"""Operator-facing API client for live AtoCore instances.

This script is intentionally external to the app runtime. It is for admins
and operators who want a convenient way to inspect live project state,
refresh projects, audit retrieval quality, manage trusted project-state
entries, and drive the Phase 9 reflection loop (capture, extract, queue,
promote, reject).

Environment variables
---------------------

ATOCORE_BASE_URL
    Base URL of the AtoCore service (default: ``http://dalidou:8100``).

    When running ON the Dalidou host itself or INSIDE the Dalidou
    container, override this with loopback or the real IP::

        ATOCORE_BASE_URL=http://127.0.0.1:8100 \\
            python scripts/atocore_client.py health

    The default hostname "dalidou" is meant for cases where the
    caller is a remote machine (laptop, T420/OpenClaw, etc.) with
    "dalidou" in its /etc/hosts or resolvable via Tailscale. It does
    NOT reliably resolve on the host itself or inside the container,
    and when it fails the client returns
    ``{"status": "unavailable", "fail_open": true}`` — the right
    diagnosis when that happens is to set ATOCORE_BASE_URL explicitly
    to 127.0.0.1:8100 and retry.

ATOCORE_TIMEOUT_SECONDS
    Request timeout for most operations (default: 30).

ATOCORE_REFRESH_TIMEOUT_SECONDS
    Longer timeout for project refresh operations which can be slow
    (default: 1800).

ATOCORE_FAIL_OPEN
    When "true" (default), network errors return a small fail-open
    envelope instead of raising. Set to "false" for admin operations
    where you need the real error.
"""

from __future__ import annotations

import argparse
import json
import os
import re
import sys
import urllib.error
import urllib.parse
import urllib.request
from typing import Any


BASE_URL = os.environ.get("ATOCORE_BASE_URL", "http://dalidou:8100").rstrip("/")
TIMEOUT = int(os.environ.get("ATOCORE_TIMEOUT_SECONDS", "30"))
REFRESH_TIMEOUT = int(os.environ.get("ATOCORE_REFRESH_TIMEOUT_SECONDS", "1800"))
FAIL_OPEN = os.environ.get("ATOCORE_FAIL_OPEN", "true").lower() == "true"

# Bumped when the subcommand surface or JSON output shapes meaningfully
# change. See docs/architecture/llm-client-integration.md for the
# semver rules. History:
#   0.1.0  initial stable-ops-only client
#   0.2.0  Phase 9 reflection loop added: capture, extract,
#          reinforce-interaction, list-interactions, get-interaction,
#          queue, promote, reject
CLIENT_VERSION = "0.2.0"


def print_json(payload: Any) -> None:
    print(json.dumps(payload, ensure_ascii=True, indent=2))


def fail_open_payload() -> dict[str, Any]:
    return {"status": "unavailable", "source": "atocore", "fail_open": True}


def request(
    method: str,
    path: str,
    data: dict[str, Any] | None = None,
    timeout: int | None = None,
) -> Any:
    url = f"{BASE_URL}{path}"
    headers = {"Content-Type": "application/json"} if data is not None else {}
    payload = json.dumps(data).encode("utf-8") if data is not None else None
    req = urllib.request.Request(url, data=payload, headers=headers, method=method)
    try:
        with urllib.request.urlopen(req, timeout=timeout or TIMEOUT) as response:
            body = response.read().decode("utf-8")
    except urllib.error.HTTPError as exc:
        body = exc.read().decode("utf-8")
        if body:
            print(body)
        raise SystemExit(22) from exc
    except (urllib.error.URLError, TimeoutError, OSError):
        if FAIL_OPEN:
            print_json(fail_open_payload())
            raise SystemExit(0)
        raise

    if not body.strip():
        return {}
    return json.loads(body)


def parse_aliases(aliases_csv: str) -> list[str]:
    return [alias.strip() for alias in aliases_csv.split(",") if alias.strip()]


