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

.devcontainer/devcontainer.json

@@ -3,7 +3,7 @@
 {
   "name": "Langflow Dev Container",
   // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
-  "image": "mcr.microsoft.com/devcontainers/python:1-3.10-bullseye",
+  "image": "mcr.microsoft.com/devcontainers/python:3.10",
 
   // Features to add to the dev container. More info: https://containers.dev/features.
   "features": {

.github/workflows/pre-release-base.yml

@@ -13,9 +13,12 @@ env:
   POETRY_VERSION: "1.8.2"
 
 jobs:
-  if_release:
+  release:
+    name: Release Langflow Base
     if: inputs.release_package == true
     runs-on: ubuntu-latest
+    outputs:
+      version: ${{ steps.check-version.outputs.version }}
     steps:
       - uses: actions/checkout@v4
       - name: Install poetry
@@ -49,6 +52,12 @@ jobs:
           POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }}
         run: |
           make publish base=true
+  docker_build:
+    name: Build Docker Image
+    runs-on: ubuntu-latest
+    needs: release
+    steps:
+      - uses: actions/checkout@v4
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v3
       - name: Set up Docker Buildx
@@ -65,4 +74,4 @@ jobs:
           push: true
           file: ./build_and_push_base.Dockerfile
           tags: |
-            logspace/langflow:base-${{ steps.check-version.outputs.version }}
+            logspace/langflow:base-${{ needs.release.outputs.version }}

.github/workflows/pre-release-langflow.yml

@@ -17,9 +17,12 @@ env:
   POETRY_VERSION: "1.8.2"
 
 jobs:
-  if_release:
+  release:
+    name: Release Langflow
     if: inputs.release_package == true
     runs-on: ubuntu-latest
+    outputs:
+      version: ${{ steps.check-version.outputs.version }}
     steps:
       - uses: actions/checkout@v4
       - name: Install poetry
@@ -49,6 +52,17 @@ jobs:
           POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }}
         run: |
           make publish main=true
+      - name: Upload Artifact
+        uses: actions/upload-artifact@v2
+        with:
+          name: dist
+          path: dist
+
+  docker_build:
+    name: Build Docker Image
+    runs-on: ubuntu-latest
+    needs: release
+    steps:
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v3
       - name: Set up Docker Buildx
@@ -65,9 +79,18 @@ jobs:
           push: true
           file: ./build_and_push.Dockerfile
           tags: |
-            logspace/langflow:${{ steps.check-version.outputs.version }}
+            logspace/langflow:${{ needs.release.outputs.version }}
             logspace/langflow:1.0-alpha
 
+  create_release:
+    name: Create Release
+    runs-on: ubuntu-latest
+    needs: [docker_build, release]
+    steps:
+      - uses: actions/download-artifact@v2
+        with:
+          name: dist
+          path: dist
       - name: Create Release
         uses: ncipollo/release-action@v1
         with:
@@ -76,5 +99,5 @@ jobs:
           draft: false
           generateReleaseNotes: true
           prerelease: true
-          tag: v${{ steps.check-version.outputs.version }}
+          tag: v${{ needs.release.outputs.version }}
           commit: dev

.github/workflows/typescript_test.yml

@@ -19,8 +19,8 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        shardIndex: [1, 2, 3, 4]
-        shardTotal: [4]
+        shardIndex: [1]
+        shardTotal: [1]
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
@@ -38,27 +38,6 @@ jobs:
           npm ci
         if: ${{ steps.setup-node.outputs.cache-hit != 'true' }}
 
-      # Attempt to restore the correct Playwright browser binaries based on the
-      # currently installed version of Playwright (The browser binary versions
-      # may change with Playwright versions).
-      # Note: Playwright's cache directory is hard coded because that's what it
-      # says to do in the docs. There doesn't appear to be a command that prints
-      # it out for us.
-      # - uses: actions/cache@v4
-      #   id: playwright-cache
-      #   with:
-      #     path: ${{ env.PLAYWRIGHT_BROWSERS_PATH }}
-      #     key: "${{ runner.os }}-playwright-${{ hashFiles('src/frontend/package-lock.json') }}"
-      #     # As a fallback, if the Playwright version has changed, try use the
-      #     # most recently cached version. There's a good chance that at least one
-      #     # of the browser binary versions haven't been updated, so Playwright can
-      #     # skip installing that in the next step.
-      #     # Note: When falling back to an old cache, `cache-hit` (used below)
-      #     # will be `false`. This allows us to restore the potentially out of
-      #     # date cache, but still let Playwright decide if it needs to download
-      #     # new binaries or not.
-      #     restore-keys: |
-      #       ${{ runner.os }}-playwright-
       - name: Cache playwright binaries
         uses: actions/cache@v4
         id: playwright-cache
@@ -82,32 +61,26 @@ jobs:
           npx playwright install-deps
         if: steps.playwright-cache.outputs.cache-hit != 'true'
 
-      # If the Playwright browser binaries weren't able to be restored, we tell
-      # paywright to install everything for us.
-      # - name: Install Playwright's dependencies
-      #   if: steps.playwright-cache.outputs.cache-hit != 'true'
-      #   run: npx playwright install --with-deps
-
-      - name: Install Poetry
-        run: pipx install "poetry==${{ env.POETRY_VERSION }}"
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        id: setup-python
+      - name: Set up Python ${{ env.PYTHON_VERSION }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_caching"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          cache: "poetry"
-
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: ${{ runner.os }}-poetry-${{ env.POETRY_VERSION }}-${{ hashFiles('**/poetry.lock') }}
       - name: Install Python dependencies
         run: |
           poetry env use ${{ env.PYTHON_VERSION }}
           poetry install
-        if: ${{ steps.setup-python.outputs.cache-hit != 'true' }}
+
+      - name: create .env
+        run: |
+          touch .env
+          echo "${{ secrets.ENV_VARS }}" > .env
 
       - name: Run Playwright Tests
         run: |
           cd src/frontend
-          npx playwright test --shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }}
+          npx playwright test
 
       - name: Upload blob report to GitHub Actions Artifacts
         if: always()

CODE_OF_CONDUCT.md

@@ -17,23 +17,23 @@ diverse, inclusive, and healthy community.
 Examples of behavior that contributes to a positive environment for our
 community include:
 
-* Demonstrating empathy and kindness toward other people
-* Being respectful of differing opinions, viewpoints, and experiences
-* Giving and gracefully accepting constructive feedback
-* Accepting responsibility and apologizing to those affected by our mistakes,
+- Demonstrating empathy and kindness toward other people
+- Being respectful of differing opinions, viewpoints, and experiences
+- Giving and gracefully accepting constructive feedback
+- Accepting responsibility and apologizing to those affected by our mistakes,
   and learning from the experience
-* Focusing on what is best not just for us as individuals, but for the
+- Focusing on what is best not just for us as individuals, but for the
   overall community
 
 Examples of unacceptable behavior include:
 
-* The use of sexualized language or imagery, and sexual attention or
+- The use of sexualized language or imagery, and sexual attention or
   advances of any kind
-* Trolling, insulting or derogatory comments, and personal or political attacks
-* Public or private harassment
-* Publishing others' private information, such as a physical or email
+- Trolling, insulting or derogatory comments, and personal or political attacks
+- Public or private harassment
+- Publishing others' private information, such as a physical or email
   address, without their explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
+- Other conduct which could reasonably be considered inappropriate in a
   professional setting
 
 ## Enforcement Responsibilities
@@ -60,7 +60,7 @@ representative at an online or offline event.
 
 Instances of abusive, harassing, or otherwise unacceptable behavior may be
 reported to the community leaders responsible for enforcement at
-contact@logspace.ai.
+contact@langflow.org.
 All complaints will be reviewed and investigated promptly and fairly.
 
 All community leaders are obligated to respect the privacy and security of the
@@ -106,7 +106,7 @@ Violating these terms may lead to a permanent ban.
 ### 4. Permanent Ban
 
 **Community Impact**: Demonstrating a pattern of violation of community
-standards, including sustained inappropriate behavior,  harassment of an
+standards, including sustained inappropriate behavior, harassment of an
 individual, or aggression toward or disparagement of classes of individuals.
 
 **Consequence**: A permanent ban from any sort of public interaction within

GCP_DEPLOYMENT.md

@@ -6,7 +6,7 @@ This guide will help you set up a Langflow development VM in a Google Cloud Plat
 
 ## Standard VM
 
-[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md)
+[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md)
 
 This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment.
 
@@ -14,7 +14,7 @@ This script sets up a Debian-based VM with the Langflow package, Nginx, and the
 
 ## Spot/Preemptible Instance
 
-[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
+[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md)
 
 When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts.
 

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2024 Logspace
+Copyright (c) 2024 Langflow
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

base.Dockerfile

@@ -63,8 +63,10 @@ RUN --mount=type=cache,target=/root/.cache \
 
 # copy project requirement files here to ensure they will be cached.
 WORKDIR $PYSETUP_PATH
+# Copy just one file to avoid rebuilding the whole image
 COPY poetry.lock pyproject.toml ./
-COPY ./src/backend/langflow/main.py ./src/backend/langflow/main.py
+COPY ./src/backend/langflow ./src/backend/langflow
+COPY ./src/backend/base/pyproject.toml ./src/backend/base/pyproject.toml
 # Copy README.md to the build context
 COPY README.md .
 # install runtime deps - uses $POETRY_VIRTUALENVS_IN_PROJECT internally
@@ -84,7 +86,7 @@ COPY --from=builder-base $POETRY_HOME $POETRY_HOME
 COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH
 
 # Copy just one file to avoid rebuilding the whole image
-COPY ./src/backend/langflow/__init__.py ./src/backend/langflow/__init__.py
+COPY ./src/backend/langflow ./src/backend/langflow
 # quicker install as runtime deps are already installed
 RUN --mount=type=cache,target=/root/.cache \
     poetry install --with=dev --extras deploy

build_and_push.Dockerfile

@@ -74,10 +74,11 @@ RUN $POETRY_HOME/bin/poetry build
 FROM python-base as final
 
 # Copy virtual environment and built .tar.gz from builder base
+RUN useradd -m -u 1000 user
 COPY --from=builder-base /app/dist/*.tar.gz ./
-
 # Install the package from the .tar.gz
-RUN pip install *.tar.gz
+RUN python -m pip install *.tar.gz --user
 
 WORKDIR /app
-CMD ["python", "-m", "langflow", "run", "--host", "0.0.0.0", "--port", "7860"]
+ENTRYPOINT ["python", "-m", "langflow", "run"]
+CMD ["--host", "0.0.0.0", "--port", "7860"]

build_and_push_base.Dockerfile

@@ -82,10 +82,11 @@ RUN cd src/backend/base && $POETRY_HOME/bin/poetry build --format sdist
 FROM python-base as final
 
 # Copy virtual environment and built .tar.gz from builder base
+RUN useradd -m -u 1000 user
 COPY --from=builder-base /app/src/backend/base/dist/*.tar.gz ./
-
 # Install the package from the .tar.gz
-RUN pip install *.tar.gz
+RUN pip install *.tar.gz --user
 
 WORKDIR /app
-CMD ["python", "-m", "langflow", "run", "--host", "0.0.0.0", "--port", "7860"]
+ENTRYPOINT ["python", "-m", "langflow", "run"]
+CMD ["--host", "0.0.0.0", "--port", "7860"]

deploy/base.Dockerfile

@@ -1,92 +0,0 @@
-
-
-# syntax=docker/dockerfile:1
-# Keep this syntax directive! It's used to enable Docker BuildKit
-
-# Based on https://github.com/python-poetry/poetry/discussions/1879?sort=top#discussioncomment-216865
-# but I try to keep it updated (see history)
-
-################################
-# PYTHON-BASE
-# Sets up all our shared environment variables
-################################
-FROM python:3.10-slim as python-base
-
-# python
-ENV PYTHONUNBUFFERED=1 \
-    # prevents python creating .pyc files
-    PYTHONDONTWRITEBYTECODE=1 \
-    \
-    # pip
-    PIP_DISABLE_PIP_VERSION_CHECK=on \
-    PIP_DEFAULT_TIMEOUT=100 \
-    \
-    # poetry
-    # https://python-poetry.org/docs/configuration/#using-environment-variables
-    POETRY_VERSION=1.8.2 \
-    # make poetry install to this location
-    POETRY_HOME="/opt/poetry" \
-    # make poetry create the virtual environment in the project's root
-    # it gets named `.venv`
-    POETRY_VIRTUALENVS_IN_PROJECT=true \
-    # do not ask any interactive question
-    POETRY_NO_INTERACTION=1 \
-    \
-    # paths
-    # this is where our requirements + virtual environment will live
-    PYSETUP_PATH="/opt/pysetup" \
-    VENV_PATH="/opt/pysetup/.venv"
-
-
-# prepend poetry and venv to path
-ENV PATH="$POETRY_HOME/bin:$VENV_PATH/bin:$PATH"
-
-
-################################
-# BUILDER-BASE
-# Used to build deps + create our virtual environment
-################################
-FROM python-base as builder-base
-RUN apt-get update \
-    && apt-get install --no-install-recommends -y \
-    # deps for installing poetry
-    curl \
-    # deps for building python deps
-    build-essential
-
-# install poetry - respects $POETRY_VERSION & $POETRY_HOME
-# The --mount will mount the buildx cache directory to where
-# Poetry and Pip store their cache so that they can reuse it
-RUN --mount=type=cache,target=/root/.cache \
-    curl -sSL https://install.python-poetry.org | python3 -
-
-# copy project requirement files here to ensure they will be cached.
-WORKDIR $PYSETUP_PATH
-COPY ./poetry.lock ./pyproject.toml ./
-# Copy README.md to the build context
-COPY ./README.md ./
-# install runtime deps - uses $POETRY_VIRTUALENVS_IN_PROJECT internally
-RUN --mount=type=cache,target=/root/.cache \
-    poetry install --without dev --extras deploy
-
-
-################################
-# DEVELOPMENT
-# Image used during development / testing
-################################
-FROM python-base as development
-WORKDIR $PYSETUP_PATH
-
-# copy in our built poetry + venv
-COPY --from=builder-base $POETRY_HOME $POETRY_HOME
-COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH
-
-# Copy just one file to avoid rebuilding the whole image
-COPY ./src/backend/langflow/__init__.py ./src/backend/langflow/__init__.py
-# quicker install as runtime deps are already installed
-RUN --mount=type=cache,target=/root/.cache \
-    poetry install --with=dev --extras deploy
-
-# copy in our app code
-COPY ./src/backend ./src/backend
-COPY ./tests ./tests

deploy/docker-compose.yml

@@ -69,10 +69,7 @@ services:
         - traefik.http.routers.${STACK_NAME?Variable not set}-proxy-http.middlewares=${STACK_NAME?Variable not set}-www-redirect,${STACK_NAME?Variable not set}-https-redirect
 
   backend: &backend
-    image: "ogabrielluiz/langflow:latest"
-    build:
-      context: ../
-      dockerfile: base.Dockerfile
+    image: "logspace/langflow:latest"
     depends_on:
       - db
       - broker
@@ -143,9 +140,6 @@ services:
     <<: *backend
     env_file:
       - .env
-    build:
-      context: ../
-      dockerfile: base.Dockerfile
     command: celery -A langflow.worker.celery_app worker --loglevel=INFO --concurrency=1 -n lf-worker@%h -P eventlet
     healthcheck:
       test: "exit 0"
@@ -158,9 +152,6 @@ services:
       - .env
     networks:
       - default
-    build:
-      context: ../
-      dockerfile: base.Dockerfile
     environment:
       - FLOWER_PORT=5555
 

docs/docs/deployment/gcp-deployment.md

@@ -8,7 +8,7 @@ This guide will help you set up a Langflow development VM in a Google Cloud Plat
 
 ## Standard VM
 
-[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md)
+[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md)
 
 This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment.
 
@@ -16,7 +16,7 @@ This script sets up a Debian-based VM with the Langflow package, Nginx, and the
 
 ## Spot/Preemptible Instance
 
-[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
+[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md)
 
 When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts.
 

docs/docusaurus.config.js

@@ -7,11 +7,11 @@ module.exports = {
   title: "Langflow Documentation",
   tagline: "Langflow is a GUI for LangChain, designed with react-flow",
   favicon: "img/favicon.ico",
-  url: "https://logspace-ai.github.io",
+  url: "https://langflow-ai.github.io",
   baseUrl: "/",
   onBrokenLinks: "throw",
   onBrokenMarkdownLinks: "warn",
-  organizationName: "logspace-ai",
+  organizationName: "langflow-ai",
   projectName: "langflow",
   trailingSlash: false,
   staticDirectories: ["static"],
@@ -131,7 +131,7 @@ module.exports = {
       },
       footer: {
         links: [],
-        copyright: `Copyright © ${new Date().getFullYear()} Logspace.`,
+        copyright: `Copyright © ${new Date().getFullYear()} Langflow.`,
       },
       zoom: {
         selector: ".markdown :not(a) > img:not(.no-zoom)",

pyproject.toml

@@ -1,16 +1,16 @@
 [tool.poetry]
 name = "langflow"
-version = "1.0.0a18"
+version = "1.0.0a24"
 description = "A Python package with a built-in web application"
-authors = ["Logspace <contact@logspace.ai>"]
+authors = ["Langflow <contact@langflow.org>"]
 maintainers = [
-    "Carlos Coelho <carlos@logspace.ai>",
+    "Carlos Coelho <carlos@langflow.org>",
     "Cristhian Zanforlin <cristhian.lousa@gmail.com>",
-    "Gabriel Almeida <gabriel@logspace.ai>",
+    "Gabriel Almeida <gabriel@langflow.org>",
     "Igor Carvalho <igorr.ackerman@gmail.com>",
     "Lucas Eduoli <lucaseduoli@gmail.com>",
     "Otávio Anovazzi <otavio2204@gmail.com>",
-    "Rodrigo Nader <rodrigo@logspace.ai>",
+    "Rodrigo Nader <rodrigo@langflow.org>",
 ]
 repository = "https://github.com/langflow-ai/langflow"
 license = "MIT"

src/backend/base/langflow/alembic/versions/1a110b568907_replace_credential_table_with_variable.py

