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44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
import time
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from langchain.schema import Document
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from models.brains import Brain
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from models.files import File
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from models.settings import CommonsDep
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from utils.vectors import Neurons
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async def process_file(
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commons: CommonsDep,
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file: File,
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loader_class,
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enable_summarization,
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brain_id,
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user_openai_api_key,
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):
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dateshort = time.strftime("%Y%m%d")
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file.compute_documents(loader_class)
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for doc in file.documents: # pyright: ignore reportPrivateUsage=none
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metadata = {
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"file_sha1": file.file_sha1,
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"file_size": file.file_size,
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"file_name": file.file_name,
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"chunk_size": file.chunk_size,
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"chunk_overlap": file.chunk_overlap,
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"date": dateshort,
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"summarization": "true" if enable_summarization else "false",
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}
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doc_with_metadata = Document(page_content=doc.page_content, metadata=metadata)
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neurons = Neurons(commons=commons)
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created_vector = neurons.create_vector(doc_with_metadata, user_openai_api_key)
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# add_usage(stats_db, "embedding", "audio", metadata={"file_name": file_meta_name,"file_type": ".txt", "chunk_size": chunk_size, "chunk_overlap": chunk_overlap})
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created_vector_id = created_vector[0] # pyright: ignore reportPrivateUsage=none
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brain = Brain(id=brain_id)
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brain.create_brain_vector(created_vector_id, file.file_sha1)
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return
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