update branch with changes from dev
54
.github/workflows/docker-build.yml
vendored
Normal file
|
|
@ -0,0 +1,54 @@
|
|||
name: Docker Build and Push
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
version:
|
||||
required: true
|
||||
type: string
|
||||
release_type:
|
||||
required: true
|
||||
type: string
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
version:
|
||||
required: true
|
||||
type: string
|
||||
release_type:
|
||||
required: true
|
||||
type: choice
|
||||
options:
|
||||
- base
|
||||
- main
|
||||
|
||||
jobs:
|
||||
docker_build:
|
||||
name: Build Docker Image
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
- name: Login to Docker Hub
|
||||
uses: docker/login-action@v3
|
||||
with:
|
||||
username: ${{ secrets.DOCKERHUB_USERNAME }}
|
||||
password: ${{ secrets.DOCKERHUB_TOKEN }}
|
||||
- name: Set Dockerfile and Tags
|
||||
id: set-vars
|
||||
run: |
|
||||
if [ "${{ inputs.release_type }}" == "base" ]; then
|
||||
echo "DOCKERFILE=./docker/build_and_push_base.Dockerfile" >> $GITHUB_ENV
|
||||
echo "TAGS=langflowai/langflow:base-${{ inputs.version }}" >> $GITHUB_ENV
|
||||
else
|
||||
echo "DOCKERFILE=./docker/build_and_push.Dockerfile" >> $GITHUB_ENV
|
||||
echo "TAGS=langflowai/langflow:${{ inputs.version }},langflowai/langflow:1.0-alpha" >> $GITHUB_ENV
|
||||
fi
|
||||
- name: Build and push
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ${{ env.DOCKERFILE }}
|
||||
tags: ${{ env.TAGS }}
|
||||
2
.github/workflows/pre-release-base.yml
vendored
|
|
@ -72,6 +72,6 @@ jobs:
|
|||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./build_and_push_base.Dockerfile
|
||||
file: ./docker/build_and_push_base.Dockerfile
|
||||
tags: |
|
||||
langflowai/langflow:base-${{ needs.release.outputs.version }}
|
||||
|
|
|
|||
2
.github/workflows/pre-release-langflow.yml
vendored
|
|
@ -78,7 +78,7 @@ jobs:
|
|||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./build_and_push.Dockerfile
|
||||
file: ./docker/build_and_push.Dockerfile
|
||||
tags: |
|
||||
langflowai/langflow:${{ needs.release.outputs.version }}
|
||||
langflowai/langflow:1.0-alpha
|
||||
|
|
|
|||
101
.github/workflows/pre-release.yml
vendored
Normal file
|
|
@ -0,0 +1,101 @@
|
|||
name: Langflow Pre-release (Unified)
|
||||
run-name: Langflow (${{inputs.release_type}}) Pre-release by @${{ github.actor }}
|
||||
on:
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
release_package:
|
||||
description: "Release package"
|
||||
required: true
|
||||
type: boolean
|
||||
default: false
|
||||
release_type:
|
||||
description: "Type of release (base or main)"
|
||||
required: true
|
||||
type: choice
|
||||
options:
|
||||
- base
|
||||
- main
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.8.2"
|
||||
|
||||
jobs:
|
||||
release:
|
||||
name: Release Langflow
|
||||
if: inputs.release_package == true
|
||||
runs-on: ubuntu-latest
|
||||
outputs:
|
||||
version: ${{ steps.check-version.outputs.version }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.10"
|
||||
cache: "poetry"
|
||||
- name: Check Version
|
||||
id: check-version
|
||||
run: |
|
||||
if [ "${{ inputs.release_type }}" == "base" ]; then
|
||||
version=$(cd src/backend/base && poetry version --short)
|
||||
last_released_version=$(curl -s "https://pypi.org/pypi/langflow-base/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1)
|
||||
else
|
||||
version=$(poetry version --short)
|
||||
last_released_version=$(curl -s "https://pypi.org/pypi/langflow/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1)
|
||||
fi
|
||||
if [ "$version" = "$last_released_version" ]; then
|
||||
echo "Version $version is already released. Skipping release."
