Add ability to passadditional parameters to ollama library like host and timeout
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@@ -1,4 +1,7 @@
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import os
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import logging
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logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.DEBUG)
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from lightrag import LightRAG, QueryParam
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from lightrag.llm import ollama_model_complete, ollama_embedding
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@@ -11,15 +14,17 @@ if not os.path.exists(WORKING_DIR):
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rag = LightRAG(
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working_dir=WORKING_DIR,
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llm_model_func=ollama_model_complete,
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llm_model_name='your_model_name',
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tiktoken_model_name="mistral:7b",
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llm_model_func=ollama_model_complete,
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llm_model_name="mistral:7b",
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llm_model_max_async=2,
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llm_model_kwargs={"host": "http://localhost:11434"},
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embedding_func=EmbeddingFunc(
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embedding_dim=768,
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max_token_size=8192,
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func=lambda texts: ollama_embedding(
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texts,
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embed_model="nomic-embed-text"
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)
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texts, embed_model="nomic-embed-text", host="http://localhost:11434"
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),
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),
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)
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@@ -28,13 +33,21 @@ with open("./book.txt") as f:
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rag.insert(f.read())
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# Perform naive search
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print(rag.query("What are the top themes in this story?", param=QueryParam(mode="naive")))
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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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)
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# Perform local search
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print(rag.query("What are the top themes in this story?", param=QueryParam(mode="local")))
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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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)
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# Perform global search
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print(rag.query("What are the top themes in this story?", param=QueryParam(mode="global")))
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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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)
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# Perform hybrid search
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print(rag.query("What are the top themes in this story?", param=QueryParam(mode="hybrid")))
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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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)
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