Merge branch 'authentication' into login

2023-08-15 16:03:42 -03:00 · 2023-08-15 16:03:42 -03:00 · 015064b453
commit 015064b453
parent 4a7ccda51c 695a337c6c
38 changed files with 1009 additions and 793 deletions
--- a/.dockerignore
+++ b/.dockerignore
@ -0,0 +1 @@
+.venv/
--- a/dev.Dockerfile
+++ b/dev.Dockerfile
@ -15,4 +15,4 @@ COPY ./ ./
 # Install dependencies
 RUN poetry config virtualenvs.create false && poetry install --no-interaction --no-ansi

-CMD ["uvicorn","--factory", "langflow.main:create_app", "--host", "0.0.0.0", "--port", "5003", "--reload", "log-level", "debug"]
+CMD ["uvicorn", "--factory", "src.backend.langflow.main:create_app", "--host", "0.0.0.0", "--port", "7860", "--reload", "--log-level", "debug"]
--- a/docker-compose.debug.yml
+++ b/docker-compose.debug.yml
@ -11,7 +11,7 @@ services:
      [
        "sh",
        "-c",
-        "pip install debugpy -t /tmp && python /tmp/debugpy --wait-for-client --listen 0.0.0.0:5678 -m uvicorn --factory langflow.main:create_app --host 0.0.0.0 --port 7860 --reload",
+        "pip install debugpy -t /tmp && python /tmp/debugpy --wait-for-client --listen 0.0.0.0:5678 -m uvicorn --factory src.backend.langflow.main:create_app --host 0.0.0.0 --port 7860 --reload",
      ]
    ports:
      - 7860:7860
--- a/docker-compose.yml
+++ b/docker-compose.yml
@ -9,7 +9,7 @@ services:
      - "7860:7860"
    volumes:
      - ./:/app
-    command: bash -c "uvicorn --factory langflow.main:create_app --host 0.0.0.0 --port 7860 --reload"
+    command: bash -c "uvicorn --factory src.backend.langflow.main:create_app --host 0.0.0.0 --port 7860 --reload"

  frontend:
    build:
--- a/docs/docs/components/embeddings.mdx
+++ b/docs/docs/components/embeddings.mdx
@ -73,3 +73,25 @@ Used to load [OpenAI’s](https://openai.com/) embedding models.
 - **request_timeout:** Used to specify the maximum amount of time, in milliseconds, to wait for a response from the OpenAI API when generating embeddings for a given text.

 - **tiktoken_model_name:** Used to count the number of tokens in documents to constrain them to be under a certain limit. By default, when set to None, this will be the same as the embedding model name.
+
+---
+
+### VertexAIEmbeddings
+
+Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) [Embeddings API](https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings).
+
+:::info
+Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
+:::
+
+- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
+- **location:** The default location to use when making API calls – defaults to `us-central1`.
+- **max_output_tokens:** Token limit determines the maximum amount of text output from one prompt – defaults to `128`.
+- **model_name:** The name of the Vertex AI large language model – defaults to `text-bison`.
+- **project:** The default GCP project to use when making Vertex API calls.
+- **request_parallelism:** The amount of parallelism allowed for requests issued to VertexAI models – defaults to `5`.
+- **temperature:** Tunes the degree of randomness in text generations. Should be a non-negative value – defaults to `0`.
+- **top_k:** How the model selects tokens for output, the next token is selected from – defaults to `40`.
+- **top_p:** Tokens are selected from most probable to least until the sum of their – defaults to `0.95`.
+- **tuned_model_name:** The name of a tuned model. If provided, model_name is ignored.
+- **verbose:** This parameter is used to control the level of detail in the output of the chain. When set to True, it will print out some internal states of the chain while it is being run, which can help debug and understand the chain's behavior. If set to False, it will suppress the verbose output – defaults to `False`.
--- a/docs/docs/components/llms.mdx
+++ b/docs/docs/components/llms.mdx
@ -185,6 +185,28 @@ Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) large lang
 Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
 :::

+- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
+- **location:** The default location to use when making API calls – defaults to `us-central1`.
+- **max_output_tokens:** Token limit determines the maximum amount of text output from one prompt – defaults to `128`.
+- **model_name:** The name of the Vertex AI large language model – defaults to `text-bison`.
+- **project:** The default GCP project to use when making Vertex API calls.
+- **request_parallelism:** The amount of parallelism allowed for requests issued to VertexAI models – defaults to `5`.
+- **temperature:** Tunes the degree of randomness in text generations. Should be a non-negative value – defaults to `0`.
+- **top_k:** How the model selects tokens for output, the next token is selected from – defaults to `40`.
+- **top_p:** Tokens are selected from most probable to least until the sum of their – defaults to `0.95`.
+- **tuned_model_name:** The name of a tuned model. If provided, model_name is ignored.
+- **verbose:** This parameter is used to control the level of detail in the output of the chain. When set to True, it will print out some internal states of the chain while it is being run, which can help debug and understand the chain's behavior. If set to False, it will suppress the verbose output – defaults to `False`.
+
+---
+
+### ChatVertexAI
+
+Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) large language models.
+
+:::info
+Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
+:::
+
 - **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
 - **location:** The default location to use when making API calls – defaults to `us-central1`.
 - **max_output_tokens:** Token limit determines the maximum amount of text output from one prompt – defaults to `128`.
--- a/docs/docs/guidelines/custom-component.mdx
+++ b/docs/docs/guidelines/custom-component.mdx
@ -65,7 +65,6 @@ class DocumentProcessor(CustomComponent):
        light: "img/document_processor.png",
    }}
    style={{
-        width: "40%",
        margin: "0 auto",
        display: "flex",
        justifyContent: "center",
--- a/poetry.lock
+++ b/poetry.lock
@ -2,13 +2,13 @@

 [[package]]
 name = "aiofiles"
-version = "23.1.0"
+version = "23.2.1"
 description = "File support for asyncio."
 optional = false
-python-versions = ">=3.7,<4.0"
+python-versions = ">=3.7"
 files = [
-    {file = "aiofiles-23.1.0-py3-none-any.whl", hash = "sha256:9312414ae06472eb6f1d163f555e466a23aed1c8f60c30cccf7121dba2e53eb2"},
-    {file = "aiofiles-23.1.0.tar.gz", hash = "sha256:edd247df9a19e0db16534d4baaf536d6609a43e1de5401d7a4c1c148753a1635"},
+    {file = "aiofiles-23.2.1-py3-none-any.whl", hash = "sha256:19297512c647d4b27a2cf7c34caa7e405c0d60b5560618a29a9fe027b18b0107"},
+    {file = "aiofiles-23.2.1.tar.gz", hash = "sha256:84ec2218d8419404abcb9f0c02df3f34c6e0a68ed41072acfb1cef5cbc29051a"},
 ]

 [[package]]
@ -165,13 +165,13 @@ tz = ["python-dateutil"]

 [[package]]
 name = "anthropic"
-version = "0.3.8"
+version = "0.3.9"
 description = "Client library for the anthropic API"
 optional = false
 python-versions = ">=3.7,<4.0"
 files = [
-    {file = "anthropic-0.3.8-py3-none-any.whl", hash = "sha256:97ffe1bacc4214dc89b19f496cf2769746971e86f7c835a05aa21b76f260d279"},
-    {file = "anthropic-0.3.8.tar.gz", hash = "sha256:6651099807456c3b95b3879f5ad7d00f7e7e4f7649a2394d18032ab8be54ef16"},
+    {file = "anthropic-0.3.9-py3-none-any.whl", hash = "sha256:23e8daf266c707faa0b85328ada03dcf885e62c2f236eb0159352e29b9c4e2e3"},
+    {file = "anthropic-0.3.9.tar.gz", hash = "sha256:c19b75308c07cb1ecbea03ffcdde9ba68e5ca22a22479217712396385678bde3"},
 ]

 [package.dependencies]
@ -180,7 +180,7 @@ distro = ">=1.7.0,<2"
 httpx = ">=0.23.0,<1"
 pydantic = ">=1.9.0,<2.0.0"
 tokenizers = ">=0.13.0"
-typing-extensions = ">=4.1.1,<5"
+typing-extensions = ">=4.5,<5"

 [[package]]
 name = "anyio"
@ -272,13 +272,13 @@ test = ["astroid", "pytest"]

 [[package]]
 name = "async-timeout"
-version = "4.0.2"
+version = "4.0.3"
 description = "Timeout context manager for asyncio programs"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
-    {file = "async-timeout-4.0.2.tar.gz", hash = "sha256:2163e1640ddb52b7a8c80d0a67a08587e5d245cc9c553a74a847056bc2976b15"},
-    {file = "async_timeout-4.0.2-py3-none-any.whl", hash = "sha256:8ca1e4fcf50d07413d66d1a5e416e42cfdf5851c981d679a09851a6853383b3c"},
+    {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
+    {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
 ]

 [[package]]
@ -792,13 +792,13 @@ sqlalchemy = ["sqlalchemy (>1.3.21,<2.0)"]

