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21 lines
626 B
Python
21 lines
626 B
Python
from uuid import UUID
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from models.settings import get_embeddings, get_supabase_client
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from vectorstore.supabase import CustomSupabaseVectorStore
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def get_question_context_from_brain(brain_id: UUID, question: str) -> str:
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supabase_client = get_supabase_client()
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embeddings = get_embeddings()
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vector_store = CustomSupabaseVectorStore(
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supabase_client,
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embeddings,
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table_name="vectors",
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brain_id=brain_id,
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)
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documents = vector_store.similarity_search(question)
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# aggregate all the documents into one string
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return "\n".join([doc.page_content for doc in documents])
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