"""FastAPI backend for Northwestern CS Kiosk - API only (no frontend)."""

from __future__ import annotations
import csv
import json
import logging
import os
import threading
import time
import warnings

try:
    from huggingface_hub import CommitScheduler, hf_hub_download
except ImportError:
    CommitScheduler = None  # type: ignore
    hf_hub_download = None  # type: ignore
from functools import lru_cache
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple

from fastapi import FastAPI, HTTPException, Query
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel

from .data import load_default_catalog
from .tools import (
    AnalysisEngine,
    FacultyByTopicBlueprint,
    LocationBlueprint,
    CenterBlueprint,
    AdvisorshipBlueprint,
    PersonLookupBlueprint,
    StaffSupportBlueprint,
    UpcomingEventsBlueprint,
    OfficeHoursBlueprint,
    BlueprintResult,
)
from .responders import LLMResponder, Responder
from .providers import (
    BaseLLM,
    ProviderConfig,
    available_providers,
    get_provider,
    normalize_provider_name,
)
from .data.utils import canonicalize_name
from .mcp import (
    Action,
    PlannerContext,
    LLMActionPlanner,
)
from .mcp.tool_schemas import get_all_tool_schemas
from .mcp.tool_executor import ToolExecutor
from .mcp.context_resolver import (
    is_affirmation,
    resolve as resolve_context,
    strip_context_on_topic_switch,
)

BASE_DIR = Path(__file__).resolve().parent
ARCHIVE_DIR = BASE_DIR.parent / "Archive"
DATA_DIR = BASE_DIR / "storage"
DATA_DIR.mkdir(parents=True, exist_ok=True)

HISTORY_FILE = DATA_DIR / "chat_history.jsonl"
USAGE_FILE = DATA_DIR / "usage_metrics.jsonl"

DEFAULT_SESSION = "default"

app = FastAPI(
    title="Northwestern CS Kiosk API",
    description="REST API for the Northwestern CS Department Kiosk",
    version="1.0.0",
)

# Enable CORS for external integrations
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Configure as needed for your integration
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

_orchestrator_lock = threading.Lock()
logger = logging.getLogger(__name__)
_hf_scheduler = None
_entity_names: List[str] = []


def _load_entity_names() -> None:
    """Scrape entity names from Archive folder at startup and store in memory."""
    global _entity_names

    def _extract_names_from_csv(filepath: Path) -> List[str]:
        names = []
        try:
            with open(filepath, "r", encoding="utf-8") as f:
                reader = csv.DictReader(f)
                if reader.fieldnames is None:
                    return names
                fieldnames = reader.fieldnames
                name_columns = []
                for field in fieldnames:
                    field_lower = field.lower()
                    if field_lower == "name" or field_lower == "assignee name":
                        name_columns = [field]
                        break
                    elif field_lower == "first name":
                        name_columns.append(field)
                    elif field_lower == "last name":
                        name_columns.insert(0, field)
                for row in reader:
                    if name_columns:
                        if len(name_columns) == 1 and row.get(name_columns[0]):
                            name = row[name_columns[0]].strip()
                            if name and name.upper() != "NA":
                                names.append(name)
                        elif len(name_columns) == 2:
                            last_name = row.get(name_columns[0], "").strip()
                            first_name = row.get(name_columns[1], "").strip()
                            if (last_name or first_name) and last_name.upper() != "NA" and first_name.upper() != "NA":
                                full_name = f"{first_name} {last_name}".strip() if (last_name and first_name) else (first_name or last_name)
                                if full_name:
                                    names.append(full_name)
        except Exception as e:
            logger.warning("Error reading CSV %s: %s", filepath, e)
        return names

    def _extract_names_from_text(filepath: Path) -> List[str]:
        names = []
        try:
            with open(filepath, "r", encoding="utf-8") as f:
                for line in f:
                    line = line.strip()
                    if line.startswith("Name:"):
                        name = line.replace("Name:", "").strip()
                        if name:
                            names.append(name)
        except Exception as e:
            logger.warning("Error reading text file %s: %s", filepath, e)
        return names

    try:
        archive_dir = ARCHIVE_DIR
        if not archive_dir.exists():
            logger.warning("Archive directory not found at %s", archive_dir)
            _entity_names = []
            return
        all_names: set = set()
        file_count = 0
        for filepath in sorted(archive_dir.iterdir()):
            if filepath.is_file():
                if filepath.suffix.lower() == ".csv":
                    names = _extract_names_from_csv(filepath)
                    all_names.update(names)
                    file_count += 1
                elif filepath.suffix.lower() == ".txt":
                    names = _extract_names_from_text(filepath)
                    all_names.update(names)
                    file_count += 1
        _entity_names = sorted(all_names)
        logger.info("Scraped %d unique entity names from %d files in Archive", len(_entity_names), file_count)
    except Exception as e:
        logger.error("Failed to scrape entity names from Archive: %s", e)
        _entity_names = []


