"""Isolated test — just explain(). Checks it correctly uses final_verdict
(set by verify_dual on agreement) to call /attribute with the right label_id,
now that final_verdict is always pre-populated before explain() runs.

Requires GROQ_API_KEY not needed here (no LLM call in explain) — only hits
the live clAIm /attribute endpoint directly.

Run from the veriscite/ root:
    python -m tests.test_explain_live
"""

import asyncio
from app.graph.nodes import explain

SAMPLE_CLAIM_CITATION = {
    "claim": "Attention mechanisms allow transformer models to capture "
             "long-range dependencies in sequential data without relying on recurrence",
    "citation_marker": "[1]",
    "reference_string": "Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., "
                         "Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). "
                         "Attention is all you need. In NeurIPS 2017.",
    "resolved_paper_id": "204e3073870fae3d05bcbc2f6a8e263d9b72e776",
    "evidence_text": (
        "The dominant sequence transduction models are based on complex "
        "recurrent or convolutional neural networks in an encoder-decoder "
        "configuration. We propose a new simple network architecture, the "
        "Transformer, based solely on attention mechanisms, dispensing with "
        "recurrence and convolutions entirely."
    ),
}

# Mirrors exactly what verify_dual produces on agreement — final_verdict
# already set, matching the current (post-bugfix) flow.
SAMPLE_AUDIT = {
    "claim_citation": SAMPLE_CLAIM_CITATION,
    "winner_sentence": "We propose a new simple network architecture, the "
                        "Transformer, based solely on attention mechanisms, "
                        "dispensing with recurrence and convolutions entirely.",
    "attribution_available": True,
    "deberta_verdict": {"label": "SUPPORT", "confidence": 0.9658, "source": "deberta"},
    "llm_verdict": {"label": "SUPPORT", "confidence": 1.0, "source": "llm"},
    "agreement": True,
    "escalated": False,
    "escalation_retry_succeeded": None,
    "adjudicator_reasoning": None,
    "final_verdict": {"label": "SUPPORT", "confidence": 0.9658, "source": "deberta"},
    "attribution": None,
}


async def main():
    state = {
        "source_text": "",
        "claims": [SAMPLE_CLAIM_CITATION],
        "audits": [SAMPLE_AUDIT],
        "current_index": 0,
        "report": None,
    }
    result = await explain(state)
    audit = result["audits"][0]

    print("attribution_available:", audit["attribution_available"])
    print("attribution (first 5 tokens):")
    for item in (audit["attribution"] or [])[:5]:
        print(" ", item)
    print("total tokens:", len(audit["attribution"] or []))


if __name__ == "__main__":
    asyncio.run(main())