 [[package]]
 name = "cohere"
-version = "4.19.2"
+version = "4.20.0"
 description = ""
 optional = false
 python-versions = ">=3.7,<4.0"
 files = [
-    {file = "cohere-4.19.2-py3-none-any.whl", hash = "sha256:0b6a4fe04380a481a8e975ebcc9bb6433febe4d3eb583b6d6e04342a5e998345"},
-    {file = "cohere-4.19.2.tar.gz", hash = "sha256:a0b0fa698b3d3983fb328bb90d68fcf08faaa2268f3772ebc6bfea6ba55acf27"},
+    {file = "cohere-4.20.0-py3-none-any.whl", hash = "sha256:bebe4b1d21da0719aaa7db2cc180b5f3d0a802c19ad2d893d627971286e50497"},
+    {file = "cohere-4.20.0.tar.gz", hash = "sha256:a16e86981945c201bab67ad6d47e57f42a37bf2a774f6ac6b8b12233aae6409a"},
 ]

 [package.dependencies]
@ -858,71 +858,63 @@ typing = ["mypy (>=0.990)"]

 [[package]]
 name = "coverage"
-version = "7.2.7"
+version = "7.3.0"
 description = "Code coverage measurement for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
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 install-types = ["pip"]
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 reports = ["lxml"]

 [[package]]
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 [[package]]
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 [package.extras]
@ -6734,33 +6751,33 @@ scipy = ["scipy"]

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 python-versions = ">= 3.8"
 files = [
-    {file = "tornado-6.3.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:c367ab6c0393d71171123ca5515c61ff62fe09024fa6bf299cd1339dc9456829"},
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-    {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:834ae7540ad3a83199a8da8f9f2d383e3c3d5130a328889e4cc991acc81e87a0"},
-    {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:6a0848f1aea0d196a7c4f6772197cbe2abc4266f836b0aac76947872cd29b411"},
-    {file = "tornado-6.3.2-cp38-abi3-win32.whl", hash = "sha256:7efcbcc30b7c654eb6a8c9c9da787a851c18f8ccd4a5a3a95b05c7accfa068d2"},
-    {file = "tornado-6.3.2-cp38-abi3-win_amd64.whl", hash = "sha256:0c325e66c8123c606eea33084976c832aa4e766b7dff8aedd7587ea44a604cdf"},
-    {file = "tornado-6.3.2.tar.gz", hash = "sha256:4b927c4f19b71e627b13f3db2324e4ae660527143f9e1f2e2fb404f3a187e2ba"},
+    {file = "tornado-6.3.3-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:502fba735c84450974fec147340016ad928d29f1e91f49be168c0a4c18181e1d"},
+    {file = "tornado-6.3.3-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:805d507b1f588320c26f7f097108eb4023bbaa984d63176d1652e184ba24270a"},
+    {file = "tornado-6.3.3-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1bd19ca6c16882e4d37368e0152f99c099bad93e0950ce55e71daed74045908f"},
+    {file = "tornado-6.3.3-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ac51f42808cca9b3613f51ffe2a965c8525cb1b00b7b2d56828b8045354f76a"},
+    {file = "tornado-6.3.3-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:71a8db65160a3c55d61839b7302a9a400074c9c753040455494e2af74e2501f2"},
+    {file = "tornado-6.3.3-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:ceb917a50cd35882b57600709dd5421a418c29ddc852da8bcdab1f0db33406b0"},
+    {file = "tornado-6.3.3-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:7d01abc57ea0dbb51ddfed477dfe22719d376119844e33c661d873bf9c0e4a16"},
+    {file = "tornado-6.3.3-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:9dc4444c0defcd3929d5c1eb5706cbe1b116e762ff3e0deca8b715d14bf6ec17"},
+    {file = "tornado-6.3.3-cp38-abi3-win32.whl", hash = "sha256:65ceca9500383fbdf33a98c0087cb975b2ef3bfb874cb35b8de8740cf7f41bd3"},
+    {file = "tornado-6.3.3-cp38-abi3-win_amd64.whl", hash = "sha256:22d3c2fa10b5793da13c807e6fc38ff49a4f6e1e3868b0a6f4164768bb8e20f5"},
+    {file = "tornado-6.3.3.tar.gz", hash = "sha256:e7d8db41c0181c80d76c982aacc442c0783a2c54d6400fe028954201a2e032fe"},
 ]

 [[package]]
 name = "tqdm"
-version = "4.65.1"
+version = "4.66.1"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.65.1-py3-none-any.whl", hash = "sha256:16181c62ad2c6f8f6f29876e66322faad1c7fd3cc70aa9cc25ff63e50d1da031"},
-    {file = "tqdm-4.65.1.tar.gz", hash = "sha256:2cb0075cc5269f8edac40bdeb757cc36ab5b6648caf014822b67e1a49fba141d"},
+    {file = "tqdm-4.66.1-py3-none-any.whl", hash = "sha256:d302b3c5b53d47bce91fea46679d9c3c6508cf6332229aa1e7d8653723793386"},
+    {file = "tqdm-4.66.1.tar.gz", hash = "sha256:d88e651f9db8d8551a62556d3cff9e3034274ca5d66e93197cf2490e2dcb69c7"},
 ]

 [package.dependencies]
@ -6935,13 +6952,13 @@ files = [

 [[package]]
 name = "types-pytz"
-version = "2023.3.0.0"
+version = "2023.3.0.1"
 description = "Typing stubs for pytz"
 optional = false
 python-versions = "*"
 files = [
-    {file = "types-pytz-2023.3.0.0.tar.gz", hash = "sha256:ecdc70d543aaf3616a7e48631543a884f74205f284cefd6649ddf44c6a820aac"},
-    {file = "types_pytz-2023.3.0.0-py3-none-any.whl", hash = "sha256:4fc2a7fbbc315f0b6630e0b899fd6c743705abe1094d007b0e612d10da15e0f3"},
+    {file = "types-pytz-2023.3.0.1.tar.gz", hash = "sha256:1a7b8d4aac70981cfa24478a41eadfcd96a087c986d6f150d77e3ceb3c2bdfab"},
+    {file = "types_pytz-2023.3.0.1-py3-none-any.whl", hash = "sha256:65152e872137926bb67a8fe6cc9cfd794365df86650c5d5fdc7b167b0f38892e"},
 ]

 [[package]]
@ -7176,20 +7193,15 @@ test = ["Cython (>=0.29.32,<0.30.0)", "aiohttp", "flake8 (>=3.9.2,<3.10.0)", "my

 [[package]]
 name = "validators"
-version = "0.20.0"
-description = "Python Data Validation for Humans™."
+version = "0.21.0"
+description = "Python Data Validation for Humans™"
 optional = false
-python-versions = ">=3.4"
+python-versions = ">=3.8,<4.0"
 files = [
-    {file = "validators-0.20.0.tar.gz", hash = "sha256:24148ce4e64100a2d5e267233e23e7afeb55316b47d30faae7eb6e7292bc226a"},
+    {file = "validators-0.21.0-py3-none-any.whl", hash = "sha256:3470db6f2384c49727ee319afa2e97aec3f8fad736faa6067e0fd7f9eaf2c551"},
+    {file = "validators-0.21.0.tar.gz", hash = "sha256:245b98ab778ed9352a7269c6a8f6c2a839bed5b2a7e3e60273ce399d247dd4b3"},
 ]

-[package.dependencies]
-decorator = ">=3.4.0"
-
-[package.extras]
-test = ["flake8 (>=2.4.0)", "isort (>=4.2.2)", "pytest (>=2.2.3)"]
-
 [[package]]
 name = "watchfiles"
 version = "0.19.0"
@ -7681,4 +7693,4 @@ local = ["ctransformers", "llama-cpp-python", "sentence-transformers"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "0549d60fd69bb53ccdc466b76e05647ceb5502dcd01f6040e82eb9d7d9050292"
+content-hash = "0f7d3f932eb130e7f3b6d234fc36e403ef409d63cfc825ba9f4c470203425ad2"
--- a/pyproject.toml
+++ b/pyproject.toml
@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.4.3"
+version = "0.4.7"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [
@ -45,7 +45,7 @@ unstructured = "^0.7.0"
 pypdf = "^3.11.0"
 lxml = "^4.9.2"
 pysrt = "^1.1.2"
-fake-useragent = "^1.1.3"
+fake-useragent = "^1.2.1"
 docstring-parser = "^0.15"
 psycopg2-binary = "^2.9.6"
 pyarrow = "^12.0.0"
@ -81,6 +81,7 @@ alembic = "^1.11.2"
 passlib = "^1.7.4"
 bcrypt = "^4.0.1"
 python-jose = "^3.3.0"
+metaphor-python = "^0.1.11"

 [tool.poetry.group.dev.dependencies]
 black = "^23.1.0"
--- a/src/backend/Dockerfile
+++ b/src/backend/Dockerfile
@ -11,4 +11,4 @@ RUN rm *.whl

