13 lines
532 B
Python
13 lines
532 B
Python
from langchain_ollama import OllamaEmbeddings, Ollama
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from langchain_qdrant import QdrantVectorStore
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from langchain_text_splitters import RecursiveCharacterTextSplitter
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from langchain_core.documents import Document
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embeddings = OllamaEmbeddings(model="nomic-embed-text")
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llm = Ollama(model="llama3", temperature=0.0)
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vector_store = QdrantVectorStore(
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embedding_function=embeddings,
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url="http://localhost:6333",
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collection_name="knowledge",
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)
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splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200) |