68 lines
2.6 KiB
Python
68 lines
2.6 KiB
Python
import warnings
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from datetime import datetime
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import json
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import os
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from src.scrub import scrub_web
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from src.key import create_queries
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from src.evaluate import sort_results, CLS_POOLING, MEAN_POOLING, MAX_POOLING
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# Suppress FutureWarnings and other warnings
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warnings.simplefilter(action='ignore', category=FutureWarning)
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def hin_fetch(subject, weights, pooling):
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current_time = datetime.now().strftime("%m-%d_%H-%M")
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data_path = f"web_data/{hash(subject)}.json"
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file_path = f"logs/run_{current_time}_{weights}{pooling}.md"
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log_content = f"# Hin run, {current_time}\n\nSubject : {subject}\n\n"
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results = []
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if os.path.exists(data_path) :
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log_content += f"## Query results from {data_path}*\n\n"
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print(f"* Subject known from {data_path}")
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with open(data_path, 'r', encoding='utf-8') as f:
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results = json.load(f)
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else :
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queries, keyword_log = create_queries(subject)
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log_content += keyword_log
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results, scrub_log = scrub_web(queries)
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log_content += scrub_log
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with open(data_path, 'w', encoding='utf-8') as f:
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json.dump(results, f, ensure_ascii=False, indent=4)
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log_content += f"*Stored results in {data_path}*\n\n"
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print(f"\n* Stored results in {data_path}")
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sorted_results, results_log = sort_results(subject, results, weights, pooling)
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log_content += results_log
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print("### Done ###\n")
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report = "## Results\n"
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# Print the top 10 results
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for idx, result in enumerate(sorted_results[:10], 1):
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report += f"\nRank {idx} ({result['score']:.4f}):\nTitle: {result['title']}\nURL: {result['url']}\nSnippet: {result['snippet']}\n" + "-" * 40
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print(report + "\n")
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# Create and save the file
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with open(file_path, 'w') as file:
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file.write(log_content + report)
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#subject = input("Enter subject : ")
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subject = "State of the art on the identification of wood structure natural frequencies. Influence of the mechanical properties and interest in sensitivity analysis as prospects for reverse identification method of wood elastic properties."
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#subject = "Experiments, numerical models and optimization of carbon-epoxy plates damped by a frequency-dependent interleaved viscoelastic layer"
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# hin_fetch(subject, [title_weight, snippet_weight], [title_pooling, snippet_pooling])
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hin_fetch(subject, [1,0], [CLS_POOLING, MAX_POOLING])
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hin_fetch(subject, [1,0], [MEAN_POOLING,MAX_POOLING])
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hin_fetch(subject, [1,0], [MAX_POOLING, MAX_POOLING])
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hin_fetch(subject, [0,1], [CLS_POOLING, CLS_POOLING])
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hin_fetch(subject, [0,1], [CLS_POOLING, MEAN_POOLING])
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hin_fetch(subject, [0,1], [CLS_POOLING, MAX_POOLING])
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