 EXPOSE 80

-CMD [ "uvicorn", "--host", "0.0.0.0", "--port", "80", "langflow.backend.app:app" ]
+CMD [ "uvicorn", "--host", "0.0.0.0", "--port", "7860", "--factory", "langflow.main:create_app" ]
--- a/src/backend/langflow/auth/auth.py
+++ b/src/backend/langflow/auth/auth.py
@ -1,3 +1,4 @@
+from uuid import UUID
 from typing import Annotated
 from jose import JWTError, jwt
 from sqlalchemy.orm import Session
@ -6,21 +7,60 @@ from fastapi.security import OAuth2PasswordBearer
 from fastapi import Depends, HTTPException, status
 from datetime import datetime, timedelta, timezone

+from langflow.services.utils import get_settings_manager
+
 from langflow.services.utils import get_session
-from langflow.database.models.token import TokenData
-from langflow.database.models.user import User, get_user_by_username
+from langflow.database.models.user import (
+    User,
+    get_user_by_id,
+    get_user_by_username,
+    update_user_last_login_at,
+)


-# TODO: Move to env - JUST FOR TEST!!!!!
-SECRET_KEY = "698619adad2d916f1f32d264540976964b3c0d3828e0870a65add5800a8cc6b9"
-ALGORITHM = "HS256"
-ACCESS_TOKEN_EXPIRE_MINUTES = 60
-REFRESH_TOKEN_EXPIRE_MINUTES = 70
-
 pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
 oauth2_scheme = OAuth2PasswordBearer(tokenUrl="login")


+async def get_current_user(
+    token: Annotated[str, Depends(oauth2_scheme)], db: Session = Depends(get_session)
+) -> User:
+    settings_manager = get_settings_manager()
+
+    credentials_exception = HTTPException(
+        status_code=status.HTTP_401_UNAUTHORIZED,
+        detail="Could not validate credentials",
+        headers={"WWW-Authenticate": "Bearer"},
+    )
+
+    try:
+        payload = jwt.decode(
+            token,
+            settings_manager.settings.SECRET_KEY,
+            algorithms=[settings_manager.settings.ALGORITHM],
+        )
+        user_id: UUID = payload.get("sub")  # type: ignore
+        token_type: str = payload.get("type")  # type: ignore
+
+        if user_id is None or token_type:
+            raise credentials_exception
+    except JWTError as e:
+        raise credentials_exception from e
+
+    user = get_user_by_id(db, user_id)  # type: ignore
+    if user is None:
+        raise credentials_exception
+    return user
+
+
+async def get_current_active_user(
+    current_user: Annotated[User, Depends(get_current_user)]
+):
+    if not current_user.is_active:
+        raise HTTPException(status_code=400, detail="Inactive user")
+    return current_user
+
+
 def verify_password(plain_password, hashed_password):
    return pwd_context.verify(plain_password, hashed_password)

@ -30,27 +70,64 @@ def get_password_hash(password):


 def create_token(data: dict, expires_delta: timedelta):
-    to_encode = data.copy()
+    settings_manager = get_settings_manager()

+    to_encode = data.copy()
    expire = datetime.now(timezone.utc) + expires_delta
    to_encode["exp"] = expire

-    return jwt.encode(to_encode, SECRET_KEY, algorithm=ALGORITHM)
+    return jwt.encode(
+        to_encode,
+        settings_manager.settings.SECRET_KEY,
+        algorithm=settings_manager.settings.ALGORITHM,
+    )


-def create_user_tokens(username: str) -> dict:
-    access_token_expires = timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES)
+def create_user_longterm_token(
+    user_id: UUID, db: Session = Depends(get_session), update_last_login: bool = False
+) -> dict:
+    access_token_expires_longterm = timedelta(days=365)
    access_token = create_token(
-        data={"sub": username},
+        data={"sub": str(user_id)},
+        expires_delta=access_token_expires_longterm,
+    )
+
+    # Update: last_login_at
+    if update_last_login:
+        update_user_last_login_at(user_id, db)
+
+    return {
+        "access_token": access_token,
+        "refresh_token": None,
+        "token_type": "bearer",
+    }
+
+
+def create_user_tokens(
+    user_id: UUID, db: Session = Depends(get_session), update_last_login: bool = False
+) -> dict:
+    settings_manager = get_settings_manager()
+
+    access_token_expires = timedelta(
+        minutes=settings_manager.settings.ACCESS_TOKEN_EXPIRE_MINUTES
+    )
+    access_token = create_token(
+        data={"sub": str(user_id)},
        expires_delta=access_token_expires,
    )

-    refresh_token_expires = timedelta(minutes=REFRESH_TOKEN_EXPIRE_MINUTES)
+    refresh_token_expires = timedelta(
+        minutes=settings_manager.settings.REFRESH_TOKEN_EXPIRE_MINUTES
+    )
    refresh_token = create_token(
-        data={"sub": username, "type": "rf"},
+        data={"sub": str(user_id), "type": "rf"},
        expires_delta=refresh_token_expires,
    )

+    # Update: last_login_at
+    if update_last_login:
+        update_user_last_login_at(user_id, db)
+
    return {
        "access_token": access_token,
        "refresh_token": refresh_token,
@ -58,18 +135,24 @@ def create_user_tokens(username: str) -> dict:
    }


-def create_refresh_token(refresh_token: str):
+def create_refresh_token(refresh_token: str, db: Session = Depends(get_session)):
+    settings_manager = get_settings_manager()
+
    try:
-        payload = jwt.decode(refresh_token, SECRET_KEY, algorithms=[ALGORITHM])
-        username: str = payload.get("sub")  # type: ignore
+        payload = jwt.decode(
+            refresh_token,
+            settings_manager.settings.SECRET_KEY,
+            algorithms=[settings_manager.settings.ALGORITHM],
+        )
+        user_id: UUID = payload.get("sub")  # type: ignore
        token_type: str = payload.get("type")  # type: ignore

-        if username is None or token_type is None:
+        if user_id is None or token_type is None:
            raise HTTPException(
                status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid refresh token"
            )

-        return create_user_tokens(username)
+        return create_user_tokens(user_id, db)

    except JWTError as e:
        raise HTTPException(
@ -78,41 +161,17 @@ def create_refresh_token(refresh_token: str):
        ) from e


-def authenticate_user(db: Session, username: str, password: str):
-    if user := get_user_by_username(db, username):
-        return user if verify_password(password, user.password) else False
-    else:
-        return False
+def authenticate_user(
+    username: str, password: str, db: Session = Depends(get_session)
+) -> User | None:
+    user = get_user_by_username(db, username)