def detect_project(prompt: str) -> dict[str, Any]:
    payload = request("GET", "/projects")
    prompt_lower = prompt.lower()
    best_project = None
    best_alias = None
    best_score = -1

    for project in payload.get("projects", []):
        candidates = [project.get("id", ""), *project.get("aliases", [])]
        for candidate in candidates:
            candidate = (candidate or "").strip()
            if not candidate:
                continue
            pattern = rf"(?<![a-z0-9]){re.escape(candidate.lower())}(?![a-z0-9])"
            matched = re.search(pattern, prompt_lower) is not None
            if not matched and candidate.lower() not in prompt_lower:
                continue
            score = len(candidate)
            if score > best_score:
                best_project = project.get("id")
                best_alias = candidate
                best_score = score

    return {"matched_project": best_project, "matched_alias": best_alias}


def classify_result(result: dict[str, Any]) -> dict[str, Any]:
    source_file = (result.get("source_file") or "").lower()
    heading = (result.get("heading_path") or "").lower()
    title = (result.get("title") or "").lower()
    text = " ".join([source_file, heading, title])

    labels: list[str] = []
    if any(token in text for token in ["_archive", "/archive", "archive/", "pre-cleanup", "pre-migration", "history"]):
        labels.append("archive_or_history")
    if any(token in text for token in ["status", "dashboard", "current-state", "current state", "next-steps", "next steps"]):
        labels.append("current_status")
    if any(token in text for token in ["decision", "adr", "tradeoff", "selected architecture", "selection"]):
        labels.append("decision")
    if any(token in text for token in ["requirement", "spec", "constraints", "baseline", "cdr", "sow"]):
        labels.append("requirements")
    if any(token in text for token in ["roadmap", "milestone", "plan", "workflow", "calibration", "contract"]):
        labels.append("execution_plan")
    if not labels:
        labels.append("reference")

    return {
        "score": result.get("score"),
        "title": result.get("title"),
        "heading_path": result.get("heading_path"),
        "source_file": result.get("source_file"),
        "labels": labels,
        "is_noise_risk": "archive_or_history" in labels,
    }


def audit_query(prompt: str, top_k: int, project: str | None) -> dict[str, Any]:
    response = request(
        "POST",
        "/query",
        {"prompt": prompt, "top_k": top_k, "project": project or None},
    )
    classifications = [classify_result(result) for result in response.get("results", [])]
    broad_prompt = len(prompt.split()) <= 2
    noise_hits = sum(1 for item in classifications if item["is_noise_risk"])
    current_hits = sum(1 for item in classifications if "current_status" in item["labels"])
    decision_hits = sum(1 for item in classifications if "decision" in item["labels"])
    requirements_hits = sum(1 for item in classifications if "requirements" in item["labels"])

    recommendations: list[str] = []
    if broad_prompt:
        recommendations.append("Prompt is broad; prefer a project-specific question with intent, artifact type, or constraint language.")
    if noise_hits:
        recommendations.append("Archive/history noise is present; prefer current-status, decision, requirements, and baseline docs in the next ingestion/ranking pass.")
    if current_hits == 0:
        recommendations.append("No current-status docs surfaced in the top results; Wave 2 should ingest or strengthen trusted operational truth.")
    if decision_hits == 0:
        recommendations.append("No decision docs surfaced in the top results; add or freeze decision logs for the active project.")
    if requirements_hits == 0:
        recommendations.append("No requirements/baseline docs surfaced in the top results; prioritize baseline and architecture-freeze material.")
    if not recommendations:
        recommendations.append("Ranking looks healthy for this prompt.")

