from __future__ import annotations

import re

from .shared import *

class LLMStructuredCandidatesMixin:
    @staticmethod
    def _normalize_string_list(value: Any) -> list[str]:
        if value is None:
            return []
        if not isinstance(value, (list, tuple, set)):
            value = [value]
        normalized: list[str] = []
        seen: set[str] = set()
        for raw in value:
            text = str(raw or "").strip()
            if not text:
                continue
            key = text.lower()
            if key in seen:
                continue
            seen.add(key)
            normalized.append(text[:120])
        return normalized

    @staticmethod
    def _normalize_int_list(value: Any) -> list[int]:
        if value is None:
            return []
        if not isinstance(value, (list, tuple, set)):
            value = [value]
        normalized: list[int] = []
        seen: set[int] = set()
        for raw in value:
            if isinstance(raw, bool):
                continue
            try:
                number = int(str(raw).strip())
            except (TypeError, ValueError):
                continue
            if number <= 0 or number in seen:
                continue
            seen.add(number)
            normalized.append(number)
        return normalized

    @classmethod
    def _coerce_task_breakdown_item(cls, payload: dict[str, Any]) -> dict[str, Any]:
        normalized = dict(payload)
        title = str(normalized.get("title") or normalized.get("task_name") or "").strip()
        description = normalized.get("description")
        task_type = str(normalized.get("type") or normalized.get("task_type") or "backend").strip().lower() or "backend"
        task_key = str(normalized.get("task_key") or normalized.get("key") or "").strip()
        if not task_key and title:
            task_key = re.sub(r"[^a-z0-9]+", "-", title.lower()).strip("-") or title
        normalized["task_key"] = task_key
        normalized["title"] = title
        if description is not None:
            normalized["description"] = str(description or "").strip() or None
        normalized["type"] = task_type

        estimated_hours = cls._coerce_number(normalized.get("estimated_hours"))
        normalized["estimated_hours"] = float(estimated_hours or 0.0)

        required_skill_names = normalized.get("required_skill_names")
        normalized["required_skill_names"] = cls._normalize_string_list(required_skill_names)
        normalized["required_skill_tag_ids"] = cls._normalize_int_list(normalized.get("required_skill_tag_ids"))
        normalized["depends_on_task_keys"] = cls._normalize_string_list(normalized.get("depends_on_task_keys"))

        risk_level = str(normalized.get("risk_level") or "medium").strip().lower() or "medium"
        normalized["risk_level"] = risk_level
        risk_notes = normalized.get("risk_notes")
        normalized["risk_notes"] = str(risk_notes or "").strip() or None

        confidence = cls._coerce_number(normalized.get("confidence"))
        if confidence is None:
            confidence = 0.0
        if confidence > 1 and confidence <= 100:
            confidence = confidence / 100.0
        normalized["confidence"] = max(0.0, min(float(confidence), 1.0))

        normalized["evidence_refs"] = cls._normalize_string_list(normalized.get("evidence_refs"))
        normalized["priority"] = str(normalized.get("priority") or "medium").strip().lower() or "medium"
        return normalized

    @classmethod
    def _coerce_task_breakdown_payload(cls, payload: dict[str, Any]) -> dict[str, Any]:
        normalized = dict(payload)
        tasks = normalized.get("tasks")
        if isinstance(tasks, list):
            normalized["tasks"] = [
                cls._coerce_task_breakdown_item(item)
                for item in tasks
                if isinstance(item, dict)
            ]
        normalized["detected_skills"] = cls._normalize_string_list(normalized.get("detected_skills"))
        source_context = normalized.get("source_context")
        if source_context is not None and not isinstance(source_context, dict):
            normalized["source_context"] = source_context if isinstance(source_context, dict) else None
        return normalized