_load_entity_names()


class QueryPayload(BaseModel):
    """Request payload for the /api/query endpoint."""
    question: str
    session_id: Optional[str] = None
    provider: Optional[str] = None


PROVIDER_ENV_SETTINGS: Dict[str, Dict[str, Optional[str]]] = {
    "claude": {
        "api_key": "ANTHROPIC_API_KEY",
        "model": "ANTHROPIC_MODEL",
        "base_url": "ANTHROPIC_BASE_URL",
        "default_model": "claude-haiku-4-5",
    },
    "gpt": {
        "api_key": "OPENAI_API_KEY",
        "model": "OPENAI_MODEL",
        "base_url": "OPENAI_BASE_URL",
        "default_model": "gpt-4.1-mini",
    },
    "gemini": {
        "api_key": "GEMINI_API_KEY",
        "model": "GEMINI_MODEL",
        "base_url": "GEMINI_BASE_URL",
        "default_model": "gemini-2.0-flash",
    },
    "echo": {
        "api_key": None,
        "model": None,
        "base_url": None,
        "default_model": "echo",
    },
}


def _load_env_once() -> None:
    """Load environment variables from .env exactly once."""
    if getattr(_load_env_once, "_loaded", False):
        return

    env_path = os.getenv("KIOSK_ENV_FILE")
    if not env_path:
        default_path = BASE_DIR / ".env"
        env_path = str(default_path) if default_path.exists() else ".env"

    try:
        from dotenv import load_dotenv
    except ImportError:
        _load_env_once._loaded = True
        return

    load_dotenv(env_path, override=False)
    _load_env_once._loaded = True


def _get_env_value(name: Optional[str]) -> str:
    """
    Read environment variables with an HF Spaces secret fallback.
    HF Secrets expose values as HF_<NAME>, so check both keys.
    """
    if not name:
        return ""
    direct = os.getenv(name, "").strip()
    if direct:
        return direct
    return os.getenv(f"HF_{name}", "").strip()


def _maybe_download_existing_metrics() -> None:
    """Download existing usage metrics from HF dataset on startup."""
    repo_id = os.getenv("KIOSK_HF_DATASET_REPO", "").strip()
    if not repo_id or hf_hub_download is None:
        return
    _load_env_once()
    token = _get_env_value("KIOSK_HF_TOKEN") or os.getenv("HF_TOKEN", "").strip()
    path_in_repo = os.getenv("KIOSK_HF_DATASET_PATH", "chat_history").strip()
    filename = f"{path_in_repo}/{USAGE_FILE.name}" if path_in_repo else USAGE_FILE.name
    try:
        import shutil
        downloaded = hf_hub_download(
            repo_id=repo_id, repo_type="dataset", filename=filename, token=token or None,
        )
        USAGE_FILE.parent.mkdir(parents=True, exist_ok=True)
        shutil.copy(downloaded, USAGE_FILE)
        logger.info("Downloaded usage metrics from HF: repo=%s file=%s", repo_id, filename)
    except Exception as exc:
        logger.info("No existing metrics to download (starting fresh): %s", exc)


def _maybe_download_existing_history() -> None:
    """Download existing chat history from HF dataset on startup."""
    repo_id = os.getenv("KIOSK_HF_DATASET_REPO", "").strip()
    if not repo_id or hf_hub_download is None:
        return