|
||||
exit 1
|
||||
else
|
||||
echo version=$version >> $GITHUB_OUTPUT
|
||||
fi
|
||||
- name: Build project for distribution
|
||||
run: |
|
||||
if [ "${{ inputs.release_type }}" == "base" ]; then
|
||||
make build base=true
|
||||
else
|
||||
make build main=true
|
||||
fi
|
||||
- name: Publish to PyPI
|
||||
env:
|
||||
POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }}
|
||||
run: |
|
||||
if [ "${{ inputs.release_type }}" == "base" ]; then
|
||||
make publish base=true
|
||||
else
|
||||
make publish main=true
|
||||
fi
|
||||
|
||||
call_docker_build:
|
||||
name: Call Docker Build Workflow
|
||||
runs-on: ubuntu-latest
|
||||
needs: release
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: ./.github/workflows/docker-build.yml
|
||||
with:
|
||||
version: ${{ needs.release.outputs.version }}
|
||||
release_type: ${{ inputs.release_type }}
|
||||
|
||||
create_release:
|
||||
name: Create Release
|
||||
runs-on: ubuntu-latest
|
||||
needs: [call_docker_build, release]
|
||||
if: ${{ inputs.release_type == 'main' }}
|
||||
steps:
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: dist
|
||||
path: dist
|
||||
- name: Create Release
|
||||
uses: ncipollo/release-action@v1
|
||||
with:
|
||||
artifacts: "dist/*"
|
||||
token: ${{ secrets.GITHUB_TOKEN }}
|
||||
draft: false
|
||||
generateReleaseNotes: true
|
||||
prerelease: true
|
||||
tag: v${{ needs.release.outputs.version }}
|
||||
commit: dev
|
||||
2
.github/workflows/release.yml
vendored
|
|
@ -50,7 +50,7 @@ jobs:
|
|||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./build_and_push.Dockerfile
|
||||
file: ./docker/build_and_push.Dockerfile
|
||||
tags: |
|
||||
langflowai/langflow:${{ steps.check-version.outputs.version }}
|
||||
langflowai/langflow:latest
|
||||
|
|
|
|||
16
.github/workflows/typescript_test.yml
vendored
|
|
@ -19,8 +19,8 @@ jobs:
|
|||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
shardIndex: [1]
|
||||
shardTotal: [1]
|
||||
shardIndex: [1, 2, 3, 4]
|
||||
shardTotal: [4]
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
|
|
@ -30,7 +30,15 @@ jobs:
|
|||
id: setup-node
|
||||
with:
|
||||
node-version: ${{ env.NODE_VERSION }}
|
||||
cache: "npm"
|
||||
|
||||
- name: Cache Node.js dependencies
|
||||
uses: actions/cache@v4
|
||||
id: npm-cache
|
||||
with:
|
||||
path: ~/.npm
|
||||
key: ${{ runner.os }}-node-${{ hashFiles('src/frontend/package-lock.json') }}
|
||||
restore-keys: |
|
||||
${{ runner.os }}-node-
|
||||
|
||||
- name: Install Node.js dependencies
|
||||
run: |
|
||||
|
|
@ -80,7 +88,7 @@ jobs:
|
|||
- name: Run Playwright Tests
|
||||
run: |
|
||||
cd src/frontend
|
||||
npx playwright test
|
||||
npx playwright test --shard ${{ matrix.shardIndex }}/${{ matrix.shardTotal }} --workers 2
|
||||
|
||||
- name: Upload blob report to GitHub Actions Artifacts
|
||||
if: always()
|
||||
|
|
|
|||
|
|
@ -18,7 +18,10 @@ repos:
|
|||
hooks:
|
||||
- id: check-case-conflict
|
||||
- id: end-of-file-fixer
|
||||
# python, js and ts only
|
||||
files: \.(py|js|ts)$
|
||||
- id: mixed-line-ending
|
||||
files: \.(py|js|ts)$
|
||||
args:
|
||||
- --fix=lf
|
||||
- id: trailing-whitespace
|
||||
|
|
|
|||
|
|
@ -1,31 +0,0 @@
|
|||
# Read the Docs configuration file for Sphinx projects
|
||||
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
|
||||
|
||||
# Required
|
||||
version: 2
|
||||
|
||||
# Set the OS, Python version and other tools you might need
|
||||
build:
|
||||
os: ubuntu-22.04
|
||||
tools:
|
||||
python: "3.11"
|
||||
# You can also specify other tool versions:
|
||||
# nodejs: "19"
|
||||
# rust: "1.64"
|
||||
# golang: "1.19"
|
||||
|
||||
# Build documentation in the "docs/" directory with Sphinx
|
||||
sphinx:
|
||||
configuration: docs/conf.py
|
||||
|
||||
# Optionally build your docs in additional formats such as PDF and ePub
|
||||
# formats:
|
||||
# - pdf
|
||||
# - epub
|
||||
|
||||
# Optional but recommended, declare the Python requirements required
|
||||
# to build your documentation
|
||||
# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
|
||||
# python:
|
||||
# install:
|
||||
# - requirements: docs/requirements.txt
|
||||
|
|
@ -65,7 +65,6 @@ Each option is detailed below:
|
|||
- `--workers`: Sets the number of worker processes. Can be set using the `LANGFLOW_WORKERS` environment variable. The default is `1`.