+    if not user:
+        return None

-async def get_current_user(
-    token: Annotated[str, Depends(oauth2_scheme)], db: Session = Depends(get_session)
-) -> User:
-    credentials_exception = HTTPException(
-        status_code=status.HTTP_401_UNAUTHORIZED,
-        detail="Could not validate credentials",
-        headers={"WWW-Authenticate": "Bearer"},
-    )
-    try:
-        payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
-        username: str = payload.get("sub")  # type: ignore
-        token_type: str = payload.get("type")  # type: ignore
-
-        if username is None or token_type:
-            raise credentials_exception
-        token_data = TokenData(username=username)
-    except JWTError as e:
-        raise credentials_exception from e
-
-    user = get_user_by_username(db, token_data.username)  # type: ignore
-    if user is None:
-        raise credentials_exception
-    return user
-
-
-async def get_current_active_user(
-    current_user: Annotated[User, Depends(get_current_user)]
-):
-    if current_user.is_disabled:
+    if not user.is_active:
+        if not user.last_login_at:
+            raise HTTPException(status_code=400, detail="Waiting for approval")
        raise HTTPException(status_code=400, detail="Inactive user")
-    return current_user
+
+    return user if verify_password(password, user.password) else None
--- a/src/backend/langflow/components/chains/prompt_runner.py
+++ b/src/backend/langflow/components/chains/prompt_runner.py
--- a/src/backend/langflow/components/toolkits/Metaphor.py
+++ b/src/backend/langflow/components/toolkits/Metaphor.py
@ -0,0 +1,56 @@
+from typing import List, Union
+from langflow import CustomComponent
+
+from metaphor_python import Metaphor  # type: ignore
+from langchain.tools import Tool
+from langchain.agents import tool
+from langchain.agents.agent_toolkits.base import BaseToolkit
+
+
+class MetaphorToolkit(CustomComponent):
+    display_name: str = "Metaphor"
+    description: str = "Metaphor Toolkit"
+    documentation = (
+        "https://python.langchain.com/docs/integrations/tools/metaphor_search"
+    )
+    beta = True
+    # api key should be password = True
+    field_config = {
+        "metaphor_api_key": {"display_name": "Metaphor API Key", "password": True},
+        "code": {"advanced": True},
+    }
+
+    def build(
+        self,
+        metaphor_api_key: str,
+        use_autoprompt: bool = True,
+        search_num_results: int = 5,
+        similar_num_results: int = 5,
+    ) -> Union[Tool, BaseToolkit]:
+        # If documents, then we need to create a Vectara instance using .from_documents
+        client = Metaphor(api_key=metaphor_api_key)
+
+        @tool
+        def search(query: str):
+            """Call search engine with a query."""
+            return client.search(
+                query, use_autoprompt=use_autoprompt, num_results=search_num_results
+            )
+
+        @tool
+        def get_contents(ids: List[str]):
+            """Get contents of a webpage.
+
+            The ids passed in should be a list of ids as fetched from `search`.
+            """
+            return client.get_contents(ids)
+
+        @tool
+        def find_similar(url: str):
+            """Get search results similar to a given URL.
+
+            The url passed in should be a URL returned from `search`
+            """
+            return client.find_similar(url, num_results=similar_num_results)
+
+        return [search, get_contents, find_similar]  # type: ignore
--- a/src/backend/langflow/components/toolkits/init.py
+++ b/src/backend/langflow/components/toolkits/init.py
--- a/src/backend/langflow/components/vectorstores/Vectara.py
+++ b/src/backend/langflow/components/vectorstores/Vectara.py
@ -0,0 +1,50 @@
+from typing import Optional, Union
+from langflow import CustomComponent
+
+from langchain.vectorstores import Vectara
+from langchain.schema import Document
+from langchain.vectorstores.base import VectorStore
+from langchain.schema import BaseRetriever
+from langchain.embeddings.base import Embeddings
+
+
+class VectaraComponent(CustomComponent):
+    display_name: str = "Vectara"
+    description: str = "Implementation of Vector Store using Vectara"
+    documentation = (
+        "https://python.langchain.com/docs/integrations/vectorstores/vectara"
+    )
+    beta = True
+    # api key should be password = True
+    field_config = {
+        "vectara_customer_id": {"display_name": "Vectara Customer ID"},
+        "vectara_corpus_id": {"display_name": "Vectara Corpus ID"},
+        "vectara_api_key": {"display_name": "Vectara API Key", "password": True},
+        "code": {"show": False},
+        "documents": {"display_name": "Documents"},
+        "embedding": {"display_name": "Embedding"},
+    }
+
+    def build(
+        self,
+        vectara_customer_id: str,
+        vectara_corpus_id: str,
+        vectara_api_key: str,
+        embedding: Optional[Embeddings] = None,
+        documents: Optional[Document] = None,
+    ) -> Union[VectorStore, BaseRetriever]:
+        # If documents, then we need to create a Vectara instance using .from_documents
+        if documents is not None and embedding is not None:
+            return Vectara.from_documents(
+                documents=documents,  # type: ignore
+                vectara_customer_id=vectara_customer_id,
+                vectara_corpus_id=vectara_corpus_id,
+                vectara_api_key=vectara_api_key,
+                embedding=embedding,
+            )
+
+        return Vectara(
+            vectara_customer_id=vectara_customer_id,
+            vectara_corpus_id=vectara_corpus_id,
+            vectara_api_key=vectara_api_key,
+        )
--- a/src/backend/langflow/components/vectorstores/init.py
+++ b/src/backend/langflow/components/vectorstores/init.py
--- a/src/backend/langflow/config.yaml
+++ b/src/backend/langflow/config.yaml
@ -104,6 +104,8 @@ embeddings:
    documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/sentence_transformers"
  CohereEmbeddings:
    documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/cohere"
+  VertexAIEmbeddings:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/google_vertex_ai_palm"
 llms:
  OpenAI:
    documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai"
@ -127,8 +129,8 @@ llms:
  # There's a bug in this component deactivating until we get it sorted: _language_models.py", line 804, in send_message
  #     is_blocked=safety_attributes.get("blocked", False),
  # AttributeError: 'list' object has no attribute 'get'
-  # ChatVertexAI:
-  #   documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/integrations/google_vertex_ai_palm"
+  ChatVertexAI:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/integrations/google_vertex_ai_palm"
  ###
 memories:
  # https://github.com/supabase-community/supabase-py/issues/482
--- a/src/backend/langflow/database/models/token.py
+++ b/src/backend/langflow/database/models/token.py
@ -5,7 +5,3 @@ class Token(BaseModel):
    access_token: str
    refresh_token: str
    token_type: str
-
-
-class TokenData(BaseModel):
-    username: str | None = None
--- a/src/backend/langflow/database/models/user.py
+++ b/src/backend/langflow/database/models/user.py
@ -1,41 +1,52 @@
-from datetime import datetime
-from sqlalchemy.orm import Session
-
-from langflow.services.database.models.base import SQLModelSerializable, SQLModel
 from sqlmodel import Field
 from uuid import UUID, uuid4
+from pydantic import BaseModel
+from typing import Optional, List
+from sqlalchemy.orm import Session
+from datetime import timezone, datetime
+from sqlalchemy.exc import IntegrityError
+from fastapi import HTTPException, Depends
+
+from langflow.services.utils import get_session
+from langflow.services.database.models.base import SQLModelSerializable, SQLModel


 class User(SQLModelSerializable, table=True):
    id: UUID = Field(default_factory=uuid4, primary_key=True, unique=True)
    username: str = Field(index=True, unique=True)
    password: str = Field()
-    is_disabled: bool = Field(default=False)
+    is_active: bool = Field(default=False)
    is_superuser: bool = Field(default=False)
    create_at: datetime = Field(default_factory=datetime.utcnow)
    updated_at: datetime = Field(default_factory=datetime.utcnow)
+    last_login_at: Optional[datetime] = Field()


 class UserAddModel(SQLModel):
    username: str = Field()
    password: str = Field()
-    is_disabled: bool = Field(default=False)
-    is_superuser: bool = Field(default=False)


 class UserListModel(SQLModel):
    id: UUID = Field(default_factory=uuid4)
    username: str = Field()
-    is_disabled: bool = Field()
+    is_active: bool = Field()
    is_superuser: bool = Field()
    create_at: datetime = Field()
    updated_at: datetime = Field()
+    last_login_at: Optional[datetime] = Field()


 class UserPatchModel(SQLModel):
-    username: str = Field()
-    is_disabled: bool = Field()
-    is_superuser: bool = Field()
+    username: Optional[str] = Field()
+    is_active: Optional[bool] = Field()
+    is_superuser: Optional[bool] = Field()
+    last_login_at: Optional[datetime] = Field()
+
+
+class UsersResponse(BaseModel):
+    total_count: int
+    users: List[UserListModel]


 def get_user_by_username(db: Session, username: str) -> User:
@ -46,3 +57,38 @@ def get_user_by_username(db: Session, username: str) -> User:
 def get_user_by_id(db: Session, id: UUID) -> User:
    db_user = db.query(User).filter(User.id == id).first()
    return User.from_orm(db_user) if db_user else None  # type: ignore
+
+
+def update_user(
+    user_id: UUID, user: UserPatchModel, db: Session = Depends(get_session)
+) -> User:
+    user_db = get_user_by_username(db, user.username)  # type: ignore
+    if user_db and user_db.id != user_id:
+        raise HTTPException(status_code=409, detail="Username already exists")
+
+    user_db = get_user_by_id(db, user_id)
+    if not user_db:
+        raise HTTPException(status_code=404, detail="User not found")
+
+    try:
+        user_data = user.dict(exclude_unset=True)
+        for key, value in user_data.items():
+            setattr(user_db, key, value)
+
+        user_db.updated_at = datetime.now(timezone.utc)
+        user_db = db.merge(user_db)
+        db.commit()
+        if db.identity_key(instance=user_db) is not None:
+            db.refresh(user_db)
+
+    except IntegrityError as e:
+        db.rollback()
+        raise HTTPException(status_code=400, detail=str(e)) from e
+
+    return user_db
+
+
+def update_user_last_login_at(user_id: UUID, db: Session = Depends(get_session)):
+    user_data = UserPatchModel(last_login_at=datetime.now(timezone.utc))  # type: ignore
+
+    return update_user(user_id, user_data, db)
--- a/src/backend/langflow/interface/custom/component.py
+++ b/src/backend/langflow/interface/custom/component.py
@ -66,6 +66,9 @@ class Component(BaseModel):
                elif "beta" in item_name:
                    template_config["beta"] = ast.literal_eval(item_value)

+                elif "documentation" in item_name:
+                    template_config["documentation"] = ast.literal_eval(item_value)
+
        return template_config

    def build(self, *args: Any, **kwargs: Any) -> Any:
--- a/src/backend/langflow/interface/custom/custom_component.py
+++ b/src/backend/langflow/interface/custom/custom_component.py
@ -50,7 +50,9 @@ class CustomComponent(Component, extra=Extra.allow):
        reader = DirectoryReader("", False)

        for type_hint in TYPE_HINT_LIST:
-            if reader.is_type_hint_used_but_not_imported(type_hint, code):
+            if reader._is_type_hint_used_in_args(
+                "Optional", code
+            ) and not reader._is_type_hint_imported("Optional", code):
                error_detail = {
                    "error": "Type hint Error",
                    "traceback": f"Type hint '{type_hint}' is used but not imported in the code.",
@ -93,9 +95,9 @@ class CustomComponent(Component, extra=Extra.allow):
        return build_method["args"]