    @staticmethod
    def _validate_task_breakdown_item(payload: dict[str, Any]) -> bool:
        required_text_fields = ("task_key", "title", "type", "risk_level")
        for key in required_text_fields:
            value = str(payload.get(key) or "").strip()
            if not value:
                return False
        if not isinstance(payload.get("estimated_hours"), (int, float)) or isinstance(payload.get("estimated_hours"), bool):
            return False
        if not isinstance(payload.get("confidence"), (int, float)) or isinstance(payload.get("confidence"), bool):
            return False
        for key in ("required_skill_names", "required_skill_tag_ids", "depends_on_task_keys", "evidence_refs"):
            if not isinstance(payload.get(key), list):
                return False
        priority = payload.get("priority")
        if priority is not None and not isinstance(priority, str):
            return False
        risk_notes = payload.get("risk_notes")
        if risk_notes is not None and not isinstance(risk_notes, str):
            return False
        description = payload.get("description")
        if description is not None and not isinstance(description, str):
            return False
        return True

    def _iter_structured_candidates(
        self,
        *,
        message: Any,
        choice: Any,
        response: Any,
        include_reasoning: bool = True,
    ) -> list[tuple[str, Any]]:
        candidates: list[tuple[str, Any]] = []
        if isinstance(message, dict):
            tool_calls = message.get("tool_calls")
            if isinstance(tool_calls, list) and tool_calls:
                first = tool_calls[0] if isinstance(tool_calls[0], dict) else {}
                fn = first.get("function") if isinstance(first, dict) else {}
                candidates.append(("tool_calls.function.arguments", fn.get("arguments") if isinstance(fn, dict) else None))
            candidates.append(("message.content", message.get("content")))
        if isinstance(choice, dict):
            candidates.append(("choice.text", choice.get("text")))
        if isinstance(response, dict):
            candidates.append(("response.output_text", response.get("output_text")))
        if include_reasoning:
            if isinstance(message, dict):
                candidates.append(("message.reasoning_content", message.get("reasoning_content")))
                candidates.append(("message.reasoning_content", message.get("reasoning")))
            if isinstance(choice, dict):
                candidates.append(("choice.reasoning_content", choice.get("reasoning_content")))
                candidates.append(("choice.reasoning_content", choice.get("reasoning")))
            if isinstance(response, dict):
                candidates.append(("response.reasoning_content", response.get("reasoning_content")))
                candidates.append(("response.reasoning_content", response.get("reasoning")))
        return candidates

    @classmethod
    def _unwrap_structured_payload_once(cls, payload: Any) -> Any:
        if not isinstance(payload, dict):
            return payload
        for key in ("json", "data", "result", "arguments"):
            if key not in payload:
                continue
            inner = payload.get(key)
            if isinstance(inner, str):
                candidate = cls._extract_json_candidate(cls._strip_code_fence(inner))
                if not candidate:
                    continue
                try:
                    return json.loads(candidate)
                except Exception:
                    return inner
            if isinstance(inner, (dict, list)):
                return inner
        return payload

    @staticmethod
    def _matches_expected_type(value: Any, expected: str) -> bool:
        if expected == "bool":
            return isinstance(value, bool)
        if expected == "str":
            return isinstance(value, str)
        if expected == "list":
            return isinstance(value, list)
        if expected == "number":
            return isinstance(value, (int, float)) and not isinstance(value, bool)
        if expected == "number_or_none":
            return value is None or (isinstance(value, (int, float)) and not isinstance(value, bool))
        if expected == "str_or_none":
            return value is None or isinstance(value, str)
        if expected == "dict_or_none":
            return value is None or isinstance(value, dict)
        return True

    @staticmethod
    def _coerce_number(value: Any) -> Optional[float]:
        if isinstance(value, bool):
            return None
        if isinstance(value, (int, float)):
            return float(value)
        text = str(value or "").strip()
        if not text:
            return None
        try:
            return float(text)
        except Exception:
            return None

    @staticmethod
    def _coerce_int(value: Any) -> Optional[int]:
        number = LLMStructuredCandidatesMixin._coerce_number(value)
        if number is None:
            return None
        try:
            return int(number)
        except Exception:
            return None

    @staticmethod
    def _coerce_bool(value: Any) -> Optional[bool]:
        if isinstance(value, bool):
            return value
        if isinstance(value, (int, float)) and not isinstance(value, bool):
            return bool(int(value))
        text = str(value or "").strip().lower()
        if not text:
            return None
        if text in BOOL_TRUE_VALUES:
            return True
        if text in {"0", "false", "no", "off", "n"}:
            return False
        return None

