mirror of
https://github.com/StanGirard/quivr.git
synced 2024-12-26 12:52:05 +03:00
5fc837b250
* feat(functions): simplified * refactor(openai): changed to brainpicking * feat(functions): made them inherit from brainpicking * feat(privatebrainpicking): added new class * feat(history&context): added * Delete test_brainpicking.py * Delete __init__.py
46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
from typing import Annotated
|
|
|
|
from fastapi import Depends
|
|
from langchain.embeddings.openai import OpenAIEmbeddings
|
|
from pydantic import BaseSettings
|
|
from supabase import Client, create_client
|
|
from vectorstore.supabase import SupabaseVectorStore
|
|
|
|
|
|
class BrainSettings(BaseSettings):
|
|
openai_api_key: str
|
|
anthropic_api_key: str
|
|
supabase_url: str
|
|
supabase_service_key: str
|
|
|
|
|
|
class LLMSettings(BaseSettings):
|
|
private: bool = False
|
|
model_path: str = "gpt2"
|
|
model_n_ctx: int = 1000
|
|
model_n_batch: int = 8
|
|
|
|
|
|
def common_dependencies() -> dict:
|
|
settings = BrainSettings()
|
|
embeddings = OpenAIEmbeddings(openai_api_key=settings.openai_api_key)
|
|
supabase_client: Client = create_client(
|
|
settings.supabase_url, settings.supabase_service_key
|
|
)
|
|
documents_vector_store = SupabaseVectorStore(
|
|
supabase_client, embeddings, table_name="vectors"
|
|
)
|
|
summaries_vector_store = SupabaseVectorStore(
|
|
supabase_client, embeddings, table_name="summaries"
|
|
)
|
|
|
|
return {
|
|
"supabase": supabase_client,
|
|
"embeddings": embeddings,
|
|
"documents_vector_store": documents_vector_store,
|
|
"summaries_vector_store": summaries_vector_store,
|
|
}
|
|
|
|
|
|
CommonsDep = Annotated[dict, Depends(common_dependencies)]
|