@@ -5,6 +5,7 @@ Revises: 63b9c451fd30
 Create Date: 2024-03-25 09:40:02.743453
 
 """
+
 from typing import Sequence, Union
 
 import sqlalchemy as sa

src/backend/base/langflow/alembic/versions/4e5980a44eaa_fix_date_times_again.py

@@ -0,0 +1,130 @@
+"""Fix date times again
+
+Revision ID: 4e5980a44eaa
+Revises: 79e675cb6752
+Create Date: 2024-04-12 18:11:06.454037
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+from loguru import logger
+from sqlalchemy.dialects import postgresql
+from sqlalchemy.engine.reflection import Inspector
+
+# revision identifiers, used by Alembic.
+revision: str = "4e5980a44eaa"
+down_revision: Union[str, None] = "79e675cb6752"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    table_names = inspector.get_table_names()
+    # ### commands auto generated by Alembic - please adjust! ###
+    if "apikey" in table_names:
+        columns = inspector.get_columns("apikey")
+        created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
+        if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP):
+            with op.batch_alter_table("apikey", schema=None) as batch_op:
+                batch_op.alter_column(
+                    "created_at",
+                    existing_type=postgresql.TIMESTAMP(),
+                    type_=sa.DateTime(timezone=True),
+                    existing_nullable=False,
+                )
+        else:
+            if created_at_column is None:
+                logger.warning("Column 'created_at' not found in table 'apikey'")
+            else:
+                logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'")
+    if "variable" in table_names:
+        columns = inspector.get_columns("variable")
+        created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
+        updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None)
+        with op.batch_alter_table("variable", schema=None) as batch_op:
+            if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP):
+                batch_op.alter_column(
+                    "created_at",
+                    existing_type=postgresql.TIMESTAMP(),
+                    type_=sa.DateTime(timezone=True),
+                    existing_nullable=True,
+                )
+            else:
+                if created_at_column is None:
+                    logger.warning("Column 'created_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'")
+            if updated_at_column is not None and isinstance(updated_at_column["type"], postgresql.TIMESTAMP):
+                batch_op.alter_column(
+                    "updated_at",
+                    existing_type=postgresql.TIMESTAMP(),
+                    type_=sa.DateTime(timezone=True),
+                    existing_nullable=True,
+                )
+            else:
+                if updated_at_column is None:
+                    logger.warning("Column 'updated_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'")
+
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    table_names = inspector.get_table_names()
+    # ### commands auto generated by Alembic - please adjust! ###
+    if "variable" in table_names:
+        columns = inspector.get_columns("variable")
+        created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
+        updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None)
+        with op.batch_alter_table("variable", schema=None) as batch_op:
+            if updated_at_column is not None and isinstance(updated_at_column["type"], sa.DateTime):
+                batch_op.alter_column(
+                    "updated_at",
+                    existing_type=sa.DateTime(timezone=True),
+                    type_=postgresql.TIMESTAMP(),
+                    existing_nullable=True,
+                )
+            else:
+                if updated_at_column is None:
+                    logger.warning("Column 'updated_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'")
+            if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime):
+                batch_op.alter_column(
+                    "created_at",
+                    existing_type=sa.DateTime(timezone=True),
+                    type_=postgresql.TIMESTAMP(),
+                    existing_nullable=True,
+                )
+            else:
+                if created_at_column is None:
+                    logger.warning("Column 'created_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'")
+
+    if "apikey" in table_names:
+        columns = inspector.get_columns("apikey")
+        created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
+        if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime):
+            with op.batch_alter_table("apikey", schema=None) as batch_op:
+                batch_op.alter_column(
+                    "created_at",
+                    existing_type=sa.DateTime(timezone=True),
+                    type_=postgresql.TIMESTAMP(),
+                    existing_nullable=False,
+                )
+        else:
+            if created_at_column is None:
+                logger.warning("Column 'created_at' not found in table 'apikey'")
+            else:
+                logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'")
+
+    # ### end Alembic commands ###

src/backend/base/langflow/alembic/versions/58b28437a398_modify_nullable.py

@@ -0,0 +1,66 @@
+"""Modify nullable
+
+Revision ID: 58b28437a398
+Revises: 4e5980a44eaa
+Create Date: 2024-04-13 10:57:23.061709
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+from loguru import logger
+from sqlalchemy.engine.reflection import Inspector
+
+down_revision: Union[str, None] = "4e5980a44eaa"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+# Revision identifiers, used by Alembic.
+revision = "58b28437a398"
+down_revision = "4e5980a44eaa"
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)
+    tables = ["apikey", "variable"]  # List of tables to modify
+
+    for table_name in tables:
+        modify_nullable(conn, inspector, table_name, upgrade=True)
+
+
+def downgrade():
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)
+    tables = ["apikey", "variable"]  # List of tables to revert
+
+    for table_name in tables:
+        modify_nullable(conn, inspector, table_name, upgrade=False)
+
+
+def modify_nullable(conn, inspector, table_name, upgrade=True):
+    columns = inspector.get_columns(table_name)
+    nullable_changes = {"apikey": {"created_at": False}, "variable": {"created_at": True, "updated_at": True}}
+
+    if table_name in columns:
+        with op.batch_alter_table(table_name, schema=None) as batch_op:
+            for column_name, nullable_setting in nullable_changes.get(table_name, {}).items():
+                column_info = next((col for col in columns if col["name"] == column_name), None)
+                if column_info:
+                    current_nullable = column_info["nullable"]
+                    target_nullable = nullable_setting if upgrade else not nullable_setting
+
+                    if current_nullable != target_nullable:
+                        batch_op.alter_column(
+                            column_name, existing_type=sa.DateTime(timezone=True), nullable=target_nullable
+                        )
+                    else:
+                        logger.info(
+                            f"Column '{column_name}' in table '{table_name}' already has nullable={target_nullable}"
+                        )
+                else:
+                    logger.warning(f"Column '{column_name}' not found in table '{table_name}'")

src/backend/base/langflow/alembic/versions/79e675cb6752_change_datetime_type.py

@@ -5,13 +5,14 @@ Revises: e3bc869fa272
 Create Date: 2024-04-11 19:23:10.697335
 
 """
-from calendar import c
+
 from typing import Sequence, Union
 
 import sqlalchemy as sa
 from alembic import op
 from sqlalchemy.dialects import postgresql
 from sqlalchemy.engine.reflection import Inspector
+from loguru import logger
 
 # revision identifiers, used by Alembic.
 revision: str = "79e675cb6752"
@@ -28,7 +29,7 @@ def upgrade() -> None:
     if "apikey" in table_names:
         columns = inspector.get_columns("apikey")
         created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
-        if created_at_column is not None and created_at_column["type"] == postgresql.TIMESTAMP():
+        if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP):
             with op.batch_alter_table("apikey", schema=None) as batch_op:
                 batch_op.alter_column(
                     "created_at",
@@ -36,25 +37,40 @@ def upgrade() -> None:
                     type_=sa.DateTime(timezone=True),
                     existing_nullable=False,
                 )
+        else:
+            if created_at_column is None:
+                logger.warning("Column 'created_at' not found in table 'apikey'")
+            else:
+                logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'")
     if "variable" in table_names:
         columns = inspector.get_columns("variable")
         created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
         updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None)
         with op.batch_alter_table("variable", schema=None) as batch_op:
-            if created_at_column is not None and created_at_column["type"] == postgresql.TIMESTAMP():
+            if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP):
                 batch_op.alter_column(
                     "created_at",
                     existing_type=postgresql.TIMESTAMP(),
                     type_=sa.DateTime(timezone=True),
                     existing_nullable=True,
                 )
-            if updated_at_column is not None and updated_at_column["type"] == postgresql.TIMESTAMP():
+            else:
+                if created_at_column is None:
+                    logger.warning("Column 'created_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'")
+            if updated_at_column is not None and isinstance(updated_at_column["type"], postgresql.TIMESTAMP):
                 batch_op.alter_column(
                     "updated_at",
                     existing_type=postgresql.TIMESTAMP(),
                     type_=sa.DateTime(timezone=True),
                     existing_nullable=True,
                 )
+            else:
+                if updated_at_column is None:
+                    logger.warning("Column 'updated_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'")
 
     # ### end Alembic commands ###
 
@@ -69,25 +85,35 @@ def downgrade() -> None:
         created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
         updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None)
         with op.batch_alter_table("variable", schema=None) as batch_op:
-            if updated_at_column is not None and updated_at_column["type"] == sa.DateTime(timezone=True):
+            if updated_at_column is not None and isinstance(updated_at_column["type"], sa.DateTime):
                 batch_op.alter_column(
                     "updated_at",
                     existing_type=sa.DateTime(timezone=True),
                     type_=postgresql.TIMESTAMP(),
                     existing_nullable=True,
                 )
-            if created_at_column is not None and created_at_column["type"] == sa.DateTime(timezone=True):
+            else:
+                if updated_at_column is None:
+                    logger.warning("Column 'updated_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'")
+            if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime):
                 batch_op.alter_column(
                     "created_at",
                     existing_type=sa.DateTime(timezone=True),
                     type_=postgresql.TIMESTAMP(),
                     existing_nullable=True,
                 )
+            else:
+                if created_at_column is None:
+                    logger.warning("Column 'created_at' not found in table 'variable'")
+                else:
+                    logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'")
 
     if "apikey" in table_names:
         columns = inspector.get_columns("apikey")
         created_at_column = next((column for column in columns if column["name"] == "created_at"), None)
-        if created_at_column is not None and created_at_column["type"] == sa.DateTime(timezone=True):
+        if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime):
             with op.batch_alter_table("apikey", schema=None) as batch_op:
                 batch_op.alter_column(
                     "created_at",
@@ -95,5 +121,10 @@ def downgrade() -> None:
                     type_=postgresql.TIMESTAMP(),
                     existing_nullable=False,
                 )
+        else:
+            if created_at_column is None:
+                logger.warning("Column 'created_at' not found in table 'apikey'")
+            else:
+                logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'")
 
     # ### end Alembic commands ###

src/backend/base/langflow/api/v1/endpoints.py

@@ -109,6 +109,7 @@ async def simplified_run_flow(
     This endpoint provides a powerful interface for executing flows with enhanced flexibility and efficiency, supporting a wide range of applications by allowing for dynamic input and output configuration along with performance optimizations through session management and caching.
     """
     session_id = input_request.session_id
+
     try:
         task_result: List[RunOutputs] = []
         artifacts = {}
@@ -127,8 +128,9 @@ async def simplified_run_flow(
             if flow.data is None:
                 raise ValueError(f"Flow {flow_id} has no data")
             graph_data = flow.data
-            graph_data = process_tweaks(graph_data, input_request.tweaks or {})
-            graph = Graph.from_payload(graph_data, flow_id=flow_id)
+
+            graph_data = process_tweaks(graph_data, input_request.tweaks or {}, stream=stream)
+            graph = Graph.from_payload(graph_data, flow_id=flow_id, user_id=api_key_user.id)
         inputs = [
             InputValueRequest(components=[], input_value=input_request.input_value, type=input_request.input_type)
         ]

src/backend/base/langflow/api/v1/store.py

@@ -2,6 +2,7 @@ from typing import Annotated, List, Optional, Union
 from uuid import UUID
 
 from fastapi import APIRouter, Depends, HTTPException, Query
+from loguru import logger
 
 from langflow.api.utils import check_langflow_version
 from langflow.services.auth import utils as auth_utils
@@ -27,8 +28,11 @@ def get_user_store_api_key(
 ):
     if not user.store_api_key:
         raise HTTPException(status_code=400, detail="You must have a store API key set.")
-    decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service)
-    return decrypted
+    try:
+        decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service)
+        return decrypted
+    except Exception as e:
+        raise HTTPException(status_code=500, detail="Failed to decrypt API key. Please set a new one.") from e
 
 
 def get_optional_user_store_api_key(
@@ -37,8 +41,12 @@ def get_optional_user_store_api_key(
 ):
     if not user.store_api_key:
         return None
-    decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service)
-    return decrypted
+    try:
+        decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service)
+        return decrypted
+    except Exception as e:
+        logger.error(f"Failed to decrypt API key: {e}")
+        return user.store_api_key
 
 
 @router.get("/check/")

src/backend/base/langflow/base/agents/agent.py

@@ -1,13 +1,19 @@
 from typing import List, Optional, Union, cast
 
 from langchain.agents import AgentExecutor, BaseMultiActionAgent, BaseSingleActionAgent
+from langchain_core.messages import BaseMessage
 from langchain_core.runnables import Runnable
 
+from langflow.base.agents.utils import get_agents_list, records_to_messages
 from langflow.custom import CustomComponent
-from langflow.field_typing import BaseMemory, Text, Tool
+from langflow.field_typing import Text, Tool
+from langflow.schema.schema import Record
 
 
 class LCAgentComponent(CustomComponent):
+    def get_agents_list(self):
+        return get_agents_list()
+
     def build_config(self):
         return {
             "lc": {
@@ -42,9 +48,8 @@ class LCAgentComponent(CustomComponent):
         self,
         agent: Union[Runnable, BaseSingleActionAgent, BaseMultiActionAgent, AgentExecutor],
         inputs: str,
-        input_variables: list[str],
         tools: List[Tool],
-        memory: Optional[BaseMemory] = None,
+        message_history: Optional[List[Record]] = None,
         handle_parsing_errors: bool = True,
         output_key: str = "output",
     ) -> Text:
@@ -55,13 +60,11 @@ class LCAgentComponent(CustomComponent):
                 agent=agent,  # type: ignore
                 tools=tools,
                 verbose=True,
-                memory=memory,
                 handle_parsing_errors=handle_parsing_errors,
             )
-        input_dict = {"input": inputs}
-        for var in input_variables:
-            if var not in ["agent_scratchpad", "input"]:
-                input_dict[var] = ""
+        input_dict: dict[str, str | list[BaseMessage]] = {"input": inputs}
+        if message_history:
+            input_dict["chat_history"] = records_to_messages(message_history)
         result = await runnable.ainvoke(input_dict)
         self.status = result
         if output_key in result:

src/backend/base/langflow/base/agents/default_prompts.py

@@ -0,0 +1,23 @@
+XML_AGENT_PROMPT = """You are a helpful assistant. Help the user answer any questions.
+
+            You have access to the following tools:
+
+            {tools}
+
+            In order to use a tool, you can use <tool></tool> and <tool_input></tool_input> tags. You will then get back a response in the form <observation></observation>
+            For example, if you have a tool called 'search' that could run a google search, in order to search for the weather in SF you would respond:
+
+            <tool>search</tool><tool_input>weather in SF</tool_input>
+            <observation>64 degrees</observation>
+
+            When you are done, respond with a final answer between <final_answer></final_answer>. For example:
+
+            <final_answer>The weather in SF is 64 degrees</final_answer>
+
+            Begin!
+
+            Previous Conversation:
+            {chat_history}
+
+            Question: {input}
+            {agent_scratchpad}"""

src/backend/base/langflow/base/agents/utils.py

@@ -0,0 +1,143 @@
+from typing import Any, Callable, Dict, List, Optional, Sequence, Union
+
+from langchain.agents import (
+    create_json_chat_agent,
+    create_openai_tools_agent,
+    create_tool_calling_agent,
+    create_xml_agent,
+)
+from langchain.agents.xml.base import render_text_description
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import BaseMessage
+from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate
+from langchain_core.tools import BaseTool
+from pydantic import BaseModel
+
+from langflow.schema.schema import Record
+
+from .default_prompts import XML_AGENT_PROMPT
+
+
+class AgentSpec(BaseModel):
+    func: Callable[
+        [
+            BaseLanguageModel,
+            Sequence[BaseTool],
+            BasePromptTemplate | ChatPromptTemplate,
+            Optional[Callable[[List[BaseTool]], str]],
+            Optional[Union[bool, List[str]]],
+        ],
+        Any,
+    ]
+    prompt: Optional[Any] = None
+    fields: List[str]
+    hub_repo: Optional[str] = None
+
+
+def records_to_messages(records: List[Record]) -> List[BaseMessage]:
+    """
+    Convert a list of records to a list of messages.
+
+    Args:
+        records (List[Record]): The records to convert.
+
+    Returns:
+        List[Message]: The records as messages.
+    """
+    return [record.to_lc_message() for record in records]
+
+
+def validate_and_create_xml_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: BasePromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_xml_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+        tools_renderer=tools_renderer,
+        stop_sequence=stop_sequence,
+    )
+
+
+def validate_and_create_openai_tools_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: ChatPromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_openai_tools_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+    )
+
+
+def validate_and_create_tool_calling_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: ChatPromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_tool_calling_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+    )
+
+
+def validate_and_create_json_chat_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: ChatPromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_json_chat_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+        tools_renderer=tools_renderer,
+        stop_sequence=stop_sequence,
+    )
+
+
+AGENTS: Dict[str, AgentSpec] = {
+    "Tool Calling Agent": AgentSpec(
+        func=validate_and_create_tool_calling_agent,
+        prompt=None,
+        fields=["llm", "tools", "prompt"],
+        hub_repo=None,
+    ),
+    "XML Agent": AgentSpec(
+        func=validate_and_create_xml_agent,
+        prompt=XML_AGENT_PROMPT,  # Ensure XML_AGENT_PROMPT is properly defined and typed.
+        fields=["llm", "tools", "prompt", "tools_renderer", "stop_sequence"],
+        hub_repo="hwchase17/xml-agent-convo",
+    ),
+    "OpenAI Tools Agent": AgentSpec(
+        func=validate_and_create_openai_tools_agent,
+        prompt=None,
+        fields=["llm", "tools", "prompt"],
+        hub_repo=None,
+    ),
+    "JSON Chat Agent": AgentSpec(
+        func=validate_and_create_json_chat_agent,
+        prompt=None,
+        fields=["llm", "tools", "prompt", "tools_renderer", "stop_sequence"],
+        hub_repo="hwchase17/react-chat-json",
+    ),
+}
+
+
+def get_agents_list():
+    return list(AGENTS.keys())

src/backend/base/langflow/base/constants.py

@@ -6,6 +6,7 @@ Constants:
 - NODE_FORMAT_ATTRIBUTES: A list of attributes used for formatting nodes.
 - FIELD_FORMAT_ATTRIBUTES: A list of attributes used for formatting fields.
 """
+
 STREAM_INFO_TEXT = "Stream the response from the model. Streaming works only in Chat."
 
