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272 lines
8.3 KiB
Python
272 lines
8.3 KiB
Python
import os
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from typing import Any, List, Optional
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from uuid import UUID
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from logger import get_logger
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from models.settings import CommonsDep, common_dependencies
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from models.users import User
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from pydantic import BaseModel
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from utils.vectors import get_unique_files_from_vector_ids
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logger = get_logger(__name__)
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class Brain(BaseModel):
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id: Optional[UUID] = None
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name: Optional[str] = "Default brain"
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status: Optional[str] = "public"
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model: Optional[str] = "gpt-3.5-turbo-0613"
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temperature: Optional[float] = 0.0
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max_tokens: Optional[int] = 256
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max_brain_size: Optional[int] = int(os.getenv("MAX_BRAIN_SIZE",52428800))
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files: List[Any] = []
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class Config:
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arbitrary_types_allowed = True
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@property
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def commons(self) -> CommonsDep:
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return common_dependencies()
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@property
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def brain_size(self):
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self.get_unique_brain_files()
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current_brain_size = sum(float(doc["size"]) for doc in self.files)
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return current_brain_size
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@property
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def remaining_brain_size(self):
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return (
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float(self.max_brain_size) # pyright: ignore reportPrivateUsage=none
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- self.brain_size # pyright: ignore reportPrivateUsage=none
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)
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@classmethod
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def create(cls, *args, **kwargs):
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commons = common_dependencies()
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return cls(
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commons=commons, *args, **kwargs # pyright: ignore reportPrivateUsage=none
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) # pyright: ignore reportPrivateUsage=none
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def get_user_brains(self, user_id):
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response = (
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self.commons["supabase"]
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.from_("brains_users")
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.select("id:brain_id, brains (id: brain_id, name)")
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.filter("user_id", "eq", user_id)
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.execute()
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)
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return [item["brains"] for item in response.data]
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def get_brain_for_user(self, user_id):
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response = (
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self.commons["supabase"]
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.from_("brains_users")
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.select("id:brain_id, rights, brains (id: brain_id, name)")
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.filter("user_id", "eq", user_id)
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.filter("brain_id", "eq", self.id)
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.execute()
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)
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if len(response.data) == 0:
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return None
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return response.data[0]
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def get_brain_details(self):
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response = (
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self.commons["supabase"]
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.from_("brains")
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.select("id:brain_id, name, *")
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.filter("brain_id", "eq", self.id)
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.execute()
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)
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return response.data
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def delete_brain(self, user_id):
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results = (
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self.commons["supabase"]
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.table("brains_users")
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.select("*")
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.match({"brain_id": self.id, "user_id": user_id, "rights": "Owner"})
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.execute()
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)
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if len(results.data) == 0:
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return {"message": "You are not the owner of this brain."}
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else:
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results = (
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self.commons["supabase"]
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.table("brains_vectors")
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.delete()
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.match({"brain_id": self.id})
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.execute()
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)
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results = (
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self.commons["supabase"]
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.table("brains_users")
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.delete()
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.match({"brain_id": self.id})
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.execute()
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)
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results = (
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self.commons["supabase"]
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.table("brains")
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.delete()
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.match({"brain_id": self.id})
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.execute()
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)
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def create_brain(self):
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commons = common_dependencies()
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response = (
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commons["supabase"].table("brains").insert({"name": self.name}).execute()
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)
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self.id = response.data[0]["brain_id"]
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return response.data
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def create_brain_user(self, user_id: UUID, rights, default_brain):
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commons = common_dependencies()
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response = (
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commons["supabase"]
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.table("brains_users")
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.insert(
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{
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"brain_id": str(self.id),
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"user_id": str(user_id),
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"rights": rights,
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"default_brain": default_brain,
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}
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)
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.execute()
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)
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return response.data
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def create_brain_vector(self, vector_id, file_sha1):
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response = (
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self.commons["supabase"]
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.table("brains_vectors")
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.insert(
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{
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"brain_id": str(self.id),
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"vector_id": str(vector_id),
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"file_sha1": file_sha1,
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}
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)
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.execute()
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)
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return response.data
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def get_vector_ids_from_file_sha1(self, file_sha1: str):
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# move to vectors class
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vectorsResponse = (
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self.commons["supabase"]
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.table("vectors")
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.select("id")
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.filter("metadata->>file_sha1", "eq", file_sha1)
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.execute()
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)
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return vectorsResponse.data
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def update_brain_fields(self):
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self.commons["supabase"].table("brains").update({"name": self.name}).match(
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{"brain_id": self.id}
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).execute()
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def update_brain_with_file(self, file_sha1: str):
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# not used
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vector_ids = self.get_vector_ids_from_file_sha1(file_sha1)
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for vector_id in vector_ids:
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self.create_brain_vector(vector_id, file_sha1)
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def get_unique_brain_files(self):
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"""
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Retrieve unique brain data (i.e. uploaded files and crawled websites).
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"""
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response = (
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self.commons["supabase"]
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.from_("brains_vectors")
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.select("vector_id")
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.filter("brain_id", "eq", self.id)
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.execute()
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)
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vector_ids = [item["vector_id"] for item in response.data]
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if len(vector_ids) == 0:
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return []
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self.files = get_unique_files_from_vector_ids(vector_ids)
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return self.files
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def delete_file_from_brain(self, file_name: str):
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# First, get the vector_ids associated with the file_name
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vector_response = (
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self.commons["supabase"]
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.table("vectors")
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.select("id")
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.filter("metadata->>file_name", "eq", file_name)
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.execute()
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)
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vector_ids = [item["id"] for item in vector_response.data]
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# For each vector_id, delete the corresponding entry from the 'brains_vectors' table
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for vector_id in vector_ids:
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self.commons["supabase"].table("brains_vectors").delete().filter(
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"vector_id", "eq", vector_id
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).filter("brain_id", "eq", self.id).execute()
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# Check if the vector is still associated with any other brains
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associated_brains_response = (
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self.commons["supabase"]
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.table("brains_vectors")
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.select("brain_id")
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.filter("vector_id", "eq", vector_id)
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.execute()
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)
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associated_brains = [
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item["brain_id"] for item in associated_brains_response.data
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]
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# If the vector is not associated with any other brains, delete it from 'vectors' table
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if not associated_brains:
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self.commons["supabase"].table("vectors").delete().filter(
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"id", "eq", vector_id
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).execute()
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return {"message": f"File {file_name} in brain {self.id} has been deleted."}
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def get_default_user_brain(user: User):
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commons = common_dependencies()
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response = (
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commons["supabase"]
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.from_("brains_users")
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.select("brain_id")
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.filter("user_id", "eq", user.id)
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.filter("default_brain", "eq", True)
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.execute()
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)
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logger.info("Default brain response:", response.data)
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default_brain_id = response.data[0]["brain_id"] if response.data else None
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logger.info(f"Default brain id: {default_brain_id}")
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if default_brain_id:
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brain_response = (
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commons["supabase"]
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.from_("brains")
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.select("id:brain_id, name, *")
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.filter("brain_id", "eq", default_brain_id)
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.execute()
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)
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return brain_response.data[0] if brain_response.data else None
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return None
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