|
||||
- `--timeout`: Sets the worker timeout in seconds. The default is `60`.
|
||||
- `--port`: Sets the port to listen on. Can be set using the `LANGFLOW_PORT` environment variable. The default is `7860`.
|
||||
- `--config`: Defines the path to the configuration file. The default is `config.yaml`.
|
||||
- `--env-file`: Specifies the path to the .env file containing environment variables. The default is `.env`.
|
||||
- `--log-level`: Defines the logging level. Can be set using the `LANGFLOW_LOG_LEVEL` environment variable. The default is `critical`.
|
||||
- `--components-path`: Specifies the path to the directory containing custom components. Can be set using the `LANGFLOW_COMPONENTS_PATH` environment variable. The default is `langflow/components`.
|
||||
|
|
|
|||
|
|
@ -1,99 +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 just one file to avoid rebuilding the whole image
|
||||
COPY poetry.lock pyproject.toml ./
|
||||
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
|
||||
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 ./src/backend/langflow
|
||||
# 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
|
||||
RUN --mount=type=cache,target=/root/.cache \
|
||||
poetry install --with=dev --extras deploy
|
||||
COPY ./tests ./tests=
|
||||
|
||||
|
|
@ -1,33 +0,0 @@
|
|||
version: "3.4"
|
||||
|
||||
services:
|
||||
backend:
|
||||
volumes:
|
||||
- ./:/app
|
||||
build:
|
||||
context: ./
|
||||
dockerfile: ./dev.Dockerfile
|
||||
command:
|
||||
[
|
||||
"sh",
|
||||
"-c",
|
||||
"pip install debugpy -t /tmp && python /tmp/debugpy --wait-for-client --listen 0.0.0.0:5678 -m uvicorn --factory langflow.main:create_app --host 0.0.0.0 --port 7860 --reload --loop asyncio",
|
||||
]
|
||||
ports:
|
||||
- 7860:7860
|
||||
- 5678:5678
|
||||
restart: on-failure
|
||||
|
||||
frontend:
|
||||
build:
|
||||
context: ./src/frontend
|
||||
dockerfile: ./dev.Dockerfile
|
||||
args:
|
||||
- BACKEND_URL=http://backend:7860
|
||||
ports:
|
||||
- "3000:3000"
|
||||
volumes:
|
||||
- ./src/frontend/public:/home/node/app/public
|
||||
- ./src/frontend/src:/home/node/app/src
|
||||
- ./src/frontend/package.json:/home/node/app/package.json
|
||||
restart: on-failure
|
||||
|
|
@ -78,9 +78,10 @@ RUN $POETRY_HOME/bin/poetry build
|
|||
|
||||
# Copy virtual environment and built .tar.gz from builder base
|
||||
RUN useradd -m -u 1000 user
|
||||
RUN chown -R user:user /app
|
||||
USER user
|
||||
# Install the package from the .tar.gz
|
||||
RUN python -m pip install /app/dist/*.tar.gz --user
|
||||
|
||||
RUN python -m pip install /app/dist/*.tar.gz
|
||||
|
||||
ENTRYPOINT ["python", "-m", "langflow", "run"]
|
||||
CMD ["--host", "0.0.0.0", "--port", "7860"]
|
||||
CMD ["--host", "0.0.0.0", "--port", "7860"]
|
||||
|
|
@ -78,13 +78,15 @@ RUN cd src/frontend && npm run build
|
|||
COPY src/backend ./src/backend
|
||||
RUN cp -r src/frontend/build src/backend/base/langflow/frontend
|
||||
RUN rm -rf src/backend/base/dist
|
||||
RUN cd src/backend/base && $POETRY_HOME/bin/poetry build --format sdist
|
||||