 NODE_FORMAT_ATTRIBUTES = ["beta", "icon", "display_name", "description"]

src/backend/base/langflow/base/models/model.py

@@ -2,7 +2,7 @@ from typing import Optional, Union
 
 from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_core.language_models.llms import LLM
-from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
 
 from langflow.custom import CustomComponent
 
@@ -31,6 +31,47 @@ class LCModelComponent(CustomComponent):
             self.status = result
         return result
 
+    def build_status_message(self, message: AIMessage):
+        """
+        Builds a status message from an AIMessage object.
+
+        Args:
+            message (AIMessage): The AIMessage object to build the status message from.
+
+        Returns:
+            The status message.
+        """
+        if message.response_metadata:
+            # Build a well formatted status message
+            content = message.content
+            response_metadata = message.response_metadata
+            openai_keys = ["token_usage", "model_name", "finish_reason"]
+            inner_openai_keys = ["completion_tokens", "prompt_tokens", "total_tokens"]
+            anthropic_keys = ["model", "usage", "stop_reason"]
+            inner_anthropic_keys = ["input_tokens", "output_tokens"]
+            if all(key in response_metadata for key in openai_keys) and all(
+                key in response_metadata["token_usage"] for key in inner_openai_keys
+            ):
+                token_usage = response_metadata["token_usage"]
+                completion_tokens = token_usage["completion_tokens"]
+                prompt_tokens = token_usage["prompt_tokens"]
+                total_tokens = token_usage["total_tokens"]
+                finish_reason = response_metadata["finish_reason"]
+                status_message = f"Tokens:\n- Input: {prompt_tokens}\nOutput: {completion_tokens}\nTotal Tokens: {total_tokens}\nStop Reason: {finish_reason}\nResponse: {content}"
+            elif all(key in response_metadata for key in anthropic_keys) and all(
+                key in response_metadata["usage"] for key in inner_anthropic_keys
+            ):
+                usage = response_metadata["usage"]
+                input_tokens = usage["input_tokens"]
+                output_tokens = usage["output_tokens"]
+                stop_reason = response_metadata["stop_reason"]
+                status_message = f"Tokens:\n- Input: {input_tokens}\n- Output: {output_tokens}\nStop Reason: {stop_reason}\nResponse: {content}"
+            else:
+                status_message = f"Response: {content}"
+        else:
+            status_message = f"Response: {message.content}"
+        return status_message
+
     def get_chat_result(
         self, runnable: BaseChatModel, stream: bool, input_value: str, system_message: Optional[str] = None
     ):
@@ -46,5 +87,9 @@ class LCModelComponent(CustomComponent):
         else:
             message = runnable.invoke(messages)
             result = message.content
-            self.status = result
+            if isinstance(message, AIMessage):
+                status_message = self.build_status_message(message)
+                self.status = status_message
+            else:
+                self.status = result
             return result

src/backend/base/langflow/components/agents/ToolCallingAgent.py

@@ -0,0 +1,64 @@
+from typing import List, Optional
+
+from langchain.agents.tool_calling_agent.base import create_tool_calling_agent
+from langchain_core.prompts import ChatPromptTemplate
+
+from langflow.base.agents.agent import LCAgentComponent
+from langflow.field_typing import BaseLanguageModel, Text, Tool
+from langflow.schema.schema import Record
+
+
+class ToolCallingAgentComponent(LCAgentComponent):
+    display_name: str = "Tool Calling Agent"
+    description: str = "Agent that uses tools. Only models that are compatible with function calling are supported."
+
+    def build_config(self):
+        return {
+            "llm": {"display_name": "LLM"},
+            "tools": {"display_name": "Tools"},
+            "user_prompt": {
+                "display_name": "Prompt",
+                "multiline": True,
+                "info": "This prompt must contain 'input' key.",
+            },
+            "handle_parsing_errors": {
+                "display_name": "Handle Parsing Errors",
+                "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.",
+                "advanced": True,
+            },
+            "memory": {
+                "display_name": "Memory",
+                "info": "Memory to use for the agent.",
+            },
+            "input_value": {
+                "display_name": "Inputs",
+                "info": "Input text to pass to the agent.",
+            },
+        }
+
+    async def build(
+        self,
+        input_value: str,
+        llm: BaseLanguageModel,
+        tools: List[Tool],
+        user_prompt: str = "{input}",
+        message_history: Optional[List[Record]] = None,
+        system_message: str = "You are a helpful assistant",
+        handle_parsing_errors: bool = True,
+    ) -> Text:
+        if "input" not in user_prompt:
+            raise ValueError("Prompt must contain 'input' key.")
+        messages = [
+            ("system", system_message),
+            (
+                "placeholder",
+                "{chat_history}",
+            ),
+            ("human", user_prompt),
+            ("placeholder", "{agent_scratchpad}"),
+        ]
+        prompt = ChatPromptTemplate.from_messages(messages)
+        agent = create_tool_calling_agent(llm, tools, prompt)
+        result = await self.run_agent(agent, input_value, tools, message_history, handle_parsing_errors)
+        self.status = result
+        return result

src/backend/base/langflow/components/agents/XMLAgent.py

@@ -1,10 +1,12 @@
 from typing import List, Optional
 
 from langchain.agents import create_xml_agent
-from langchain_core.prompts import PromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
+
 
 from langflow.base.agents.agent import LCAgentComponent
-from langflow.field_typing import BaseLanguageModel, BaseMemory, Text, Tool
+from langflow.field_typing import BaseLanguageModel, Text, Tool
+from langflow.schema.schema import Record
 
 
 class XMLAgentComponent(LCAgentComponent):
@@ -15,7 +17,7 @@ class XMLAgentComponent(LCAgentComponent):
         return {
             "llm": {"display_name": "LLM"},
             "tools": {"display_name": "Tools"},
-            "prompt": {
+            "user_prompt": {
                 "display_name": "Prompt",
                 "multiline": True,
                 "info": "This prompt must contain 'tools' and 'agent_scratchpad' keys.",
@@ -43,6 +45,11 @@ class XMLAgentComponent(LCAgentComponent):
             Question: {input}
             {agent_scratchpad}""",
             },
+            "system_message": {
+                "display_name": "System Message",
+                "info": "System message to be passed to the LLM.",
+                "advanced": True,
+            },
             "tool_template": {
                 "display_name": "Tool Template",
                 "info": "Template for rendering tools in the prompt. Tools have 'name' and 'description' keys.",
@@ -53,9 +60,9 @@ class XMLAgentComponent(LCAgentComponent):
                 "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.",
                 "advanced": True,
             },
-            "memory": {
-                "display_name": "Memory",
-                "info": "Memory to use for the agent.",
+            "message_history": {
+                "display_name": "Message History",
+                "info": "Message history to pass to the agent.",
             },
             "input_value": {
                 "display_name": "Inputs",
@@ -68,12 +75,13 @@ class XMLAgentComponent(LCAgentComponent):
         input_value: str,
         llm: BaseLanguageModel,
         tools: List[Tool],
-        prompt: str,
-        memory: Optional[BaseMemory] = None,
+        user_prompt: str = "{input}",
+        system_message: str = "You are a helpful assistant",
+        message_history: Optional[List[Record]] = None,
         tool_template: str = "{name}: {description}",
         handle_parsing_errors: bool = True,
     ) -> Text:
-        if "input" not in prompt:
+        if "input" not in user_prompt:
             raise ValueError("Prompt must contain 'input' key.")
 
         def render_tool_description(tools):
@@ -81,9 +89,23 @@ class XMLAgentComponent(LCAgentComponent):
                 [tool_template.format(name=tool.name, description=tool.description, args=tool.args) for tool in tools]
             )
 
-        prompt_template = PromptTemplate.from_template(prompt)
-        input_variables = prompt_template.input_variables
-        agent = create_xml_agent(llm, tools, prompt_template, tools_renderer=render_tool_description)
-        result = await self.run_agent(agent, input_value, input_variables, tools, memory, handle_parsing_errors)
+        messages = [
+            ("system", system_message),
+            (
+                "placeholder",
+                "{chat_history}",
+            ),
+            ("human", user_prompt),
+            ("placeholder", "{agent_scratchpad}"),
+        ]
+        prompt = ChatPromptTemplate.from_messages(messages)
+        agent = create_xml_agent(llm, tools, prompt, tools_renderer=render_tool_description)
+        result = await self.run_agent(
+            agent=agent,
+            inputs=input_value,
+            tools=tools,
+            message_history=message_history,
+            handle_parsing_errors=handle_parsing_errors,
+        )
         self.status = result
         return result

src/backend/base/langflow/components/experimental/AgentComponent.py

@@ -0,0 +1,185 @@
+from typing import Any, List, Optional, cast
+
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.prompts.chat import HumanMessagePromptTemplate, SystemMessagePromptTemplate
+
+from langflow.base.agents.agent import LCAgentComponent
+from langflow.base.agents.utils import AGENTS, AgentSpec, get_agents_list
+from langflow.field_typing import BaseLanguageModel, Text, Tool
+from langflow.schema.dotdict import dotdict
+from langflow.schema.schema import Record
+
+
+class AgentComponent(LCAgentComponent):
+    display_name = "Agent"
+    description = "Run any LangChain agent using a simplified interface."
+    field_order = [
+        "agent_name",
+        "llm",
+        "tools",
+        "prompt",
+        "tool_template",
+        "handle_parsing_errors",
+        "memory",
+        "input_value",
+    ]
+
+    def build_config(self):
+        return {
+            "agent_name": {
+                "display_name": "Agent",
+                "info": "The agent to use.",
+                "refresh_button": True,
+                "real_time_refresh": True,
+                "options": get_agents_list(),
+            },
+            "llm": {"display_name": "LLM"},
+            "tools": {"display_name": "Tools"},
+            "user_prompt": {
+                "display_name": "Prompt",
+                "multiline": True,
+                "info": "This prompt must contain 'tools' and 'agent_scratchpad' keys.",
+            },
+            "system_message": {
+                "display_name": "System Message",
+                "info": "System message to be passed to the LLM.",
+                "advanced": True,
+            },
+            "tool_template": {
+                "display_name": "Tool Template",
+                "info": "Template for rendering tools in the prompt. Tools have 'name' and 'description' keys.",
+                "advanced": True,
+            },
+            "handle_parsing_errors": {
+                "display_name": "Handle Parsing Errors",
+                "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.",
+                "advanced": True,
+            },
+            "message_history": {
+                "display_name": "Message History",
+                "info": "Message history to pass to the agent.",
+            },
+            "input_value": {
+                "display_name": "Input",
+                "info": "Input text to pass to the agent.",
+            },
+            "langchain_hub_api_key": {
+                "display_name": "LangChain Hub API Key",
+                "info": "API key to use for LangChain Hub. If provided, prompts will be fetched from LangChain Hub.",
+                "advanced": True,
+            },
+        }
+
+    def get_system_and_user_message_from_prompt(self, prompt: Any):
+        """
+        Extracts the system message and user prompt from a given prompt object.
+
+        Args:
+            prompt (Any): The prompt object from which to extract the system message and user prompt.
+
+        Returns:
+            Tuple[Optional[str], Optional[str]]: A tuple containing the system message and user prompt.
+                If the prompt object does not have any messages, both values will be None.
+        """
+        if hasattr(prompt, "messages"):
+            system_message = None
+            user_prompt = None
+            for message in prompt.messages:
+                if isinstance(message, SystemMessagePromptTemplate):
+                    s_prompt = message.prompt
+                    if isinstance(s_prompt, list):
+                        s_template = " ".join([cast(str, s.template) for s in s_prompt if hasattr(s, "template")])
+                    elif hasattr(s_prompt, "template"):
+                        s_template = s_prompt.template
+                    system_message = s_template
+                elif isinstance(message, HumanMessagePromptTemplate):
+                    h_prompt = message.prompt
+                    if isinstance(h_prompt, list):
+                        h_template = " ".join([cast(str, h.template) for h in h_prompt if hasattr(h, "template")])
+                    elif hasattr(h_prompt, "template"):
+                        h_template = h_prompt.template
+                    user_prompt = h_template
+            return system_message, user_prompt
+        return None, None
+
+    def update_build_config(self, build_config: dotdict, field_value: Any, field_name: Text | None = None):
+        """
+        Updates the build configuration based on the provided field value and field name.
+
+        Args:
+            build_config (dotdict): The build configuration to be updated.
+            field_value (Any): The value of the field being updated.
+            field_name (Text | None, optional): The name of the field being updated. Defaults to None.
+
+        Returns:
+            dotdict: The updated build configuration.
+        """
+        if field_name == "agent":
+            build_config["agent"]["options"] = get_agents_list()
+            if field_value in AGENTS:
+                # if langchain_hub_api_key is provided, fetch the prompt from LangChain Hub
+                if build_config["langchain_hub_api_key"]["value"] and AGENTS[field_value].hub_repo:
+                    from langchain import hub
+
+                    hub_repo: str | None = AGENTS[field_value].hub_repo
+                    if hub_repo:
+                        hub_api_key: str = build_config["langchain_hub_api_key"]["value"]
+                        prompt = hub.pull(hub_repo, api_key=hub_api_key)
+                        system_message, user_prompt = self.get_system_and_user_message_from_prompt(prompt)
+                        if system_message:
+                            build_config["system_message"]["value"] = system_message
+                        if user_prompt:
+                            build_config["user_prompt"]["value"] = user_prompt
+
+                if AGENTS[field_value].prompt:
+                    build_config["user_prompt"]["value"] = AGENTS[field_value].prompt
+                else:
+                    build_config["user_prompt"]["value"] = "{input}"
+            fields = AGENTS[field_value].fields
+            for field in ["llm", "tools", "prompt", "tools_renderer"]:
+                if field not in fields:
+                    build_config[field]["show"] = False
+        return build_config
+
+    async def build(
+        self,
+        agent_name: str,
+        input_value: str,
+        llm: BaseLanguageModel,
+        tools: List[Tool],
+        system_message: str = "You are a helpful assistant. Help the user answer any questions.",
+        user_prompt: str = "{input}",
+        message_history: Optional[List[Record]] = None,
+        tool_template: str = "{name}: {description}",
+        handle_parsing_errors: bool = True,
+    ) -> Text:
+        agent_spec: Optional[AgentSpec] = AGENTS.get(agent_name)
+        if agent_spec is None:
+            raise ValueError(f"{agent_name} not found.")
+
+        def render_tool_description(tools):
+            return "\n".join(
+                [tool_template.format(name=tool.name, description=tool.description, args=tool.args) for tool in tools]
+            )
+
+        messages = [
+            ("system", system_message),
+            (
+                "placeholder",
+                "{chat_history}",
+            ),
+            ("human", user_prompt),
+            ("placeholder", "{agent_scratchpad}"),
+        ]
+        prompt = ChatPromptTemplate.from_messages(messages)
+        agent_func = agent_spec.func
+        agent = agent_func(llm, tools, prompt, render_tool_description, True)
+        result = await self.run_agent(
+            agent=agent,
+            inputs=input_value,
+            tools=tools,
+            message_history=message_history,
+            handle_parsing_errors=handle_parsing_errors,
+        )
+        self.status = result
+        return result

src/backend/base/langflow/components/experimental/__init__.py

@@ -10,8 +10,10 @@ from .RunFlow import RunFlowComponent
 from .RunnableExecutor import RunnableExecComponent
 from .SQLExecutor import SQLExecutorComponent
 from .SubFlow import SubFlowComponent
+from .AgentComponent import AgentComponent
 
 __all__ = [
+    "AgentComponent",
     "ClearMessageHistoryComponent",
     "ExtractKeyFromRecordComponent",
     "FlowToolComponent",

src/backend/base/langflow/components/models/AzureOpenAIModel.py

@@ -105,7 +105,7 @@ class AzureChatOpenAIComponent(LCModelComponent):
         system_message: Optional[str] = None,
         max_tokens: Optional[int] = 1000,
         stream: bool = False,
-    ) -> BaseLanguageModel:
+    ) -> Text:
         if api_key:
             secret_api_key = SecretStr(api_key)
         else:

src/backend/base/langflow/components/models/ChatLiteLLMModel.py

@@ -142,7 +142,7 @@ class ChatLiteLLMModelComponent(LCModelComponent):
         max_retries: int = 6,
         verbose: bool = False,
         system_message: Optional[str] = None,
-    ) -> BaseLanguageModel:
+    ) -> Text:
         try:
             import litellm  # type: ignore
 

src/backend/base/langflow/components/models/OpenAIModel.py

@@ -40,6 +40,7 @@ class OpenAIModelComponent(LCModelComponent):
                 "display_name": "Model Name",
                 "advanced": False,
                 "options": [
+                    "gpt-4-turbo-2024-04-09",
                     "gpt-4-turbo-preview",
                     "gpt-3.5-turbo",
                     "gpt-4-0125-preview",

src/backend/base/langflow/components/vectorstores/AstraDB.py

@@ -1,5 +1,6 @@
-from typing import List, Optional
+from typing import List, Optional, Union
 
+from langchain.schema import BaseRetriever
 from langchain_astradb import AstraDBVectorStore
 from langchain_astradb.utils.astradb import SetupMode
 
@@ -110,7 +111,7 @@ class AstraDBVectorStoreComponent(CustomComponent):
         metadata_indexing_include: Optional[List[str]] = None,
         metadata_indexing_exclude: Optional[List[str]] = None,
         collection_indexing_policy: Optional[dict] = None,
-    ) -> VectorStore:
+    ) -> Union[VectorStore, BaseRetriever]:
         try:
             setup_mode_value = SetupMode[setup_mode.upper()]
         except KeyError:

src/backend/base/langflow/graph/graph/base.py

@@ -1,5 +1,7 @@
 import asyncio
+import uuid
 from collections import defaultdict, deque
+from functools import partial
 from itertools import chain
 from typing import TYPE_CHECKING, Callable, Coroutine, Dict, Generator, List, Optional, Type, Union
 
@@ -16,6 +18,7 @@ from langflow.graph.vertex.types import ChatVertex, FileToolVertex, LLMVertex, R
 from langflow.interface.tools.constants import FILE_TOOLS
 from langflow.schema import Record
 from langflow.schema.schema import INPUT_FIELD_NAME, InputType
+from langflow.services.deps import get_chat_service
 
 if TYPE_CHECKING:
     from langflow.graph.schema import ResultData
@@ -29,6 +32,7 @@ class Graph:
         nodes: List[Dict],
         edges: List[Dict[str, str]],
         flow_id: Optional[str] = None,
+        user_id: Optional[str] = None,
     ) -> None:
         """
         Initializes a new instance of the Graph class.
@@ -44,6 +48,7 @@ class Graph:
         self._runs = 0
         self._updates = 0
         self.flow_id = flow_id
+        self.user_id = user_id
         self._is_input_vertices: List[str] = []
         self._is_output_vertices: List[str] = []
         self._is_state_vertices: List[str] = []
@@ -164,13 +169,14 @@ class Graph:
             raise ValueError("Run ID not set")
         return self._run_id
 
-    def set_run_id(self, run_id: str):
+    def set_run_id(self, run_id: str | uuid.UUID):
         """
         Sets the ID of the current run.
 
         Args:
             run_id (str): The run ID.
         """
+        run_id = str(run_id)
         for vertex in self.vertices:
             self.state_manager.subscribe(run_id, vertex.update_graph_state)
         self._run_id = run_id
@@ -446,7 +452,7 @@ class Graph:
         self.__init__(**state)
 
     @classmethod
-    def from_payload(cls, payload: Dict, flow_id: Optional[str] = None) -> "Graph":
+    def from_payload(cls, payload: Dict, flow_id: Optional[str] = None, user_id: Optional[str] = None) -> "Graph":
         """
         Creates a graph from a payload.
 
