from __future__ import annotations

from typing import Any, Optional

from pydantic import BaseModel, ConfigDict, Field


class MountedAISourceItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    source_system: str
    run_count: int = 0
    topic_count: int = 0
    active_topic_count: int = 0
    last_seen_at: Optional[str] = None


class MountedAISourceListPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    items: list[MountedAISourceItem] = Field(default_factory=list)


class MountedAISourceActivationItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    source_system: str
    scope_type: str
    scope_ref: str
    status: str
    cutover_mode: str
    auto_reply_enabled: bool
    last_seen_at: Optional[str] = None
    notes: Optional[str] = None
    metadata_json: Optional[Any] = None


class MountedAISourceActivationListPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    items: list[MountedAISourceActivationItem] = Field(default_factory=list)


class MountedAISourceActivationUpsertRequest(BaseModel):
    model_config = ConfigDict(extra="ignore")

    source_system: str = Field(min_length=1, max_length=32)
    scope_type: str = Field(default="tenant", min_length=1, max_length=24)
    scope_ref: str = Field(min_length=1, max_length=128)
    status: str = Field(default="active", min_length=1, max_length=24)
    cutover_mode: str = Field(default="shadow", min_length=1, max_length=24)
    auto_reply_enabled: bool = False
    notes: Optional[str] = None
    metadata_json: Optional[Any] = None


class MountedAISourceActivationUpsertPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    item: MountedAISourceActivationItem


class MountedAIToolPolicyItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    tool_name: str
    risk_level: str
    confirm_required: bool
    auto_execute_allowed: bool
    is_active: bool
    source_scope: Optional[Any] = None
    tenant_scope: Optional[Any] = None
    policy_metadata: Optional[Any] = None
    notes: Optional[str] = None


class MountedAIToolPolicyListPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    items: list[MountedAIToolPolicyItem] = Field(default_factory=list)


class MountedAIToolPolicyUpsertRequest(BaseModel):
    model_config = ConfigDict(extra="ignore")

    tool_name: str = Field(min_length=1, max_length=128)
    risk_level: str = Field(default="medium", min_length=1, max_length=24)
    confirm_required: bool = True
    auto_execute_allowed: bool = False
    is_active: bool = True
    source_scope: Optional[Any] = None
    tenant_scope: Optional[Any] = None
    policy_metadata: Optional[Any] = None
    notes: Optional[str] = None


class MountedAIToolPolicyUpsertPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    item: MountedAIToolPolicyItem


class MountedAITopicItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    topic_key: str
    source_system: str
    channel_ref: Optional[str] = None
    thread_key: Optional[str] = None
    mode: str
    status: str
    plan_status: Optional[str] = None
    readiness_score: Optional[float] = None
    draft_state: Optional[str] = None
    draft_version: Optional[int] = None
    updated_at: Optional[str] = None


class MountedAITopicListPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    items: list[MountedAITopicItem] = Field(default_factory=list)
    total: int = 0


class MountedAIRunItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    trace_id: str
    source_system: str
    source_message_id: Optional[str] = None
    mode_before: Optional[str] = None
    mode_after: Optional[str] = None
    active_agent: Optional[str] = None
    status: str
    trigger_reason: Optional[str] = None
    final_reply: Optional[str] = None
    trace_count: int = 0
    updated_at: Optional[str] = None


class MountedAIRunListPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    items: list[MountedAIRunItem] = Field(default_factory=list)
    total: int = 0


class MountedAIAgentTraceItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    agent_name: str
    status: str
    latency_ms: Optional[int] = None
    failure_reason: Optional[str] = None
    input_summary: Optional[Any] = None
    output_summary: Optional[Any] = None
    tool_trace: Optional[Any] = None
    created_at: Optional[str] = None


class MountedAIRunDetailPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    item: MountedAIRunItem
    agent_traces: list[MountedAIAgentTraceItem] = Field(default_factory=list)
    context_layers_hit: Optional[Any] = None
    tool_calls: Optional[Any] = None
    execution_outcome: Optional[Any] = None


class MountedAICutoverStatusPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    mounted_runtime_ready: bool
    topic_workspace_count: int = 0
    conversation_run_count: int = 0
    tool_policy_count: int = 0
    observed_source_systems: list[str] = Field(default_factory=list)
    legacy_cutover_state: str
    retired_item_count: int = 0
    active_item_count: int = 0
    legacy_cutover_items: list["MountedAILegacyCutoverItem"] = Field(default_factory=list)


class MountedAILegacyCutoverItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    key: str
    title: str
    status: str
    summary: str
    evidence: str


class MountedAIEvalSuiteItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    dataset_type: str
    version: str
    status: str
    suite_kind: str
    sample_count: int = 0
    latest_score: Optional[float] = None
    last_evaluated_at: Optional[str] = None


class MountedAIEvalSuiteListPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    items: list[MountedAIEvalSuiteItem] = Field(default_factory=list)
    total: int = 0


class MountedAIEvalResultItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    evaluation_type: str
    status: str
    score: Optional[float] = None


class MountedAIEvalSuiteDetailPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    item: MountedAIEvalSuiteItem
    selection_rules: Optional[Any] = None
    notes: Optional[str] = None
    evaluations: list[MountedAIEvalResultItem] = Field(default_factory=list)


class MountedAIRegressionBucketItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    bucket_key: str
    run_count: int = 0
    avg_score: Optional[float] = None
    last_seen_at: Optional[str] = None


class MountedAITrainingDatasetItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    dataset_type: str
    version: str
    status: str
    sample_count: int = 0
    suite_kind: Optional[str] = None


class MountedAITrainingJobItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    id: int
    job_type: str
    target_slot: str
    status: str
    provider_backend: str
    dataset_id: int
    artifact_ref: Optional[str] = None


class MountedAITrainingAcceptanceGate(BaseModel):
    model_config = ConfigDict(extra="ignore")

    ready_for_acceptance: bool = False
    threshold_score: float = 90.0
    frozen_eval_score: Optional[float] = None
    severe_blocker_count: int = 0
    blocking_reason: str


class MountedAITrainingOpsPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    dataset_count: int = 0
    ready_eval_suite_count: int = 0
    pending_job_count: int = 0
    candidate_deployment_count: int = 0
    approved_golden_asset_count: int = 0
    approved_failure_asset_count: int = 0
    preference_pair_count: int = 0
    hard_case_count: int = 0
    last_training_job_at: Optional[str] = None
    regression_buckets: list[MountedAIRegressionBucketItem] = Field(default_factory=list)
    recent_datasets: list[MountedAITrainingDatasetItem] = Field(default_factory=list)
    recent_jobs: list[MountedAITrainingJobItem] = Field(default_factory=list)
    acceptance_gate: MountedAITrainingAcceptanceGate


class MountedAIHardCaseItem(BaseModel):
    model_config = ConfigDict(extra="ignore")

    judge_run_id: int
    asset_id: Optional[int] = None
    bucket_key: str
    judge_status: str
    overall_score: Optional[float] = None
    prompt_key: Optional[str] = None
    workflow_type: Optional[str] = None
    asked_via: Optional[str] = None
    question_text: Optional[str] = None
    answer_text: Optional[str] = None
    corrected_answer: Optional[str] = None
    findings: Optional[Any] = None
    created_at: Optional[str] = None


class MountedAIHardCaseListPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    items: list[MountedAIHardCaseItem] = Field(default_factory=list)
    total: int = 0


class MountedAIReplayRunRequest(BaseModel):
    model_config = ConfigDict(extra="ignore")

    run_id: int
    asset_type: str = Field(default="failure", min_length=1, max_length=16)
    bucket_key: Optional[str] = Field(default=None, max_length=255)
    question_text: Optional[str] = None
    answer_text: Optional[str] = None
    corrected_answer: Optional[str] = None
    notes: Optional[str] = None
    persist_quality_asset: bool = True
    overall_score: Optional[float] = None
    rule_score: Optional[float] = None
    llm_score: Optional[float] = None
    findings: Optional[Any] = None


class MountedAIReplayRunPayload(BaseModel):
    model_config = ConfigDict(extra="ignore")

    run_id: int
    asset: Optional[Any] = None
    judge_run: Optional[Any] = None