    @property
-    def get_function_entrypoint_return_type(self) -> str:
+    def get_function_entrypoint_return_type(self) -> List[str]:
        if not self.code:
-            return ""
+            return []
        tree = self.get_code_tree(self.code)

        component_classes = [
@ -104,7 +106,7 @@ class CustomComponent(Component, extra=Extra.allow):
            if self.code_class_base_inheritance in cls["bases"]
        ]
        if not component_classes:
-            return ""
+            return []

        # Assume the first Component class is the one we're interested in
        component_class = component_classes[0]
@ -115,11 +117,21 @@ class CustomComponent(Component, extra=Extra.allow):
        ]

        if not build_methods:
-            return ""
+            return []

        build_method = build_methods[0]
+        return_type = build_method["return_type"]
+        if not return_type:
+            return []
+        # If the return type is not a Union, then we just return it as a list
+        if "Union" not in return_type:
+            return [return_type] if return_type in self.return_type_valid_list else []

-        return build_method["return_type"]
+        # If the return type is a Union, then we need to parse it
+        return_type = return_type.replace("Union", "").replace("[", "").replace("]", "")
+        return_type = return_type.split(",")
+        return_type = [item.strip() for item in return_type]
+        return [item for item in return_type if item in self.return_type_valid_list]

    @property
    def get_main_class_name(self):
--- a/src/backend/langflow/interface/custom/directory_reader.py
+++ b/src/backend/langflow/interface/custom/directory_reader.py
@ -152,15 +152,19 @@ class DirectoryReader:
        Check if a specific type hint is used in the
        function definitions within the given code.
        """
-        module = ast.parse(code)
+        try:
+            module = ast.parse(code)

-        for node in ast.walk(module):
-            if isinstance(node, ast.FunctionDef):
-                for arg in node.args.args:
-                    if self._is_type_hint_in_arg_annotation(
-                        arg.annotation, type_hint_name
-                    ):
-                        return True
+            for node in ast.walk(module):
+                if isinstance(node, ast.FunctionDef):
+                    for arg in node.args.args:
+                        if self._is_type_hint_in_arg_annotation(
+                            arg.annotation, type_hint_name
+                        ):
+                            return True
+        except SyntaxError:
+            # Returns False if the code is not valid Python
+            return False
        return False

    def _is_type_hint_in_arg_annotation(self, annotation, type_hint_name: str) -> bool:
@ -204,8 +208,13 @@ class DirectoryReader:
            return False, "Syntax error"
        elif not self.validate_build(file_content):
            return False, "Missing build function"
-        elif self.is_type_hint_used_but_not_imported("Optional", file_content):
-            return False, "Type hint 'Optional' is used but not imported in the code."
+        elif self._is_type_hint_used_in_args(
+            "Optional", file_content
+        ) and not self._is_type_hint_imported("Optional", file_content):
+            return (
+                False,
+                "Type hint 'Optional' is used but not imported in the code.",
+            )
        else:
            if self.compress_code_field:
                file_content = str(StringCompressor(file_content).compress_string())
--- a/src/backend/langflow/interface/initialize/loading.py
+++ b/src/backend/langflow/interface/initialize/loading.py
@ -88,7 +88,7 @@ def instantiate_based_on_type(class_object, base_type, node_type, params):
    elif base_type == "toolkits":
        return instantiate_toolkit(node_type, class_object, params)
    elif base_type == "embeddings":
-        return instantiate_embedding(class_object, params)
+        return instantiate_embedding(node_type, class_object, params)
    elif base_type == "vectorstores":
        return instantiate_vectorstore(class_object, params)
    elif base_type == "documentloaders":
@ -116,9 +116,12 @@ def instantiate_based_on_type(class_object, base_type, node_type, params):


 def instantiate_custom_component(node_type, class_object, params):
-    class_object = get_function_custom(params.pop("code"))
+    # we need to make a copy of the params because we will be
+    # modifying it
+    params_copy = params.copy()
+    class_object = get_function_custom(params_copy.pop("code"))
    custom_component = class_object()
-    built_object = custom_component.build(**params)
+    built_object = custom_component.build(**params_copy)
    return built_object, {"repr": custom_component.custom_repr()}


@ -144,7 +147,7 @@ def instantiate_llm(node_type, class_object, params: Dict):
    # This is a workaround so JinaChat works until streaming is implemented
    # if "openai_api_base" in params and "jina" in params["openai_api_base"]:
    # False if condition is True
-    if node_type == "VertexAI":
+    if "VertexAI" in node_type:
        return initialize_vertexai(class_object=class_object, params=params)
    # max_tokens sometimes is a string and should be an int
    if "max_tokens" in params:
@ -258,9 +261,13 @@ def instantiate_toolkit(node_type, class_object: Type[BaseToolkit], params: Dict
    return loaded_toolkit


-def instantiate_embedding(class_object, params: Dict):
+def instantiate_embedding(node_type, class_object, params: Dict):
    params.pop("model", None)
    params.pop("headers", None)
+
+    if "VertexAI" in node_type:
+        return initialize_vertexai(class_object=class_object, params=params)
+
    try:
        return class_object(**params)
    except ValidationError:
--- a/src/backend/langflow/interface/initialize/vector_store.py
+++ b/src/backend/langflow/interface/initialize/vector_store.py
@ -130,8 +130,8 @@ def initialize_pinecone(class_object: Type[Pinecone], params: dict):

    import pinecone  # type: ignore

-    pinecone_api_key = params.get("pinecone_api_key")
-    pinecone_env = params.get("pinecone_env")
+    pinecone_api_key = params.pop("pinecone_api_key")
+    pinecone_env = params.pop("pinecone_env")

    if pinecone_api_key is None or pinecone_env is None:
        if os.getenv("PINECONE_API_KEY") is not None:
--- a/src/backend/langflow/interface/types.py
+++ b/src/backend/langflow/interface/types.py
@ -1,6 +1,6 @@
 import ast
 import contextlib
-from typing import Any
+from typing import Any, List
 from langflow.api.utils import merge_nested_dicts_with_renaming
 from langflow.interface.agents.base import agent_creator
 from langflow.interface.chains.base import chain_creator
@ -199,6 +199,9 @@ def update_attributes(frontend_node, template_config):
    if "beta" in template_config:
        frontend_node["beta"] = template_config["beta"]

+    if "documentation" in template_config:
+        frontend_node["documentation"] = template_config["documentation"]
+

 def build_field_config(custom_component: CustomComponent):
    """Build the field configuration for a custom component"""
@ -257,26 +260,27 @@ def get_field_properties(extra_field):
    return field_name, field_type, field_value, field_required


-def add_base_classes(frontend_node, return_type):
+def add_base_classes(frontend_node, return_types: List[str]):
    """Add base classes to the frontend node"""
-    if return_type not in CUSTOM_COMPONENT_SUPPORTED_TYPES or return_type is None:
-        raise HTTPException(
-            status_code=400,
-            detail={
-                "error": (
-                    "Invalid return type should be one of: "
-                    f"{list(CUSTOM_COMPONENT_SUPPORTED_TYPES.keys())}"
-                ),
-                "traceback": traceback.format_exc(),
-            },
-        )
+    for return_type in return_types:
+        if return_type not in CUSTOM_COMPONENT_SUPPORTED_TYPES or return_type is None:
+            raise HTTPException(
+                status_code=400,
+                detail={
+                    "error": (
+                        "Invalid return type should be one of: "
+                        f"{list(CUSTOM_COMPONENT_SUPPORTED_TYPES.keys())}"
+                    ),
+                    "traceback": traceback.format_exc(),
+                },
+            )

-    return_type_instance = CUSTOM_COMPONENT_SUPPORTED_TYPES.get(return_type)
-    base_classes = get_base_classes(return_type_instance)
+        return_type_instance = CUSTOM_COMPONENT_SUPPORTED_TYPES.get(return_type)
+        base_classes = get_base_classes(return_type_instance)

-    for base_class in base_classes:
-        if base_class not in CLASSES_TO_REMOVE:
-            frontend_node.get("base_classes").append(base_class)
+        for base_class in base_classes:
+            if base_class not in CLASSES_TO_REMOVE:
+                frontend_node.get("base_classes").append(base_class)


 def build_langchain_template_custom_component(custom_component: CustomComponent):
--- a/src/backend/langflow/routers/login.py
+++ b/src/backend/langflow/routers/login.py
@ -1,3 +1,4 @@
+from uuid import UUID
 from sqlalchemy.orm import Session
 from fastapi import APIRouter, Depends, HTTPException, status
 from fastapi.security import OAuth2PasswordRequestForm
@ -8,17 +9,22 @@ from langflow.auth.auth import (
    authenticate_user,
    create_user_tokens,
    create_refresh_token,
+    create_user_longterm_token,
 )

+from langflow.services.utils import get_settings_manager
+
 router = APIRouter()