    _load_env_once()
    token = _get_env_value("KIOSK_HF_TOKEN") or os.getenv("HF_TOKEN", "").strip()
    path_in_repo = os.getenv("KIOSK_HF_DATASET_PATH", "chat_history").strip()
    filename = f"{path_in_repo}/{HISTORY_FILE.name}" if path_in_repo else HISTORY_FILE.name

    try:
        import shutil

        downloaded = hf_hub_download(
            repo_id=repo_id,
            repo_type="dataset",
            filename=filename,
            token=token or None,
        )
        HISTORY_FILE.parent.mkdir(parents=True, exist_ok=True)
        shutil.copy(downloaded, HISTORY_FILE)
        logger.info(
            "Downloaded chat history from HF dataset: repo=%s file=%s",
            repo_id,
            filename,
        )
    except Exception as exc:
        logger.info("No existing chat history to download (starting fresh): %s", exc)


def _maybe_start_hf_sync() -> None:
    """Start optional HF dataset syncing for chat history and usage metrics."""
    global _hf_scheduler
    if _hf_scheduler is not None:
        return
    repo_id = os.getenv("KIOSK_HF_DATASET_REPO", "").strip()
    if not repo_id or CommitScheduler is None:
        return
    _load_env_once()
    token = _get_env_value("KIOSK_HF_TOKEN") or os.getenv("HF_TOKEN", "").strip()
    path_in_repo = os.getenv("KIOSK_HF_DATASET_PATH", "chat_history").strip()
    interval_minutes = float(os.getenv("KIOSK_HF_SYNC_INTERVAL_MINUTES", "10"))
    try:
        _hf_scheduler = CommitScheduler(
            repo_id=repo_id,
            repo_type="dataset",
            folder_path=str(DATA_DIR),
            path_in_repo=path_in_repo,
            token=token or None,
            allow_patterns=[HISTORY_FILE.name, USAGE_FILE.name],
            every=interval_minutes,
        )
        logger.info(
            "Started HF CommitScheduler for chat_history and usage_metrics: repo=%s path=%s interval=%s",
            repo_id, path_in_repo or ".", interval_minutes,
        )
    except Exception as exc:
        warnings.warn(f"Unable to start HF sync: {exc}")


def _run_startup_tasks_in_background() -> None:
    """Run HF download and sync in a background thread so the server starts immediately."""
    def _run() -> None:
        try:
            _maybe_download_existing_metrics()
            _maybe_download_existing_history()
            _maybe_start_hf_sync()
        except Exception as exc:
            logger.warning("Background startup tasks failed: %s", exc)

    t = threading.Thread(target=_run, daemon=True)
    t.start()


_run_startup_tasks_in_background()


def _is_placeholder(value: Optional[str]) -> bool:
    if not value:
        return True
    lowered = value.strip().lower()
    return lowered.startswith("your-") or lowered in {"changeme", "placeholder"}


def _build_client_from_env(provider: str, model_override: Optional[str]) -> Optional[BaseLLM]:
    canonical = normalize_provider_name(provider)
    settings = PROVIDER_ENV_SETTINGS.get(canonical)
    if not settings:
        warnings.warn(f"Provider '{provider}' not recognized; falling back to echo responder.")
        return None

    timeout = int(os.getenv("KIOSK_LLM_TIMEOUT", "60"))
    max_tokens_raw = os.getenv("KIOSK_LLM_MAX_TOKENS", "").strip()
    max_tokens = int(max_tokens_raw) if max_tokens_raw.isdigit() else None
    api_env = settings.get("api_key")
    model_env = settings.get("model")
    base_url_env = settings.get("base_url")
    default_model = settings.get("default_model") or ""

    if api_env:
        api_key = _get_env_value(api_env)
        if not api_key or _is_placeholder(api_key):
            warnings.warn(f"{api_env} not set; falling back to echo responder.")
            return None
    else:
        api_key = "local-echo"
    model = model_override or (_get_env_value(model_env) if model_env else "") or default_model
    base_url = _get_env_value(base_url_env) if base_url_env else ""

    config = ProviderConfig(
        api_key=api_key,
        model=model,
        timeout_sec=timeout,
        base_url=base_url or None,
        max_tokens=max_tokens,
    )

    try:
        return get_provider(canonical, config)
    except ValueError as exc:
        warnings.warn(str(exc))
        return None


def _build_responder(
    provider: Optional[str],
    model_override: Optional[str],
) -> LLMResponder:
    _load_env_once()
    system_prompt = os.getenv(
        "KIOSK_LLM_SYSTEM_PROMPT",
        "You are a conversational receptionist for the Northwestern CS Kiosk whose responses are spoken aloud. Speak naturally and never include stage directions or annotations.",
    )
    style = os.getenv("KIOSK_LLM_STYLE", "Be very brief. One or two sentences max. No long lists—summarize top 2-3 items only.")

