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41 lines
1.3 KiB
41 lines
1.3 KiB
2 weeks ago
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import sys, os
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from pathlib import Path
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script_directory = Path(__file__).resolve().parent.parent
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sys.path.append(os.path.abspath(script_directory))
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import logging
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httpx_logger = logging.getLogger("httpx") # disable openai's logger output
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httpx_logger.setLevel(logging.WARNING)
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current_dir = os.path.dirname(os.path.abspath(__file__))
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# Customize your config here
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from deepsearcher.configuration import Configuration, init_config
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config = Configuration()
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init_config(config=config)
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# # Load your local data
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# # Hint: You can load from a directory or a single file, please execute it in the root directory of the deep searcher project
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from deepsearcher.offline_loading import load_from_local_files
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load_from_local_files(
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paths_or_directory=os.path.join(current_dir, "data/WhatisMilvus.pdf"),
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collection_name="milvus_docs",
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collection_description="All Milvus Documents",
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# force_new_collection=True, # If you want to drop origin collection and create a new collection every time, set force_new_collection to True
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)
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# Query
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from deepsearcher.online_query import query
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question = 'Write a report comparing Milvus with other vector databases.'
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answer, retrieved_results, consumed_token = query(question)
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print(answer)
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# # get consumed tokens, about: 2.5~3w tokens when using openai gpt-4o model
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# print(f"Consumed tokens: {consumed_token}")
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