wehub-resource-sync
64 lines
2.0 KiB
Python
64 lines
2.0 KiB
Python
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"""This example demonstrates the Query State mechanisms and ability to generate reports across multiple queries:
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1. Create a library
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2. Run multiple queries - saving query state
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3. Generate reports from query state and export
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"""
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import os
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from llmware.configs import LLMWareConfig
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from llmware.library import Library
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from llmware.retrieval import Query
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from llmware.setup import Setup
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def create_un_500_sample_library(library_name):
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library = Library().create_new_library(library_name)
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sample_files_path = Setup().load_sample_files(over_write=False)
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ingestion_folder_path = os.path.join(sample_files_path, "UN-Resolutions-500")
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parsing_output = library.add_files(ingestion_folder_path)
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return library
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# Demonstrate some methods involved with persisting and loading Query state as well as export
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def query_state_and_export(library):
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# Create a Query instance with history persistence
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query = Query(library, save_history=True)
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# Capture the query_id
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query_id = query.query_id
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# Run a series of queries
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query_results = query.text_query("sustainable development", result_count=20)
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query_results = query.text_query("africa", result_count=26)
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query_results = query.text_query("pandemic risk", result_count=15)
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# Save state - this will write the query state as JSON file in /query_history path
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query.save_query_state()
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# Generate Retrieval Report. The report will be stored in the llmware_data/query_history folder
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csv_file = query.generate_csv_report()
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csv_file_path = os.path.join(LLMWareConfig().get_query_path(), csv_file)
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print (f"\nSaving Retrieval State and Export'")
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print (f"Export for query id '{query_id}': {csv_file_path}")
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# Additionally here is how can clear state and reload based on a query_id:
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query.clear_query_state()
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query.load_query_state(query_id)
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return 0
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if __name__ == "__main__":
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lib = create_un_500_sample_library("lib_query_state_1")
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query_state_and_export(lib)
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