    provider_name = provider or os.getenv("KIOSK_LLM_PROVIDER", "anthropic")
    model_override = model_override if provider else (model_override or os.getenv("KIOSK_LLM_MODEL"))

    client = _build_client_from_env(provider_name, model_override)
    canonical = normalize_provider_name(provider_name)

    if client:
        return LLMResponder(
            client=client,
            system_prompt=system_prompt,
            style_guidelines=style,
            provider_id=canonical,
        )
    warnings.warn("LLM provider not configured; using echo responder for kiosk responses.")
    return LLMResponder(
        system_prompt=system_prompt,
        style_guidelines=style,
        provider_id="echo",
    )


def _default_responder_from_env() -> Responder:
    try:
        return _build_responder(None, None)
    except RuntimeError as exc:
        warnings.warn(f"Failed to initialize LLM responder: {exc}")
        return LLMResponder(provider_id="echo")


def _create_planner() -> LLMActionPlanner:
    provider = os.getenv("KIOSK_PLANNER_PROVIDER") or os.getenv("KIOSK_LLM_PROVIDER", "anthropic")
    model_override = os.getenv("KIOSK_PLANNER_MODEL") or os.getenv("KIOSK_LLM_MODEL")
    client = _build_client_from_env(provider, model_override)
    if not client:
        raise RuntimeError("LLM planner requires a configured provider (set KIOSK_LLM_PROVIDER/KEY).")
    schemas = get_all_tool_schemas()
    return LLMActionPlanner(client, schemas=schemas, entity_names=_entity_names)


class ConversationOrchestrator:
    """Glue class that ties planner, executor, and responder together."""

    def __init__(self, engine: AnalysisEngine, responder: Optional[Responder] = None) -> None:
        _load_env_once()
        self.engine = engine
        self.responder = responder or _default_responder_from_env()
        self.executor = ToolExecutor(engine)
        self.planner = _create_planner()
        self.last_subject: Optional[str] = None
        self._faculty_lookup = self._build_name_lookup("faculty")
        self._student_lookup = self._build_name_lookup("students")
        self.provider_id = getattr(self.responder, "provider_id", None)

    def answer(
        self,
        question: str,
        context: Optional[PlannerContext] = None,
        resolved_input: Optional[Any] = None,
    ) -> Tuple[str, BlueprintResult, Action]:
        if context is None:
            context = PlannerContext(last_subject=self.last_subject)

        if is_affirmation(question) and context.last_subject:
            last_answer = ""
            if context.short_history:
                last_answer = (context.short_history[-1].get("answer") or "").lower()
            if any(
                x in last_answer
                for x in ("would you like", "look up", "find", "room number", "office")
            ):
                actions = [Action("lookup_location", {"use_last_subject": True})]
            else:
                actions = self.planner.plan(question, context)
        else:
            actions = self.planner.plan(question, context)

        if not actions:
            actions = [Action("noop", {"message": "I'm not sure how to help with that yet."})]

        # Inject resolved day (e.g. "F" → "friday", "today" → "wednesday") when planner returns lookup_office_hours without day
        if actions and resolved_input and getattr(resolved_input, "resolved_day", None):
            for act in actions:
                if act.type == "lookup_office_hours" and not act.arguments.get("day"):
                    act.arguments["day"] = resolved_input.resolved_day

        if len(actions) > 1:
            merged_facts: List = []
            merged_notes: List[str] = []
            ran: List[str] = []
            for act in actions:
                ran.append(act.type)
                sub_result = self.executor.execute(act, context)
                merged_facts.extend(sub_result.facts)
                for note in sub_result.notes:
                    if note not in merged_notes:
                        merged_notes.append(note)
            result = BlueprintResult("composite", {}, facts=merged_facts, notes=merged_notes)
            action = Action("composite", {"actions": [a.to_dict() for a in actions], "merged_actions": ran})
        else:
            action = actions[0]
            name_like = None
            if isinstance(action.arguments, dict):
                for key in ("name", "person", "student", "faculty"):
                    val = action.arguments.get(key)
                    if val:
                        name_like = val
                        break

