Merge remote-tracking branch 'origin/dev' into celery

2023-08-16 19:26:06 -03:00 · 2023-08-16 19:26:06 -03:00 · 97ad9889be
commit 97ad9889be
parent c2cfcafc17 2a4668d90d
123 changed files with 7000 additions and 3272 deletions
--- a/.dockerignore
+++ b/.dockerignore
@ -0,0 +1 @@
+.venv/
--- a/9
+++ b/9
@ -32,7 +32,10 @@ lint:
 	poetry run ruff . --fix

 install_frontend:
-	cd src/frontend && npm install
+		cd src/frontend && npm install;
+
+install_frontendc:
+		cd src/frontend && npm ci;

 run_frontend:
 	cd src/frontend && npm start
@ -40,6 +43,10 @@ run_frontend:
 frontend:
 	make install_frontend
 	make run_frontend
+	
+frontendc:
+	make install_frontendc
+	make run_frontend

 install_backend:
 	poetry install --extras deploy
--- 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/package-lock.json
+++ b/package-lock.json
@ -1,5 +1,5 @@
 {
-  "name": "langflow",
+  "name": "reactFlow",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
--- a/poetry.lock
+++ b/poetry.lock
@ -146,13 +146,13 @@ files = [

 [[package]]
 name = "alembic"
-version = "1.11.2"
+version = "1.11.3"
 description = "A database migration tool for SQLAlchemy."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "alembic-1.11.2-py3-none-any.whl", hash = "sha256:7981ab0c4fad4fe1be0cf183aae17689fe394ff874fd2464adb774396faf0796"},
-    {file = "alembic-1.11.2.tar.gz", hash = "sha256:678f662130dc540dac12de0ea73de9f89caea9dbea138f60ef6263149bf84657"},
+    {file = "alembic-1.11.3-py3-none-any.whl", hash = "sha256:d6c96c2482740592777c400550a523bc7a9aada4e210cae2e733354ddae6f6f8"},
+    {file = "alembic-1.11.3.tar.gz", hash = "sha256:3db4ce81a9072e1b5aa44c2d202add24553182672a12daf21608d6f62a8f9cf9"},
 ]

 [package.dependencies]
@ -179,20 +179,20 @@ vine = ">=5.0.0"

 [[package]]
 name = "anthropic"
-version = "0.3.9"
+version = "0.3.10"
 description = "Client library for the anthropic API"
 optional = false
 python-versions = ">=3.7,<4.0"
 files = [
-    {file = "anthropic-0.3.9-py3-none-any.whl", hash = "sha256:23e8daf266c707faa0b85328ada03dcf885e62c2f236eb0159352e29b9c4e2e3"},
-    {file = "anthropic-0.3.9.tar.gz", hash = "sha256:c19b75308c07cb1ecbea03ffcdde9ba68e5ca22a22479217712396385678bde3"},
+    {file = "anthropic-0.3.10-py3-none-any.whl", hash = "sha256:95cd73168296a4f91a5899a28660991e044322cf94442d07b99901d4ca74acd6"},
+    {file = "anthropic-0.3.10.tar.gz", hash = "sha256:d1f66efc541fbff0ecfd37fd4d3690f9daaa748fc42d9ded5863a10815a5d97b"},
 ]

 [package.dependencies]
 anyio = ">=3.5.0,<4"
 distro = ">=1.7.0,<2"
 httpx = ">=0.23.0,<1"
-pydantic = ">=1.9.0,<2.0.0"
+pydantic = ">=1.9.0,<3"
 tokenizers = ">=0.13.0"
 typing-extensions = ">=4.5,<5"

@ -349,6 +349,40 @@ files = [
    {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
 ]

+[[package]]
+name = "bcrypt"
+version = "4.0.1"
+description = "Modern password hashing for your software and your servers"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "bcrypt-4.0.1-cp36-abi3-macosx_10_10_universal2.whl", hash = "sha256:b1023030aec778185a6c16cf70f359cbb6e0c289fd564a7cfa29e727a1c38f8f"},
+    {file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:08d2947c490093a11416df18043c27abe3921558d2c03e2076ccb28a116cb6d0"},
+    {file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0eaa47d4661c326bfc9d08d16debbc4edf78778e6aaba29c1bc7ce67214d4410"},
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+    {file = "bcrypt-4.0.1.tar.gz", hash = "sha256:27d375903ac8261cfe4047f6709d16f7d18d39b1ec92aaf72af989552a650ebd"},
+]
+
+[package.extras]
+tests = ["pytest (>=3.2.1,!=3.3.0)"]
+typecheck = ["mypy"]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.12.2"
@ -2552,13 +2586,13 @@ pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_ve

