from __future__ import annotations

from typing import Any, Dict

from skills.base import (
    Skill,
    SkillCategory,
    SkillContext,
    SkillLevel,
    SkillMetadata,
    SkillResult,
)


class FastReflexVectorMapperSkill(Skill):
    """Vector encoding and retrieval mapping."""

    def metadata(self) -> SkillMetadata:
        return SkillMetadata(
            id="foundational/fast-reflex-vector-mapper",
            name="Fast Reflex Vector Mapper",
            description="Encode queries into vectors and map to retrieval steps",
            category=SkillCategory.DATA,
            level=SkillLevel.INTERMEDIATE,
            tags=["retrieval", "vectors", "mapping"],
        )

    def input_schema(self) -> Dict[str, Any]:
        return {
            "type": "object",
            "properties": {
                "capability": {"type": "string", "enum": ["encode", "search"]},
                "query": {"type": "string"},
            },
            "required": ["capability"],
            "additionalProperties": False,
        }

    def output_schema(self) -> Dict[str, Any]:
        return {"type": "object", "properties": {"steps": {"type": "array"}}}

    def execute(self, input_data: Dict[str, Any], context: SkillContext) -> SkillResult:
        capability = input_data.get("capability")
        query = input_data.get("query", "query")

        if capability == "encode":
            steps = [
                f"Normalize query: {query}",
                "Generate embedding vector",
                "Store vector for retrieval",
            ]
            return SkillResult(success=True, output={"steps": steps}, skill_id=self.metadata().id)

        if capability == "search":
            steps = [
                "Compute vector similarity",
                "Rank nearest neighbors",
                "Return top-k document IDs",
            ]
            return SkillResult(success=True, output={"steps": steps}, skill_id=self.metadata().id)

        return SkillResult(success=False, output=None, error="Unknown capability", skill_id=self.metadata().id)


__all__ = ["FastReflexVectorMapperSkill"]