            if name_like:
                result = self.executor.execute(action, context)
                if not result.facts:
                    canonical = canonicalize_name(name_like)
                    faculty_match = self._faculty_lookup.get(canonical)
                    student_match = self._student_lookup.get(canonical)
                    if faculty_match and not student_match:
                        action.arguments.pop("name", None)
                        action.arguments.pop("person", None)
                        action.arguments["faculty"] = faculty_match
                        result = self.executor.execute(action, context)
                    elif student_match and not faculty_match:
                        action.arguments.pop("name", None)
                        action.arguments.pop("person", None)
                        action.arguments["student"] = student_match
                        result = self.executor.execute(action, context)
                    elif faculty_match and student_match:
                        action = Action(
                            "noop",
                            {
                                "message": (
                                    f"I found both a faculty member and a student named {name_like}. "
                                    "Do you mean the faculty member or the student?"
                                )
                            },
                        )
                        result = BlueprintResult("noop", action.arguments, facts=[], notes=[action.arguments.get("message")])
            else:
                result = self.executor.execute(action, context)
        response_text = self.responder.render(question, result.name, result)

        subject = self._select_subject_from_result(result)
        if subject:
            self.last_subject = subject
        else:
            for key in ("name", "student", "faculty"):
                if key in action.arguments and action.arguments[key]:
                    self.last_subject = action.arguments[key]
                    break
        return response_text, result, action

    def ensure_responder(self, provider: Optional[str], model_override: Optional[str] = None) -> None:
        canonical = normalize_provider_name(provider) if provider else None
        if canonical and canonical == getattr(self.responder, "provider_id", None):
            return
        if not canonical and getattr(self.responder, "provider_id", None) != "unknown":
            return
        self.responder = _build_responder(provider, model_override)
        self.provider_id = getattr(self.responder, "provider_id", canonical)

    @staticmethod
    def _infer_subject(result: BlueprintResult) -> Optional[str]:
        if not result.facts:
            return None
        return result.facts[0].subject

    def _build_name_lookup(self, entity_name: str) -> Dict[str, str]:
        mapping: Dict[str, str] = {}
        entity = self.engine.catalog.try_get(entity_name)
        if not entity:
            return mapping
        for row in entity.records:
            name = row.get("Name")
            if not name:
                continue
            mapping[canonicalize_name(name)] = name
        return mapping

    def _select_subject_from_result(self, result: BlueprintResult) -> Optional[str]:
        candidates: List[str] = []
        for fact in result.facts:
            if isinstance(fact.subject, str):
                candidates.append(fact.subject)
            if isinstance(fact.value, str):
                candidates.append(fact.value)
        for candidate in candidates:
            canonical = canonicalize_name(candidate)
            if canonical in self._faculty_lookup:
                return self._faculty_lookup[canonical]
        for candidate in candidates:
            canonical = canonicalize_name(candidate)
            if canonical in self._student_lookup:
                return self._student_lookup[canonical]
        return self._infer_subject(result)


def _append_json_line(path: Path, payload: Dict[str, Any]) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    with path.open("a", encoding="utf-8") as handle:
        handle.write(json.dumps(payload, ensure_ascii=False) + "\n")


def record_history(
    *,
    session_id: str,
    question: str,
    answer: str,
    blueprint: str,
    metadata: Dict[str, Any],
    facts: List[Dict[str, Any]],
    notes: List[str],
    action: Dict[str, Any],
) -> float:
    timestamp = time.time()
    payload = {
        "timestamp": timestamp,
        "session_id": session_id,
        "question": question,
        "answer": answer,
        "blueprint": blueprint,
        "facts": facts,
        "notes": notes,
        "usage": metadata,
        "action": action,
    }
    _append_json_line(HISTORY_FILE, payload)
    usage_entry = {
        "timestamp": timestamp,
        "session_id": session_id,
        "blueprint": blueprint,
        "question": question,
    }
    usage_entry.setdefault("action_type", action.get("type"))
    _append_json_line(USAGE_FILE, usage_entry)
    return timestamp


def load_history(session_id: str) -> List[Dict[str, Any]]:
    if not HISTORY_FILE.exists():
        return []
    rows: List[Dict[str, Any]] = []
    with HISTORY_FILE.open(encoding="utf-8") as handle:
        for line in handle:
            try:
                record = json.loads(line)
            except json.JSONDecodeError:
                continue
            if record.get("session_id") == session_id:
                rows.append(record)
    rows.sort(key=lambda row: row.get("timestamp", 0))
    return rows


