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40 lines
1.4 KiB
40 lines
1.4 KiB
2 weeks ago
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import logging
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import os
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from deepsearcher.offline_loading import load_from_local_files
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from deepsearcher.online_query import query
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from deepsearcher.configuration import Configuration, init_config
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# Suppress unnecessary logging from third-party libraries
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logging.getLogger("httpx").setLevel(logging.WARNING)
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# (Optional) Set API keys (ensure these are set securely in real applications)
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os.environ['UNSTRUCTURED_API_KEY'] = '***************'
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os.environ['UNSTRUCTURED_API_URL'] = '***************'
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def main():
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# Step 1: Initialize configuration
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config = Configuration()
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# Configure Vector Database (Milvus) and File Loader (UnstructuredLoader)
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config.set_provider_config("vector_db", "Milvus", {})
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config.set_provider_config("file_loader", "UnstructuredLoader", {})
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# Apply the configuration
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init_config(config)
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# Step 2: Load data from a local file or directory into Milvus
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input_file = "your_local_file_or_directory" # Replace with your actual file path
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collection_name = "Unstructured"
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collection_description = "All Milvus Documents"
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load_from_local_files(paths_or_directory=input_file, collection_name=collection_name, collection_description=collection_description)
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# Step 3: Query the loaded data
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question = "What is Milvus?" # Replace with your actual question
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result = query(question)
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print(result)
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if __name__ == "__main__":
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main()
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