with a formal Lean module
that analyzes current agent performance and designs next-generation improvements.

Per AGENTS.md:
  - Q16_16 for scoring (§1.4)
  - PascalCase types, camelCase functions (§2)
  - Theorems for correctness (§4)
  - No proof placeholders in committed code (§1.6)
-/

import Mathlib.Data.Nat.Basic
import Mathlib.Data.List.Basic
import Lean.Data.Json

namespace Semantics.NextGenAgentDesign

-- ═══════════════════════════════════════════════════════════════════════════
-- §0  Q16.16 Fixed-Point for Scoring
-- ═══════════════════════════════════════════════════════════════════════════

structure Q16_16 where
  raw : Int
  deriving Repr, DecidableEq, Inhabited, BEq

namespace Q16_16

def zero : Q16_16 := ⟨0⟩
def one : Q16_16 := ⟨65536⟩
def ofNat (n : Nat) : Q16_16 := ⟨n * 65536⟩
def toNat (q : Q16_16) : Nat := q.raw.toNat / 65536
def ofFrac (num denom : Nat) : Q16_16 :=
  if denom = 0 then zero else ⟨(num * 65536) / denom⟩

instance : LE Q16_16 := ⟨fun a b => a.raw ≤ b.raw⟩
instance : LT Q16_16 := ⟨fun a b => a.raw < b.raw⟩
instance : Add Q16_16 := ⟨fun a b => ⟨a.raw + b.raw⟩⟩
instance : Sub Q16_16 := ⟨fun a b => ⟨a.raw - b.raw⟩⟩
instance : Mul Q16_16 := ⟨fun a b => ⟨(a.raw * b.raw) / 65536⟩⟩
instance : HDiv Q16_16 Q16_16 Q16_16 := ⟨fun a b => ⟨(a.raw * 65536) / b.raw⟩⟩

end Q16_16

instance : Lean.ToJson Q16_16 := ⟨fun q => Lean.toJson q.raw⟩
instance : Lean.FromJson Q16_16 := ⟨fun j => match Lean.fromJson? j with | .ok r => .ok ⟨r⟩ | .error e => .error e⟩

-- ═══════════════════════════════════════════════════════════════════════════
-- §1  Agent Generation Types
-- ═══════════════════════════════════════════════════════════════════════════

inductive AgentGeneration
  | gen1
  | gen2
  | gen3
  deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson

structure CurrentAgentMetrics where
  totalImprovement : Q16_16
  iterations : Nat
  agentCount : Nat
  tsmUtilization : Q16_16
  bestOptimization : String
  synergyFactor : Q16_16
  diminishingReturns : Q16_16
  deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson

structure BottleneckAnalysis where
  name : String
  severity : Q16_16
  impact : String
  rootCause : String
  proposedSolution : String
  deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson

inductive InnovationType
  | incremental
  | breakthrough
  | paradigmShift
  deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson

inductive Complexity
  | low
  | medium
  | high
  deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson

structure NextGenAgentFeature where
  name : String
  description : String
  innovationType : InnovationType
  estimatedImprovement : Q16_16
  implementationComplexity : Complexity
  dependencies : List String
  deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson

-- ═══════════════════════════════════════════════════════════════════════════
-- §2  Current Metrics (511% Achievement)
-- ═══════════════════════════════════════════════════════════════════════════

def currentBaseline : CurrentAgentMetrics :=
  { totalImprovement := Q16_16.ofNat 511
    iterations := 3
    agentCount := 50
    tsmUtilization := Q16_16.ofFrac 50 100
    bestOptimization := "memory_prefetch"
    synergyFactor := Q16_16.ofFrac 1007 1000
    diminishingReturns := Q16_16.ofFrac 10 1000 }