def build_planner_context_from_history(history: List[Dict[str, Any]]) -> PlannerContext:
    """Build session context: full history, short window, and topic-aware follow-up state."""
    if not history:
        return PlannerContext()

    cap = 20
    full_history: List[Dict[str, Any]] = []
    for rec in history[-cap:]:
        full_history.append({
            "question": rec.get("question", ""),
            "answer": rec.get("answer", ""),
        })

    short_history: List[Dict[str, Any]] = []
    for rec in history[-4:]:
        short_history.append({
            "question": rec.get("question", ""),
            "answer": rec.get("answer", ""),
            "action": rec.get("action"),
        })
    short_history = short_history[-3:]

    last = history[-1]
    action = last.get("action") or {}
    args = action.get("arguments") or {}
    facts = last.get("facts") or []
    action_type = (action.get("type") or "").lower()

    topic: Optional[str] = None
    subject: Optional[str] = None
    last_class: Optional[str] = None

    if facts and isinstance(facts[0], dict) and facts[0].get("subject"):
        subject = facts[0]["subject"]
    if not subject:
        for key in ("name", "person", "student", "faculty", "class_name", "course"):
            if args.get(key):
                subject = args[key]
                break

    if action_type == "lookup_office_hours":
        topic = "office_hours"
        cls_val = args.get("class_name") or args.get("course") or ""
        if cls_val:
            last_class = cls_val
        elif subject and (any(c.isdigit() for c in subject) or subject.upper().startswith("CS")):
            last_class = subject
    elif action_type in (
        "lookup_person",
        "lookup_location",
        "lookup_center",
        "lookup_advisorship",
        "lookup_faculty_topic",
    ):
        if action_type == "lookup_advisorship" and args.get("student"):
            topic = "student"
        elif action_type == "lookup_faculty_topic" or action_type == "lookup_center":
            topic = "professor"
        else:
            topic = "professor"

    last_subject = subject

    return PlannerContext(
        full_history=full_history,
        short_history=short_history,
        topic=topic,
        subject=subject,
        last_class=last_class,
        last_subject=last_subject,
    )


def _display_name_from_timestamp(ts: float) -> str:
    from datetime import datetime
    dt = datetime.fromtimestamp(ts)
    return dt.strftime("Chat – %b %d, %I:%M %p")


def summarize_sessions() -> List[Dict[str, Any]]:
    if not HISTORY_FILE.exists():
        return []
    sessions: Dict[str, Dict[str, Any]] = {}
    with HISTORY_FILE.open(encoding="utf-8") as handle:
        for line in handle:
            try:
                record = json.loads(line)
            except json.JSONDecodeError:
                continue
            session_id = record.get("session_id")
            ts = record.get("timestamp")
            if not session_id or not ts:
                continue
            session = sessions.setdefault(
                session_id,
                {"session_id": session_id, "created_at": ts, "updated_at": ts},
            )
            session["created_at"] = min(session["created_at"], ts)
            session["updated_at"] = max(session["updated_at"], ts)
    for session in sessions.values():
        session["title"] = _display_name_from_timestamp(session["created_at"])
    ordered = sorted(sessions.values(), key=lambda item: item["updated_at"], reverse=True)
    return ordered


def get_session_summary(session_id: str) -> Optional[Dict[str, Any]]:
    for session in summarize_sessions():
        if session["session_id"] == session_id:
            return session
    return None


def describe_providers() -> Dict[str, Dict[str, Any]]:
    """Expose provider metadata and configuration status."""
    _load_env_once()
    inventory: Dict[str, Dict[str, Any]] = {}
    for name, meta in available_providers().items():
        entry = dict(meta)
        settings = PROVIDER_ENV_SETTINGS.get(name, {})
        api_env = settings.get("api_key")
        configured = True
        note = ""
        if api_env:
            value = os.getenv(api_env, "").strip()
            configured = bool(value) and not _is_placeholder(value)
            if not configured:
                note = f"Set {api_env} before using this provider."
        entry["configured"] = configured
        if note:
            entry["note"] = note
        entry.setdefault("default_model", settings.get("default_model"))
        inventory[name] = entry
    return inventory