@@ -461,7 +467,7 @@ class Graph:
         try:
             vertices = payload["nodes"]
             edges = payload["edges"]
-            return cls(vertices, edges, flow_id)
+            return cls(vertices, edges, flow_id, user_id)
         except KeyError as exc:
             logger.exception(exc)
             if "nodes" not in payload and "edges" not in payload:
@@ -748,31 +754,53 @@ class Graph:
     async def process(self, start_component_id: Optional[str] = None) -> "Graph":
         """Processes the graph with vertices in each layer run in parallel."""
 
-        self.sort_vertices(start_component_id=start_component_id)
-        vertices_layers = self.sorted_vertices_layers
+        first_layer = self.sort_vertices(start_component_id=start_component_id)
         vertex_task_run_count: Dict[str, int] = {}
-        for layer_index, layer in enumerate(vertices_layers):
+        to_process = deque(first_layer)
+        layer_index = 0
+        chat_service = get_chat_service()
+        run_id = uuid.uuid4()
+        self.set_run_id(run_id)
+        while to_process:
+            current_batch = list(to_process)  # Copy current deque items to a list
+            to_process.clear()  # Clear the deque for new items
             tasks = []
-            for vertex_id in layer:
+            for vertex_id in current_batch:
                 vertex = self.get_vertex(vertex_id)
+                lock = chat_service._cache_locks[self.run_id]
+                set_cache_coro = partial(chat_service.set_cache, flow_id=self.run_id)
                 task = asyncio.create_task(
-                    vertex.build(),
+                    self.build_vertex(
+                        lock=lock,
+                        set_cache_coro=set_cache_coro,
+                        vertex_id=vertex_id,
+                        user_id=self.user_id,
+                        inputs_dict={},
+                    ),
                     name=f"{vertex.display_name} Run {vertex_task_run_count.get(vertex_id, 0)}",
                 )
                 tasks.append(task)
                 vertex_task_run_count[vertex_id] = vertex_task_run_count.get(vertex_id, 0) + 1
+
             logger.debug(f"Running layer {layer_index} with {len(tasks)} tasks")
-            await self._execute_tasks(tasks)
+            next_runnable_vertices = await self._execute_tasks(tasks)
+            to_process.extend(next_runnable_vertices)
+
         logger.debug("Graph processing complete")
         return self
 
-    async def _execute_tasks(self, tasks):
+    async def _execute_tasks(self, tasks: List[asyncio.Task]) -> List[str]:
         """Executes tasks in parallel, handling exceptions for each task."""
         results = []
         for i, task in enumerate(asyncio.as_completed(tasks)):
             try:
                 result = await task
-                results.append(result)
+                if isinstance(result, tuple) and len(result) == 7:
+                    # Get the next runnable vertices
+                    next_runnable_vertices = result[0]
+                    results.extend(next_runnable_vertices)
+                else:
+                    raise ValueError(f"Invalid result: {result}")
             except Exception as e:
                 # Log the exception along with the task name for easier debugging
                 # task_name = task.get_name()

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, world!).json

@@ -161,7 +161,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-2024-04-09\",\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -222,6 +222,7 @@
                 "file_path": "",
                 "password": false,
                 "options": [
+                  "gpt-4-turbo-2024-04-09",
                   "gpt-4-turbo-preview",
                   "gpt-3.5-turbo",
                   "gpt-4-0125-preview",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json

@@ -494,7 +494,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-2024-04-09\",\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -555,6 +555,7 @@
                 "file_path": "",
                 "password": false,
                 "options": [
+                  "gpt-4-turbo-2024-04-09",
                   "gpt-4-turbo-preview",
                   "gpt-3.5-turbo",
                   "gpt-4-0125-preview",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json

@@ -651,7 +651,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-2024-04-09\",\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -712,6 +712,7 @@
                 "file_path": "",
                 "password": false,
                 "options": [
+                  "gpt-4-turbo-2024-04-09",
                   "gpt-4-turbo-preview",
                   "gpt-3.5-turbo",
                   "gpt-4-0125-preview",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json

@@ -751,7 +751,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-2024-04-09\",\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -812,6 +812,7 @@
                 "file_path": "",
                 "password": false,
                 "options": [
+                  "gpt-4-turbo-2024-04-09",
                   "gpt-4-turbo-preview",
                   "gpt-3.5-turbo",
                   "gpt-4-0125-preview",

src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json

@@ -884,7 +884,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-2024-04-09\",\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -945,6 +945,7 @@
                 "file_path": "",
                 "password": false,
                 "options": [
+                  "gpt-4-turbo-2024-04-09",
                   "gpt-4-turbo-preview",
                   "gpt-3.5-turbo",
                   "gpt-4-0125-preview",
@@ -1270,7 +1271,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": [\n                    \"gpt-4-turbo-2024-04-09\",\n                    \"gpt-4-turbo-preview\",\n                    \"gpt-3.5-turbo\",\n                    \"gpt-4-0125-preview\",\n                    \"gpt-4-1106-preview\",\n                    \"gpt-4-vision-preview\",\n                    \"gpt-3.5-turbo-0125\",\n                    \"gpt-3.5-turbo-1106\",\n                ],\n                \"value\": \"gpt-4-turbo-preview\",\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str,\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -1331,6 +1332,7 @@
                 "file_path": "",
                 "password": false,
                 "options": [
+                  "gpt-4-turbo-2024-04-09",
                   "gpt-4-turbo-preview",
                   "gpt-3.5-turbo",
                   "gpt-4-0125-preview",

src/backend/base/langflow/interface/run.py

@@ -1,9 +1,5 @@
-from typing import Dict, Tuple
-
 from loguru import logger
 
-from langflow.graph import Graph
-
 
 def get_memory_key(langchain_object):
     """

src/backend/base/langflow/main.py

@@ -11,6 +11,7 @@ from fastapi.responses import FileResponse
 from fastapi.staticfiles import StaticFiles
 from loguru import logger
 from rich import print as rprint
+from starlette.middleware.base import BaseHTTPMiddleware
 
 from langflow.api import router
 from langflow.initial_setup.setup import create_or_update_starter_projects
@@ -20,15 +21,38 @@ from langflow.services.utils import initialize_services, teardown_services
 from langflow.utils.logger import configure
 
 
+class JavaScriptMIMETypeMiddleware(BaseHTTPMiddleware):
+    async def dispatch(self, request: Request, call_next):
+        try:
+            response = await call_next(request)
+        except Exception as exc:
+            logger.error(exc)
+            raise exc
+        if "files/" not in request.url.path and request.url.path.endswith(".js") and response.status_code == 200:
+            response.headers["Content-Type"] = "text/javascript"
+        return response
+
+
 def get_lifespan(fix_migration=False, socketio_server=None):
+    from langflow.version import __version__  # type: ignore
+
     @asynccontextmanager
     async def lifespan(app: FastAPI):
         nest_asyncio.apply()
-        initialize_services(fix_migration=fix_migration, socketio_server=socketio_server)
-        setup_llm_caching()
-        LangfuseInstance.update()
-        create_or_update_starter_projects()
-        yield
+        # Startup message
+        if __version__:
+            rprint(f"[bold green]Starting Langflow v{__version__}...[/bold green]")
+        else:
+            rprint("[bold green]Starting Langflow...[/bold green]")
+        try:
+            initialize_services(fix_migration=fix_migration, socketio_server=socketio_server)
+            setup_llm_caching()
+            LangfuseInstance.update()
+            create_or_update_starter_projects()
+            yield
+        except Exception as exc:
+            if "langflow migration --fix" not in str(exc):
+                logger.error(exc)
         # Shutdown message
         rprint("[bold red]Shutting down Langflow...[/bold red]")
         teardown_services()
@@ -52,6 +76,7 @@ def create_app():
         allow_methods=["*"],
         allow_headers=["*"],
     )
+    app.add_middleware(JavaScriptMIMETypeMiddleware)
 
     @app.middleware("http")
     async def flatten_query_string_lists(request: Request, call_next):

src/backend/base/langflow/processing/process.py

@@ -243,7 +243,6 @@ def apply_tweaks(node: Dict[str, Any], node_tweaks: Dict[str, Any]) -> None:
 
     for tweak_name, tweak_value in node_tweaks.items():
         if tweak_name not in template_data:
-            logger.warning(f"Node {node.get('id')} does not have a tweak named {tweak_name}")
             continue
         if tweak_name in template_data:
             key = "file_path" if template_data[tweak_name]["type"] == "file" else "value"
@@ -256,21 +255,24 @@ def apply_tweaks_on_vertex(vertex: Vertex, node_tweaks: Dict[str, Any]) -> None:
             vertex.params[tweak_name] = tweak_value
 
 
-def process_tweaks(graph_data: Dict[str, Any], tweaks: Union["Tweaks", Dict[str, Dict[str, Any]]]) -> Dict[str, Any]:
+def process_tweaks(
+    graph_data: Dict[str, Any], tweaks: Union["Tweaks", Dict[str, Dict[str, Any]]], stream: bool = False
+) -> Dict[str, Any]:
     """
     This function is used to tweak the graph data using the node id and the tweaks dict.
 
     :param graph_data: The dictionary containing the graph data. It must contain a 'data' key with
                        'nodes' as its child or directly contain 'nodes' key. Each node should have an 'id' and 'data'.
     :param tweaks: The dictionary containing the tweaks. The keys can be the node id or the name of the tweak.
-                     The values can be a dictionary containing the tweaks for the node or the value of the tweak.
+                   The values can be a dictionary containing the tweaks for the node or the value of the tweak.
+    :param stream: A boolean flag indicating whether streaming should be deactivated across all components or not. Default is False.
     :return: The modified graph_data dictionary.
-
     :raises ValueError: If the input is not in the expected format.
     """
     if not isinstance(tweaks, dict):
         tweaks = tweaks.model_dump()
-
+    if "stream" not in tweaks:
+        tweaks["stream"] = stream
     nodes = validate_input(graph_data, tweaks)
     nodes_map = {node.get("id"): node for node in nodes}
     nodes_display_name_map = {node.get("data", {}).get("node", {}).get("display_name"): node for node in nodes}

src/backend/base/langflow/schema/schema.py

@@ -2,7 +2,9 @@ import copy
 from typing import Literal, Optional
 
 from langchain_core.documents import Document
+from langchain_core.messages import BaseMessage
 from pydantic import BaseModel, model_validator
+from langchain_core.messages import HumanMessage, AIMessage, BaseMessage
 
 
 class Record(BaseModel):
@@ -54,6 +56,21 @@ class Record(BaseModel):
         data["text"] = document.page_content
         return cls(data=data, text_key="text")
 
+    @classmethod
+    def from_lc_message(cls, message: BaseMessage) -> "Record":
+        """
+        Converts a BaseMessage to a Record.
+
+        Args:
+            message (BaseMessage): The BaseMessage to convert.
+
+        Returns:
+            Record: The converted Record.
+        """
+        data = {"text": message.content}
+        data["metadata"] = message.to_json()
+        return cls(data=data, text_key="text")
+
     def __add__(self, other: "Record") -> "Record":
         """
         Combines the data of two records by attempting to add values for overlapping keys
@@ -85,6 +102,26 @@ class Record(BaseModel):
         text = self.data.pop(self.text_key, self.default_value)
         return Document(page_content=text, metadata=self.data)
 
+    def to_lc_message(self) -> BaseMessage:
+        """
+        Converts the Record to a BaseMessage.
+
+        Returns:
+            BaseMessage: The converted BaseMessage.
+        """
+        # The idea of this function is to be a helper to convert a Record to a BaseMessage
+        # It will use the "sender" key to determine if the message is Human or AI
+        # If the key is not present, it will default to AI
+        # But first we check if all required keys are present in the data dictionary
+        # they are: "text", "sender"
+        if not all(key in self.data for key in ["text", "sender"]):
+            raise ValueError(f"Missing required keys ('text', 'sender') in Record: {self.data}")
+        sender = self.data.get("sender", "Machine")
+        text = self.data.get("text", "")
+        if sender == "User":
+            return HumanMessage(content=text)
+        return AIMessage(content=text)
+
     def __getattr__(self, key):
         """
         Allows attribute-like access to the data dictionary.

src/backend/base/langflow/services/database/models/api_key/crud.py

@@ -24,6 +24,7 @@ def create_api_key(session: Session, api_key_create: ApiKeyCreate, user_id: UUID
         api_key=generated_api_key,
         name=api_key_create.name,
         user_id=user_id,
+        created_at=api_key_create.created_at or datetime.datetime.now(datetime.timezone.utc),
     )
 
     session.add(api_key)

src/backend/base/langflow/services/database/models/api_key/model.py

@@ -3,17 +3,18 @@ from typing import TYPE_CHECKING, Optional
 from uuid import UUID, uuid4
 
 from pydantic import field_validator, validator
-from sqlmodel import Field, Relationship, SQLModel, Column, func, DateTime
+from sqlmodel import Column, DateTime, Field, Relationship, SQLModel, func
 
 if TYPE_CHECKING:
     from langflow.services.database.models.user import User
 
 
+def utc_now():
+    return datetime.now(timezone.utc)
+
+
 class ApiKeyBase(SQLModel):
     name: Optional[str] = Field(index=True, nullable=True, default=None)
-    created_at: datetime = Field(
-        default=None, sa_column=Column(DateTime(timezone=True), server_default=func.now(), nullable=False)
-    )
     last_used_at: Optional[datetime] = Field(default=None, nullable=True)
     total_uses: int = Field(default=0)
     is_active: bool = Field(default=True)
@@ -21,7 +22,9 @@ class ApiKeyBase(SQLModel):
 
 class ApiKey(ApiKeyBase, table=True):
     id: UUID = Field(default_factory=uuid4, primary_key=True, unique=True)
-
+    created_at: datetime = Field(
+        default=None, sa_column=Column(DateTime(timezone=True), server_default=func.now(), nullable=False)
+    )
     api_key: str = Field(index=True, unique=True)
     # User relationship
     # Delete API keys when user is deleted
@@ -34,10 +37,11 @@ class ApiKey(ApiKeyBase, table=True):
 class ApiKeyCreate(ApiKeyBase):
     api_key: Optional[str] = None
     user_id: Optional[UUID] = None
+    created_at: Optional[datetime] = Field(default_factory=utc_now)
 
     @field_validator("created_at", mode="before")
     def set_created_at(cls, v):
-        return v or datetime.now(timezone.utc)
+        return v or utc_now()
 
 
 class UnmaskedApiKeyRead(ApiKeyBase):

src/backend/base/langflow/services/database/service.py

@@ -133,7 +133,7 @@ class DatabaseService(Service):
         alembic_cfg = Config(stdout=buffer)
         # alembic_cfg.attributes["connection"] = session
         alembic_cfg.set_main_option("script_location", str(self.script_location))
-        alembic_cfg.set_main_option("sqlalchemy.url", self.database_url)
+        alembic_cfg.set_main_option("sqlalchemy.url", self.database_url.replace('%', '%%'))
 
         should_initialize_alembic = False
         with Session(self.engine) as session:

src/backend/base/langflow/services/settings/base.py

@@ -121,7 +121,7 @@ class Settings(BaseSettings):
 
             # Define the app name and author
             app_name = "langflow"
-            app_author = "logspace"
+            app_author = "langflow"
 
             # Get the cache directory for the application
             cache_dir = user_cache_dir(app_name, app_author)

src/backend/base/langflow/services/utils.py

@@ -163,7 +163,6 @@ def initialize_services(fix_migration: bool = False, socketio_server=None):
     try:
         initialize_database(fix_migration=fix_migration)
     except Exception as exc:
-        logger.error(exc)
         raise exc
     setup_superuser(get_service(ServiceType.SETTINGS_SERVICE), next(get_session()))
     try:

src/backend/base/langflow/utils/logger.py

@@ -54,22 +54,24 @@ def configure(log_level: Optional[str] = None, log_file: Optional[Path] = None,
 
     if not log_file:
         cache_dir = Path(user_cache_dir("langflow"))
+        logger.debug(f"Cache directory: {cache_dir}")
         log_file = cache_dir / "langflow.log"
+        logger.debug(f"Log file: {log_file}")
+    try:
+        log_file = Path(log_file)
+        log_file.parent.mkdir(parents=True, exist_ok=True)
 
-    log_file = Path(log_file)
-    log_file.parent.mkdir(parents=True, exist_ok=True)
-
-    logger.add(
-        sink=str(log_file),
-        level=log_level.upper(),
-        format=log_format,
-        rotation="10 MB",  # Log rotation based on file size
-        serialize=True,
-    )
+        logger.add(
+            sink=str(log_file),
+            level=log_level.upper(),
+            format=log_format,
+            rotation="10 MB",  # Log rotation based on file size
+            serialize=True,
+        )
+    except Exception as exc:
+        logger.error(f"Error setting up log file: {exc}")
 
     logger.debug(f"Logger set up with log level: {log_level}")
-    if log_file:
-        logger.debug(f"Log file: {log_file}")
 
     setup_uvicorn_logger()
     setup_gunicorn_logger()

src/backend/base/poetry.lock

@@ -2,87 +2,87 @@
 
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+version = "3.9.5"
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 ]
 
 [package.dependencies]
@@ -828,22 +828,23 @@ test = ["objgraph", "psutil"]
 
 [[package]]
 name = "gunicorn"
-version = "21.2.0"
+version = "22.0.0"
 description = "WSGI HTTP Server for UNIX"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.7"
 files = [
-    {file = "gunicorn-21.2.0-py3-none-any.whl", hash = "sha256:3213aa5e8c24949e792bcacfc176fef362e7aac80b76c56f6b5122bf350722f0"},
-    {file = "gunicorn-21.2.0.tar.gz", hash = "sha256:88ec8bff1d634f98e61b9f65bc4bf3cd918a90806c6f5c48bc5603849ec81033"},
+    {file = "gunicorn-22.0.0-py3-none-any.whl", hash = "sha256:350679f91b24062c86e386e198a15438d53a7a8207235a78ba1b53df4c4378d9"},
+    {file = "gunicorn-22.0.0.tar.gz", hash = "sha256:4a0b436239ff76fb33f11c07a16482c521a7e09c1ce3cc293c2330afe01bec63"},
 ]
 
 [package.dependencies]
 packaging = "*"
 
 [package.extras]
-eventlet = ["eventlet (>=0.24.1)"]
+eventlet = ["eventlet (>=0.24.1,!=0.36.0)"]
 gevent = ["gevent (>=1.4.0)"]
 setproctitle = ["setproctitle"]
+testing = ["coverage", "eventlet", "gevent", "pytest", "pytest-cov"]
 tornado = ["tornado (>=0.2)"]
 
 [[package]]
@@ -1063,19 +1064,19 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
 