    return {
        "prompt": prompt,
        "project": project,
        "top_k": top_k,
        "broad_prompt": broad_prompt,
        "noise_hits": noise_hits,
        "current_status_hits": current_hits,
        "decision_hits": decision_hits,
        "requirements_hits": requirements_hits,
        "results": classifications,
        "recommendations": recommendations,
    }


def project_payload(
    project_id: str,
    aliases_csv: str,
    source: str,
    subpath: str,
    description: str,
    label: str,
) -> dict[str, Any]:
    return {
        "project_id": project_id,
        "aliases": parse_aliases(aliases_csv),
        "description": description,
        "ingest_roots": [{"source": source, "subpath": subpath, "label": label}],
    }


def build_parser() -> argparse.ArgumentParser:
    parser = argparse.ArgumentParser(description="AtoCore live API client")
    sub = parser.add_subparsers(dest="command", required=True)

    for name in ["health", "sources", "stats", "projects", "project-template", "debug-context", "ingest-sources"]:
        sub.add_parser(name)

    p = sub.add_parser("detect-project")
    p.add_argument("prompt")

    p = sub.add_parser("auto-context")
    p.add_argument("prompt")
    p.add_argument("budget", nargs="?", type=int, default=3000)
    p.add_argument("project", nargs="?", default="")

    for name in ["propose-project", "register-project"]:
        p = sub.add_parser(name)
        p.add_argument("project_id")
        p.add_argument("aliases_csv")
        p.add_argument("source")
        p.add_argument("subpath")
        p.add_argument("description", nargs="?", default="")
        p.add_argument("label", nargs="?", default="")

    p = sub.add_parser("update-project")
    p.add_argument("project")
    p.add_argument("description")
    p.add_argument("aliases_csv", nargs="?", default="")

    p = sub.add_parser("refresh-project")
    p.add_argument("project")
    p.add_argument("purge_deleted", nargs="?", default="false")

    p = sub.add_parser("project-state")
    p.add_argument("project")
    p.add_argument("category", nargs="?", default="")

    p = sub.add_parser("project-state-set")
    p.add_argument("project")
    p.add_argument("category")
    p.add_argument("key")
    p.add_argument("value")
    p.add_argument("source", nargs="?", default="")
    p.add_argument("confidence", nargs="?", type=float, default=1.0)

    p = sub.add_parser("project-state-invalidate")
    p.add_argument("project")
    p.add_argument("category")
    p.add_argument("key")

    p = sub.add_parser("query")
    p.add_argument("prompt")
    p.add_argument("top_k", nargs="?", type=int, default=5)
    p.add_argument("project", nargs="?", default="")

    p = sub.add_parser("context-build")
    p.add_argument("prompt")
    p.add_argument("project", nargs="?", default="")
    p.add_argument("budget", nargs="?", type=int, default=3000)

    p = sub.add_parser("audit-query")
    p.add_argument("prompt")
    p.add_argument("top_k", nargs="?", type=int, default=5)
    p.add_argument("project", nargs="?", default="")

    # --- Phase 9 reflection loop surface --------------------------------
    #
    # capture: record one interaction (prompt + response + context used).
    #   Mirrors POST /interactions. response is positional so shell
    #   callers can pass it via $(cat file.txt) or heredoc. project,
    #   client, and session_id are optional positionals with empty
    #   defaults, matching the existing script's style.
    p = sub.add_parser("capture")
    p.add_argument("prompt")
    p.add_argument("response", nargs="?", default="")
    p.add_argument("project", nargs="?", default="")
    p.add_argument("client", nargs="?", default="")
    p.add_argument("session_id", nargs="?", default="")
    p.add_argument("reinforce", nargs="?", default="true")

    # extract: run the Phase 9 C rule-based extractor against an
    #   already-captured interaction. persist='true' writes the
    #   candidates as status='candidate' memories; default is
    #   preview-only.
    p = sub.add_parser("extract")
    p.add_argument("interaction_id")
    p.add_argument("persist", nargs="?", default="false")

    # reinforce: backfill reinforcement on an already-captured interaction.
    p = sub.add_parser("reinforce-interaction")
    p.add_argument("interaction_id")

