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https://github.com/oobabooga/text-generation-webui.git
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72 lines
2.7 KiB
Python
72 lines
2.7 KiB
Python
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"""
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This module implements a benchmark function to evaluate the performance of the embedding pipeline. It expects a configuration JSON file. It must have questions and expected retrieved text.
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For each question, it's essential to have variants of that question. Language is fluid and each person might have their own spin on how they may ask it.
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At the end, it will save the results inside a benchmark_{sysdate}.txt file in the main directory.
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The benchmark function will return the score as an integer.
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"""
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import datetime
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import json
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import os
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from pathlib import Path
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from .data_processor import process_and_add_to_collector, preprocess_text
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from .parameters import get_chunk_count, get_max_token_count
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from .utils import create_metadata_source
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def benchmark(config_path, collector):
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# Get the current system date
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sysdate = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"benchmark_{sysdate}.txt"
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# Open the log file in append mode
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with open(filename, 'a') as log:
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with open(config_path, 'r') as f:
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data = json.load(f)
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total_points = 0
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max_points = 0
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for item in data:
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filepath = item["text"]
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corpus = ""
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# Check if the file exists
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if os.path.isfile(Path(filepath)):
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# Open the file and read its content
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with open(Path(filepath), 'r') as file:
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corpus = file.read()
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process_and_add_to_collector(corpus, collector, True, create_metadata_source('benchmark'))
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else:
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raise f'Cannot find specified file {filepath}.'
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for question_group in item["questions"]:
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question_variants = question_group["question_variants"]
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criteria = question_group["criteria"]
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for q in question_variants:
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max_points += len(criteria)
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processed_text = preprocess_text(q)
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# Get the most similar chunks
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results = collector.get_sorted_by_dist(processed_text, n_results=get_chunk_count(), max_token_count=get_max_token_count())
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points = 0
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for c in criteria:
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for p in results:
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if c in p:
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points += 1
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total_points += 1
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break
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info = f"The question '{q}' scored {points}/{len(criteria)} points."
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print(info, file=log)
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print('\n---\n', file=log)
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print(f'##Total points:\n\n{total_points}/{max_points}', file=log)
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return total_points, max_points
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