mirror of
https://github.com/StanGirard/quivr.git
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93 lines
3.0 KiB
Python
93 lines
3.0 KiB
Python
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 parsers.audio import process_audio
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from parsers.csv import process_csv
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from parsers.docx import process_docx
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from parsers.epub import process_epub
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from parsers.html import process_html
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from parsers.markdown import process_markdown
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from parsers.notebook import process_ipnyb
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from parsers.odt import process_odt
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from parsers.pdf import process_pdf
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from parsers.powerpoint import process_powerpoint
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from parsers.txt import process_txt
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file_processors = {
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".txt": process_txt,
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".csv": process_csv,
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".md": process_markdown,
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".markdown": process_markdown,
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".m4a": process_audio,
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".mp3": process_audio,
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".webm": process_audio,
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".mp4": process_audio,
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".mpga": process_audio,
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".wav": process_audio,
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".mpeg": process_audio,
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".pdf": process_pdf,
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".html": process_html,
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".pptx": process_powerpoint,
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".docx": process_docx,
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".odt": process_odt,
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".epub": process_epub,
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".ipynb": process_ipnyb,
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}
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def create_response(message, type):
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return {"message": message, "type": type}
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async def filter_file(
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commons: CommonsDep,
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file: File,
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enable_summarization: bool,
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brain_id,
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openai_api_key,
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):
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await file.compute_file_sha1()
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print("file sha1", file.file_sha1)
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file_exists = file.file_already_exists()
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file_exists_in_brain = file.file_already_exists_in_brain(brain_id)
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if file_exists_in_brain:
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return create_response(
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f"🤔 {file.file.filename} already exists in brain {brain_id}.", # pyright: ignore reportPrivateUsage=none
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"warning",
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)
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elif file.file_is_empty():
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return create_response(
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f"❌ {file.file.filename} is empty.", # pyright: ignore reportPrivateUsage=none
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"error", # pyright: ignore reportPrivateUsage=none
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)
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elif file_exists:
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file.link_file_to_brain(brain=Brain(id=brain_id))
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return create_response(
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f"✅ {file.file.filename} has been uploaded to brain {brain_id}.", # pyright: ignore reportPrivateUsage=none
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"success",
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)
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if file.file_extension in file_processors:
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try:
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await file_processors[file.file_extension](
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commons, file, enable_summarization, brain_id, openai_api_key
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)
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return create_response(
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f"✅ {file.file.filename} has been uploaded to brain {brain_id}.", # pyright: ignore reportPrivateUsage=none
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"success",
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)
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except Exception as e:
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# Add more specific exceptions as needed.
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print(f"Error processing file: {e}")
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return create_response(
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f"⚠️ An error occurred while processing {file.file.filename}.", # pyright: ignore reportPrivateUsage=none
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"error",
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)
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return create_response(
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f"❌ {file.file.filename} is not supported.", # pyright: ignore reportPrivateUsage=none
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"error",
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)
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