-- ═══════════════════════════════════════════════════════════════════════════
-- §3  Bottleneck Identification
-- ═══════════════════════════════════════════════════════════════════════════

def identifyBottlenecks : List BottleneckAnalysis :=
  [
    { name := "Static Memory Allocation"
      severity := Q16_16.ofFrac 70 100
      impact := "Agents locked to 6.57GB quota, no dynamic scaling"
      rootCause := "Pre-allocated per-agent memory, no borrow/lend"
      proposedSolution := "Dynamic memory market with borrow/lend protocol" },
    { name := "Single Optimization Target"
      severity := Q16_16.ofFrac 60 100
      impact := "Each agent locked to one target, no crossover"
      rootCause := "Specialization without generalization"
      proposedSolution := "Multi-objective optimization with target blending" },
    { name := "No Self-Modification"
      severity := Q16_16.ofFrac 80 100
      impact := "Agents cannot improve their own optimization strategy"
      rootCause := "Fixed optimization logic, no meta-learning"
      proposedSolution := "Self-modifying agents with meta-optimization loops" },
    { name := "Synchronous Iterations"
      severity := Q16_16.ofFrac 50 100
      impact := "Wait for all agents to complete before next iteration"
      rootCause := "Barrier synchronization between iterations"
      proposedSolution := "Asynchronous continuous optimization pipeline" },
    { name := "No Knowledge Transfer"
      severity := Q16_16.ofFrac 60 100
      impact := "Each iteration starts from scratch, no cumulative learning"
      rootCause := "Stateless agents, no persistent memory across runs"
      proposedSolution := "Knowledge graph with transferable optimizations" },
    { name := "Homogeneous Agent Design"
      severity := Q16_16.ofFrac 40 100
      impact := "All 50 agents have same capabilities, no specialization"
      rootCause := "One-size-fits-all agent template"
      proposedSolution := "Heterogeneous swarm with role specialization" }
  ]

-- ═══════════════════════════════════════════════════════════════════════════
-- §4  Next-Generation Features
-- ═══════════════════════════════════════════════════════════════════════════

def designNextGenFeatures : List NextGenAgentFeature :=
  [
    { name := "Dynamic Memory Market"
      description := "Agents can borrow/lend memory quota in real-time based on task complexity"
      innovationType := .breakthrough
      estimatedImprovement := Q16_16.ofFrac 35 100
      implementationComplexity := .high
      dependencies := ["Real-time resource monitoring", "Credit system", "Bankruptcy handling"] },
    { name := "Self-Modifying Optimization"
      description := "Agents can rewrite their own optimization strategy based on success/failure"
      innovationType := .paradigmShift
      estimatedImprovement := Q16_16.ofFrac 50 100
      implementationComplexity := .high
      dependencies := ["Code introspection", "Safe self-modification", "Validation hooks"] },
    { name := "Multi-Objective Blending"
      description := "Agents optimize multiple targets simultaneously with weighted blending"
      innovationType := .breakthrough
      estimatedImprovement := Q16_16.ofFrac 25 100
      implementationComplexity := .medium
      dependencies := ["Pareto frontier tracking", "Dynamic weight adjustment"] },
    { name := "Asynchronous Pipeline"
      description := "Continuous optimization without iteration barriers"
      innovationType := .breakthrough
      estimatedImprovement := Q16_16.ofFrac 20 100
      implementationComplexity := .medium
      dependencies := ["Streaming results", "Conflict resolution", "Progress tracking"] },
    { name := "Knowledge Graph Persistence"
      description := "Cumulative learning across runs via shared knowledge graph"
      innovationType := .breakthrough
      estimatedImprovement := Q16_16.ofFrac 30 100
      implementationComplexity := .high
      dependencies := ["Graph database", "Semantic embedding", "Retrieval system"] },
    { name := "Heterogeneous Swarm Roles"
      description := "Specialized agent types: Explorers, Exploiters, Validators, Synthesizers"
      innovationType := .breakthrough
      estimatedImprovement := Q16_16.ofFrac 40 100
      implementationComplexity := .high
      dependencies := ["Role assignment protocol", "Inter-role communication", "Dynamic rebalancing"] },
    { name := "Curvature-Guided Agent Placement"
      description := "Place agents on manifold topology based on optimization affinity"
      innovationType := .incremental
      estimatedImprovement := Q16_16.ofFrac 15 100
      implementationComplexity := .medium
      dependencies := ["Manifold awareness", "Affinity scoring", "Migration protocol"] },
    { name := "Triumvirate Meta-Validation"
      description := "Builder/Judge/Warden for the agents themselves, not just results"
      innovationType := .breakthrough
      estimatedImprovement := Q16_16.ofFrac 20 100
      implementationComplexity := .high
      dependencies := ["Agent introspection", "Behavior validation", "Self-correction"] },
    { name := "Gene-JIT Integration"
      description := "Compile agent strategies to gene bytecode for fast execution"
      innovationType := .breakthrough
      estimatedImprovement := Q16_16.ofFrac 30 100
      implementationComplexity := .high
      dependencies := ["Strategy-to-bytecode compiler", "Gene JIT runtime", "Hot-swapping"] },
    { name := "Emergent Coalition Formation"
      description := "Agents self-organize into coalitions for complex multi-target optimization"
      innovationType := .paradigmShift
      estimatedImprovement := Q16_16.ofFrac 45 100
      implementationComplexity := .high
      dependencies := ["Coalition protocol", "Voting mechanism", "Reward distribution"] }
  ]

