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@@ -52,6 +52,7 @@ async def test_funcs():
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# asyncio.run(test_funcs())
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async def main():
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try:
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embedding_dimension = await get_embedding_dim()
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@@ -61,35 +62,47 @@ async def main():
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working_dir=WORKING_DIR,
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llm_model_func=llm_model_func,
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embedding_func=EmbeddingFunc(
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embedding_dim=embedding_dimension, max_token_size=8192, func=embedding_func
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embedding_dim=embedding_dimension,
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max_token_size=8192,
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func=embedding_func,
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),
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)
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with open("./book.txt", "r", encoding="utf-8") as f:
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rag.insert(f.read())
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# Perform naive search
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print(
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rag.query("What are the top themes in this story?", param=QueryParam(mode="naive"))
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="naive")
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)
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)
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# Perform local search
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print(
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rag.query("What are the top themes in this story?", param=QueryParam(mode="local"))
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="local")
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)
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)
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# Perform global search
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print(
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rag.query("What are the top themes in this story?", param=QueryParam(mode="global"))
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rag.query(
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"What are the top themes in this story?",
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param=QueryParam(mode="global"),
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)
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)
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# Perform hybrid search
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print(
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rag.query("What are the top themes in this story?", param=QueryParam(mode="hybrid"))
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rag.query(
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"What are the top themes in this story?",
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param=QueryParam(mode="hybrid"),
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)
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)
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except Exception as e:
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print(f"An error occurred: {e}")
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if __name__ == "__main__":
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asyncio.run(main())
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asyncio.run(main())
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