"""ReviewFinalizer: apply human decisions, targeted reruns, RFIs, final artifacts.

All LLM-touching helpers degrade gracefully: a failed or empty targeted rerun
becomes a visible ``analysis_gap`` finding instead of raising, and RFI drafting
returns whatever was produced (possibly []). Finalization never crashes the job
on a single bad scope.
"""

import json
import os
from typing import Dict, List, Optional, Tuple

from backend import config
from backend.agents.base import AgentScope, AgentUsage
from backend.agents.conflict_critic import ConflictCriticAgent
from backend.agents.memory import ProjectMemory
from backend.agents.orchestrator import Orchestrator
from backend.agents.rfi_writer import RFIWriterAgent
# Private import, acceptable here: the runner's _finding_as_conflict is the
# canonical finding -> report["conflicts"] mapping; reusing it keeps the
# finalized report's conflicts in exactly the shape build_report produces.
from backend.agents.runner import _finding_as_conflict
from backend.pipeline.report import to_markdown
from backend.review.store import ReviewStore


def apply_decisions(prioritized: List[dict], decisions: Dict[str, dict]) -> Tuple[List[dict], List[dict]]:
    kept: List[dict] = []
    suppressed: List[dict] = []
    for issue in prioritized:
        review_id = f"finding:{issue.get('issue_id')}"
        decision = decisions.get(review_id) or {}
        action = decision.get("decision")
        if action == "reject":
            suppressed.append({
                **issue,
                "review_state": "rejected",
                "reason_code": decision.get("reason_code"),
                "review_comment": decision.get("comment") or "",
            })
        elif action == "unsure":
            kept.append({**issue, "review_state": "unsure"})
        else:
            kept.append({**issue, "review_state": "confirmed" if action == "confirm" else "unreviewed"})
    return kept, suppressed


def _gap_finding(index: int, scope_id: str, description: str) -> dict:
    """Same shape as the runner's gap_findings: low severity, high confidence."""
    return {
        "issue_id": f"AGENT-GAP-CLARIFY-{index + 1:03d}",
        "source_stage": "qaqc",
        "category": "analysis_gap",
        "severity": "low",
        "confidence": "high",
        "location": scope_id.split(":", 2)[1] if ":" in scope_id else "",
        "disciplines": [],
        "sheets": [],
        "description": description,
        "evidence": [],
        "recommended_resolution": "Review this scope manually or rerun the job.",
        "code_reference": None,
        "agent": "completeness",
        "scope_id": scope_id,
    }


def rerun_clarified_scopes(
    memory_snapshot: dict,
    decisions: Dict[str, dict],
    prioritized: Optional[List[dict]] = None,
) -> List[dict]:
    """Bounded targeted reruns for ``needs_clarification`` decisions.

    v1 reruns conflict scopes only: at most ONE ConflictCriticAgent scope per
    clarified finding. The clarification answer is injected as a pseudo
    "Reviewer" assertion prepended to the cluster's assertions so it reaches
    the critic's evidence block (and survives front-truncation to
    AGENT_CLUSTER_MAX_ASSERTIONS); ``page_to_b64`` is empty (cluster
    assertions may carry their own
    base64). Every per-scope failure degrades to an ``analysis_gap`` finding
    and never raises. Non-conflict scopes are NOT rerun; they produce an
    ``analysis_gap`` noting the scope is not rerunnable in v1.
    """
    findings_pool = list(prioritized or []) + list(memory_snapshot.get("findings") or [])
    clusters = memory_snapshot.get("clusters") or []
    out: List[dict] = []
    for item_id, decision in (decisions or {}).items():
        if (decision or {}).get("decision") != "needs_clarification":
            continue
        answer = str(decision.get("clarification_answer") or "").strip()
        if not answer:
            continue
        issue_id = item_id.split(":", 1)[1] if item_id.startswith("finding:") else item_id
        finding = next((f for f in findings_pool if f.get("issue_id") == issue_id), None)
        scope_id = str((finding or {}).get("scope_id") or "")
        if not scope_id.startswith("conflict:"):
            out.append(_gap_finding(
                len(out), scope_id or item_id,
                f"Clarification rerun not supported in v1 for non-conflict scope "
                f"{scope_id or item_id!r} (finding {issue_id}).",
            ))
            continue
        cluster_key = scope_id.split(":", 1)[1]
        cluster = next((c for c in clusters if c.get("key") == cluster_key), None)
        if cluster is None:
            out.append(_gap_finding(
                len(out), scope_id,
                f"Clarification rerun failed: cluster {cluster_key!r} not found "
                f"for scope {scope_id} (finding {issue_id}).",
            ))
            continue
        rerun_cluster = {
            **cluster,
            # Prepend: ConflictCriticAgent truncates assertions from the front
            # (AGENT_CLUSTER_MAX_ASSERTIONS), so the clarification must come
            # first or a full cluster would silently drop it.
            "assertions": [{
                "discipline": "Reviewer",
                "sheet_number": "REVIEW",
                "attribute": "clarification",
                "value": answer,
                "source_text": answer,
            }] + list(cluster.get("assertions") or []),
        }
        scope = AgentScope(
            scope_id=scope_id,
            payload={"cluster": rerun_cluster, "page_to_b64": {}},
        )
        result = ConflictCriticAgent(AgentUsage()).run(scope)
        if result.error or not result.artifacts:
            out.append(_gap_finding(
                len(out), scope_id,
                f"Clarification rerun did not complete for scope {scope_id} "
                f"(finding {issue_id}): {result.error or 'no findings produced'}.",
            ))
            continue
        for rerun_finding in result.artifacts:
            rerun_finding["clarification_of"] = issue_id
            out.append(rerun_finding)
    return out