    # list-interactions: paginated listing with filters.
    p = sub.add_parser("list-interactions")
    p.add_argument("project", nargs="?", default="")
    p.add_argument("session_id", nargs="?", default="")
    p.add_argument("client", nargs="?", default="")
    p.add_argument("since", nargs="?", default="")
    p.add_argument("limit", nargs="?", type=int, default=50)

    # get-interaction: fetch one by id
    p = sub.add_parser("get-interaction")
    p.add_argument("interaction_id")

    # queue: list the candidate review queue
    p = sub.add_parser("queue")
    p.add_argument("memory_type", nargs="?", default="")
    p.add_argument("project", nargs="?", default="")
    p.add_argument("limit", nargs="?", type=int, default=50)

    # promote: candidate -> active
    p = sub.add_parser("promote")
    p.add_argument("memory_id")

    # reject: candidate -> invalid
    p = sub.add_parser("reject")
    p.add_argument("memory_id")

    # batch-extract: fan out /interactions/{id}/extract?persist=true across
    #   recent interactions. Idempotent — the extractor create_memory path
    #   silently skips duplicates, so re-running is safe.
    p = sub.add_parser("batch-extract")
    p.add_argument("since", nargs="?", default="")
    p.add_argument("project", nargs="?", default="")
    p.add_argument("limit", nargs="?", type=int, default=100)
    p.add_argument("persist", nargs="?", default="true")

    # triage: interactive candidate review loop. Fetches the queue, shows
    #   each candidate, accepts p/r/s (promote / reject / skip) / q (quit).
    p = sub.add_parser("triage")
    p.add_argument("memory_type", nargs="?", default="")
    p.add_argument("project", nargs="?", default="")
    p.add_argument("limit", nargs="?", type=int, default=50)