 [[package]]
 name = "humanize"
-version = "4.7.0"
+version = "4.8.0"
 description = "Python humanize utilities"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "humanize-4.7.0-py3-none-any.whl", hash = "sha256:df7c429c2d27372b249d3f26eb53b07b166b661326e0325793e0a988082e3889"},
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+    {file = "humanize-4.8.0-py3-none-any.whl", hash = "sha256:8bc9e2bb9315e61ec06bf690151ae35aeb65651ab091266941edf97c90836404"},
+    {file = "humanize-4.8.0.tar.gz", hash = "sha256:9783373bf1eec713a770ecaa7c2d7a7902c98398009dfa3d8a2df91eec9311e8"},
 ]

 [package.extras]
@ -3140,13 +3174,13 @@ test = ["psutil", "pytest", "pytest-asyncio"]

 [[package]]
 name = "langsmith"
-version = "0.0.22"
+version = "0.0.23"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
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+    {file = "langsmith-0.0.23-py3-none-any.whl", hash = "sha256:68a48ecd5b389d14de55e9b6ac237a280ed3720814907277e25026b18e037103"},
+    {file = "langsmith-0.0.23.tar.gz", hash = "sha256:2d26d78bef5ab928da632d0dfbae8985afa6ffdaec5a895dfa277ed24c6936fd"},
 ]

 [package.dependencies]
@ -3723,33 +3757,38 @@ dill = ">=0.3.7"

 [[package]]
 name = "mypy"
-version = "1.5.0"
+version = "1.5.1"
 description = "Optional static typing for Python"
 optional = false
 python-versions = ">=3.8"
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+    {file = "mypy-1.5.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a9ec1f695f0c25986e6f7f8778e5ce61659063268836a38c951200c57479cc12"},
+    {file = "mypy-1.5.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:abed92d9c8f08643c7d831300b739562b0a6c9fcb028d211134fc9ab20ccad5d"},
+    {file = "mypy-1.5.1-cp310-cp310-win_amd64.whl", hash = "sha256:a156e6390944c265eb56afa67c74c0636f10283429171018446b732f1a05af25"},
+    {file = "mypy-1.5.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6ac9c21bfe7bc9f7f1b6fae441746e6a106e48fc9de530dea29e8cd37a2c0cc4"},
+    {file = "mypy-1.5.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:51cb1323064b1099e177098cb939eab2da42fea5d818d40113957ec954fc85f4"},
+    {file = "mypy-1.5.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:596fae69f2bfcb7305808c75c00f81fe2829b6236eadda536f00610ac5ec2243"},
+    {file = "mypy-1.5.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:32cb59609b0534f0bd67faebb6e022fe534bdb0e2ecab4290d683d248be1b275"},
+    {file = "mypy-1.5.1-cp311-cp311-win_amd64.whl", hash = "sha256:159aa9acb16086b79bbb0016145034a1a05360626046a929f84579ce1666b315"},
+    {file = "mypy-1.5.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:f6b0e77db9ff4fda74de7df13f30016a0a663928d669c9f2c057048ba44f09bb"},
+    {file = "mypy-1.5.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:26f71b535dfc158a71264e6dc805a9f8d2e60b67215ca0bfa26e2e1aa4d4d373"},
+    {file = "mypy-1.5.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2fc3a600f749b1008cc75e02b6fb3d4db8dbcca2d733030fe7a3b3502902f161"},
+    {file = "mypy-1.5.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:26fb32e4d4afa205b24bf645eddfbb36a1e17e995c5c99d6d00edb24b693406a"},
+    {file = "mypy-1.5.1-cp312-cp312-win_amd64.whl", hash = "sha256:82cb6193de9bbb3844bab4c7cf80e6227d5225cc7625b068a06d005d861ad5f1"},
+    {file = "mypy-1.5.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:4a465ea2ca12804d5b34bb056be3a29dc47aea5973b892d0417c6a10a40b2d65"},
+    {file = "mypy-1.5.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:9fece120dbb041771a63eb95e4896791386fe287fefb2837258925b8326d6160"},
+    {file = "mypy-1.5.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d28ddc3e3dfeab553e743e532fb95b4e6afad51d4706dd22f28e1e5e664828d2"},
+    {file = "mypy-1.5.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:57b10c56016adce71fba6bc6e9fd45d8083f74361f629390c556738565af8eeb"},
+    {file = "mypy-1.5.1-cp38-cp38-win_amd64.whl", hash = "sha256:ff0cedc84184115202475bbb46dd99f8dcb87fe24d5d0ddfc0fe6b8575c88d2f"},
+    {file = "mypy-1.5.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8f772942d372c8cbac575be99f9cc9d9fb3bd95c8bc2de6c01411e2c84ebca8a"},
+    {file = "mypy-1.5.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5d627124700b92b6bbaa99f27cbe615c8ea7b3402960f6372ea7d65faf376c14"},
+    {file = "mypy-1.5.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:361da43c4f5a96173220eb53340ace68cda81845cd88218f8862dfb0adc8cddb"},
+    {file = "mypy-1.5.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:330857f9507c24de5c5724235e66858f8364a0693894342485e543f5b07c8693"},
+    {file = "mypy-1.5.1-cp39-cp39-win_amd64.whl", hash = "sha256:c543214ffdd422623e9fedd0869166c2f16affe4ba37463975043ef7d2ea8770"},
+    {file = "mypy-1.5.1-py3-none-any.whl", hash = "sha256:f757063a83970d67c444f6e01d9550a7402322af3557ce7630d3c957386fa8f5"},
+    {file = "mypy-1.5.1.tar.gz", hash = "sha256:b031b9601f1060bf1281feab89697324726ba0c0bae9d7cd7ab4b690940f0b92"},
 ]