 [[package]]
 name = "langchain-community"
-version = "0.0.32"
+version = "0.0.33"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_community-0.0.32-py3-none-any.whl", hash = "sha256:406977009999952d0705de3806de2b4867e9bb8eda8ca154a59c7a8ed58da38d"},
-    {file = "langchain_community-0.0.32.tar.gz", hash = "sha256:1510217d646c8380f54e9850351f6d2a0b0dd73c501b666c6f4b40baa8160b29"},
+    {file = "langchain_community-0.0.33-py3-none-any.whl", hash = "sha256:830f0d5f4ff9638b99ca01820c26abfa4b65fa705ef89b5ce55ac9aa3a7d83af"},
+    {file = "langchain_community-0.0.33.tar.gz", hash = "sha256:bb56dbc1ef11ca09f258468e11368781adda9219e144073e30cda69496d342b2"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.7"
-langchain-core = ">=0.1.41,<0.2.0"
+langchain-core = ">=0.1.43,<0.2.0"
 langsmith = ">=0.1.0,<0.2.0"
 numpy = ">=1,<2"
 PyYAML = ">=5.3"
@@ -1089,13 +1090,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
 
 [[package]]
 name = "langchain-core"
-version = "0.1.42"
+version = "0.1.44"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.1.42-py3-none-any.whl", hash = "sha256:c5653ffa08a44f740295c157a24c0def4a753333f6a2c41f76bf431cd00be8b5"},
-    {file = "langchain_core-0.1.42.tar.gz", hash = "sha256:40751bf60ea5d8e2b2efe65290db434717ee3834870c002e40e2811f09d814e6"},
+    {file = "langchain_core-0.1.44-py3-none-any.whl", hash = "sha256:d8772dccef95fc97bfa2dcd19412e620ebe14def1f0e218374971f6e30a46a49"},
+    {file = "langchain_core-0.1.44.tar.gz", hash = "sha256:e313975d9ae2926342e6f2ad760338d31f18b1223e9b8b4dc408daeeade46a83"},
 ]
 
 [package.dependencies]
@@ -1144,15 +1145,30 @@ langchain-core = ">=0.1.28,<0.2.0"
 [package.extras]
 extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
 
+[[package]]
+name = "langchainhub"
+version = "0.1.15"
+description = "The LangChain Hub API client"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
+    {file = "langchainhub-0.1.15-py3-none-any.whl", hash = "sha256:89a0951abd1db255e91c6d545d092a598fc255aa865d1ffc3ce8f93bbeae60e7"},
+    {file = "langchainhub-0.1.15.tar.gz", hash = "sha256:fa3ff81a31946860f84c119f1e2f6b7c7707e2bd7ed2394a7313b286d59f3bda"},
+]
+
+[package.dependencies]
+requests = ">=2,<3"
+types-requests = ">=2.31.0.2,<3.0.0.0"
+
 [[package]]
 name = "langsmith"
-version = "0.1.45"
+version = "0.1.48"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.45-py3-none-any.whl", hash = "sha256:5a5b7fafe767fa28826c925f175875c09bf5368bfdb141286381a94bf737e6ef"},
-    {file = "langsmith-0.1.45.tar.gz", hash = "sha256:713206107df636db1edf30867d64b92495afb1f09d2fee0857a77b7a8ee083d5"},
+    {file = "langsmith-0.1.48-py3-none-any.whl", hash = "sha256:2f8967e2aaaed8881efe6f346590681243b315af8ba8a037d969c299d42071d3"},
+    {file = "langsmith-0.1.48.tar.gz", hash = "sha256:9cd21cd0928123b2bd2363f03515cb1f6a833d9a9f00420240d5132861d15fcc"},
 ]
 
 [package.dependencies]
@@ -2568,6 +2584,20 @@ rich = ">=10.11.0"
 shellingham = ">=1.3.0"
 typing-extensions = ">=3.7.4.3"
 
+[[package]]
+name = "types-requests"
+version = "2.31.0.20240406"
+description = "Typing stubs for requests"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "types-requests-2.31.0.20240406.tar.gz", hash = "sha256:4428df33c5503945c74b3f42e82b181e86ec7b724620419a2966e2de604ce1a1"},
+    {file = "types_requests-2.31.0.20240406-py3-none-any.whl", hash = "sha256:6216cdac377c6b9a040ac1c0404f7284bd13199c0e1bb235f4324627e8898cf5"},
+]
+
+[package.dependencies]
+urllib3 = ">=2"
+
 [[package]]
 name = "typing-extensions"
 version = "4.11.0"
@@ -2861,4 +2891,4 @@ local = []
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.12"
-content-hash = "4f3f355cb54985a10ab577f0f2b495c7e6d9e7a8e21838b1742c43de927aba88"
+content-hash = "cd3479e6f463fcdce1bef948ca71952b0650d1d7f4891ba1bc873368cd4b095d"

src/backend/base/pyproject.toml

@@ -1,16 +1,16 @@
 [tool.poetry]
 name = "langflow-base"
-version = "0.0.30"
+version = "0.0.36"
 description = "A Python package with a built-in web application"
-authors = ["Logspace <contact@logspace.ai>"]
+authors = ["Langflow <contact@langflow.org>"]
 maintainers = [
-    "Carlos Coelho <carlos@logspace.ai>",
+    "Carlos Coelho <carlos@langflow.org>",
     "Cristhian Zanforlin <cristhian.lousa@gmail.com>",
-    "Gabriel Almeida <gabriel@logspace.ai>",
+    "Gabriel Almeida <gabriel@langflow.org>",
     "Igor Carvalho <igorr.ackerman@gmail.com>",
     "Lucas Eduoli <lucaseduoli@gmail.com>",
     "Otávio Anovazzi <otavio2204@gmail.com>",
-    "Rodrigo Nader <rodrigo@logspace.ai>",
+    "Rodrigo Nader <rodrigo@langflow.org>",
 ]
 repository = "https://github.com/langflow-ai/langflow"
 license = "MIT"
@@ -29,8 +29,9 @@ python = ">=3.10,<3.12"
 fastapi = "^0.110.1"
 httpx = "*"
 uvicorn = "^0.29.0"
-gunicorn = "^21.2.0"
-langchain = "~0.1.14"
+gunicorn = "^22.0.0"
+langchain = "~0.1.16"
+langchainhub = "~0.1.15"
 sqlmodel = "^0.0.16"
 loguru = "^0.7.1"
 rich = "^13.7.0"

src/frontend/cdk.Dockerfile

@@ -1,5 +1,5 @@
 #baseline
-FROM --platform=linux/amd64 node:19-bullseye-slim AS base
+FROM --platform=linux/amd64 node:21-bookworm-slim AS base
 RUN mkdir -p /home/node/app
 RUN chown -R node:node /home/node && chmod -R 770 /home/node
 RUN apt-get update && apt-get install -y jq curl

src/frontend/dev.Dockerfile

@@ -1,5 +1,5 @@
 #baseline
-FROM node:19-bullseye-slim AS base
+FROM node:21-bookworm-slim AS base
 RUN mkdir -p /home/node/app
 RUN chown -R node:node /home/node && chmod -R 770 /home/node
 RUN apt-get update && apt-get install -y jq

src/frontend/package-lock.json

@@ -38,6 +38,7 @@
         "clsx": "^1.2.1",
         "cmdk": "^1.0.0",
         "dompurify": "^3.0.5",
+        "dotenv": "^16.4.5",
         "esbuild": "^0.17.19",
         "framer-motion": "^11.0.6",
         "lodash": "^4.17.21",
@@ -5680,6 +5681,17 @@
         "tslib": "^2.0.3"
       }
     },
+    "node_modules/dotenv": {
+      "version": "16.4.5",
+      "resolved": "https://registry.npmjs.org/dotenv/-/dotenv-16.4.5.tgz",
+      "integrity": "sha512-ZmdL2rui+eB2YwhsWzjInR8LldtZHGDoQ1ugH85ppHKwpUHL7j7rN0Ti9NCnGiQbhaZ11FpR+7ao1dNsmduNUg==",
+      "engines": {
+        "node": ">=12"
+      },
+      "funding": {
+        "url": "https://dotenvx.com"
+      }
+    },
     "node_modules/eastasianwidth": {
       "version": "0.2.0",
       "resolved": "https://registry.npmjs.org/eastasianwidth/-/eastasianwidth-0.2.0.tgz",

src/frontend/package.json

@@ -33,6 +33,7 @@
     "clsx": "^1.2.1",
     "cmdk": "^1.0.0",
     "dompurify": "^3.0.5",
+    "dotenv": "^16.4.5",
     "esbuild": "^0.17.19",
     "framer-motion": "^11.0.6",
     "lodash": "^4.17.21",

src/frontend/playwright.config.ts

@@ -1,14 +1,17 @@
 import { defineConfig, devices } from "@playwright/test";
+import * as dotenv from "dotenv";
+import path from "path";
+dotenv.config();
+dotenv.config({ path: path.resolve(__dirname, "../../.env") });
 
 /**
  * Read environment variables from file.
  * https://github.com/motdotla/dotenv
  */
-// require('dotenv').config();
-
 /**
  * See https://playwright.dev/docs/test-configuration.
  */
+
 export default defineConfig({
   testDir: "./tests",
   /* Run tests in files in parallel */
@@ -18,7 +21,7 @@ export default defineConfig({
   /* Retry on CI only */
   retries: process.env.CI ? 2 : 0,
   /* Opt out of parallel tests on CI. */
-  workers: 3,
+  workers: 1,
   /* Reporter to use. See https://playwright.dev/docs/test-reporters */
   timeout: 120 * 1000,
   // reporter: [
@@ -40,24 +43,32 @@ export default defineConfig({
   projects: [
     {
       name: "chromium",
-      use: { ...devices["Desktop Chrome"] },
+      use: {
+        ...devices["Desktop Chrome"],
+        contextOptions: {
+          // chromium-specific permissions
+          permissions: ["clipboard-read", "clipboard-write"],
+        },
+      },
     },
 
     {
       name: "firefox",
-      use: { ...devices["Desktop Firefox"] },
+      use: {
+        ...devices["Desktop Firefox"],
+        launchOptions: {
+          firefoxUserPrefs: {
+            "dom.events.asyncClipboard.readText": true,
+            "dom.events.testing.asyncClipboard": true,
+          },
+        },
+      },
     },
-
-    // {
-    //   name: "webkit",
-    //   use: { ...devices["Desktop Safari"] },
-    // },
   ],
-  /* Run your local dev server before starting the tests */
   webServer: [
     {
       command:
-        "poetry run uvicorn --factory langflow.main:create_app --host 127.0.0.1 --port 7860",
+        "poetry run uvicorn --factory langflow.main:create_app --host 127.0.0.1 --port 7860 --loop asyncio",
       port: 7860,
       env: {
         LANGFLOW_DATABASE_URL: "sqlite:///./temp",
@@ -65,7 +76,7 @@ export default defineConfig({
       },
       stdout: "ignore",
 
-      reuseExistingServer: !process.env.CI,
+      reuseExistingServer: true,
       timeout: 120 * 1000,
     },
     {

src/frontend/src/components/headerComponent/components/menuBar/index.tsx

@@ -83,7 +83,9 @@ export const MenuBar = ({
           <DropdownMenuTrigger asChild>
             <Button asChild variant="primary" size="sm">
               <div className="header-menu-bar-display">
-                <div className="header-menu-flow-name">{currentFlow.name}</div>
+                <div className="header-menu-flow-name" data-testid="flow_name">
+                  {currentFlow.name}
+                </div>
                 <IconComponent name="ChevronDown" className="h-4 w-4" />
               </div>
             </Button>

src/frontend/src/controllers/API/api.tsx

@@ -24,6 +24,9 @@ function ApiInterceptor() {
       async (error: AxiosError) => {
         if (error.response?.status === 403 || error.response?.status === 401) {
           if (!autoLogin) {
+            if (error?.config?.url?.includes("github")) {
+              return Promise.reject(error);
+            }
             const stillRefresh = checkErrorCount();
             if (!stillRefresh) {
               return Promise.reject(error);

src/frontend/src/modals/IOModal/components/chatView/chatMessage/index.tsx

@@ -135,7 +135,12 @@ export default function ChatMessage({
                 alt={!chat.isSend ? "robot_image" : "male_technology"}
               />
             </div>
-            <span className="max-w-24 truncate text-xs">
+            <span
+              className="max-w-24 truncate text-xs"
+              data-testid={
+                "sender_name_" + chat.sender_name?.toLocaleLowerCase()
+              }
+            >
               {chat.sender_name}
             </span>
           </div>

src/frontend/src/modals/shareModal/index.tsx

@@ -237,6 +237,7 @@ export default function ShareModal({
               onCheckedChange={(event: boolean) => {
                 setSharePublic(event);
               }}
+              data-testid="public-checkbox"
             />
             <label htmlFor="public" className="export-modal-save-api text-sm ">
               Set {nameComponent} status to public

src/frontend/src/pages/FlowPage/index.tsx

@@ -38,7 +38,7 @@ export default function FlowPage({ view }: { view?: boolean }): JSX.Element {
         <a
           target={"_blank"}
           href="https://medium.com/logspace/langflow-datastax-better-together-1b7462cebc4d"
-          className="logspace-page-icon"
+          className="langflow-page-icon"
         >
           {version && <div className="mt-1">Langflow 🤝 DataStax</div>}
           <div className={version ? "mt-2" : "mt-1"}>⛓️ v{version}</div>

src/frontend/src/stores/darkStore.tsx

@@ -18,6 +18,11 @@ export const useDarkStore = create<DarkStoreType>((set, get) => ({
     });
   },
   refreshStars: () => {
+    if (import.meta.env.CI) {
+      window.localStorage.setItem("githubStars", "0");
+      set(() => ({ stars: 0, lastUpdated: new Date() }));
+      return;
+    }
     let lastUpdated = window.localStorage.getItem("githubStarsLastUpdated");
     let diff = 0;
     // check if lastUpdated actually exists
@@ -27,7 +32,7 @@ export const useDarkStore = create<DarkStoreType>((set, get) => ({
 
     // if lastUpdated is null or the difference is greater than 2 hours
     if (lastUpdated === null || diff > 7200000) {
-      getRepoStars("logspace-ai", "langflow").then((res) => {
+      getRepoStars("langflow-ai", "langflow").then((res) => {
         window.localStorage.setItem("githubStars", res.toString());
         window.localStorage.setItem(
           "githubStarsLastUpdated",

src/frontend/src/style/applies.css

@@ -205,11 +205,11 @@
   .flow-page-positioning {
     @apply h-full w-full overflow-hidden;
   }
-  .logspace-page-icon {
+  .langflow-page-icon {
     @apply absolute bottom-2 left-7 flex h-6 cursor-pointer flex-col items-center justify-start overflow-hidden rounded-lg bg-foreground px-2 text-center font-sans text-xs tracking-wide text-secondary transition-all duration-500 ease-in-out;
   }
 
-  .logspace-page-icon:hover {
+  .langflow-page-icon:hover {
     @apply hover:h-12;
   }
 

src/frontend/tests/end-to-end/assets/test_file.txt

@@ -0,0 +1 @@
+this is a test file

src/frontend/tests/end-to-end/auto_login.spec.ts

@@ -2,12 +2,12 @@ import { test } from "@playwright/test";
 
 test.describe("Auto_login tests", () => {
   test("auto_login sign in", async ({ page }) => {
-    await page.goto("http:localhost:3000/");
+    await page.goto("/");
     await page.locator('//*[@id="new-project-btn"]').click();
   });
 
   test("auto_login block_admin", async ({ page }) => {
-    await page.goto("http:localhost:3000/");
+    await page.goto("/");
     await page.locator('//*[@id="new-project-btn"]').click();
     await page.waitForTimeout(5000);
 

src/frontend/tests/end-to-end/chatInputOutput.spec.ts

@@ -0,0 +1,149 @@
+import { expect, test } from "@playwright/test";
+import * as dotenv from "dotenv";
+import { readFileSync } from "fs";
+import path from "path";
+
+test("user must interact with chat with Input/Output", async ({ page }) => {
+  if (!process.env.CI) {
+    dotenv.config();
+    dotenv.config({ path: path.resolve(__dirname, "../../.env") });
+  }
+
+  await page.goto("/");
+
+  await page.waitForTimeout(1000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+
+  await page.getByRole("heading", { name: "Basic Prompting" }).click();
+  await page.waitForTimeout(1000);
+
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+
+  if (!process.env.OPENAI_API_KEY) {
+    //You must set the OPENAI_API_KEY on .env file to run this test
+    expect(false).toBe(true);
+  }
+
+  await page
+    .getByTestId("input-openai_api_key")
+    .fill(process.env.OPENAI_API_KEY ?? "");
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByPlaceholder("Send a message...").fill("Hello, how are you?");
+  await page.getByTestId("icon-LucideSend").click();
+  let valueUser = await page.getByTestId("sender_name_user").textContent();
+  let valueAI = await page.getByTestId("sender_name_ai").textContent();
+
+  expect(valueUser).toBe("User");
+  expect(valueAI).toBe("AI");
+
+  await page.keyboard.press("Escape");
+
+  await page
+    .getByTestId("textarea-input_value")
+    .nth(1)
+    .fill(
+      "testtesttesttesttesttestte;.;.,;,.;,.;.,;,..,;;;;;;;;;;;;;;;;;;;;;,;.;,.;,.,;.,;.;.,~~çççççççççççççççççççççççççççççççççççççççisdajfdasiopjfaodisjhvoicxjiovjcxizopjviopasjioasfhjaiohf23432432432423423sttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttestççççççççççççççççççççççççççççççççç,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,!"
+    );
+  await page.getByTestId("input-sender_name").nth(1).fill("TestSenderNameUser");
+  await page.getByTestId("input-sender_name").nth(0).fill("TestSenderNameAI");
+
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByTestId("icon-LucideSend").click();
+
+  valueUser = await page
+    .getByTestId("sender_name_testsendernameuser")
+    .textContent();
+  valueAI = await page
+    .getByTestId("sender_name_testsendernameai")
+    .textContent();
+
+  expect(valueUser).toBe("TestSenderNameUser");
+  expect(valueAI).toBe("TestSenderNameAI");
+
+  expect(
+    await page
+      .getByText(
+        "testtesttesttesttesttestte;.;.,;,.;,.;.,;,..,;;;;;;;;;;;;;;;;;;;;;,;.;,.;,.,;.,;.;.,~~çççççççççççççççççççççççççççççççççççççççisdajfdasiopjfaodisjhvoicxjiovjcxizopjviopasjioasfhjaiohf23432432432423423sttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttestççççççççççççççççççççççççççççççççç,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,!",
+        { exact: true }
+      )
+      .isVisible()
+  );
+});
+
+test("chat_io_teste", async ({ page }) => {
+  await page.goto("/");
+  await page.locator("span").filter({ hasText: "My Collection" }).isVisible();
+  // Read your file into a buffer.
+  const jsonContent = readFileSync(
+    "tests/end-to-end/assets/ChatTest.json",
+    "utf-8"
+  );
+
+  await page.waitForTimeout(3000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+
+  await page.getByTestId("blank-flow").click();
+  await page.waitForTimeout(2000);
+
+  // Create the DataTransfer and File
+  const dataTransfer = await page.evaluateHandle((data) => {
+    const dt = new DataTransfer();
+    // Convert the buffer to a hex array
+    const file = new File([data], "ChatTest.json", {
+      type: "application/json",
+    });
+    dt.items.add(file);
+    return dt;
+  }, jsonContent);
+
+  // Now dispatch
+  await page.dispatchEvent(
+    '//*[@id="react-flow-id"]/div[1]/div[1]/div',
+    "drop",
+    {
+      dataTransfer,
+    }
+  );
+  await page.getByLabel("fit view").click();
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByPlaceholder("Send a message...").click();
+  await page.getByPlaceholder("Send a message...").fill("teste");
+  await page.getByRole("button").nth(1).click();
+  const chat_output = page.getByTestId("chat-message-AI-teste");
+  const chat_input = page.getByTestId("chat-message-User-teste");
+  await expect(chat_output).toHaveText("teste");
+  await expect(chat_input).toHaveText("teste");
+});

