"""Thin client around clAIm's deployed HF Space API.

Reuses the existing fine-tuned DeBERTa-v3 NLI model and IntGrad attribution
endpoint rather than reloading/retraining a model. See clAIm report Section 2.2
for endpoint definitions.
"""

import httpx

CLAIM_BASE_URL = "https://minoola-claim-ai.hf.space"


LABEL2ID = {"SUPPORT": 0, "NOT_ENOUGH_INFO": 1, "CONTRADICT": 2}


async def analyze(claim: str, evidence: str) -> dict:
    """Calls clAIm's /analyze endpoint: sentence-split + NLI verdict.

    Request:  {"claim": ..., "evidence": ...}
    Response: {"winner": {"sentence", "label", "confidence", "sentence_index"},
               "supporting": [...], "all_scores": [...],
               "attribution_available": bool}
    """
    async with httpx.AsyncClient(timeout=30.0) as client:
        resp = await client.post(
            f"{CLAIM_BASE_URL}/analyze",
            json={"claim": claim, "evidence": evidence},
        )
        resp.raise_for_status()
        return resp.json()


async def attribute(claim: str, winner_sentence: str, label_id: int) -> list[dict]:
    """Calls clAIm's /attribute endpoint: Captum Integrated Gradients, N=25.

    Must be called with the WINNER sentence only (not the full evidence text),
    and label_id must match the winner's predicted label.

    Request:  {"claim": ..., "evidence": ..., "label_id": 0|1|2}
    Response: [{"token": ..., "score": ...}, ...]
    """
    async with httpx.AsyncClient(timeout=30.0) as client:
        resp = await client.post(
            f"{CLAIM_BASE_URL}/attribute",
            json={"claim": claim, "evidence": winner_sentence, "label_id": label_id},
        )
        resp.raise_for_status()
        return resp.json()