import warnings
from datetime import datetime
import json
import os

from src.scrub import scrub_web
from src.key import create_queries
from src.evaluate import sort_results

# Suppress FutureWarnings and other warnings
warnings.simplefilter(action='ignore', category=FutureWarning)


def hin_fetch(subject, weights):
    current_time = datetime.now().strftime("%m-%d_%H-%M")
    data_path = f"web_data/{hash(subject)}.json"
    file_path = f"logs/run_{current_time}.md"
    log_content = f"# Hin run, {current_time}\n\nSubject : {subject}\n\n"

    results = []
    
    if os.path.exists(data_path) :
        log_content += f"## Query results from {data_path}*\n\n"
        print(f"* Subject known from {data_path}")
        
        with open(data_path, 'r', encoding='utf-8') as f:
            results = json.load(f)
    else :
        queries, keyword_log = create_queries(subject)
        log_content += keyword_log

        results, scrub_log = scrub_web(queries)
        log_content += scrub_log

        with open(data_path, 'w', encoding='utf-8') as f:
            json.dump(results, f, ensure_ascii=False, indent=4)

        log_content += f"*Stored results in {data_path}*\n\n"
        print(f"\n* Stored results in {data_path}")
        
    sorted_results, results_log = sort_results(subject, results, weights)
    log_content += results_log

    print("### Done ###\n")

    report = "## Results\n"
    # Print the top 10 results
    for idx, result in enumerate(sorted_results[:10], 1):
        report += f"\nRank {idx} ({result['score']:.4f}):\nTitle: {result['title']}\nURL: {result['url']}\nSnippet: {result['snippet']}\n" + "-" * 40

    print(report + "\n")

    # Create and save the file
    with open(file_path, 'w') as file:
        file.write(log_content + report)

#subject = input("Enter subject : ")
subject = "Experiments, numerical models and optimization of carbon-epoxy plates damped by a frequency-dependent interleaved viscoelastic layer"

hin_fetch(subject, [1,0])
hin_fetch(subject, [0,1])