src/frontend/tests/end-to-end/chat_io.spec.ts

@@ -1,49 +0,0 @@
-import { expect, test } from "@playwright/test";
-import { readFileSync } from "fs";
-
-test("chat_io_teste", async ({ page }) => {
-  await page.goto("/");
-  await page.locator("span").filter({ hasText: "My Collection" }).isVisible();
-  // Read your file into a buffer.
-  const jsonContent = readFileSync(
-    "tests/end-to-end/assets/ChatTest.json",
-    "utf-8"
-  );
-
-  await page.waitForTimeout(3000);
-
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.locator('//*[@id="new-project-btn"]').click();
-
-  await page.getByTestId("blank-flow").click();
-  await page.waitForTimeout(2000);
-
-  // Create the DataTransfer and File
-  const dataTransfer = await page.evaluateHandle((data) => {
-    const dt = new DataTransfer();
-    // Convert the buffer to a hex array
-    const file = new File([data], "ChatTest.json", {
-      type: "application/json",
-    });
-    dt.items.add(file);
-    return dt;
-  }, jsonContent);
-
-  // Now dispatch
-  await page.dispatchEvent(
-    '//*[@id="react-flow-id"]/div[1]/div[1]/div',
-    "drop",
-    {
-      dataTransfer,
-    }
-  );
-  await page.getByLabel("fit view").click();
-  await page.getByText("Run", { exact: true }).click();
-  await page.getByPlaceholder("Send a message...").click();
-  await page.getByPlaceholder("Send a message...").fill("teste");
-  await page.getByRole("button").nth(1).click();
-  const chat_output = page.getByTestId("chat-message-AI-teste");
-  const chat_input = page.getByTestId("chat-message-User-teste");
-  await expect(chat_output).toHaveText("teste");
-  await expect(chat_input).toHaveText("teste");
-});

src/frontend/tests/end-to-end/codeAreaModalComponent.spec.ts

@@ -1,49 +1,63 @@
 import { expect, test } from "@playwright/test";
 
 test("CodeAreaModalComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+
   await page.waitForTimeout(1000);
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
   await page.getByTestId("extended-disclosure").click();
   await page.getByPlaceholder("Search").click();
-  await page.getByPlaceholder("Search").fill("pythonfunctiontool");
+  await page.getByPlaceholder("Search").fill("python function");
 
   await page.waitForTimeout(1000);
 
   await page
-    .getByTestId("toolsPythonFunctionTool")
+    .getByTestId("experimentalPython Function")
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("div-generic-node").click();
   await page.getByTestId("code-button-modal").click();
 
-  let value = await page.locator('//*[@id="codeValue"]').inputValue();
-  const code =
-    'def python_function(text: str) -> str:\n    """This is a default python function that returns the input text"""\n    return text';
   const wCode =
     'def python_function(text: str) -> st:    """This is a default python function that returns the input text"""    return text';
-  const assertCode =
-    'def python_function(text: str) -> str:    """This is a default python function that returns the input text"""    return text';
+
+  const customComponentCode = `from typing import Callable
+from langflow.field_typing import Code
+from langflow.interface.custom.custom_component import CustomComponent
+from langflow.interface.custom.utils import get_function
+
+class PythonFunctionComponent(CustomComponent):
+    def python_function(text: str) -> str:
+        """This is a default python function that returns the input text"""
+        return text`;
+
   await page
     .locator("#CodeEditor div")
-    .filter({ hasText: "def python_function(text: str" })
+    .filter({ hasText: "PythonFunctionComponent" })
     .nth(1)
     .click();
   await page.locator("textarea").press("Control+a");
@@ -55,13 +69,14 @@ test("CodeAreaModalComponent", async ({ page }) => {
   ).toBeTruthy();
   await page.locator("textarea").press("Control+a");
   await page.locator("textarea").fill(wCode);
-  await page.locator("textarea").fill(code);
+  await page.locator("textarea").fill(customComponentCode);
   await page.locator('//*[@id="checkAndSaveBtn"]').click();
   await page.waitForTimeout(1000);
 
-  expect(await page.getByText("Code is ready to run").isVisible()).toBeTruthy();
   await page.getByTestId("code-button-modal").click();
-  expect(await page.locator('//*[@id="codeValue"]').inputValue()).toBe(
-    assertCode
-  );
+  const inputCodeValue = await page
+    .locator('//*[@id="codeValue"]')
+    .inputValue();
+
+  expect(inputCodeValue).toContain("def python_function(text: str) -> str");
 });

src/frontend/tests/end-to-end/curl_api_generation.spec.ts

@@ -1,9 +1,22 @@
 import { expect, test } from "@playwright/test";
 
 test("curl_api_generation", async ({ page, context }) => {
-  await page.goto("http:localhost:3000/");
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  await page.goto("/");
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.getByRole("heading", { name: "Basic Prompting" }).click();
   await page.waitForTimeout(2000);
   await page.getByText("API", { exact: true }).click();

src/frontend/tests/end-to-end/dragAndDrop.spec.ts

@@ -4,7 +4,25 @@ import { readFileSync } from "fs";
 test.describe("drag and drop test", () => {
   /// <reference lib="dom"/>
   test("drop collection", async ({ page }) => {
-    await page.goto("http:localhost:3000/");
+    await page.goto("/");
+
+    let modalCount = 0;
+    try {
+      const modalTitleElement = await page?.getByTestId("modal-title");
+      if (modalTitleElement) {
+        modalCount = await modalTitleElement.count();
+      }
+    } catch (error) {
+      modalCount = 0;
+    }
+
+    while (modalCount === 0) {
+      await page.locator('//*[@id="new-project-btn"]').click();
+      await page.waitForTimeout(5000);
+      modalCount = await page.getByTestId("modal-title")?.count();
+    }
+    await page.locator("span").filter({ hasText: "Close" }).first().click();
+
     await page.locator("span").filter({ hasText: "My Collection" }).isVisible();
     // Read your file into a buffer.
     const jsonContent = readFileSync(
@@ -36,7 +54,7 @@ test.describe("drag and drop test", () => {
     await page.waitForTimeout(1000);
 
     const genericNoda = page.getByTestId("div-generic-node");
-    const elementCount = await genericNoda.count();
+    const elementCount = await genericNoda?.count();
     if (elementCount > 0) {
       expect(true).toBeTruthy();
     }

src/frontend/tests/end-to-end/dropdownComponent.spec.ts

@@ -1,10 +1,24 @@
 import { expect, test } from "@playwright/test";
 
 test("dropDownComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.waitForTimeout(1000);
 
   await page.getByTestId("blank-flow").click();
@@ -22,17 +36,10 @@ test("dropDownComponent", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("title-Amazon Bedrock").click();
 
   await page.getByTestId("dropdown-model_id").click();

src/frontend/tests/end-to-end/fileUploadComponent.spec.ts

@@ -0,0 +1,88 @@
+import { expect, test } from "@playwright/test";
+import path from "path";
+
+test("dropDownComponent", async ({ page }) => {
+  await page.goto("/");
+  await page.waitForTimeout(2000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+  await page.waitForTimeout(1000);
+
+  await page.getByTestId("blank-flow").click();
+  await page.waitForTimeout(1000);
+
+  await page.getByTestId("extended-disclosure").click();
+  await page.getByPlaceholder("Search").click();
+  await page.getByPlaceholder("Search").fill("file");
+
+  await page.waitForTimeout(1000);
+
+  await page
+    .getByTestId("dataFile")
+    .first()
+    .dragTo(page.locator('//*[@id="react-flow-id"]'));
+  await page.mouse.up();
+  await page.mouse.down();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  const fileChooserPromise = page.waitForEvent("filechooser");
+  await page.getByTestId("icon-FileSearch2").click();
+  const fileChooser = await fileChooserPromise;
+  await fileChooser.setFiles(path.join(__dirname, "/assets/test_file.txt"));
+  await page.getByText("test_file.txt").isVisible();
+
+  await page.getByPlaceholder("Search").click();
+  await page.getByPlaceholder("Search").fill("text output");
+
+  await page
+    .getByTestId("outputsText Output")
+    .first()
+    .dragTo(page.locator('//*[@id="react-flow-id"]'));
+  await page.mouse.up();
+  await page.mouse.down();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+
+  // Click and hold on the first element
+  await page
+    .locator(
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div[1]/div/div[2]/div[6]/button/div/div'
+    )
+    .hover();
+  await page.mouse.down();
+
+  // Move to the second element
+  await page
+    .locator(
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div[2]/div/div[2]/div[3]/div/button/div/div'
+    )
+    .hover();
+
+  // Release the mouse
+  await page.mouse.up();
+
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByText("Run Flow", { exact: true }).click();
+  await page.waitForTimeout(3000);
+  const textOutput = await page.getByPlaceholder("Empty").first().inputValue();
+
+  expect(textOutput).toContain("this is a test file");
+});

src/frontend/tests/end-to-end/filterEdge.spec.ts

@@ -1,11 +1,24 @@
 import { expect, test } from "@playwright/test";
 
 test("LLMChain - Tooltip", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
@@ -20,18 +33,10 @@ test("LLMChain - Tooltip", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
   await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
 
   await page
     .locator(
@@ -39,26 +44,20 @@ test("LLMChain - Tooltip", async ({ page }) => {
     )
     .hover()
     .then(async () => {
-      await expect(
-        page.getByTestId("available-input-model_specs").first()
-      ).toBeVisible();
+      await expect(page.getByTestId("tooltip-Chains").first()).toBeVisible();
 
-      await expect(page.getByTestId("tooltip-Models").first()).toBeVisible();
+      await expect(page.getByTestId("tooltip-Inputs").first()).toBeVisible();
 
-      await expect(
-        page.getByTestId("tooltip-AzureOpenAIModel").first()
-      ).toBeVisible();
-
-      await expect(
-        page.getByTestId("tooltip-Model Specs").first()
-      ).toBeVisible();
+      await expect(page.getByTestId("tooltip-Outputs").first()).toBeVisible();
 
       await page.getByTestId("icon-X").click();
       await page.waitForTimeout(500);
     });
 
   await page.getByTitle("fit view").click();
-
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page
     .locator(
       '//*[@id="react-flow-id"]/div[1]/div[1]/div/div/div[2]/div/div/div[2]/div[4]/div/button/div/div'
@@ -66,18 +65,12 @@ test("LLMChain - Tooltip", async ({ page }) => {
     .hover()
     .then(async () => {
       await expect(
-        page.getByTestId("available-input-memories").first()
+        page.getByTestId("tooltip-Model Specs").first()
       ).toBeVisible();
+      await page.waitForTimeout(2000);
 
-      await expect(page.getByTestId("tooltip-Memories").first()).toBeVisible();
+      await expect(page.getByTestId("tooltip-Models").first()).toBeVisible();
 
-      await expect(
-        page
-          .getByTestId(
-            "tooltip-ConversationBufferMemory, ConversationBufferWindowMemory, ConversationEntityMemory, ConversationKGMemory, ConversationSummaryMemory, MotorheadMemory, VectorStoreRetrieverMemory"
-          )
-          .first()
-      ).toBeVisible();
       await page.getByTestId("icon-Search").click();
 
       await page.waitForTimeout(500);
@@ -97,11 +90,29 @@ test("LLMChain - Tooltip", async ({ page }) => {
 });
 
 test("LLMChain - Filter", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
+  await page.waitForTimeout(2000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.waitForTimeout(1000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
+  await page.getByTestId(
+    "input-list-plus-btn-edit_metadata_indexing_include-2"
+  );
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
@@ -115,43 +126,28 @@ test("LLMChain - Filter", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
   await page.getByTitle("fit view").click();
-
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.waitForTimeout(500);
 
   await page
     .locator(
-      '//*[@id="react-flow-id"]/div[1]/div[1]/div/div/div[2]/div/div/div[2]/div[3]/div/button/div/div'
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div/div/div[2]/div[4]/div/button/div/div'
     )
     .click();
 
   await page
     .locator(
-      '//*[@id="react-flow-id"]/div[1]/div[1]/div/div/div[2]/div/div/div[2]/div[3]/div/button/div/div'
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div/div/div[2]/div[4]/div/button/div/div'
     )
     .click();
-  await page.getByTestId("icon-Search").click();
 
   await expect(page.getByTestId("disclosure-models")).toBeVisible();
-  await expect(page.getByTestId("disclosure-model specs")).toBeVisible();
-
-  await expect(page.getByTestId("modelsAzure OpenAI")).toBeVisible();
+  await expect(page.getByTestId("model_specsAnthropic").first()).toBeVisible();
   await expect(page.getByTestId("model_specsAmazon Bedrock")).toBeVisible();
-  await expect(page.getByTestId("model_specsAnthropic")).toBeVisible();
-  await expect(page.getByTestId("model_specsAnthropicLLM")).toBeVisible();
   await expect(page.getByTestId("model_specsAzureChatOpenAI")).toBeVisible();
-  await expect(page.getByTestId("model_specsChatAnthropic")).toBeVisible();
   await expect(page.getByTestId("model_specsChatLiteLLM")).toBeVisible();
   await expect(page.getByTestId("model_specsChatOllama")).toBeVisible();
   await expect(page.getByTestId("model_specsChatOpenAI")).toBeVisible();
@@ -176,8 +172,6 @@ test("LLMChain - Filter", async ({ page }) => {
   await expect(page.getByTestId("model_specsCTransformers")).not.toBeVisible();
   await expect(page.getByTestId("model_specsAmazon Bedrock")).not.toBeVisible();
   await expect(page.getByTestId("modelsAzure OpenAI")).not.toBeVisible();
-  await expect(page.getByTestId("model_specsAnthropic")).not.toBeVisible();
-  await expect(page.getByTestId("model_specsAnthropicLLM")).not.toBeVisible();
   await expect(
     page.getByTestId("model_specsAzureChatOpenAI")
   ).not.toBeVisible();
@@ -190,52 +184,19 @@ test("LLMChain - Filter", async ({ page }) => {
 
   await page
     .locator(
-      '//*[@id="react-flow-id"]/div[1]/div[1]/div/div/div[2]/div/div/div[2]/div[4]/div/button/div/div'
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div/div/div[2]/div[7]/button/div/div'
     )
     .click();
 
   await page
     .locator(
-      '//*[@id="react-flow-id"]/div[1]/div[1]/div/div/div[2]/div/div/div[2]/div[4]/div/button/div/div'
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div/div/div[2]/div[7]/button/div/div'
     )
     .click();
 
-  await expect(page.getByTestId("disclosure-memories")).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesConversationBufferMemory")
-  ).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesConversationBufferWindowMemory")
-  ).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesConversationEntityMemory")
-  ).toBeVisible();
-  await expect(page.getByTestId("memoriesConversationKGMemory")).toBeVisible();
-  await expect(page.getByTestId("memoriesConversationKGMemory")).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesConversationSummaryMemory")
-  ).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesVectorStoreRetrieverMemory")
-  ).toBeVisible();
-
-  await page.getByTestId("rf__wrapper").click();
-
-  await expect(
-    page.getByTestId("memoriesConversationBufferMemory")
-  ).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesConversationBufferWindowMemory")
-  ).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesConversationEntityMemory")
-  ).toBeVisible();
-  await expect(page.getByTestId("memoriesConversationKGMemory")).toBeVisible();
-  await expect(page.getByTestId("memoriesConversationKGMemory")).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesConversationSummaryMemory")
-  ).toBeVisible();
-  await expect(
-    page.getByTestId("memoriesVectorStoreRetrieverMemory")
-  ).toBeVisible();
+  await expect(page.getByTestId("inputsChat Input")).toBeVisible();
+  await expect(page.getByTestId("outputsChat Output")).toBeVisible();
+  await expect(page.getByTestId("helpersID Generator")).toBeVisible();
+  await expect(page.getByTestId("vectorstoresChroma")).toBeVisible();
+  await expect(page.getByTestId("disclosure-vector stores")).toBeVisible();
 });

src/frontend/tests/end-to-end/floatComponent.spec.ts

@@ -1,10 +1,24 @@
 import { expect, test } from "@playwright/test";
 
 test("FloatComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.waitForTimeout(1000);
 
   await page.getByTestId("blank-flow").click();
@@ -20,28 +34,10 @@ test("FloatComponent", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
 
   await page.locator('//*[@id="float-input"]').click();
   await page.locator('//*[@id="float-input"]').fill("3");
@@ -145,7 +141,7 @@ test("FloatComponent", async ({ page }) => {
   await page.locator('//*[@id="saveChangesBtn"]').click();
 
   const plusButtonLocator = page.locator('//*[@id="float-input"]');
-  const elementCount = await plusButtonLocator.count();
+  const elementCount = await plusButtonLocator?.count();
   if (elementCount === 0) {
     expect(true).toBeTruthy();
 

src/frontend/tests/end-to-end/flowPage.spec.ts

@@ -1,17 +1,25 @@
-import { Page, test } from "@playwright/test";
+import { test } from "@playwright/test";
 
 test.describe("Flow Page tests", () => {
-  async function goToFlowPage(page: Page) {
-    await page.goto("http:localhost:3000/");
-    await page.getByRole("button", { name: "New Project" }).click();
-  }
-
   test("save", async ({ page }) => {
-    await page.goto("http:localhost:3000/");
+    await page.goto("/");
     await page.waitForTimeout(2000);
 
