import json
import sys
import unittest
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from pharmacy_agent import QUERY_SETTINGS, build_aliases, detect_drugs, prepare_query
from scripts.evaluation.run_evaluation import metrics, summarize
from scripts.evaluation.judge_answers import parse_verdict


def product(name, subs, rep="https://example.org/a"):
    return dict(name=name,subs=subs,rep=rep,url=rep or "https://example.org/b",form="",rx="",type="",group="",ind="")


class AgentTests(unittest.TestCase):
    def setUp(self):
        self.products=[product("Nurofen 200 mg",["ibuprofén"]),product("Warfarin 5 mg",["warfarín"])]
        self.aliases,self.prefixes,_=build_aliases(self.products)

    def test_slovak_inflection_and_brand(self):
        matches=detect_drugs("Nurofen spolu s warfarínom",self.aliases,self.prefixes)
        self.assertEqual({m["label"].lower() for m in matches},{"nurofen","warfarín"})

    def test_short_brand_and_full_name(self):
        items=[product("ACC Long 600 mg",["acetylcysteín"])]
        a,p,_=build_aliases(items)
        self.assertEqual(len(detect_drugs("Na čo je ACC Long?",a,p)),1)

    def test_ambiguous_brand_does_not_invent_single_substance(self):
        items=[product("Brand 200 mg",["one"]),product("Brand Plus 200 mg",["one","two"])]
        a,p,_=build_aliases(items)
        result=prepare_query("Môžem užiť Brand?",items,a,p)
        self.assertIn("nejednoznačný",result["user_prompt"])
        self.assertNotIn("Brand = účinná látka one",result["query"])

    def test_unrelated_prefix_not_detected(self):
        self.assertEqual(detect_drugs("warfarinovyneznamyprodukt",self.aliases,self.prefixes),[])

    def test_missing_data_is_not_no_interaction(self):
        items=[product("Spofaplast náplasť",[],None)]
        a,p,_=build_aliases(items)
        result=prepare_query("Spofaplast a iné lieky?",items,a,p)
        self.assertIn("neznamená",result["user_prompt"])

    def test_source_identity_accepts_pil_and_detail(self):
        case={"sources":["https://adc.sk/detail/x"]}
        response={"references":[{"file_path":"https://adc.sk/pil/x","content":["text"]}]}
        self.assertEqual(metrics(case,response,"mix")["source_hit"],1)
        self.assertIsNone(metrics(case,response,"bypass")["source_hit"])

    def test_failures_are_reported_not_scored_as_wrong(self):
        result=summarize([{"mode":"mix","status":"error"},{"mode":"mix","status":"ok","seconds":2,"metrics":{"source_hit":1}}])
        self.assertEqual(result["mix"]["failed"],1)
        self.assertEqual(result["mix"]["source_hit"],1)

    def test_graph_budget_reserves_original_source_text(self):
        available=QUERY_SETTINGS["max_total_tokens"]-QUERY_SETTINGS["max_entity_tokens"]-QUERY_SETTINGS["max_relation_tokens"]
        self.assertGreaterEqual(available,4000)

    def test_judge_rejects_more_supported_claims_than_claims(self):
        verdict={"grounding":{"total":2,"supported":3},"coverage":{"total":1,"supported":1},"appropriate_abstention":False}
        with self.assertRaises(ValueError):
            parse_verdict(json.dumps(verdict))

    def test_judge_accepts_reasoning_prefix_without_scoring_it(self):
        verdict={"grounding":{"total":2,"supported":1},"coverage":{"total":1,"supported":1},"appropriate_abstention":False}
        self.assertEqual(parse_verdict("<think>not a verdict</think>"+json.dumps(verdict)),verdict)


if __name__ == "__main__":
    unittest.main()