quivr/backend/core/models/brains.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

117 lines
3.8 KiB
Python

from typing import Any, List, Optional
from uuid import UUID
from logger import get_logger
from models.databases.supabase.supabase import SupabaseDB
from models.settings import BrainRateLimiting, get_supabase_client, get_supabase_db
from pydantic import BaseModel
from supabase.client import Client
from utils.vectors import get_unique_files_from_vector_ids
logger = get_logger(__name__)
class Brain(BaseModel):
id: Optional[UUID] = None
name: Optional[str] = "Default brain"
description: Optional[str] = "This is a description"
status: Optional[str] = "private"
model: Optional[str] = "gpt-3.5-turbo-0613"
temperature: Optional[float] = 0.0
max_tokens: Optional[int] = 256
openai_api_key: Optional[str] = None
files: List[Any] = []
max_brain_size = BrainRateLimiting().max_brain_size
prompt_id: Optional[UUID] = None
class Config:
arbitrary_types_allowed = True
@property
def supabase_client(self) -> Client:
return get_supabase_client()
@property
def supabase_db(self) -> SupabaseDB:
return get_supabase_db()
@property
def brain_size(self):
self.get_unique_brain_files()
current_brain_size = sum(float(doc["size"]) for doc in self.files)
return current_brain_size
@property
def remaining_brain_size(self):
return (
float(self.max_brain_size) # pyright: ignore reportPrivateUsage=none
- self.brain_size # pyright: ignore reportPrivateUsage=none
)
@classmethod
def create(cls, *args, **kwargs):
commons = {"supabase": get_supabase_client()}
return cls(
commons=commons, *args, **kwargs # pyright: ignore reportPrivateUsage=none
) # pyright: ignore reportPrivateUsage=none
# TODO: move this to a brand new BrainService
def get_brain_users(self):
response = (
self.supabase_client.table("brains_users")
.select("id:brain_id, *")
.filter("brain_id", "eq", self.id)
.execute()
)
return response.data
# TODO: move this to a brand new BrainService
def delete_user_from_brain(self, user_id):
results = (
self.supabase_client.table("brains_users")
.select("*")
.match({"brain_id": self.id, "user_id": user_id})
.execute()
)
if len(results.data) != 0:
self.supabase_client.table("brains_users").delete().match(
{"brain_id": self.id, "user_id": user_id}
).execute()
def delete_brain(self, user_id):
results = self.supabase_db.delete_brain_user_by_id(user_id, self.id)
if len(results.data) == 0:
return {"message": "You are not the owner of this brain."}
else:
self.supabase_db.delete_brain_vector(self.id)
self.supabase_db.delete_brain_user(self.id)
self.supabase_db.delete_brain(self.id)
def create_brain_vector(self, vector_id, file_sha1):
return self.supabase_db.create_brain_vector(self.id, vector_id, file_sha1)
def get_vector_ids_from_file_sha1(self, file_sha1: str):
return self.supabase_db.get_vector_ids_from_file_sha1(file_sha1)
def update_brain_with_file(self, file_sha1: str):
# not used
vector_ids = self.get_vector_ids_from_file_sha1(file_sha1)
for vector_id in vector_ids:
self.create_brain_vector(vector_id, file_sha1)
def get_unique_brain_files(self):
"""
Retrieve unique brain data (i.e. uploaded files and crawled websites).
"""
vector_ids = self.supabase_db.get_brain_vector_ids(self.id)
self.files = get_unique_files_from_vector_ids(vector_ids)
return self.files
def delete_file_from_brain(self, file_name: str):
return self.supabase_db.delete_file_from_brain(self.id, file_name)