@router.post("/login", response_model=Token)
 async def login_to_get_access_token(
-    form_data: OAuth2PasswordRequestForm = Depends(), db: Session = Depends(get_session)
+    form_data: OAuth2PasswordRequestForm = Depends(),
+    db: Session = Depends(get_session),
+    # _: Session = Depends(get_current_active_user)
 ):
-    if user := authenticate_user(db, form_data.username, form_data.password):
-        return create_user_tokens(user.username)
+    if user := authenticate_user(form_data.username, form_data.password, db):
+        return create_user_tokens(user_id=user.id, db=db, update_last_login=True)
    else:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
@ -27,6 +33,23 @@ async def login_to_get_access_token(
        )


+@router.get("/auto_login")
+async def auto_login(db: Session = Depends(get_session)):
+    settings_manager = get_settings_manager()
+
+    if settings_manager.settings.AUTO_LOGIN:
+        user_id = UUID("3fa85f64-5717-4562-b3fc-2c963f66afa6")
+        return create_user_longterm_token(user_id, db)
+
+    raise HTTPException(
+        status_code=status.HTTP_400_BAD_REQUEST,
+        detail={
+            "message": "Auto login is disabled. Please enable it in the settings",
+            "auto_login": False,
+        },
+    )
+
+
@router.post("/refresh")
 async def refresh_token(token: str):
    if token:
--- a/src/backend/langflow/routers/users.py
+++ b/src/backend/langflow/routers/users.py
@ -1,10 +1,10 @@
-from typing import List
 from uuid import UUID
-from datetime import timezone, datetime

+from sqlalchemy import func
 from sqlalchemy.exc import IntegrityError
-from fastapi import APIRouter, Depends, HTTPException
+
 from sqlmodel import Session, select
+from fastapi import APIRouter, Depends, HTTPException

 from langflow.services.utils import get_session
 from langflow.auth.auth import get_current_active_user, get_password_hash
@ -13,8 +13,8 @@ from langflow.database.models.user import (
    UserAddModel,
    UserListModel,
    UserPatchModel,
-    get_user_by_id,
-    get_user_by_username,
+    UsersResponse,
+    update_user,
 )

 router = APIRouter(tags=["Login"])
@ -23,7 +23,6 @@ router = APIRouter(tags=["Login"])
@router.post("/user", response_model=UserListModel)
 def add_user(
    user: UserAddModel,
-    _: Session = Depends(get_current_active_user),
    db: Session = Depends(get_session),
 ) -> User:
    """
@ -32,6 +31,7 @@ def add_user(
    new_user = User(**user.dict())
    try:
        new_user.password = get_password_hash(user.password)
+
        db.add(new_user)
        db.commit()
        db.refresh(new_user)
@ -50,24 +50,30 @@ def read_current_user(current_user: User = Depends(get_current_active_user)) ->
    return current_user


-@router.get("/users", response_model=List[UserListModel])
+@router.get("/users", response_model=UsersResponse)
 def read_all_users(
    skip: int = 0,
    limit: int = 10,
    _: Session = Depends(get_current_active_user),
    db: Session = Depends(get_session),
-) -> List[UserListModel]:
+) -> UsersResponse:
    """
    Retrieve a list of users from the database with pagination.
    """
    query = select(User).offset(skip).limit(limit)
    users = db.execute(query).fetchall()

-    return [UserListModel(**dict(user.User)) for user in users]
+    count_query = select(func.count()).select_from(User)  # type: ignore
+    total_count = db.execute(count_query).scalar()
+
+    return UsersResponse(
+        total_count=total_count,  # type: ignore
+        users=[UserListModel(**dict(user.User)) for user in users],
+    )


@router.patch("/user/{user_id}", response_model=UserListModel)
-def update_user(
+def patch_user(
    user_id: UUID,
    user: UserPatchModel,
    _: Session = Depends(get_current_active_user),
@ -76,29 +82,7 @@ def update_user(
    """
    Update an existing user's data.
    """
-    user_db = get_user_by_username(db, user.username)
-    if user_db and user_db.id != user_id:
-        raise HTTPException(status_code=409, detail="Username already exists")
-
-    user_db = get_user_by_id(db, user_id)
-    if not user_db:
-        raise HTTPException(status_code=404, detail="User not found")
-
-    try:
-        user_data = user.dict(exclude_unset=True)
-        for key, value in user_data.items():
-            setattr(user_db, key, value)
-
-        user_db.updated_at = datetime.now(timezone.utc)
-        user_db = db.merge(user_db)
-        db.commit()
-        if db.identity_key(instance=user_db) is not None:
-            db.refresh(user_db)
-    except IntegrityError as e:
-        db.rollback()
-        raise HTTPException(status_code=400, detail=str(e)) from e
-
-    return user_db
+    return update_user(user_id, user, db)


@router.delete("/user/{user_id}")
@ -129,7 +113,13 @@ def add_super_user_for_testing_purposes_delete_me_before_merge_into_dev(
    Add a superuser for testing purposes.
    (This should be removed in production)
    """
-    new_user = User(username="superuser", password="12345", is_superuser=True)
+    new_user = User(
+        username="superuser",
+        password="12345",
+        is_active=True,
+        is_superuser=True,
+        last_login_at=None,
+    )

    try:
        new_user.password = get_password_hash(new_user.password)
--- a/src/backend/langflow/services/settings/base.py
+++ b/src/backend/langflow/services/settings/base.py
@ -1,6 +1,7 @@
 import contextlib
 import json
 import os
+import secrets
 from typing import Optional, List
 from pathlib import Path

@ -35,6 +36,15 @@ class Settings(BaseSettings):
    REMOVE_API_KEYS: bool = False
    COMPONENTS_PATH: List[str] = []

