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""" |
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Test script to verify the new CSV filename generation functionality |
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""" |
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import sys |
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import os |
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sys.path.append(os.path.dirname(os.path.abspath(__file__))) |
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from advanced_rag import get_short_embedding_name, get_short_llm_name, get_varied_parameter |
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def test_embedding_names(): |
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"""Test embedding model name generation""" |
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test_cases = [ |
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("🤗 sentence-transformers/all-MiniLM-L6-v2 (384 dim, fast)", "MiniLM"), |
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("🤗 BAAI/bge-base-en-v1.5 (768 dim, excellent)", "BGE-Base"), |
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("🟦 Qwen/Qwen3-Embedding-8B (1024 dim, advanced)", "Qwen3-8B"), |
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("sentence-transformers/all-mpnet-base-v2", "MPNet"), |
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("unknown-model", "unknown") |
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] |
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print("Testing embedding name generation:") |
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for input_name, expected in test_cases: |
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result = get_short_embedding_name(input_name) |
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status = "✓" if result == expected else "✗" |
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print(f" {status} {input_name} -> {result} (expected: {expected})") |
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def test_llm_names(): |
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"""Test LLM model name generation""" |
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test_cases = [ |
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("🇪🇺 Mistral-API", "Mistral"), |
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("🇺🇸 Remote Meta-Llama-3", "Llama3"), |
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("🇺🇸 GPT-4o", "GPT4o"), |
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("mistral-small-latest", "Mistral"), |
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("meta-llama/Meta-Llama-3-8B-Instruct", "Llama3"), |
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("unknown-model", "unknown") |
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] |
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print("\nTesting LLM name generation:") |
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for input_name, expected in test_cases: |
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result = get_short_llm_name(input_name) |
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status = "✓" if result == expected else "✗" |
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print(f" {status} {input_name} -> {result} (expected: {expected})") |
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def test_varied_parameter(): |
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"""Test varied parameter detection""" |
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test_cases = [ |
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({"temperature": "Constant", "top_p": "Constant", "top_k": "Constant", "bm25": "Constant"}, "None"), |
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({"temperature": "Whole range 3 values", "top_p": "Constant", "top_k": "Constant", "bm25": "Constant"}, "temperature"), |
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({"temperature": "Constant", "top_p": "Whole range 5 values", "top_k": "Constant", "bm25": "Constant"}, "top_p"), |
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({"temperature": "Whole range 3 values", "top_p": "Whole range 5 values", "top_k": "Constant", "bm25": "Constant"}, "Multi"), |
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({"temperature": "Constant", "top_p": "Constant", "top_k": "Constant", "bm25": "Whole range 7 values"}, "bm25") |
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] |
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print("\nTesting varied parameter detection:") |
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for param_configs, expected in test_cases: |
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result = get_varied_parameter(param_configs) |
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status = "✓" if result == expected else "✗" |
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print(f" {status} {param_configs} -> {result} (expected: {expected})") |
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def test_filename_generation(): |
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"""Test complete filename generation""" |
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from datetime import datetime |
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timestamp = "20241201_120000" |
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test_cases = [ |
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("🤗 sentence-transformers/all-MiniLM-L6-v2 (384 dim, fast)", "🇪🇺 Mistral-API", "temperature", "batch_MiniLM_Mistral_temperature_20241201_120000.csv"), |
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("🤗 BAAI/bge-base-en-v1.5 (768 dim, excellent)", "🇺🇸 Remote Meta-Llama-3", "top_p", "batch_BGE-Base_Llama3_top_p_20241201_120000.csv"), |
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("🟦 Qwen/Qwen3-Embedding-8B (1024 dim, advanced)", "🇺🇸 GPT-4o", "Multi", "batch_Qwen3-8B_GPT4o_Multi_20241201_120000.csv"), |
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("", "", "None", "batch_Unknown_Unknown_None_20241201_120000.csv") |
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] |
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print("\nTesting complete filename generation:") |
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for embedding, llm, param, expected in test_cases: |
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short_embedding = get_short_embedding_name(embedding) if embedding else "Unknown" |
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short_llm = get_short_llm_name(llm) if llm else "Unknown" |
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short_param = param if param else "None" |
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filename = f"batch_{short_embedding}_{short_llm}_{short_param}_{timestamp}.csv" |
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status = "✓" if filename == expected else "✗" |
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print(f" {status} Generated: {filename}") |
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print(f" Expected: {expected}") |
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if __name__ == "__main__": |
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print("Testing CSV filename generation functionality\n") |
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test_embedding_names() |
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test_llm_names() |
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test_varied_parameter() |
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test_filename_generation() |
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print("\nTest completed!") |
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