    return parser


def main() -> int:
    args = build_parser().parse_args()
    cmd = args.command

    if cmd == "health":
        print_json(request("GET", "/health"))
    elif cmd == "sources":
        print_json(request("GET", "/sources"))
    elif cmd == "stats":
        print_json(request("GET", "/stats"))
    elif cmd == "projects":
        print_json(request("GET", "/projects"))
    elif cmd == "project-template":
        print_json(request("GET", "/projects/template"))
    elif cmd == "debug-context":
        print_json(request("GET", "/debug/context"))
    elif cmd == "ingest-sources":
        print_json(request("POST", "/ingest/sources", {}))
    elif cmd == "detect-project":
        print_json(detect_project(args.prompt))
    elif cmd == "auto-context":
        project = args.project or detect_project(args.prompt).get("matched_project") or ""
        if not project:
            print_json({"status": "no_project_match", "source": "atocore", "mode": "auto-context"})
        else:
            print_json(request("POST", "/context/build", {"prompt": args.prompt, "project": project, "budget": args.budget}))
    elif cmd in {"propose-project", "register-project"}:
        path = "/projects/proposal" if cmd == "propose-project" else "/projects/register"
        print_json(request("POST", path, project_payload(args.project_id, args.aliases_csv, args.source, args.subpath, args.description, args.label)))
    elif cmd == "update-project":
        payload: dict[str, Any] = {"description": args.description}
        if args.aliases_csv.strip():
            payload["aliases"] = parse_aliases(args.aliases_csv)
        print_json(request("PUT", f"/projects/{urllib.parse.quote(args.project)}", payload))
    elif cmd == "refresh-project":
        purge_deleted = args.purge_deleted.lower() in {"1", "true", "yes", "y"}
        path = f"/projects/{urllib.parse.quote(args.project)}/refresh?purge_deleted={str(purge_deleted).lower()}"
        print_json(request("POST", path, {}, timeout=REFRESH_TIMEOUT))
    elif cmd == "project-state":
        suffix = f"?category={urllib.parse.quote(args.category)}" if args.category else ""
        print_json(request("GET", f"/project/state/{urllib.parse.quote(args.project)}{suffix}"))
    elif cmd == "project-state-set":
        print_json(request("POST", "/project/state", {
            "project": args.project,
            "category": args.category,
            "key": args.key,
            "value": args.value,
            "source": args.source,
            "confidence": args.confidence,
        }))
    elif cmd == "project-state-invalidate":
        print_json(request("DELETE", "/project/state", {"project": args.project, "category": args.category, "key": args.key}))
    elif cmd == "query":
        print_json(request("POST", "/query", {"prompt": args.prompt, "top_k": args.top_k, "project": args.project or None}))
    elif cmd == "context-build":
        print_json(request("POST", "/context/build", {"prompt": args.prompt, "project": args.project or None, "budget": args.budget}))
    elif cmd == "audit-query":
        print_json(audit_query(args.prompt, args.top_k, args.project or None))
    # --- Phase 9 reflection loop surface ------------------------------
    elif cmd == "capture":
        body: dict[str, Any] = {
            "prompt": args.prompt,
            "response": args.response,
            "project": args.project,
            "client": args.client or "atocore-client",
            "session_id": args.session_id,
            "reinforce": args.reinforce.lower() in {"1", "true", "yes", "y"},
        }
        print_json(request("POST", "/interactions", body))
    elif cmd == "extract":
        persist = args.persist.lower() in {"1", "true", "yes", "y"}
        print_json(
            request(
                "POST",
                f"/interactions/{urllib.parse.quote(args.interaction_id, safe='')}/extract",
                {"persist": persist},
            )
        )
    elif cmd == "reinforce-interaction":
        print_json(
            request(
                "POST",
                f"/interactions/{urllib.parse.quote(args.interaction_id, safe='')}/reinforce",
                {},
            )
        )
    elif cmd == "list-interactions":
        query_parts: list[str] = []
        if args.project:
            query_parts.append(f"project={urllib.parse.quote(args.project)}")
        if args.session_id:
            query_parts.append(f"session_id={urllib.parse.quote(args.session_id)}")
        if args.client:
            query_parts.append(f"client={urllib.parse.quote(args.client)}")
        if args.since:
            query_parts.append(f"since={urllib.parse.quote(args.since)}")
        query_parts.append(f"limit={int(args.limit)}")
        query = "?" + "&".join(query_parts)
        print_json(request("GET", f"/interactions{query}"))
    elif cmd == "get-interaction":
        print_json(
            request(
                "GET",
                f"/interactions/{urllib.parse.quote(args.interaction_id, safe='')}",
            )
        )
    elif cmd == "queue":
        query_parts = ["status=candidate"]
        if args.memory_type:
            query_parts.append(f"memory_type={urllib.parse.quote(args.memory_type)}")
        if args.project:
            query_parts.append(f"project={urllib.parse.quote(args.project)}")
        query_parts.append(f"limit={int(args.limit)}")
        query = "?" + "&".join(query_parts)
        print_json(request("GET", f"/memory{query}"))
    elif cmd == "promote":
        print_json(
            request(
                "POST",
                f"/memory/{urllib.parse.quote(args.memory_id, safe='')}/promote",
                {},
            )
        )
    elif cmd == "reject":
        print_json(
            request(
                "POST",
                f"/memory/{urllib.parse.quote(args.memory_id, safe='')}/reject",
                {},
            )
        )
    elif cmd == "batch-extract":
        print_json(run_batch_extract(args.since, args.project, args.limit, args.persist))
    elif cmd == "triage":
        return run_triage(args.memory_type, args.project, args.limit)
    else:
        return 1
    return 0


def run_batch_extract(since: str, project: str, limit: int, persist_flag: str) -> dict:
    """Fetch recent interactions and run the extractor against each one.

