"""One bounded corrective request based solely on retrieval evidence."""

import json
from tools.answers.answer_format import parse_answer, Answer, Claim
from tools.answers.context_policy import answer_context_issues
from tools.answers.render_answer import render_graph_answer


def generate_checked_answer(question: str, context: dict, prompt: str, complete) -> dict:
    # Candidate provenance is used by the guard, but is not part of a Claim.
    # Keep the model's selection shape identical to the actual output schema.
    sent = {
        **context,
        "answer_candidates": [
            {k: v for k, v in row.items() if k in Claim.model_fields}
            for row in context.get("answer_candidates", [])
        ],
    }
    aggregation = context.get("aggregation")
    if aggregation is not None:
        sent["aggregation"] = {
            k: v for k, v in aggregation.items() if k in {"count", "count_domain", "people", "complete"}
        }
    policy = "\nDo claims nevkladaj source_urls ani evidence_documents; source_urls patrí iba na vrchnú úroveň odpovede."
    if (
        aggregation
        and aggregation.get("complete") is True
        and type(aggregation.get("count")) is int
    ):
        policy += (
            "\nÚplná overená agregácia tohto dotazu má count="
            + str(aggregation["count"])
            + ". Pri status=ok zachovaj tento count; počet dodaných facts, claims ani answer_candidates ho nemení."
        )
    messages = [
        {"role": "system", "content": prompt + policy},
        {
            "role": "user",
            "content": json.dumps(
                {"question": question, "graph_context": sent}, ensure_ascii=False
            ),
        },
    ]
    result = {"attempts": [], "accepted_for_delivery": False}
    for number in range(2):
        record = {}
        text = ""
        try:
            response = complete(messages)
            result["response"] = response
            record["response"] = response
            text = response["choices"][0]["message"]["content"].strip()
        except Exception as error:
            result["error"] = type(error).__name__
            result["reason"] = "model_unavailable"
            result["attempts"].append(record)
            return result
        result["attempts"].append(record)
        try:
            answer, normalized = parse_answer(text)
            record["answer"] = answer
            record["format_normalized"] = normalized
        except (ValueError, TypeError) as error:
            record["format_error"] = type(error).__name__
            if number == 1:
                result["error"] = "InvalidAnswerFormat: two invalid JSON/schema responses"
                return result
            feedback = (
                "Vráť jediný platný JSON objekt podľa schémy, bez zmeny faktov z pôvodného kontextu. Schéma: "
                + json.dumps(Answer.model_json_schema(), ensure_ascii=False)
            )
        else:
            issues = answer_context_issues(answer, context, check_text=False)
            record["context_issues"] = issues
            result["answer"] = answer
            if not issues:
                rendered = render_graph_answer(answer, context)
                delivery_issues = answer_context_issues(rendered, context)
                if delivery_issues:
                    issues = delivery_issues
                    record["context_issues"] = issues
                else:
                    record["rendered_answer"] = rendered
                    result["model_answer"] = answer
                    result["answer"] = rendered
                    result["accepted_for_delivery"] = True
                    return result
            if number == 1:
                result["context_rejected"] = True
                return result
            feedback = (
                "Odpoveď porušila pravidlá dodaného kontextu: " + ", ".join(issues) + ". "
                "Oprav jediný JSON objekt výhradne z pôvodných podkladov. Použi iba source_urls zo sources. "
                "Typ práce nie je keyword. answer_candidates dokladajú spojenie požadovaného názvu alebo roku a tagu cez tú istú osobu. "
                "Answer ponechaj prázdny; text aj upozornenie zostaví aplikácia."
            )
        messages += [{"role": "assistant", "content": text}, {"role": "user", "content": feedback}]
    return result