 [package.dependencies]
@ -4451,6 +4490,23 @@ files = [
 qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
 testing = ["docopt", "pytest (<6.0.0)"]

+[[package]]
+name = "passlib"
+version = "1.7.4"
+description = "comprehensive password hashing framework supporting over 30 schemes"
+optional = false
+python-versions = "*"
+files = [
+    {file = "passlib-1.7.4-py2.py3-none-any.whl", hash = "sha256:aa6bca462b8d8bda89c70b382f0c298a20b5560af6cbfa2dce410c0a2fb669f1"},
+    {file = "passlib-1.7.4.tar.gz", hash = "sha256:defd50f72b65c5402ab2c573830a6978e5f202ad0d984793c8dde2c4152ebe04"},
+]
+
+[package.extras]
+argon2 = ["argon2-cffi (>=18.2.0)"]
+bcrypt = ["bcrypt (>=3.1.0)"]
+build-docs = ["cloud-sptheme (>=1.10.1)", "sphinx (>=1.6)", "sphinxcontrib-fulltoc (>=1.2.0)"]
+totp = ["cryptography"]
+
 [[package]]
 name = "pathspec"
 version = "0.11.2"
@ -7351,6 +7407,17 @@ files = [
    {file = "validators-0.21.0.tar.gz", hash = "sha256:245b98ab778ed9352a7269c6a8f6c2a839bed5b2a7e3e60273ce399d247dd4b3"},
 ]