@lru_cache(maxsize=1)
def get_orchestrator() -> ConversationOrchestrator:
    catalog = load_default_catalog(ARCHIVE_DIR)
    engine = AnalysisEngine(
        catalog,
        [
            FacultyByTopicBlueprint(),
            LocationBlueprint(),
            CenterBlueprint(),
            AdvisorshipBlueprint(),
            StaffSupportBlueprint(),
            UpcomingEventsBlueprint(),
            OfficeHoursBlueprint(),
            PersonLookupBlueprint(),
        ],
    )
    try:
        engine.refresh_events()
    except Exception:
        pass
    return ConversationOrchestrator(engine)


# =============================================================================
# API ENDPOINTS
# =============================================================================

@app.get("/")
def root() -> Dict[str, str]:
    """Health check endpoint."""
    return {"status": "ok", "service": "Northwestern CS Kiosk API"}


@app.get("/api/providers")
def providers_endpoint() -> Dict[str, Any]:
    """List available LLM providers and their configuration status."""
    inventory = describe_providers()
    default_provider = normalize_provider_name(os.getenv("KIOSK_LLM_PROVIDER", "anthropic"))
    return {"providers": inventory, "default_provider": default_provider}


@app.post("/api/query")
def query(payload: QueryPayload) -> Dict[str, Any]:
    """
    Main query endpoint - send a question and get an answer.
    
    This is the primary endpoint for speech-to-text integration:
    - Input: question (string from speech-to-text)
    - Output: answer (string for text-to-speech)
    """
    question = (payload.question or "").strip()
    if not question:
        raise HTTPException(status_code=400, detail="Question is required.")

    session_id = (payload.session_id or DEFAULT_SESSION).strip() or DEFAULT_SESSION
    requested_provider = (payload.provider or "").strip().lower() or None
    canonical_provider = normalize_provider_name(requested_provider) if requested_provider else None

    if canonical_provider:
        inventory = describe_providers()
        provider_meta = inventory.get(canonical_provider)
        if not provider_meta:
            raise HTTPException(status_code=400, detail=f"Unknown provider '{requested_provider}'.")
        if not provider_meta.get("configured", True):
            note = provider_meta.get("note") or f"The provider '{provider_meta.get('name', canonical_provider)}' is not configured."
            raise HTTPException(status_code=400, detail=note)

    history = load_history(session_id)
    planner_context = build_planner_context_from_history(history)
    planner_context = strip_context_on_topic_switch(question, planner_context)
    resolved = resolve_context(question, planner_context)

    orchestrator = get_orchestrator()
    with _orchestrator_lock:
        orchestrator.ensure_responder(canonical_provider)
        answer, result, action = orchestrator.answer(
            resolved.question,
            context=planner_context,
            resolved_input=resolved,
        )
        metadata = (
            orchestrator.responder.get_metadata()
            if hasattr(orchestrator, "responder") and hasattr(orchestrator.responder, "get_metadata")
            else {}
        )
        metadata.setdefault("planner_action", action.to_dict())

    facts_payload = [fact.__dict__ for fact in result.facts]
    record_history(
        session_id=session_id,
        question=question,
        answer=answer,
        blueprint=result.name,
        metadata=metadata,
        facts=facts_payload,
        notes=result.notes,
        action=action.to_dict(),
    )
    summary = get_session_summary(session_id) or {
        "session_id": session_id,
        "title": _display_name_from_timestamp(time.time()),
    }

    return {
        "session_id": session_id,
        "session_title": summary.get("title"),
        "question": question,
        "answer": answer,
        "blueprint": result.name,
        "facts": facts_payload,
        "notes": result.notes,
        "usage": metadata,
        "action": action.to_dict(),
    }


@app.get("/api/history")
def history(session_id: str = Query(DEFAULT_SESSION)) -> Dict[str, Any]:
    """Get conversation history for a session."""
    entries = load_history(session_id)
    summary = get_session_summary(session_id)
    title = summary.get("title") if summary else _display_name_from_timestamp(time.time())
    return {"session_id": session_id, "title": title, "history": entries}


@app.get("/api/sessions")
def sessions() -> Dict[str, Any]:
    """List all conversation sessions."""
    return {"sessions": summarize_sessions()}


def main() -> None:
    """Run the API server."""
    import uvicorn
    
    host = os.getenv("KIOSK_HOST", "0.0.0.0")
    port = int(os.getenv("KIOSK_PORT", "8000"))
    
    uvicorn.run(
        "backend.main:app",
        host=host,
        port=port,
        reload=False,
    )


if __name__ == "__main__":
    main()