quivr/backend/routes/crawl_routes.py

61 lines
2.8 KiB
Python

import os
import shutil
from tempfile import SpooledTemporaryFile
from auth.auth_bearer import AuthBearer, get_current_user
from crawl.crawler import CrawlWebsite
from fastapi import APIRouter, Depends, Request, UploadFile
from models.users import User
from parsers.github import process_github
from utils.common import CommonsDep
from utils.file import convert_bytes
from utils.processors import filter_file
crawl_router = APIRouter()
def get_unique_user_data(commons, user):
"""
Retrieve unique user data vectors.
"""
user_vectors_response = commons['supabase'].table("vectors").select(
"name:metadata->>file_name, size:metadata->>file_size", count="exact") \
.filter("user_id", "eq", user.email)\
.execute()
documents = user_vectors_response.data # Access the data from the response
# Convert each dictionary to a tuple of items, then to a set to remove duplicates, and then back to a dictionary
user_unique_vectors = [dict(t) for t in set(tuple(d.items()) for d in documents)]
return user_unique_vectors
@crawl_router.post("/crawl/", dependencies=[Depends(AuthBearer())], tags=["Crawl"])
async def crawl_endpoint(request: Request,commons: CommonsDep, crawl_website: CrawlWebsite, enable_summarization: bool = False, current_user: User = Depends(get_current_user)):
"""
Crawl a website and process the crawled data.
"""
max_brain_size = os.getenv("MAX_BRAIN_SIZE")
if request.headers.get('Openai-Api-Key'):
max_brain_size = os.getenv("MAX_BRAIN_SIZE_WITH_KEY",209715200)
user_unique_vectors = get_unique_user_data(commons, current_user)
current_brain_size = sum(float(doc['size']) for doc in user_unique_vectors)
file_size = 1000000
remaining_free_space = float(max_brain_size) - (current_brain_size)
if remaining_free_space - file_size < 0:
message = {"message": f"❌ User's brain will exceed maximum capacity with this upload. Maximum file allowed is : {convert_bytes(remaining_free_space)}", "type": "error"}
else:
if not crawl_website.checkGithub():
file_path, file_name = crawl_website.process()
# Create a SpooledTemporaryFile from the file_path
spooled_file = SpooledTemporaryFile()
with open(file_path, 'rb') as f:
shutil.copyfileobj(f, spooled_file)
# Pass the SpooledTemporaryFile to UploadFile
file = UploadFile(file=spooled_file, filename=file_name)
message = await filter_file(commons, file, enable_summarization, user=current_user, openai_api_key=request.headers.get('Openai-Api-Key', None))
return message
else:
message = await process_github(commons,crawl_website.url, "false", user=current_user, supabase=commons['supabase'], user_openai_api_key=request.headers.get('Openai-Api-Key', None))