+    # Login settings
+    SECRET_KEY: str = secrets.token_hex(32)
+    ALGORITHM: str = "HS256"
+    ACCESS_TOKEN_EXPIRE_MINUTES: int = 60
+    REFRESH_TOKEN_EXPIRE_MINUTES: int = 70
+    # If AUTO_LOGIN = True
+    # > The application does not request login and logs in automatically as a super user.
+    AUTO_LOGIN: bool = True
+
    @validator("DATABASE_URL", pre=True)
    def set_database_url(cls, value):
        if not value:
--- a/src/backend/langflow/services/settings/settings.py
+++ b/src/backend/langflow/services/settings/settings.py
@ -1,171 +0,0 @@
-import contextlib
-import json
-import os
-from typing import Optional, List
-from pathlib import Path
-
-import yaml
-from pydantic import BaseSettings, root_validator, validator
-from langflow.utils.logger import logger
-
-BASE_COMPONENTS_PATH = str(Path(__file__).parent / "components")
-
-
-class Settings(BaseSettings):
-    CHAINS: dict = {}
-    AGENTS: dict = {}
-    PROMPTS: dict = {}
-    LLMS: dict = {}
-    TOOLS: dict = {}
-    MEMORIES: dict = {}
-    EMBEDDINGS: dict = {}
-    VECTORSTORES: dict = {}
-    DOCUMENTLOADERS: dict = {}
-    WRAPPERS: dict = {}
-    RETRIEVERS: dict = {}
-    TOOLKITS: dict = {}
-    TEXTSPLITTERS: dict = {}
-    UTILITIES: dict = {}
-    OUTPUT_PARSERS: dict = {}
-    CUSTOM_COMPONENTS: dict = {}
-
-    DEV: bool = False
-    DATABASE_URL: Optional[str] = None
-    CACHE: str = "InMemoryCache"
-    REMOVE_API_KEYS: bool = False
-    COMPONENTS_PATH: List[str] = []
-
-    @validator("DATABASE_URL", pre=True)
-    def set_database_url(cls, value):
-        if not value:
-            logger.debug(
-                "No database_url provided, trying LANGFLOW_DATABASE_URL env variable"
-            )
-            if langflow_database_url := os.getenv("LANGFLOW_DATABASE_URL"):
-                value = langflow_database_url
-                logger.debug("Using LANGFLOW_DATABASE_URL env variable.")
-            else:
-                logger.debug("No DATABASE_URL env variable, using sqlite database")
-                value = "sqlite:///./langflow.db"
-
-        return value
-
-    @validator("COMPONENTS_PATH", pre=True)
-    def set_components_path(cls, value):
-        if os.getenv("LANGFLOW_COMPONENTS_PATH"):
-            logger.debug("Adding LANGFLOW_COMPONENTS_PATH to components_path")
-            langflow_component_path = os.getenv("LANGFLOW_COMPONENTS_PATH")
-            if (
-                Path(langflow_component_path).exists()
-                and langflow_component_path not in value
-            ):
-                if isinstance(langflow_component_path, list):
-                    for path in langflow_component_path:
-                        if path not in value:
-                            value.append(path)
-                    logger.debug(
-                        f"Extending {langflow_component_path} to components_path"
-                    )
-                elif langflow_component_path not in value:
-                    value.append(langflow_component_path)
-                    logger.debug(
-                        f"Appending {langflow_component_path} to components_path"
-                    )
-
-        if not value:
-            value = [BASE_COMPONENTS_PATH]
-            logger.debug("Setting default components path to components_path")
-        elif BASE_COMPONENTS_PATH not in value:
-            value.append(BASE_COMPONENTS_PATH)
-            logger.debug("Adding default components path to components_path")
-
-        logger.debug(f"Components path: {value}")
-        return value
-
-    class Config:
-        validate_assignment = True
-        extra = "ignore"
-        env_prefix = "LANGFLOW_"
-
-    @root_validator(allow_reuse=True)
-    def validate_lists(cls, values):
-        for key, value in values.items():
-            if key != "dev" and not value:
-                values[key] = []
-        return values
-
-    def update_from_yaml(self, file_path: str, dev: bool = False):
-        new_settings = load_settings_from_yaml(file_path)
-        self.CHAINS = new_settings.CHAINS or {}
-        self.AGENTS = new_settings.AGENTS or {}
-        self.PROMPTS = new_settings.PROMPTS or {}
-        self.LLMS = new_settings.LLMS or {}
-        self.TOOLS = new_settings.TOOLS or {}
-        self.MEMORIES = new_settings.MEMORIES or {}
-        self.WRAPPERS = new_settings.WRAPPERS or {}
-        self.TOOLKITS = new_settings.TOOLKITS or {}
-        self.TEXTSPLITTERS = new_settings.TEXTSPLITTERS or {}
-        self.UTILITIES = new_settings.UTILITIES or {}
-        self.EMBEDDINGS = new_settings.EMBEDDINGS or {}
-        self.VECTORSTORES = new_settings.VECTORSTORES or {}
-        self.DOCUMENTLOADERS = new_settings.DOCUMENTLOADERS or {}
-        self.RETRIEVERS = new_settings.RETRIEVERS or {}
-        self.OUTPUT_PARSERS = new_settings.OUTPUT_PARSERS or {}
-        self.CUSTOM_COMPONENTS = new_settings.CUSTOM_COMPONENTS or {}
-        self.COMPONENTS_PATH = new_settings.COMPONENTS_PATH or []
-        self.DEV = dev
-
-    def update_settings(self, **kwargs):
-        logger.debug("Updating settings")
-        for key, value in kwargs.items():
-            # value may contain sensitive information, so we don't want to log it
-            if not hasattr(self, key):
-                logger.debug(f"Key {key} not found in settings")
-                continue
-            logger.debug(f"Updating {key}")
-            if isinstance(getattr(self, key), list):
-                # value might be a '[something]' string
-                with contextlib.suppress(json.decoder.JSONDecodeError):
-                    value = json.loads(str(value))
-                if isinstance(value, list):
-                    for item in value:
-                        if item not in getattr(self, key):
-                            getattr(self, key).append(item)
-                    logger.debug(f"Extended {key}")
-                else:
-                    getattr(self, key).append(value)
-                    logger.debug(f"Appended {key}")
-
-            else:
-                setattr(self, key, value)
-                logger.debug(f"Updated {key}")
-            logger.debug(f"{key}: {getattr(self, key)}")
-
-
-def save_settings_to_yaml(settings: Settings, file_path: str):
-    with open(file_path, "w") as f:
-        settings_dict = settings.dict()
-        yaml.dump(settings_dict, f)
-
-
-def load_settings_from_yaml(file_path: str) -> Settings:
-    # Check if a string is a valid path or a file name
-    if "/" not in file_path:
-        # Get current path
-        current_path = os.path.dirname(os.path.abspath(__file__))
-
-        file_path = os.path.join(current_path, file_path)
-
-    with open(file_path, "r") as f:
-        settings_dict = yaml.safe_load(f)
-        settings_dict = {k.upper(): v for k, v in settings_dict.items()}
-
-        for key in settings_dict:
-            if key not in Settings.__fields__.keys():
-                raise KeyError(f"Key {key} not found in settings")
-            logger.debug(f"Loading {len(settings_dict[key])} {key} from {file_path}")
-
-    return Settings(**settings_dict)
-
-
-settings = load_settings_from_yaml("config.yaml")
--- a/src/backend/langflow/template/frontend_node/embeddings.py
+++ b/src/backend/langflow/template/frontend_node/embeddings.py
@ -5,6 +5,47 @@ from langflow.template.frontend_node.base import FrontendNode


 class EmbeddingFrontendNode(FrontendNode):
+    def add_extra_fields(self) -> None:
+        if "VertexAI" in self.template.type_name:
+            # Add credentials field which should of type file.
+            self.template.add_field(
+                TemplateField(
+                    field_type="file",
+                    required=False,
+                    show=True,
+                    name="credentials",
+                    value="",
+                    suffixes=[".json"],
+                    file_types=["json"],
+                )
+            )
+
+    @staticmethod
+    def format_vertex_field(field: TemplateField, name: str):
+        if "VertexAI" in name:
+            advanced_fields = [
+                "verbose",
+                "top_p",
+                "top_k",
+                "max_output_tokens",
+            ]
+            if field.name in advanced_fields:
+                field.advanced = True
+            show_fields = [
+                "verbose",
+                "project",
+                "location",
+                "credentials",
+                "max_output_tokens",
+                "model_name",
+                "temperature",
+                "top_p",
+                "top_k",
+            ]
+
+            if field.name in show_fields:
+                field.show = True
+
    @staticmethod
    def format_jina_fields(field: TemplateField):
        if "jina" in field.name:
@ -41,10 +82,36 @@ class EmbeddingFrontendNode(FrontendNode):
    @staticmethod
    def format_field(field: TemplateField, name: Optional[str] = None) -> None:
        FrontendNode.format_field(field, name)
+        if name and "vertex" in name.lower():
+            EmbeddingFrontendNode.format_vertex_field(field, name)
        field.advanced = not field.required
        field.show = True
        if field.name == "headers":
            field.show = False
+        if field.name == "model_kwargs":
+            field.field_type = "code"
+            field.advanced = True
+            field.show = True
+        elif field.name in [
+            "model_name",
+            "temperature",
+            "model_file",
+            "model_type",
+            "deployment_name",
+            "credentials",
+        ]:
+            field.advanced = False
+            field.show = True
+        if field.name == "credentials":
+            field.field_type = "file"
+        if name == "VertexAI" and field.name not in [
+            "callbacks",
+            "client",
+            "stop",
+            "tags",
+            "cache",
+        ]:
+            field.show = True

        # Format Jina fields
        EmbeddingFrontendNode.format_jina_fields(field)
--- a/src/frontend/src/modals/ApiModal/index.tsx
+++ b/src/frontend/src/modals/ApiModal/index.tsx
@ -22,6 +22,7 @@ import {
  getPythonApiCode,
  getPythonCode,
  getWidgetCode,
+  tabsArray,
 } from "../../utils/utils";
 import BaseModal from "../baseModal";

@ -48,39 +49,14 @@ const ApiModal = forwardRef(
    const pythonCode = getPythonCode(flow, tweak.current, tabsState);
    const widgetCode = getWidgetCode(flow, tabsState);
    const tweaksCode = buildTweaks(flow);
-    const [tabs, setTabs] = useState([
-      {
-        name: "cURL",
-        mode: "bash",
-        image: "https://curl.se/logo/curl-symbol-transparent.png",
-        language: "sh",
-        code: curl_code,
-      },
-      {
-        name: "Python API",
-        mode: "python",
-        image:
-          "https://images.squarespace-cdn.com/content/v1/5df3d8c5d2be5962e4f87890/1628015119369-OY4TV3XJJ53ECO0W2OLQ/Python+API+Training+Logo.png?format=1000w",
-        language: "py",
-        code: pythonApiCode,
-      },
-      {
-        name: "Python Code",
-        mode: "python",
-        image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
-        language: "py",
-        code: pythonCode,
-      },
-      {
-        name: "Chat Widget HTML",
-        description:
-          "Insert this code anywhere in your &lt;body&gt; tag. To use with react and other libs, check our <a class='link-color' href='https://docs.langflow.org/guidelines/widget'>documentation</a>.",
-        mode: "html",
-        image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
-        language: "py",
-        code: widgetCode,
-      },
-    ]);
+    const codesArray = [
+      curl_code,
+      pythonApiCode,
+      pythonCode,
+      widgetCode,
+      pythonCode,
+    ];
+    const [tabs, setTabs] = useState(tabsArray(codesArray, 0));

    function startState() {
      tweak.current = [];
@ -101,80 +77,9 @@ const ApiModal = forwardRef(