+[[package]]
+name = "vine"
+version = "5.0.0"
+description = "Promises, promises, promises."
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "vine-5.0.0-py2.py3-none-any.whl", hash = "sha256:4c9dceab6f76ed92105027c49c823800dd33cacce13bdedc5b914e3514b7fb30"},
+    {file = "vine-5.0.0.tar.gz", hash = "sha256:7d3b1624a953da82ef63462013bbd271d3eb75751489f9807598e8f340bd637e"},
+]
+
 [[package]]
 name = "watchfiles"
 version = "0.19.0"
@ -7842,4 +7909,4 @@ local = ["ctransformers", "llama-cpp-python", "sentence-transformers"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "00a3de3cc8916619f8434289b23a51e768b7b7c74f33e29c0ea3c61688ea3874"
+content-hash = "c1581fd2c650cc1365793ca33278917dd86bb4527cc956106a82a5c513ecc483"
--- a/pyproject.toml
+++ b/pyproject.toml
@ -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 +81,9 @@ celery = { extras = ["redis"], version = "^5.3.1", optional = true }
 redis = { version = "^4.6.0", optional = true }
 flower = { version = "^2.0.0", optional = true }
 alembic = "^1.11.2"
+passlib = "^1.7.4"
+bcrypt = "^4.0.1"
+python-jose = "^3.3.0"
 metaphor-python = "^0.1.11"


--- 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/init.py
+++ b/src/backend/langflow/auth/init.py
--- a/src/backend/langflow/auth/auth.py
+++ b/src/backend/langflow/auth/auth.py
@ -0,0 +1,177 @@
+from uuid import UUID
+from typing import Annotated
+from jose import JWTError, jwt
+from sqlalchemy.orm import Session
+from passlib.context import CryptContext
+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.user import (
+    User,
+    get_user_by_id,
+    get_user_by_username,
+    update_user_last_login_at,
+)
+
+
+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)
+
+
+def get_password_hash(password):
+    return pwd_context.hash(password)
+
+
+def create_token(data: dict, expires_delta: timedelta):
+    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,
+        settings_manager.settings.SECRET_KEY,
+        algorithm=settings_manager.settings.ALGORITHM,
+    )
+
+
+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": 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=settings_manager.settings.REFRESH_TOKEN_EXPIRE_MINUTES
+    )
+    refresh_token = create_token(
+        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,
+        "token_type": "bearer",
+    }
+
+
+def create_refresh_token(refresh_token: str, db: Session = Depends(get_session)):
+    settings_manager = get_settings_manager()
+
+    try:
+        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 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(user_id, db)
+
+    except JWTError as e:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="Invalid refresh token",
+        ) from e
+
+
+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
+
+    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 user if verify_password(password, user.password) else None
--- 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
@ -0,0 +1,7 @@
+from pydantic import BaseModel
+
+
+class Token(BaseModel):
+    access_token: str
+    refresh_token: str
+    token_type: str
--- a/src/backend/langflow/database/models/user.py
+++ b/src/backend/langflow/database/models/user.py
@ -0,0 +1,94 @@
+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_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()
+
+
+class UserListModel(SQLModel):
+    id: UUID = Field(default_factory=uuid4)
+    username: str = 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: 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:
+    db_user = db.query(User).filter(User.username == username).first()
+    return User.from_orm(db_user) if db_user else None  # type: ignore
+
+
+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/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":
@ -147,7 +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:
@ -261,9 +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/main.py
+++ b/src/backend/langflow/main.py
@ -6,6 +6,8 @@ from fastapi.responses import FileResponse
 from fastapi.staticfiles import StaticFiles

 from langflow.api import router
+from langflow.routers import login, users, health
+
 from langflow.interface.utils import setup_llm_caching
 from langflow.services.database.utils import initialize_database
 from langflow.services.manager import initialize_services
@ -19,13 +21,7 @@ def create_app():

    app = FastAPI()

-    origins = [
-        "*",
-    ]
-
-    @app.get("/health")
-    def get_health():
-        return {"status": "OK"}
+    origins = ["*"]

    app.add_middleware(
        CORSMiddleware,
@ -34,6 +30,11 @@ def create_app():
        allow_methods=["*"],
        allow_headers=["*"],
    )
+
+    app.include_router(login.router)
+    app.include_router(users.router)
+    app.include_router(health.router)
+
    app.include_router(router)

    app.on_event("startup")(initialize_services)
--- a/src/backend/langflow/routers/init.py
+++ b/src/backend/langflow/routers/init.py
--- a/src/backend/langflow/routers/health.py
+++ b/src/backend/langflow/routers/health.py
@ -0,0 +1,8 @@
+from fastapi import APIRouter
+
+router = APIRouter()
+
+
+@router.get("/health")
+def get_health():
+    return {"status": "OK"}
--- a/Show more
+++ b/Show more