"""MCP server scaffold.

This is a stub showing the three tools any MCP-based RAG integration wants:
search, generate, verify. Wire these into your real MCP server (e.g. the
`mcp-builder` skill of this workspace) when you're ready.
"""
from __future__ import annotations

from typing import Any, Dict, List

from ..core.config import Config
from ..core.types import Query
from ..pipeline import Pipeline


_pipeline: Pipeline = Pipeline.from_config(Config.default())


def mcp_search(query: str, k: int = 10) -> Dict[str, Any]:
    q = Query(text=query, k=k)
    per = _pipeline.retrievers.search_per_retriever(q, k)
    flat = [r for lst in per.values() for r in lst]
    flat.sort(key=lambda r: r.score, reverse=True)
    return {
        "results": [
            {"doc": r.chunk.doc_id, "chunk": r.chunk.chunk_id,
             "score": r.score, "retriever": r.retriever,
             "text": r.chunk.text[:500]}
            for r in flat[:k]
        ]
    }


def mcp_generate(query: str, k: int = 10) -> Dict[str, Any]:
    resp = _pipeline.run(Query(text=query, k=k))
    return resp.to_dict()


def mcp_verify(answer: str, source_ids: List[str]) -> Dict[str, Any]:
    # Minimal: verify against current cache
    q = Query(text="__verify__")
    # collect retrieved chunks that match the given source ids
    ctx = []
    for resp in _pipeline.cache.values():
        for r in resp.retrieved:
            if r.chunk.doc_id in source_ids:
                ctx.append(r)
    res = _pipeline.verifier.verify(q, answer, ctx)
    return {"passed": res.passed, "coverage": res.citation_coverage,
            "faithfulness": res.faithfulness,
            "alerts": [a.__dict__ for a in res.alerts]}