-- ═══════════════════════════════════════════════════════════════════════════
-- §5  Cumulative Improvement Calculation
-- ═══════════════════════════════════════════════════════════════════════════

def calculateCumulativeImprovement (features : List NextGenAgentFeature) : Q16_16 :=
  let cumulative := features.foldl
    (fun acc f =>
      let improvement := (Q16_16.toNat f.estimatedImprovement)
      let onePlus := Q16_16.ofNat (improvement + 1) -- Simplified relative to 1
      acc * onePlus) 
    Q16_16.one
  (cumulative - Q16_16.one)

def calculateProjectedEfficiency (baseline : Q16_16) (improvement : Q16_16) : Q16_16 :=
  baseline * (Q16_16.one + improvement)

-- ═══════════════════════════════════════════════════════════════════════════
-- §6  Architecture Blueprint
-- ═══════════════════════════════════════════════════════════════════════════

inductive AgentRole
  | explorer
  | exploiter
  | validator
  | synthesizer
  deriving Repr, DecidableEq, Inhabited, Lean.ToJson, Lean.FromJson

structure RoleDefinition where
  purpose : String
  traits : String
  populationPercentage : Q16_16
  deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson

structure ArchitectureLayer where
  name : String
  description : String
  mechanism : String
  improvement : Q16_16
  deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson

structure ArchitectureBlueprint where
  name : String
  generation : String
  philosophy : String
  corePrinciples : List String
  architectureLayers : List ArchitectureLayer
  agentRoles : List (AgentRole × RoleDefinition)
  performanceTargets : List (String × String)
  deriving Repr, Inhabited, Lean.ToJson, Lean.FromJson

-- ═══════════════════════════════════════════════════════════════════════════
-- §7  Interface for CLI
-- ═══════════════════════════════════════════════════════════════════════════

structure DesignResult where
  currentMetrics : CurrentAgentMetrics
  bottlenecks : List BottleneckAnalysis
  features : List NextGenAgentFeature
  cumulativeImprovement : Q16_16
  projectedEfficiency : Q16_16
  deriving Lean.ToJson, Lean.FromJson

def runDesignProcess : DesignResult :=
  let metrics := currentBaseline
  let bottlenecks := identifyBottlenecks
  let features := designNextGenFeatures
  let cumulative := calculateCumulativeImprovement features
  let projected := calculateProjectedEfficiency metrics.totalImprovement cumulative
  { currentMetrics := metrics
    bottlenecks := bottlenecks
    features := features
    cumulativeImprovement := cumulative
    projectedEfficiency := projected }

end Semantics.NextGenAgentDesign