    Returns an aggregated summary. Safe to re-run: the server-side
    persist path catches ValueError on duplicates and the endpoint
    reports per-interaction candidate counts either way.
    """
    persist = persist_flag.lower() in {"1", "true", "yes", "y"}
    query_parts: list[str] = []
    if project:
        query_parts.append(f"project={urllib.parse.quote(project)}")
    if since:
        query_parts.append(f"since={urllib.parse.quote(since)}")
    query_parts.append(f"limit={int(limit)}")
    query = "?" + "&".join(query_parts)

    listing = request("GET", f"/interactions{query}")
    interactions = listing.get("interactions", []) if isinstance(listing, dict) else []

    processed = 0
    total_candidates = 0
    total_persisted = 0
    errors: list[dict] = []
    per_interaction: list[dict] = []

    for item in interactions:
        iid = item.get("id") or ""
        if not iid:
            continue
        try:
            result = request(
                "POST",
                f"/interactions/{urllib.parse.quote(iid, safe='')}/extract",
                {"persist": persist},
            )
        except Exception as exc:  # pragma: no cover - network errors land here
            errors.append({"interaction_id": iid, "error": str(exc)})
            continue
        processed += 1
        count = int(result.get("candidate_count", 0) or 0)
        persisted_ids = result.get("persisted_ids") or []
        total_candidates += count
        total_persisted += len(persisted_ids)
        if count:
            per_interaction.append(
                {
                    "interaction_id": iid,
                    "candidate_count": count,
                    "persisted_count": len(persisted_ids),
                    "project": item.get("project") or "",
                }
            )

    return {
        "processed": processed,
        "total_candidates": total_candidates,
        "total_persisted": total_persisted,
        "persist": persist,
        "errors": errors,
        "interactions_with_candidates": per_interaction,
    }


def run_triage(memory_type: str, project: str, limit: int) -> int:
    """Interactive review of candidate memories.

    Loads the queue once, walks through entries, prompts for
    (p)romote / (r)eject / (s)kip / (q)uit. Stateless between runs —
    re-running picks up whatever is still status=candidate.
    """
    query_parts = ["status=candidate"]
    if memory_type:
        query_parts.append(f"memory_type={urllib.parse.quote(memory_type)}")
    if project:
        query_parts.append(f"project={urllib.parse.quote(project)}")
    query_parts.append(f"limit={int(limit)}")
    listing = request("GET", "/memory?" + "&".join(query_parts))
    memories = listing.get("memories", []) if isinstance(listing, dict) else []

    if not memories:
        print_json({"status": "empty_queue", "count": 0})
        return 0

    promoted = 0
    rejected = 0
    skipped = 0
    stopped_early = False

    print(f"Triage queue: {len(memories)} candidate(s)\n", file=sys.stderr)
    for idx, mem in enumerate(memories, 1):
        mid = mem.get("id", "")
        print(f"[{idx}/{len(memories)}] {mem.get('memory_type','?')}  project={mem.get('project','')}  conf={mem.get('confidence','?')}", file=sys.stderr)
        print(f"  id: {mid}", file=sys.stderr)
        print(f"  {mem.get('content','')}", file=sys.stderr)
        try:
            choice = input("  (p)romote / (r)eject / (s)kip / (q)uit > ").strip().lower()
        except EOFError:
            stopped_early = True
            break
        if choice in {"q", "quit"}:
            stopped_early = True
            break
        if choice in {"p", "promote"}:
            request("POST", f"/memory/{urllib.parse.quote(mid, safe='')}/promote", {})
            promoted += 1
            print("  -> promoted", file=sys.stderr)
        elif choice in {"r", "reject"}:
            request("POST", f"/memory/{urllib.parse.quote(mid, safe='')}/reject", {})
            rejected += 1
            print("  -> rejected", file=sys.stderr)
        else:
            skipped += 1
            print("  -> skipped", file=sys.stderr)

    print_json(
        {
            "reviewed": promoted + rejected + skipped,
            "promoted": promoted,
            "rejected": rejected,
            "skipped": skipped,
            "stopped_early": stopped_early,
            "remaining_in_queue": len(memories) - (promoted + rejected + skipped) - (1 if stopped_early else 0),
        }
    )
    return 0


if __name__ == "__main__":
    raise SystemExit(main())