"""ElysiumResponse v1.0.0 — matches the exact JSON your fine-tuned model emits.
Based on the user-provided training_dataset.jsonl example.
"""
from __future__ import annotations
from typing import Optional, List, Dict, Any, Literal
from pydantic import BaseModel, Field, ConfigDict


class _Base(BaseModel):
    model_config = ConfigDict(extra="allow", populate_by_name=True)


# ─── Perception ───
class MultimodalPerception(_Base):
    input_modalities_detected: List[str] = []
    ocr_extracted_text: Optional[str] = None
    image_scene_description: Optional[str] = None
    visual_entities_detected: List[str] = []
    document_type: Optional[str] = None


# ─── Hypergraph ───
class HypergraphNode(_Base):
    node_id: str
    node_type: str
    label: str
    payload: Dict[str, Any] = {}
    embedding_hint: str = ""


class HypergraphEdge(_Base):
    edge_id: str
    source_node_id: str
    target_node_id: str
    edge_type: str
    weight: float = 0.5
    payload: Dict[str, Any] = {}


class NodeUpdate(_Base):
    node_id: str
    fields_changed: Dict[str, Any] = {}
    reason: Optional[str] = None


class EdgeWeaken(_Base):
    edge_id: str
    new_weight: float
    reason: Optional[str] = None


class HypergraphDelta(_Base):
    nodes_added: List[HypergraphNode] = []
    nodes_updated: List[NodeUpdate] = []
    edges_added: List[HypergraphEdge] = []
    edges_weakened: List[EdgeWeaken] = []


# ─── Council ───
class VoiceDesign(_Base):
    voice_id: str = "voice_default"
    pace: str = "moderate"
    tone: str = "calm_grounded"


class AgentOutput(_Base):
    agent_id: str
    agent_name: str
    archetype: str
    domain: str
    thinking: str = ""
    stance: str = ""
    confidence: float = 0.8
    dissents_from: List[str] = []
    coalesces_with: List[str] = []
    veto_triggered: bool = False
    veto_reason: Optional[str] = None
    tts_speech_text: str = ""
    tts_voice_design: VoiceDesign = VoiceDesign()


class CoalitionEvent(_Base):
    event_id: str
    participants: List[str] = []
    type: str = "GENERAL"
    status: str = "ACTIVE"
    payload: Dict[str, Any] = {}


class SpeciationEvent(_Base):
    triggered: bool = False
    unsolved_tension_description: Optional[str] = None
    proposed_new_agent: Optional[Dict[str, Any]] = None


class CouncilDeliberation(_Base):
    active_agents: List[str] = []
    spawned_agents: List[str] = []
    deprecated_agents: List[str] = []
    agent_outputs: List[AgentOutput] = []
    coalition_events: List[CoalitionEvent] = []
    speciation_event: SpeciationEvent = SpeciationEvent()
    final_synthesis: str = ""
    debate_mode: str = "NONE"   # NONE | SILENT | AUDIO_DRAMA


# ─── Tools ───
class ToolCall(_Base):
    call_id: str
    tool_name: str
    calling_agent: str
    parameters: Dict[str, Any] = {}
    justification: str = ""
    priority: str = "MEDIUM"
    offline_fallback: str = ""


# ─── Action field ───
class ExecutableProtocol(_Base):
    protocol_id: str
    domain: str
    title: str
    type: str
    executing_agent: str
    time_to_execute_minutes: int = 5
    instructions: List[str] = []
    success_criteria: str = ""
    hypergraph_nodes_affected: List[str] = []


class QuestUpdate(_Base):
    quest_id: str
    domain: str
    title: str
    current_step: str
    next_step: str
    oracle_forecast: str = ""
    completion_probability: float = 0.5


class DailyActionField(_Base):
    morning_briefing_summary: Optional[str] = None
    evening_evolution_report: Optional[str] = None
    executable_protocols: List[ExecutableProtocol] = []
    quest_tree_updates: List[QuestUpdate] = []
    primary_focus: str = ""
    recommended_actions: List[str] = []
    energy_budget: str = "moderate"


# ─── Forecasts ───
class ProbabilisticForecast(_Base):
    forecast_id: str
    target: str
    distribution: str = "lognormal"
    parameters: Dict[str, Any] = {}
    confidence: float = 0.8
    horizon_seconds: int = 60


# ─── Strain ───
class StrainMetadata(_Base):
    active_strains: List[str] = ["base_civilization_v1"]
    strain_compatibility_score: float = 1.0
    recommended_strain_grafts: List[str] = []
    evolution_generation: int = 0
    cognitive_strain: float = 0.3
    emotional_strain: float = 0.2
    notes: str = ""


# ─── UI directives ───
class MyceliumThread(_Base):
    thread_id: str = ""
    source: str = ""
    target: str = ""
    type: str = "DATA_FLOW"
    from_node: str = ""
    to_node: str = ""
    color_hex: str = "#7FB3D5"
    animation: str = "pulse_slow"


class AgentEmergence(_Base):
    agent_id: str
    animation: str = "spawn_default"


class UIDirectives(_Base):
    bioluminescence_pulse_nodes: List[str] = []
    new_mycelium_threads: List[MyceliumThread] = []
    agent_emergence_animations: List[AgentEmergence] = []
    alert_level: str = "CALM"
    soundtrack_mood: str = "ambient_growth"
    camera_focus_node_id: Optional[str] = None


# ─── Meta ───
class Metadata(_Base):
    model_id: str = "elysium-minicpmv-4.6-ft-v1"
    inference_time_ms: int = 0
    hypergraph_node_count: int = 0
    hypergraph_edge_count: int = 0
    civilization_age_days: int = 0
    total_speciation_events: int = 0
    schema_validation_passed: bool = True
    generator: str = "elysium_runtime_v1"
    notes: str = ""


# ─── Root ───
class ElysiumResponse(_Base):
    schema_version: str = "1.0.0"
    session_id: str
    timestamp_utc: str
    interaction_type: str
    direct_answer: str = ""
    multimodal_perception: MultimodalPerception = MultimodalPerception()
    hypergraph_delta: HypergraphDelta = HypergraphDelta()
    council_deliberation: CouncilDeliberation = CouncilDeliberation()
    tool_calls: List[ToolCall] = []
    daily_action_field: DailyActionField = DailyActionField()
    probabilistic_forecasts: List[ProbabilisticForecast] = []
    strain_metadata: StrainMetadata = StrainMetadata()
    ui_directives: UIDirectives = UIDirectives()
    metadata: Metadata = Metadata()


class ElysiumEnvelope(_Base):
    user_msg: Optional[str] = None
    elysium_response: ElysiumResponse