def _draft_rfis(kept: List[dict]) -> List[dict]:
    """Draft RFIs for kept issues only, mirroring the runner's wave 7."""
    orchestrator = Orchestrator(ProjectMemory())
    scopes = [
        AgentScope(
            scope_id=f"rfi:{finding.get('issue_id') or index + 1}",
            payload={"finding": finding},
        )
        for index, finding in enumerate(kept)
    ]
    try:
        results = orchestrator.run_scopes(
            RFIWriterAgent(AgentUsage()), scopes, config.AGENT_RFI_CONCURRENCY
        )
    except Exception:
        return []
    return [artifact for result in results for artifact in result.artifacts]


def _read_json(path: str, default):
    try:
        with open(path, encoding="utf-8") as f:
            return json.load(f)
    except (OSError, json.JSONDecodeError):
        return default


def _dump(out_dir: str, name: str, value) -> None:
    with open(os.path.join(out_dir, name), "w", encoding="utf-8") as f:
        json.dump(value, f, indent=2)


def finalize_review(job_id: str, out_dir: str) -> dict:
    """Apply review decisions and write the final report artifacts.

    Raises ValueError("incomplete review") if any blocking queue item lacks a
    decision. Never raises for rerun/RFI degradation.
    """
    store = ReviewStore(out_dir)
    queue = store.read_queue()
    decisions = store.read_decisions()
    for item in queue:
        if item.get("blocking") and item.get("review_item_id") not in decisions:
            raise ValueError("incomplete review")

    report = _read_json(os.path.join(out_dir, "conflicts.json"), {}) or {}
    snapshot = _read_json(os.path.join(out_dir, "agent", "memory.json"), {}) or {}
    prioritized = list(report.get("validated_issues") or [])

    rerun_findings = rerun_clarified_scopes(snapshot, decisions, prioritized)
    replacements: Dict[str, List[dict]] = {}
    for finding in rerun_findings:
        origin = finding.get("clarification_of")
        if origin:
            replacements.setdefault(origin, []).append(finding)
        else:
            prioritized.append(finding)  # gap findings stay as additions
    for origin, new_findings in replacements.items():
        for index, issue in enumerate(prioritized):
            if issue.get("issue_id") == origin:
                prioritized[index:index + 1] = new_findings
                break

    kept, suppressed = apply_decisions(prioritized, decisions)
    for issue in kept:
        if issue.get("clarification_of"):
            issue["review_state"] = "clarified"
        else:
            decision = decisions.get(f"finding:{issue.get('issue_id')}") or {}
            if decision.get("decision") == "needs_clarification":
                issue["review_state"] = "clarification_failed"

    rfis = _draft_rfis(kept)

    report["validated_issues"] = kept
    report["suppressed_issues"] = suppressed
    report["rfis"] = rfis
    summary = report.setdefault("summary", {})
    summary["agent_status"] = "complete"
    by_stage = summary.get("by_stage")
    if isinstance(by_stage, dict):
        if "validated" in by_stage:
            by_stage["validated"] = len(kept)
        if "rfis" in by_stage:
            by_stage["rfis"] = len(rfis)
    # Rebuild the conflicts view and headline counts from the KEPT
    # conflict-stage findings so rejected findings no longer appear as
    # conflicts in report.md / the UI (mirrors pipeline.report.build_report).
    conflicts = [
        _finding_as_conflict(finding)
        for finding in kept
        if finding.get("source_stage") == "conflict"
    ]
    report["conflicts"] = conflicts
    by_severity = {"high": 0, "medium": 0, "low": 0}
    by_category: Dict[str, int] = {}
    for conflict in conflicts:
        by_severity[conflict["severity"]] = by_severity.get(conflict["severity"], 0) + 1
        by_category[conflict["category"]] = by_category.get(conflict["category"], 0) + 1
    summary["conflicts_found"] = len(conflicts)
    summary["by_severity"] = by_severity
    summary["by_category"] = by_category
    summary["review"] = store.progress(queue)

    os.makedirs(out_dir, exist_ok=True)
    _dump(out_dir, "conflicts.json", report)
    _dump(out_dir, "validated_issues.json", kept)
    _dump(out_dir, "suppressed_issues.json", suppressed)
    _dump(out_dir, "rfis.json", rfis)
    with open(os.path.join(out_dir, "report.md"), "w", encoding="utf-8") as f:
        f.write(to_markdown(report))
    return report