# %%
from typing import List, Dict, tuple, Any
import os
from sqlalchemy import create_engine, text
import requests

def get_all_diseases_name(engine) -> List[List[str]]:
    with engine.connect() as conn:
        with conn.begin():
            sql = f"""
                    SELECT * FROM Test.EntityEmbeddings
                    """
            result = conn.execute(text(sql))
            data = result.fetchall()

    all_diseases = [row[1] for row in data if row[1] != "nan"]
    return all_diseases

def get_uri_from_name(engine, name: str) -> str:
    with engine.connect() as conn:
        with conn.begin():
            sql = f"""
                    SELECT uri FROM Test.EntityEmbeddings
                    WHERE label = '{name}'
                    """
            result = conn.execute(text(sql))
            data = result.fetchall()
    return data[0][0].split('/')[-1]

def get_most_similar_diseases_from_uri(engine, original_disease_uri: str, threshold: float = 0.8) -> List[str]:
    with engine.connect() as conn:
        with conn.begin():
            sql = f"""
                    SELECT * FROM Test.EntityEmbeddings
                    """
            result = conn.execute(text(sql))
            data = result.fetchall()

    all_diseases = [row[1] for row in data if row[1] != "nan"]
    return all_diseases

def get_uri_from_name(engine, name: str) -> str:
    with engine.connect() as conn:
        with conn.begin():
            sql = f"""
                    SELECT uri FROM Test.EntityEmbeddings
                    WHERE label = '{name}'
                    """
            result = conn.execute(text(sql))
            data = result.fetchall()
    return data[0][0].split('/')[-1]

def get_most_similar_diseases_from_uri(engine, original_disease_uri: str, threshold: float = 0.8) -> List[str]:
    with engine.connect() as conn:
        with conn.begin():
            sql = f"""
                    SELECT TOP 10 e1.uri AS uri1, e2.uri AS uri2, e1.label AS label1, e2.label AS label2,
                    VECTOR_COSINE(e1.embedding, e2.embedding) AS distance
                    FROM Test.EntityEmbeddings e1, Test.EntityEmbeddings e2
                    WHERE e1.uri = 'http://identifiers.org/medgen/{original_disease_uri}'
                    AND VECTOR_COSINE(e1.embedding, e2.embedding) > {threshold}
                    AND e1.uri != e2.uri
                    ORDER BY distance DESC
                    """
            result = conn.execute(text(sql))
            data = result.fetchall()

    similar_diseases = [(row[1].split('/')[-1], row[3], row[4]) for row in data if row[3] != "nan"]
    return similar_diseases

def get_clinical_record_info(clinical_record_id: str) -> Dict[str, Any]:
    # Request:
    # curl -X GET "https://clinicaltrials.gov/api/v2/studies/NCT00841061" \
    # -H "accept: text/csv"
    request_url = f"https://clinicaltrials.gov/api/v2/studies/{clinical_record_id}"
    response = requests.get(request_url, headers={"accept": "application/json"})
    return response.json()

def get_clinical_records_by_ids(clinical_record_ids: List[str]) -> List[Dict[str, Any]]:
    clinical_records = []
    for clinical_record_id in clinical_record_ids:
        clinical_record_info = get_clinical_record_info(clinical_record_id)
        clinical_records.append(clinical_record_info)
    return clinical_records

def get_uris_of_similar_diseases(uri_list: List[str]) -> List[tuple[str, str, float]]:
    uri_list = tuple(uri_list)
    with engine.connect() as conn:
        with conn.begin():
            sql = f"""
                    SELECT e1.uri AS uri1, e2.uri AS uri2, VECTOR_COSINE(e1.embedding, e2.embedding) AS distance
                    FROM Test.EntityEmbeddings e1, Test.EntityEmbeddings e2
                    WHERE e1.uri IN {uri_list} AND e2.uri IN {uri_list} AND e1.uri != e2.uri
                """
            result = conn.execute(text(sql))
            data = result.fetchall()
    return data

if __name__ == "__main__":
    username = 'demo'
    password = 'demo'
    hostname = os.getenv('IRIS_HOSTNAME', 'localhost')
    port = '1972' 
    namespace = 'USER'
    CONNECTION_STRING = f"iris://{username}:{password}@{hostname}:{port}/{namespace}"

    try:
        engine = create_engine(CONNECTION_STRING)
        diseases = get_most_similar_diseases_from_uri('C1843013')
        for disease in diseases:
            print(disease)
    except Exception as e:
        print(e)

    print(get_uri_from_name(engine, 'Alzheimer disease 3'))

    clinical_record_info = get_clinical_records_by_ids(['NCT00841061'])
    print(clinical_record_info)