-    await page.locator('//*[@id="new-project-btn"]').click();
-    await page.waitForTimeout(1000);
+    let modalCount = 0;
+    try {
+      const modalTitleElement = await page?.getByTestId("modal-title");
+      if (modalTitleElement) {
+        modalCount = await modalTitleElement.count();
+      }
+    } catch (error) {
+      modalCount = 0;
+    }
+
+    while (modalCount === 0) {
+      await page.locator('//*[@id="new-project-btn"]').click();
+      await page.waitForTimeout(5000);
+      modalCount = await page.getByTestId("modal-title")?.count();
+    }
 
     await page.getByTestId("blank-flow").click();
     await page.waitForTimeout(1000);
@@ -26,18 +34,9 @@ test.describe("Flow Page tests", () => {
       .dragTo(page.locator('//*[@id="react-flow-id"]'));
     await page.mouse.up();
     await page.mouse.down();
-    await page
-      .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-      .click();
-
-    await page
-      .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-      .click();
-
-    await page
-      .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-      .click();
-    // await page.getByTestId("icon-ExternalLink").click();
-    // await page.locator('//*[@id="checkAndSaveBtn"]').click();
+    await page.getByTitle("fit view").click();
+    await page.getByTitle("zoom out").click();
+    await page.getByTitle("zoom out").click();
+    await page.getByTitle("zoom out").click();
   });
 });

src/frontend/tests/end-to-end/flowSettings.spec.ts

@@ -0,0 +1,73 @@
+import { expect, test } from "@playwright/test";
+
+test("flowSettings", async ({ page }) => {
+  await page.goto("/");
+  await page.waitForTimeout(2000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+  await page.waitForTimeout(1000);
+
+  await page.getByTestId("blank-flow").click();
+  await page.waitForTimeout(1000);
+
+  await page.getByTestId("flow_name").click();
+  await page.getByText("Settings").first().click();
+  await page
+    .getByPlaceholder("Flow name")
+    .fill(
+      "Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test"
+    );
+
+  await page.getByText("Character limit reached").isVisible();
+
+  await page.getByPlaceholder("Flow name").click();
+  const randomName = Math.random().toString(36).substring(2);
+  await page.getByPlaceholder("Flow name").fill(randomName);
+  await page.getByPlaceholder("Flow name").click();
+  await page
+    .getByPlaceholder("Flow description")
+    .fill(
+      "Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test"
+    );
+
+  await page.getByText("Save").last().click();
+
+  await page.waitForTimeout(1000);
+
+  await page.getByText("Changes saved successfully").isVisible();
+
+  await page.getByTestId("flow_name").click();
+  await page.getByText("Settings").first().click();
+
+  const flowName = await page.getByPlaceholder("Flow name").inputValue();
+  const flowDescription = await page
+    .getByPlaceholder("Flow description")
+    .inputValue();
+
+  if (flowName != randomName) {
+    expect(false).toBeTruthy();
+  }
+
+  if (
+    flowDescription !=
+    "Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test Flow Name Test"
+  ) {
+    expect(false).toBeTruthy();
+  }
+  await page.getByText("Saved").first().isVisible();
+  await page.getByTestId("icon-CheckCircle2").first().isVisible();
+});

src/frontend/tests/end-to-end/globalVariables.spec.ts

@@ -0,0 +1,72 @@
+import { expect, test } from "@playwright/test";
+
+test("GlobalVariables", async ({ page }) => {
+  await page.goto("/");
+  await page.waitForTimeout(2000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+  await page.waitForTimeout(1000);
+
+  await page.getByTestId("blank-flow").click();
+  await page.waitForTimeout(1000);
+  await page.getByTestId("extended-disclosure").click();
+  await page.getByPlaceholder("Search").click();
+  await page.getByPlaceholder("Search").fill("openai");
+
+  await page.waitForTimeout(1000);
+
+  await page
+    .getByTestId("modelsOpenAI")
+    .dragTo(page.locator('//*[@id="react-flow-id"]'));
+  await page.mouse.up();
+  await page.mouse.down();
+
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+
+  const genericName = Math.random().toString();
+  const credentialName = Math.random().toString();
+
+  await page.getByTestId("icon-Globe").nth(1).click();
+  await page.getByText("Add New Variable", { exact: true }).click();
+  await page
+    .getByPlaceholder("Insert a name for the variable...")
+    .fill(genericName);
+  await page.getByTestId("icon-ChevronsUpDown").nth(1).click();
+  await page.getByText("Generic", { exact: true }).click();
+  await page
+    .getByPlaceholder("Insert a value for the variable...")
+    .fill("This is a test of generic variable value");
+  await page.getByText("Save Variable", { exact: true }).click();
+  expect(page.getByText(genericName, { exact: true })).not.toBeNull();
+  await page.getByText(genericName, { exact: true }).isVisible();
+
+  await page.getByText("Add New Variable", { exact: true }).click();
+  await page
+    .getByPlaceholder("Insert a name for the variable...")
+    .fill(credentialName);
+  await page.getByTestId("icon-ChevronsUpDown").nth(1).click();
+  await page.getByText("Credential", { exact: true }).click();
+  await page
+    .getByPlaceholder("Insert a value for the variable...")
+    .fill("This is a test of credential variable value");
+  await page.getByText("Save Variable", { exact: true }).click();
+  expect(page.getByText(credentialName, { exact: true })).not.toBeNull();
+  await page.getByText(credentialName, { exact: true }).isVisible();
+});

src/frontend/tests/end-to-end/group.spec.ts

@@ -4,7 +4,21 @@ test.describe("group node test", () => {
   /// <reference lib="dom"/>
   test("group and ungroup updating values", async ({ page }) => {
     await page.goto("/");
-    await page.locator('//*[@id="new-project-btn"]').click();
+
+    let modalCount = 0;
+    try {
+      const modalTitleElement = await page?.getByTestId("modal-title");
+      if (modalTitleElement) {
+        modalCount = await modalTitleElement.count();
+      }
+    } catch (error) {
+      modalCount = 0;
+    }
+
+    while (modalCount === 0) {
+      await page.locator('//*[@id="new-project-btn"]').click();
+      modalCount = await page.getByTestId("modal-title")?.count();
+    }
 
     await page
       .getByRole("heading", { name: "Basic Prompting" })
@@ -13,8 +27,6 @@ test.describe("group node test", () => {
     await page.waitForTimeout(2000);
     await page.getByLabel("fit view").first().click();
     await page.getByTestId("title-OpenAI").click({ modifiers: ["Control"] });
-    await page.getByTestId("title-Prompt").click({ modifiers: ["Control"] });
-    await page.getByTestId("title-OpenAI").click({ modifiers: ["Control"] });
 
     await page.getByRole("button", { name: "Group" }).click();
     await page.getByTestId("title-Group").dblclick();

src/frontend/tests/end-to-end/inputComponent.spec.ts

@@ -1,10 +1,24 @@
 import { expect, test } from "@playwright/test";
 
 test("InputComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.waitForTimeout(1000);
 
   await page.getByTestId("blank-flow").click();
@@ -20,17 +34,10 @@ test("InputComponent", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("input-collection_name").click();
   await page
     .getByTestId("input-collection_name")
@@ -132,7 +139,7 @@ test("InputComponent", async ({ page }) => {
   await page.locator('//*[@id="saveChangesBtn"]').click();
 
   const plusButtonLocator = page.getByTestId("input-collection_name");
-  const elementCount = await plusButtonLocator.count();
+  const elementCount = await plusButtonLocator?.count();
   if (elementCount === 0) {
     expect(true).toBeTruthy();
 

src/frontend/tests/end-to-end/inputListComponent.spec.ts

@@ -1,36 +1,41 @@
 import { expect, test } from "@playwright/test";
 
 test("InputListComponent", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
-  await page.locator('//*[@id="new-project-btn"]').click();
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
   await page.getByTestId("extended-disclosure").click();
   await page.getByPlaceholder("Search").click();
-  await page.getByPlaceholder("Search").fill("astradb search");
+  await page.getByPlaceholder("Search").fill("astradb");
 
   await page.waitForTimeout(1000);
   await page
-    .getByTestId("vectorsearchAstraDB Search")
+    .getByTestId("vectorsearchAstra DB Search")
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("div-generic-node").click();
   await page.getByTestId("more-options-modal").click();
   await page.getByTestId("edit-button-modal").click();
@@ -90,7 +95,7 @@ test("InputListComponent", async ({ page }) => {
   const plusButtonLocator = page.getByTestId(
     "input-list-plus-btn_metadata_indexing_include-1"
   );
-  const elementCount = await plusButtonLocator.count();
+  const elementCount = await plusButtonLocator?.count();
 
   if (elementCount > 0) {
     expect(false).toBeTruthy();
@@ -161,12 +166,12 @@ test("InputListComponent", async ({ page }) => {
   const plusButtonLocatorEdit0 = await page.getByTestId(
     "input-list-plus-btn-edit_metadata_indexing_include-0"
   );
-  const elementCountEdit0 = await plusButtonLocatorEdit0.count();
+  const elementCountEdit0 = await plusButtonLocatorEdit0?.count();
 
   const plusButtonLocatorEdit2 = await page.getByTestId(
     "input-list-plus-btn-edit_metadata_indexing_include-2"
   );
-  const elementCountEdit2 = await plusButtonLocatorEdit2.count();
+  const elementCountEdit2 = await plusButtonLocatorEdit2?.count();
 
   if (elementCountEdit0 > 0 || elementCountEdit2 > 0) {
     expect(false).toBeTruthy();
@@ -176,13 +181,13 @@ test("InputListComponent", async ({ page }) => {
     "input-list-minus-btn-edit_metadata_indexing_include-1"
   );
 
-  const elementCountMinusEdit1 = await minusButtonLocatorEdit1.count();
+  const elementCountMinusEdit1 = await minusButtonLocatorEdit1?.count();
 
   const minusButtonLocatorEdit2 = await page.getByTestId(
     "input-list-minus-btn-edit_metadata_indexing_include-2"
   );
 
-  const elementCountMinusEdit2 = await minusButtonLocatorEdit2.count();
+  const elementCountMinusEdit2 = await minusButtonLocatorEdit2?.count();
 
   if (elementCountMinusEdit1 > 0 || elementCountMinusEdit2 > 0) {
     expect(false).toBeTruthy();

src/frontend/tests/end-to-end/intComponent.spec.ts

@@ -1,10 +1,24 @@
 import { expect, test } from "@playwright/test";
 
 test("IntComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.waitForTimeout(1000);
 
   await page.getByTestId("blank-flow").click();
@@ -21,17 +35,10 @@ test("IntComponent", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("int-input-max_tokens").click();
   await page
     .getByTestId("int-input-max_tokens")
@@ -53,17 +60,10 @@ test("IntComponent", async ({ page }) => {
   }
 
   await page.getByTestId("title-ChatOpenAI").click();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
 
   await page.getByTestId("more-options-modal").click();
   await page.getByTestId("edit-button-modal").click();
@@ -157,7 +157,7 @@ test("IntComponent", async ({ page }) => {
   await page.locator('//*[@id="saveChangesBtn"]').click();
 
   const plusButtonLocator = page.getByTestId("int-input-max_tokens");
-  const elementCount = await plusButtonLocator.count();
+  const elementCount = await plusButtonLocator?.count();
   if (elementCount === 0) {
     expect(true).toBeTruthy();
 

src/frontend/tests/end-to-end/keyPairListComponent.spec.ts

@@ -1,36 +1,43 @@
 import { expect, test } from "@playwright/test";
 
 test("KeypairListComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.waitForTimeout(1000);
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
   await page.getByTestId("extended-disclosure").click();
   await page.getByPlaceholder("Search").click();
-  await page.getByPlaceholder("Search").fill("csv");
+  await page.getByPlaceholder("Search").fill("amazon bedrock");
 
   await page.waitForTimeout(1000);
 
   await page
-    .getByTestId("documentloadersCSVLoader")
+    .getByTestId("model_specsAmazon Bedrock")
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.locator('//*[@id="keypair0"]').click();
   await page.locator('//*[@id="keypair0"]').fill("testtesttesttest");
   await page.locator('//*[@id="keypair100"]').click();
@@ -48,7 +55,7 @@ test("KeypairListComponent", async ({ page }) => {
   }
 
   const plusButtonLocatorNode = page.locator('//*[@id="plusbtn0"]');
-  const elementCountNode = await plusButtonLocatorNode.count();
+  const elementCountNode = await plusButtonLocatorNode?.count();
   if (elementCountNode > 0) {
     await plusButtonLocatorNode.click();
   }
@@ -59,7 +66,7 @@ test("KeypairListComponent", async ({ page }) => {
   await page.getByTestId("div-generic-node").click();
 
   const keyPairVerification = page.locator('//*[@id="keypair100"]');
-  const elementKeyCount = await keyPairVerification.count();
+  const elementKeyCount = await keyPairVerification?.count();
 
   if (elementKeyCount === 1) {
     expect(true).toBeTruthy();
@@ -70,16 +77,16 @@ test("KeypairListComponent", async ({ page }) => {
   await page.getByTestId("more-options-modal").click();
   await page.getByTestId("edit-button-modal").click();
 
-  await page.locator('//*[@id="showfile_path"]').click();
+  await page.locator('//*[@id="showcache"]').click();
+  expect(await page.locator('//*[@id="showcache"]').isChecked()).toBeFalsy();
+  await page.locator('//*[@id="showcredentials_profile_name"]').click();
   expect(
-    await page.locator('//*[@id="showfile_path"]').isChecked()
+    await page.locator('//*[@id="showcredentials_profile_name"]').isChecked()
   ).toBeFalsy();
-  await page.locator('//*[@id="showmetadata"]').click();
-  expect(await page.locator('//*[@id="showmetadata"]').isChecked()).toBeFalsy();
   await page.locator('//*[@id="saveChangesBtn"]').click();
 
   const plusButtonLocator = page.locator('//*[@id="plusbtn0"]');
-  const elementCount = await plusButtonLocator.count();
+  const elementCount = await plusButtonLocator?.count();
   if (elementCount === 0) {
     expect(true).toBeTruthy();
     await page.getByTestId("div-generic-node").click();
@@ -87,20 +94,18 @@ test("KeypairListComponent", async ({ page }) => {
     await page.getByTestId("more-options-modal").click();
     await page.getByTestId("edit-button-modal").click();
 
-    await page.locator('//*[@id="showfile_path"]').click();
+    await page.locator('//*[@id="showcredentials_profile_name"]').click();
     expect(
-      await page.locator('//*[@id="showfile_path"]').isChecked()
-    ).toBeTruthy();
-    await page.locator('//*[@id="showmetadata"]').click();
-    expect(
-      await page.locator('//*[@id="showmetadata"]').isChecked()
+      await page.locator('//*[@id="showcredentials_profile_name"]').isChecked()
     ).toBeTruthy();
+    await page.locator('//*[@id="showcache"]').click();
+    expect(await page.locator('//*[@id="showcache"]').isChecked()).toBeTruthy();
 
     await page.locator('//*[@id="editNodekeypair0"]').click();
     await page.locator('//*[@id="editNodekeypair0"]').fill("testtesttesttest");
 
     const keyPairVerification = page.locator('//*[@id="editNodekeypair0"]');
-    const elementKeyCount = await keyPairVerification.count();
+    const elementKeyCount = await keyPairVerification?.count();
 
     if (elementKeyCount === 1) {
       await page.locator('//*[@id="saveChangesBtn"]').click();

src/frontend/tests/end-to-end/langflowShortcuts.spec.ts

@@ -1,6 +1,7 @@
 import { expect, test } from "@playwright/test";
 import uaParser from "ua-parser-js";
 test("LangflowShortcuts", async ({ page }) => {
+  await page.goto("/");
   const getUA = await page.evaluate(() => navigator.userAgent);
   const userAgentInfo = uaParser(getUA);
   let control = "Control";
@@ -9,11 +10,23 @@ test("LangflowShortcuts", async ({ page }) => {
     control = "Meta";
   }
 
-  await page.goto("http:localhost:3000/");
   await page.waitForTimeout(1000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
@@ -30,17 +43,10 @@ test("LangflowShortcuts", async ({ page }) => {
   await page.mouse.down();
 
   await page.locator('//*[@id="react-flow-id"]/div/div[2]/button[3]').click();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("title-Ollama").click();
   await page.keyboard.press(`${control}+Shift+A`);
   await page.locator('//*[@id="saveChangesBtn"]').click();
@@ -48,7 +54,7 @@ test("LangflowShortcuts", async ({ page }) => {
   await page.getByTestId("title-Ollama").click();
   await page.keyboard.press(`${control}+d`);
 
-  let numberOfNodes = await page.getByTestId("title-Ollama").count();
+  let numberOfNodes = await page.getByTestId("title-Ollama")?.count();
   if (numberOfNodes != 2) {
     expect(false).toBeTruthy();
   }
@@ -60,7 +66,7 @@ test("LangflowShortcuts", async ({ page }) => {
     .click();
   await page.keyboard.press("Backspace");
 
-  numberOfNodes = await page.getByTestId("title-Ollama").count();
+  numberOfNodes = await page.getByTestId("title-Ollama")?.count();
   if (numberOfNodes != 1) {
     expect(false).toBeTruthy();
   }
@@ -71,7 +77,7 @@ test("LangflowShortcuts", async ({ page }) => {
   await page.getByTestId("title-Ollama").click();
   await page.keyboard.press(`${control}+v`);
 
-  numberOfNodes = await page.getByTestId("title-Ollama").count();
+  numberOfNodes = await page.getByTestId("title-Ollama")?.count();
   if (numberOfNodes != 2) {
     expect(false).toBeTruthy();
   }
@@ -86,12 +92,12 @@ test("LangflowShortcuts", async ({ page }) => {
   await page.getByTestId("title-Ollama").click();
   await page.keyboard.press(`${control}+x`);
 
