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Merge branch 'cz/bug/state/zustand' into update_lc

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This commit is contained in:
anovazzi1 2024-01-09 10:02:30 -03:00
commit 4591824a63
94 changed files with 2443 additions and 3090 deletions
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31
src/backend/langflow/api/v1/login.py
View file

@ -1,4 +1,4 @@
from fastapi import APIRouter, Depends, HTTPException, status
from fastapi import Request, Response, APIRouter, Depends, HTTPException, status
from fastapi.security import OAuth2PasswordRequestForm
from sqlmodel import Session
@ -16,6 +16,7 @@ router = APIRouter(tags=["Login"])
@router.post("/login", response_model=Token)
async def login_to_get_access_token(
response: Response,
form_data: OAuth2PasswordRequestForm = Depends(),
db: Session = Depends(get_session),
# _: Session = Depends(get_current_active_user)
@ -31,7 +32,10 @@ async def login_to_get_access_token(
) from exc
if user:
return create_user_tokens(user_id=user.id, db=db, update_last_login=True)
tokens = create_user_tokens(user_id=user.id, db=db, update_last_login=True)
response.set_cookie("refresh_token_lf", tokens["refresh_token"], httponly=True, secure=True, samesite="strict")
response.set_cookie("access_token_lf", tokens["access_token"], httponly=False, secure=True, samesite="strict")
return tokens
else:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
@ -41,9 +45,13 @@ async def login_to_get_access_token(
@router.get("/auto_login")
async def auto_login(db: Session = Depends(get_session), settings_service=Depends(get_settings_service)):
async def auto_login(
response: Response, db: Session = Depends(get_session), settings_service=Depends(get_settings_service)
):
if settings_service.auth_settings.AUTO_LOGIN:
return create_user_longterm_token(db)
tokens = create_user_longterm_token(db)
response.set_cookie("access_token_lf", tokens["access_token"], httponly=False, secure=True, samesite="strict")
return tokens
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
@ -55,12 +63,23 @@ async def auto_login(db: Session = Depends(get_session), settings_service=Depend
@router.post("/refresh")
async def refresh_token(token: str):
async def refresh_token(request: Request, response: Response):
token = request.cookies.get("refresh_token_lf")
if token:
return create_refresh_token(token)
tokens = create_refresh_token(token)
response.set_cookie("refresh_token_lf", tokens["refresh_token"], httponly=True, secure=True, samesite="strict")
response.set_cookie("access_token_lf", tokens["access_token"], httponly=False, secure=True, samesite="strict")
return tokens
else:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Invalid refresh token",
headers={"WWW-Authenticate": "Bearer"},
)
@router.post("/logout")
async def logout(response: Response):
response.delete_cookie("refresh_token_lf")
response.delete_cookie("access_token_lf")
return {"message": "Logout successful"}

45
src/backend/langflow/components/retrievers/VectaraSelfQueryRetriver.py
View file

@ -15,29 +15,21 @@ class VectaraSelfQueryRetriverComponent(CustomComponent):
display_name: str = "Vectara Self Query Retriever for Vectara Vector Store"
description: str = "Implementation of Vectara Self Query Retriever"
documentation = (
"https://python.langchain.com/docs/integrations/retrievers/self_query/vectara_self_query"
)
documentation = "https://python.langchain.com/docs/integrations/retrievers/self_query/vectara_self_query"
beta = True
field_config = {
"code": {"show": True},
"vectorstore": {
"display_name": "Vector Store",
"info": "Input Vectara Vectore Store"
},
"llm": {
"display_name": "LLM",
"info": "For self query retriever"
},
"document_content_description":{
"display_name": "Document Content Description",
"vectorstore": {"display_name": "Vector Store", "info": "Input Vectara Vectore Store"},
"llm": {"display_name": "LLM", "info": "For self query retriever"},
"document_content_description": {
"display_name": "Document Content Description",
"info": "For self query retriever",
},
},
"metadata_field_info": {
"display_name": "Metadata Field Info",
"info": "Each metadata field info is a string in the form of key value pair dictionary containing additional search metadata.\nExample input: {\"name\":\"speech\",\"description\":\"what name of the speech\",\"type\":\"string or list[string]\"}.\nThe keys should remain constant(name, description, type)",
},
"display_name": "Metadata Field Info",
"info": 'Each metadata field info is a string in the form of key value pair dictionary containing additional search metadata.\nExample input: {"name":"speech","description":"what name of the speech","type":"string or list[string]"}.\nThe keys should remain constant(name, description, type)',
},
}
def build(
@ -47,24 +39,19 @@ class VectaraSelfQueryRetriverComponent(CustomComponent):
llm: BaseLanguageModel,
metadata_field_info: List[str],
) -> BaseRetriever:
metadata_field_obj = []
for meta in metadata_field_info:
meta_obj = json.loads(meta)
if 'name' not in meta_obj or 'description' not in meta_obj or 'type' not in meta_obj :
raise Exception('Incorrect metadata field info format.')
if "name" not in meta_obj or "description" not in meta_obj or "type" not in meta_obj:
raise Exception("Incorrect metadata field info format.")
attribute_info = AttributeInfo(
name = meta_obj['name'],
description = meta_obj['description'],
type = meta_obj['type'],
name=meta_obj["name"],
description=meta_obj["description"],
type=meta_obj["type"],
)
metadata_field_obj.append(attribute_info)
return SelfQueryRetriever.from_llm(
llm,
vectorstore,
document_content_description,
metadata_field_obj,
verbose=True
)
llm, vectorstore, document_content_description, metadata_field_obj, verbose=True
)