    @classmethod
    def _coerce_intent_structured_payload(cls, payload: dict[str, Any]) -> dict[str, Any]:
        normalized = dict(payload)
        confidence = cls._coerce_number(normalized.get("confidence"))
        if confidence is None:
            for alias in ("score", "probability", "confidence_score"):
                confidence = cls._coerce_number(normalized.get(alias))
                if confidence is not None:
                    break
        if confidence is not None:
            normalized["confidence"] = confidence

        reasoning_value = normalized.get("reasoning")
        if isinstance(reasoning_value, list):
            text_items = [str(item).strip() for item in reasoning_value if str(item).strip()]
            normalized["reasoning"] = "；".join(text_items)
        elif isinstance(reasoning_value, dict):
            normalized["reasoning"] = json.dumps(reasoning_value, ensure_ascii=False)
        else:
            reasoning_text = str(reasoning_value or "").strip()
            if reasoning_text:
                normalized["reasoning"] = reasoning_text
            else:
                for alias in ("reason", "rationale", "analysis", "explanation"):
                    alias_text = str(normalized.get(alias) or "").strip()
                    if alias_text:
                        normalized["reasoning"] = alias_text
                        break

        if "requires_confirmation" in normalized:
            bool_value = cls._coerce_bool(normalized.get("requires_confirmation"))
            if bool_value is not None:
                normalized["requires_confirmation"] = bool_value

        for field in ("project_id", "requested_count"):
            if field in normalized:
                number = cls._coerce_int(normalized.get(field))
                normalized[field] = number if number is not None else None

        route_hint = str(
            normalized.get("workflow_route") or normalized.get("route") or ""
        ).strip().lower()
        if route_hint and "." in route_hint:
            family, action = route_hint.split(".", 1)
            if not str(normalized.get("family") or "").strip():
                normalized["family"] = family
            if not str(normalized.get("action") or "").strip():
                normalized["action"] = action
        return normalized

    @classmethod
    def _coerce_structured_payload(cls, *, function_name: str, payload: Any) -> Any:
        fn = str(function_name or "").strip().lower()
        if not isinstance(payload, dict):
            return payload
        if fn in {"generate_task_breakdown", "sstc_ai_breakdown"}:
            return cls._coerce_task_breakdown_payload(payload)
        if fn in {"classify_intent_ai_pmo_kernel", "classify_intent_complex"}:
            return cls._coerce_intent_structured_payload(payload)
        return payload

    def _validate_structured_payload(self, *, function_name: str, payload: Any) -> Optional[str]:
        fn = str(function_name or "").strip().lower()
        schema = STRUCTURED_OBJECT_SCHEMAS.get(fn)
        payload = self._coerce_structured_payload(function_name=fn, payload=payload)
        if schema is None:
            return None if isinstance(payload, (dict, list)) else "structured_json_invalid"
        if not isinstance(payload, dict):
            return "structured_schema_invalid"
        required_keys = schema.get("required_keys") or ()
        for key in required_keys:
            if key not in payload:
                return "structured_schema_invalid"
        type_checks = schema.get("type_checks") or {}
        for key, expected in type_checks.items():
            if not self._matches_expected_type(payload.get(key), str(expected)):
                return "structured_schema_invalid"
        optional_type_checks = schema.get("optional_type_checks") or {}
        for key, expected_values in optional_type_checks.items():
            if key not in payload:
                continue
            if not any(self._matches_expected_type(payload.get(key), str(expected)) for expected in expected_values):
                return "structured_schema_invalid"
        if fn in {"generate_task_breakdown", "sstc_ai_breakdown"}:
            tasks = payload.get("tasks")
            if not isinstance(tasks, list) or not tasks:
                return "structured_schema_invalid"
            if not all(isinstance(item, dict) and self._validate_task_breakdown_item(item) for item in tasks):
                return "structured_schema_invalid"
        return None