-  numberOfNodes = await page.getByTestId("title-Ollama").count();
+  numberOfNodes = await page.getByTestId("title-Ollama")?.count();
   if (numberOfNodes != 0) {
     expect(false).toBeTruthy();
   }
   await page.keyboard.press(`${control}+v`);
-  numberOfNodes = await page.getByTestId("title-Ollama").count();
+  numberOfNodes = await page.getByTestId("title-Ollama")?.count();
   if (numberOfNodes != 1) {
     expect(false).toBeTruthy();
   }

src/frontend/tests/end-to-end/nestedComponent.spec.ts

@@ -1,11 +1,24 @@
 import { expect, test } from "@playwright/test";
 
 test("NestedComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);

src/frontend/tests/end-to-end/promptModalComponent.spec.ts

@@ -1,11 +1,24 @@
 import { expect, test } from "@playwright/test";
 
 test("PromptTemplateComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
@@ -20,17 +33,10 @@ test("PromptTemplateComponent", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("prompt-input-template").click();
 
   await page

src/frontend/tests/end-to-end/python_api_generation.spec.ts

@@ -2,8 +2,21 @@ import { expect, test } from "@playwright/test";
 
 test("python_api_generation", async ({ page, context }) => {
   await page.goto("/");
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
   await page.getByRole("heading", { name: "Basic Prompting" }).click();
   await page.waitForTimeout(2000);
   await page.getByText("API", { exact: true }).click();

src/frontend/tests/end-to-end/saveComponents.spec.ts

@@ -1,18 +1,24 @@
-import { Page, expect, test } from "@playwright/test";
+import { expect, test } from "@playwright/test";
 import { readFileSync } from "fs";
 
 test.describe("save component tests", () => {
-  async function saveComponent(page: Page, pattern: RegExp, n: number) {
-    for (let i = 0; i < n; i++) {
-      await page.getByTestId(pattern).click();
-      await page.getByLabel("Save").click();
-    }
-  }
-
   /// <reference lib="dom"/>
   test("save group component tests", async ({ page }) => {
-    await page.goto("http:localhost:3000/");
-    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.goto("/");
+    let modalCount = 0;
+    try {
+      const modalTitleElement = await page?.getByTestId("modal-title");
+      if (modalTitleElement) {
+        modalCount = await modalTitleElement.count();
+      }
+    } catch (error) {
+      modalCount = 0;
+    }
+
+    while (modalCount === 0) {
+      await page.locator('//*[@id="new-project-btn"]').click();
+      modalCount = await page.getByTestId("modal-title")?.count();
+    }
 
     await page.getByTestId("blank-flow").click();
     await page.waitForTimeout(1000);
@@ -46,7 +52,7 @@ test.describe("save component tests", () => {
     );
 
     const genericNoda = page.getByTestId("div-generic-node");
-    const elementCount = await genericNoda.count();
+    const elementCount = await genericNoda?.count();
     if (elementCount > 0) {
       expect(true).toBeTruthy();
     }
@@ -68,13 +74,13 @@ test.describe("save component tests", () => {
     await page.getByRole("button", { name: "Group" }).click();
 
     let textArea = page.getByTestId("div-textarea-description");
-    let elementCountText = await textArea.count();
+    let elementCountText = await textArea?.count();
     if (elementCountText > 0) {
       expect(true).toBeTruthy();
     }
 
     let groupNode = page.getByTestId("title-Group");
-    let elementGroup = await groupNode.count();
+    let elementGroup = await groupNode?.count();
     if (elementGroup > 0) {
       expect(true).toBeTruthy();
     }
@@ -98,25 +104,18 @@ test.describe("save component tests", () => {
       .dragTo(page.locator('//*[@id="react-flow-id"]'));
     await page.mouse.up();
     await page.mouse.down();
-    await page
-      .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-      .click();
-
-    await page
-      .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-      .click();
-
-    await page
-      .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-      .click();
+    await page.getByTitle("fit view").click();
+    await page.getByTitle("zoom out").click();
+    await page.getByTitle("zoom out").click();
+    await page.getByTitle("zoom out").click();
     textArea = page.getByTestId("div-textarea-description");
-    elementCountText = await textArea.count();
+    elementCountText = await textArea?.count();
     if (elementCountText > 0) {
       expect(true).toBeTruthy();
     }
 
     groupNode = page.getByTestId("title-Group");
-    elementGroup = await groupNode.count();
+    elementGroup = await groupNode?.count();
     if (elementGroup > 0) {
       expect(true).toBeTruthy();
     }

src/frontend/tests/end-to-end/store.spec.ts

@@ -1,7 +1,7 @@
 import { expect, test } from "@playwright/test";
 
 test("should exists Store", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").isVisible();
@@ -9,7 +9,7 @@ test("should exists Store", async ({ page }) => {
 });
 
 test("should not have an API key", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").click();
@@ -19,7 +19,7 @@ test("should not have an API key", async ({ page }) => {
 });
 
 test("should find a searched Component on Store", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").click();
@@ -39,7 +39,7 @@ test("should find a searched Component on Store", async ({ page }) => {
 });
 
 test("should filter by tag", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").click();
@@ -66,7 +66,7 @@ test("should filter by tag", async ({ page }) => {
 });
 
 test("should order the visualization", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").click();
@@ -86,7 +86,7 @@ test("should order the visualization", async ({ page }) => {
 });
 
 test("should filter by type", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").click();
@@ -97,7 +97,7 @@ test("should filter by type", async ({ page }) => {
   await page.getByTestId("flows-button-store").click();
   await page.waitForTimeout(3000);
 
-  let iconGroup = await page.getByTestId("icon-Group").count();
+  let iconGroup = await page.getByTestId("icon-Group")?.count();
   expect(iconGroup).not.toBe(0);
 
   await page.getByText("icon-ToyBrick").isHidden();
@@ -106,14 +106,14 @@ test("should filter by type", async ({ page }) => {
   await page.waitForTimeout(3000);
 
   await page.getByTestId("icon-Group").isHidden();
-  let toyBrick = await page.getByTestId("icon-ToyBrick").count();
+  let toyBrick = await page.getByTestId("icon-ToyBrick")?.count();
   expect(toyBrick).not.toBe(0);
 
   await page.getByTestId("all-button-store").click();
   await page.waitForTimeout(3000);
 
-  iconGroup = await page.getByTestId("icon-Group").count();
-  toyBrick = await page.getByTestId("icon-ToyBrick").count();
+  iconGroup = await page.getByTestId("icon-Group")?.count();
+  toyBrick = await page.getByTestId("icon-ToyBrick")?.count();
 
   if (iconGroup === 0 || toyBrick === 0) {
     expect(false).toBe(true);
@@ -121,7 +121,7 @@ test("should filter by type", async ({ page }) => {
 });
 
 test("should add API-KEY", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").click();
@@ -154,7 +154,7 @@ test("should add API-KEY", async ({ page }) => {
 });
 
 test("should like and add components and flows", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
   await page.getByTestId("button-store").click();
@@ -216,3 +216,60 @@ test("should like and add components and flows", async ({ page }) => {
   await page.getByTestId("sidebar-nav-Components").click();
   await page.getByText("Basic RAG").first().isVisible();
 });
+
+test("should share component with share button", async ({ page }) => {
+  await page.goto("/");
+  await page.waitForTimeout(2000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+  await page.waitForTimeout(1000);
+
+  await page.getByRole("heading", { name: "Basic Prompting" }).click();
+  await page.waitForTimeout(1000);
+  const flowName = await page.getByTestId("flow_name").innerText();
+  await page.getByTestId("flow_name").click();
+  await page.getByText("Settings").click();
+  const flowDescription = await page
+    .getByPlaceholder("Flow description")
+    .inputValue();
+  await page.getByText("Save").last().click();
+
+  await page.getByTestId("icon-Share3").first().click();
+  await page.getByText("Name:").isVisible();
+  await page.getByText("Description:").isVisible();
+  await page.getByText("Set workflow status to public").isVisible();
+  await page
+    .getByText(
+      "Attention: API keys in specified fields are automatically removed upon sharing."
+    )
+    .isVisible();
+  await page.getByText("Export").first().isVisible();
+  await page.getByText("Share Flow").first().isVisible();
+
+  await page.waitForTimeout(5000);
+
+  await page.getByText("Agent").first().isVisible();
+  await page.getByText("Memory").first().isVisible();
+  await page.getByText("Chain").first().isVisible();
+  await page.getByText("Vector Store").first().isVisible();
+  await page.getByText("Prompt").last().isVisible();
+  await page.getByTestId("public-checkbox").isChecked();
+  await page.getByText(flowName).last().isVisible();
+  await page.getByText(flowDescription).last().isVisible();
+  await page.waitForTimeout(1000);
+  await page.getByText("Flow shared successfully").last().isVisible();
+});

src/frontend/tests/end-to-end/textAreaModalComponent.spec.ts

@@ -1,13 +1,25 @@
 import { expect, test } from "@playwright/test";
 
 test("TextAreaModalComponent", async ({ page }) => {
-  await page.goto("http://localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(1000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
 
-  await page.locator('//*[@id="new-project-btn"]').click();
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
   await page.getByTestId("extended-disclosure").click();
@@ -21,17 +33,10 @@ test("TextAreaModalComponent", async ({ page }) => {
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
   await page.getByTestId("prompt-input-template").click();
 
   await page.getByTestId("modal-prompt-input-template").fill("{text}");

src/frontend/tests/end-to-end/textInputOutput.spec.ts

@@ -0,0 +1,155 @@
+import { expect, test } from "@playwright/test";
+import * as dotenv from "dotenv";
+import path from "path";
+
+test("TextInputOutputComponent", async ({ page }) => {
+  if (!process.env.CI) {
+    dotenv.config();
+    dotenv.config({ path: path.resolve(__dirname, "../../.env") });
+  }
+
+  await page.goto("/");
+  await page.waitForTimeout(2000);
+
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+
+  await page.waitForTimeout(1000);
+
+  await page.getByTestId("blank-flow").click();
+  await page.waitForTimeout(1000);
+  await page.getByTestId("extended-disclosure").click();
+  await page.getByPlaceholder("Search").click();
+  await page.getByPlaceholder("Search").fill("text input");
+  await page.waitForTimeout(1000);
+
+  await page
+    .getByTestId("inputsText Input")
+    .dragTo(page.locator('//*[@id="react-flow-id"]'));
+  await page.mouse.up();
+  await page.mouse.down();
+
+  await page.getByPlaceholder("Search").click();
+  await page.getByPlaceholder("Search").fill("openai");
+  await page.waitForTimeout(1000);
+
+  await page
+    .getByTestId("modelsOpenAI")
+    .dragTo(page.locator('//*[@id="react-flow-id"]'));
+  await page.mouse.up();
+  await page.mouse.down();
+
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+
+  // Click and hold on the first element
+  await page
+    .locator(
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div[1]/div/div[2]/div[6]/button/div/div'
+    )
+    .hover();
+  await page.mouse.down();
+
+  // Move to the second element
+  await page
+    .locator(
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div[2]/div/div[2]/div[9]/div/button/div/div'
+    )
+    .hover();
+
+  // Release the mouse
+  await page.mouse.up();
+
+  await page.getByPlaceholder("Search").click();
+  await page.getByPlaceholder("Search").fill("text output");
+
+  await page
+    .getByTestId("outputsText Output")
+    .dragTo(page.locator('//*[@id="react-flow-id"]'));
+  await page.mouse.up();
+  await page.mouse.down();
+
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+
+  // Click and hold on the first element
+  await page
+    .locator(
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div[2]/div/div[2]/div[13]/button/div/div'
+    )
+    .hover();
+  await page.mouse.down();
+
+  // Move to the second element
+  await page
+    .locator(
+      '//*[@id="react-flow-id"]/div/div[1]/div[1]/div/div[2]/div[3]/div/div[2]/div[3]/div/button/div/div'
+    )
+    .hover();
+
+  // Release the mouse
+  await page.mouse.up();
+
+  if (!process.env.OPENAI_API_KEY) {
+    //You must set the OPENAI_API_KEY on .env file to run this test
+    expect(false).toBe(true);
+  }
+
+  await page.getByTestId("input-input_value").nth(0).fill("This is a test!");
+
+  await page
+    .getByTestId("input-openai_api_key")
+    .fill(process.env.OPENAI_API_KEY ?? "");
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByText("Run Flow", { exact: true }).click();
+
+  await page.waitForTimeout(5000);
+
+  let textInputContent = await page
+    .getByPlaceholder("Enter text...")
+    .textContent();
+  expect(textInputContent).toBe("This is a test!");
+
+  await page.getByText("Outputs", { exact: true }).nth(1).click();
+  await page.getByText("Text Output", { exact: true }).nth(2).click();
+  let contentOutput = await page.getByPlaceholder("Empty").inputValue();
+  expect(contentOutput).not.toBe(null);
+  expect(contentOutput).not.toBe("");
+
+  await page.keyboard.press("Escape");
+
+  await page
+    .getByTestId("input-input_value")
+    .nth(0)
+    .fill("This is a test, again just to be sure!");
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByText("Run Flow", { exact: true }).click();
+
+  await page.waitForTimeout(5000);
+
+  textInputContent = await page.getByPlaceholder("Enter text...").textContent();
+  expect(textInputContent).toBe("This is a test, again just to be sure!");
+
+  await page.getByText("Outputs", { exact: true }).nth(1).click();
+  await page.getByText("Text Output", { exact: true }).nth(2).click();
+  contentOutput = await page.getByPlaceholder("Empty").textContent();
+  expect(contentOutput).not.toBe(null);
+  expect(contentOutput).not.toBe("");
+});

src/frontend/tests/end-to-end/toggleComponent.spec.ts

@@ -1,36 +1,42 @@
 import { expect, test } from "@playwright/test";
 
 test("ToggleComponent", async ({ page }) => {
-  await page.goto("http:localhost:3000/");
+  await page.goto("/");
   await page.waitForTimeout(2000);
 
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await page.waitForTimeout(1000);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
 
   await page.getByTestId("blank-flow").click();
   await page.waitForTimeout(1000);
   await page.getByTestId("extended-disclosure").click();
   await page.getByPlaceholder("Search").click();
-  await page.getByPlaceholder("Search").fill("directoryLoader");
+  await page.getByPlaceholder("Search").fill("directory");
 
   await page.waitForTimeout(1000);
   await page
-    .getByTestId("documentloadersDirectoryLoader")
+    .getByTestId("dataDirectory")
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
   await page.mouse.up();
   await page.mouse.down();
 
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
-
-  await page
-    .locator('//*[@id="react-flow-id"]/div[1]/div[2]/button[2]')
-    .click();
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
 
   await page.getByTestId("div-generic-node").click();
 
@@ -44,8 +50,7 @@ test("ToggleComponent", async ({ page }) => {
 
   await page.locator('//*[@id="saveChangesBtn"]').click();
 
-  await page.getByTestId("toggle-load_hidden").click();
-  expect(await page.getByTestId("toggle-load_hidden").isChecked()).toBeFalsy();
+  await page.getByTitle("fit view").click();
 
   await page.getByTestId("toggle-load_hidden").click();
   expect(await page.getByTestId("toggle-load_hidden").isChecked()).toBeTruthy();
@@ -59,15 +64,20 @@ test("ToggleComponent", async ({ page }) => {
   await page.getByTestId("toggle-load_hidden").click();
   expect(await page.getByTestId("toggle-load_hidden").isChecked()).toBeFalsy();
 
+  await page.getByTestId("toggle-load_hidden").click();
+  expect(await page.getByTestId("toggle-load_hidden").isChecked()).toBeTruthy();
+
   await page.getByTestId("div-generic-node").click();
 
+  await page.getByTitle("fit view").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+  await page.getByTitle("zoom out").click();
+
   await page.getByTestId("more-options-modal").click();
   await page.getByTestId("edit-button-modal").click();
 
-  expect(await page.getByTestId("toggle-load_hidden").isChecked()).toBeFalsy();
-
-  await page.locator('//*[@id="showglob"]').click();
-  expect(await page.locator('//*[@id="showglob"]').isChecked()).toBeFalsy();
+  expect(await page.getByTestId("toggle-load_hidden").isChecked()).toBeTruthy();
 
   await page.locator('//*[@id="showload_hidden"]').click();
   expect(
@@ -79,9 +89,6 @@ test("ToggleComponent", async ({ page }) => {
     await page.locator('//*[@id="showmax_concurrency"]').isChecked()
   ).toBeTruthy();
 
-  await page.locator('//*[@id="showmetadata"]').click();
-  expect(await page.locator('//*[@id="showmetadata"]').isChecked()).toBeFalsy();
-
   await page.locator('//*[@id="showpath"]').click();
   expect(await page.locator('//*[@id="showpath"]').isChecked()).toBeFalsy();
 
@@ -100,19 +107,11 @@ test("ToggleComponent", async ({ page }) => {
     await page.locator('//*[@id="showuse_multithreading"]').isChecked()
   ).toBeTruthy();
 
-  await page.locator('//*[@id="showglob"]').click();
-  expect(await page.locator('//*[@id="showglob"]').isChecked()).toBeTruthy();
-
   await page.locator('//*[@id="showmax_concurrency"]').click();
   expect(
     await page.locator('//*[@id="showmax_concurrency"]').isChecked()
   ).toBeFalsy();
 
-  await page.locator('//*[@id="showmetadata"]').click();
-  expect(
-    await page.locator('//*[@id="showmetadata"]').isChecked()
-  ).toBeTruthy();
-
   await page.locator('//*[@id="showpath"]').click();
   expect(await page.locator('//*[@id="showpath"]').isChecked()).toBeTruthy();
 
@@ -134,7 +133,7 @@ test("ToggleComponent", async ({ page }) => {
   await page.locator('//*[@id="saveChangesBtn"]').click();
 
   const plusButtonLocator = page.getByTestId("toggle-load_hidden");
-  const elementCount = await plusButtonLocator.count();
+  const elementCount = await plusButtonLocator?.count();
   if (elementCount === 0) {
     expect(true).toBeTruthy();
 
@@ -150,15 +149,10 @@ test("ToggleComponent", async ({ page }) => {
 
     expect(
       await page.getByTestId("toggle-edit-load_hidden").isChecked()
-    ).toBeFalsy();
+    ).toBeTruthy();
 
     await page.locator('//*[@id="saveChangesBtn"]').click();
 
-    await page.getByTestId("toggle-load_hidden").click();
-    expect(
-      await page.getByTestId("toggle-load_hidden").isChecked()
-    ).toBeTruthy();
-
     await page.getByTestId("toggle-load_hidden").click();
     expect(
       await page.getByTestId("toggle-load_hidden").isChecked()
@@ -178,5 +172,10 @@ test("ToggleComponent", async ({ page }) => {
     expect(
       await page.getByTestId("toggle-load_hidden").isChecked()
     ).toBeTruthy();
+
+    await page.getByTestId("toggle-load_hidden").click();
+    expect(
+      await page.getByTestId("toggle-load_hidden").isChecked()
+    ).toBeFalsy();
   }
 });

src/frontend/tests/end-to-end/tweaks_test.spec.ts

@@ -2,8 +2,22 @@ import { expect, test } from "@playwright/test";
 
 test("curl_api_generation", async ({ page, context }) => {
   await page.goto("/");
-  await page.locator('//*[@id="new-project-btn"]').click();
-  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  let modalCount = 0;
+  try {
+    const modalTitleElement = await page?.getByTestId("modal-title");
+    if (modalTitleElement) {
+      modalCount = await modalTitleElement.count();
+    }
+  } catch (error) {
+    modalCount = 0;
+  }
+
+  while (modalCount === 0) {
+    await page.locator('//*[@id="new-project-btn"]').click();
+    await page.waitForTimeout(5000);
+    modalCount = await page.getByTestId("modal-title")?.count();
+  }
+
   await page.getByRole("heading", { name: "Basic Prompting" }).click();
   await page.waitForTimeout(2000);
   await page.getByText("API", { exact: true }).click();

tests/conftest.py

@@ -19,7 +19,6 @@ from langflow.services.database.models.flow.model import Flow, FlowCreate
 from langflow.services.database.models.user.model import User, UserCreate
 from langflow.services.database.utils import session_getter
 from langflow.services.deps import get_db_service
-from sqlmodel import Session, SQLModel, create_engine, select
 from sqlmodel.pool import StaticPool
 from typer.testing import CliRunner