      if (Object.keys(tweaksCode).length > 0) {
        setActiveTab("0");
-        setTabs([
-          {
-            name: "cURL",
-            mode: "bash",
-            image: "https://curl.se/logo/curl-symbol-transparent.png",
-            language: "sh",
-            code: curl_code,
-          },
-          {
-            name: "Python API",
-            mode: "python",
-            image:
-              "https://images.squarespace-cdn.com/content/v1/5df3d8c5d2be5962e4f87890/1628015119369-OY4TV3XJJ53ECO0W2OLQ/Python+API+Training+Logo.png?format=1000w",
-            language: "py",
-            code: pythonApiCode,
-          },
-          {
-            name: "Python Code",
-            mode: "python",
-            language: "py",
-            image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
-            code: pythonCode,
-          },
-          {
-            name: "Chat Widget HTML",
-            description:
-              "Insert this code anywhere in your &lt;body&gt; tag. To use with react and other libs, check our <a class='link-color' href='https://docs.langflow.org/guidelines/widget'>documentation</a>.",
-            mode: "html",
-            image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
-            language: "py",
-            code: widgetCode,
-          },
-          {
-            name: "Tweaks",
-            mode: "python",
-            image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
-            language: "py",
-            code: pythonCode,
-          },
-        ]);
+        setTabs(tabsArray(codesArray, 1));
      } else {
-        setTabs([
-          {
-            name: "cURL",
-            mode: "bash",
-            image: "https://curl.se/logo/curl-symbol-transparent.png",
-            language: "sh",
-            code: curl_code,
-          },
-          {
-            name: "Python API",
-            mode: "python",
-            image:
-              "https://images.squarespace-cdn.com/content/v1/5df3d8c5d2be5962e4f87890/1628015119369-OY4TV3XJJ53ECO0W2OLQ/Python+API+Training+Logo.png?format=1000w",
-            language: "py",
-            code: pythonApiCode,
-          },
-          {
-            name: "Python Code",
-            mode: "python",
-            image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
-            language: "py",
-            code: pythonCode,
-          },
-          {
-            name: "Chat Widget HTML",
-            description:
-              "Insert this code anywhere in your &lt;body&gt; tag. To use with react and other libs, check our <a class='link-color' href='https://docs.langflow.org/guidelines/widget'>documentation</a>.",
-            mode: "html",
-            image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
-            language: "py",
-            code: widgetCode,
-          },
-        ]);
+        setTabs(tabsArray(codesArray, 1));
      }
    }, [flow["data"]["nodes"], open]);

--- a/src/frontend/src/modals/formModal/index.tsx
+++ b/src/frontend/src/modals/formModal/index.tsx
@ -160,7 +160,8 @@ export default function FormModal({
  }

  function getWebSocketUrl(chatId, isDevelopment = false) {
-    const isSecureProtocol = window.location.protocol === "https:";
+    const isSecureProtocol =
+      window.location.protocol === "https:" || window.location.port === "443";
    const webSocketProtocol = isSecureProtocol ? "wss" : "ws";
    const host = isDevelopment ? "localhost:7860" : window.location.host;
    const chatEndpoint = `/api/v1/chat/${chatId}`;
--- a/src/frontend/src/style/applies.css
+++ b/src/frontend/src/style/applies.css
@ -495,6 +495,12 @@
  .header-github-link-box {
    @apply inline-flex h-9 items-center justify-center rounded-md border border-input px-3 pr-0 shadow-sm;
  }
+  .header-waitlist-link-box {
+    @apply inline-flex h-9 items-center justify-center rounded-md border border-input px-2 shadow-sm text-sm  font-medium text-muted-foreground ring-offset-background disabled:pointer-events-none disabled:opacity-50 whitespace-nowrap;
+  }
+  .header-waitlist-link-box:hover {
+    @apply hover:bg-accent hover:text-accent-foreground;
+  }
  .header-github-link {
    @apply header-github-link-box text-sm  font-medium text-muted-foreground ring-offset-background disabled:pointer-events-none disabled:opacity-50;
  }
--- a/src/frontend/src/utils/styleUtils.ts
+++ b/src/frontend/src/utils/styleUtils.ts
@ -211,6 +211,7 @@ export const nodeIconsLucide = {
  SupabaseVectorStore: SupabaseIcon,
  VertexAI: VertexAIIcon,
  ChatVertexAI: VertexAIIcon,
+  VertexAIEmbeddings: VertexAIIcon,
  agents: Rocket,
  WikipediaAPIWrapper: SvgWikipedia,
  chains: Link,
--- a/src/frontend/src/utils/utils.ts
+++ b/src/frontend/src/utils/utils.ts
@ -410,3 +410,82 @@ chat_input_field: Input key that you want the chat to send the user message with
  }host_url="http://localhost:7860"
 ></langflow-chat>`;
 }
+
+export function tabsArray(codes: string[], method: number) {
+  if (!method) return;
+  if (method === 0) {
+    return [
+      {
+        name: "cURL",
+        mode: "bash",
+        image: "https://curl.se/logo/curl-symbol-transparent.png",
+        language: "sh",
+        code: codes[0],
+      },
+      {
+        name: "Python API",
+        mode: "python",
+        image:
+          "https://images.squarespace-cdn.com/content/v1/5df3d8c5d2be5962e4f87890/1628015119369-OY4TV3XJJ53ECO0W2OLQ/Python+API+Training+Logo.png?format=1000w",
+        language: "py",
+        code: codes[1],
+      },
+      {
+        name: "Python Code",
+        mode: "python",
+        image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
+        language: "py",
+        code: codes[2],
+      },
+      {
+        name: "Chat Widget HTML",
+        description:
+          "Insert this code anywhere in your &lt;body&gt; tag. To use with react and other libs, check our <a class='link-color' href='https://langflow.org/guidelines/widget'>documentation</a>.",
+        mode: "html",
+        image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
+        language: "py",
+        code: codes[3],
+      },
+    ];
+  }
+  return [
+    {
+      name: "cURL",
+      mode: "bash",
+      image: "https://curl.se/logo/curl-symbol-transparent.png",
+      language: "sh",
+      code: codes[0],
+    },
+    {
+      name: "Python API",
+      mode: "python",
+      image:
+        "https://images.squarespace-cdn.com/content/v1/5df3d8c5d2be5962e4f87890/1628015119369-OY4TV3XJJ53ECO0W2OLQ/Python+API+Training+Logo.png?format=1000w",
+      language: "py",
+      code: codes[1],
+    },
+    {
+      name: "Python Code",
+      mode: "python",
+      language: "py",
+      image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
+      code: codes[2],
+    },
+    {
+      name: "Chat Widget HTML",
+      description:
+        "Insert this code anywhere in your &lt;body&gt; tag. To use with react and other libs, check our <a class='link-color' href='https://langflow.org/guidelines/widget'>documentation</a>.",
+      mode: "html",
+      image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
+      language: "py",
+      code: codes[3],
+    },
+    {
+      name: "Tweaks",
+      mode: "python",
+      image: "https://cdn-icons-png.flaticon.com/512/5968/5968350.png",
+      language: "py",
+      code: codes[4],
+    },
+  ];
+}
--- a/src/frontend/vite.config.ts
+++ b/src/frontend/vite.config.ts
@ -6,6 +6,9 @@ const apiRoutes = ["^/api/v1/", "/health"];
 // Use environment variable to determine the target.
 const target = process.env.VITE_PROXY_TARGET || "http://127.0.0.1:7860";

+// Use environment variable to determine the UI server port
+const port = process.env.VITE_PORT || 3000;
+
 const proxyTargets = apiRoutes.reduce((proxyObj, route) => {
  proxyObj[route] = {
    target: target,
@ -22,7 +25,7 @@ export default defineConfig(() => {
    },
    plugins: [react(), svgr()],
    server: {
-      port: 3000,
+      port: port,
      proxy: {
        ...proxyTargets,
      },
--- a/tests/test_custom_component.py
+++ b/tests/test_custom_component.py
@ -241,7 +241,7 @@ def test_custom_component_get_function_entrypoint_return_type():
        code=code_default, function_entrypoint_name="build"
    )
    return_type = custom_component.get_function_entrypoint_return_type
-    assert return_type == "Document"
+    assert return_type == ["Document"]


 def test_custom_component_get_main_class_name():
@ -436,7 +436,7 @@ class MyClass(CustomComponent):

    custom_component = CustomComponent(code=my_code, function_entrypoint_name="build")
    return_type = custom_component.get_function_entrypoint_return_type
-    assert return_type is None
+    assert return_type == []


 def test_custom_component_get_main_class_name_no_main_class():
@ -469,7 +469,7 @@ def test_build_config_no_code():
    component = CustomComponent(code=None)

    assert component.get_function_entrypoint_args == ""
-    assert component.get_function_entrypoint_return_type == ""
+    assert component.get_function_entrypoint_return_type == []


@pytest.fixture
--- a/tests/test_vectorstore_template.py
+++ b/tests/test_vectorstore_template.py
@ -10,4 +10,5 @@ def test_vectorstores_settings(client: TestClient):
    assert response.status_code == 200
    json_response = response.json()
    vectorstores = json_response["vectorstores"]
-    assert set(vectorstores.keys()) == set(settings_manager.settings.VECTORSTORES)
+    settings_vecs = set(settings_manager.settings.VECTORSTORES)
+    assert all(vs in vectorstores for vs in settings_vecs)