quivr/backend/core/utils/processors.py
ChloeMouret 711e9fb8c9
refactor: delete common_dependencies function (#843)
* use function for get_documents_vector_store

* use function for get_embeddings

* use function for get_supabase_client

* use function for get_supabase_db

* delete lasts common_dependencies
2023-08-03 20:24:42 +02:00

94 lines
3.0 KiB
Python

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