RUN cd src/backend/base && $POETRY_HOME/bin/poetry build
|
||||
|
||||
# Copy virtual environment and built .tar.gz from builder base
|
||||
RUN useradd -m -u 1000 user
|
||||
RUN chown -R user:user /app
|
||||
USER user
|
||||
# Install the package from the .tar.gz
|
||||
RUN python -m pip install /app/dist/*.tar.gz --user
|
||||
RUN python -m pip install /app/src/backend/base/dist/*.tar.gz
|
||||
|
||||
|
||||
ENTRYPOINT ["python", "-m", "langflow", "run"]
|
||||
CMD ["--host", "0.0.0.0", "--port", "7860"]
|
||||
CMD ["--host", "0.0.0.0", "--port", "7860"]
|
||||
|
|
@ -10,9 +10,9 @@ services:
|
|||
environment:
|
||||
- LANGFLOW_DATABASE_URL=postgresql://langflow:langflow@postgres:5432/langflow
|
||||
# This variable defines where the logs, file storage, monitor data and secret keys are stored.
|
||||
- LANGFLOW_CONFIG_DIR=/var/lib/langflow
|
||||
- LANGFLOW_CONFIG_DIR=app/langflow
|
||||
volumes:
|
||||
- langflow-data:/var/lib/langflow
|
||||
- langflow-data:app/langflow
|
||||
|
||||
postgres:
|
||||
image: postgres:16
|
||||
|
|
|
|||
|
|
@ -4,15 +4,13 @@ import Admonition from "@theme/Admonition";
|
|||
|
||||
# API Keys
|
||||
|
||||
## Introduction
|
||||
|
||||
Langflow offers an API Key functionality that allows users to access their individual components and flows without going through traditional login authentication. The API Key is a user-specific token that can be included in the request's header or query parameter to authenticate API calls. The following documentation outlines how to generate, use, and manage these API Keys in Langflow.
|
||||
Langflow provides an API key functionality that allows users to access their individual components and flows without traditional login authentication. The API key is a user-specific token that can be included in the request header or query parameter to authenticate API calls. This documentation outlines how to generate, use, and manage API keys in Langflow.
|
||||
|
||||
<Admonition type="warning">
|
||||
This feature requires the `LANGFLOW_AUTO_LOGIN` environment variable to be set
|
||||
to `False`. The default user and password are set using _`LANGFLOW_SUPERUSER`_
|
||||
and _`LANGFLOW_SUPERUSER_PASSWORD`_ environment variables. Default values are
|
||||
_`langflow`_ and _`langflow`_ respectively.
|
||||
This feature requires the LANGFLOW_AUTO_LOGIN environment variable to be set
|
||||
to False. The default user and password are set using the LANGFLOW_SUPERUSER
|
||||
and LANGFLOW_SUPERUSER_PASSWORD environment variables. The default values are
|
||||
langflow and langflow, respectively.
|
||||
</Admonition>
|
||||
|
||||
## Generating an API Key
|
||||
|
|
@ -93,7 +91,7 @@ print(run_flow(inputs, flow_id=FLOW_ID, tweaks=TWEAKS, apiKey=api_key))
|
|||
|
||||
### Using the Query Parameter
|
||||
|
||||
Alternatively, you can include the API key as a query parameter in the URL:
|
||||
Include the API key as a query parameter in the URL:
|
||||
|
||||
```bash
|
||||
curl -X POST \
|
||||
|
|
@ -146,9 +144,9 @@ print(run_flow(inputs, flow_id=FLOW_ID, tweaks=TWEAKS, apiKey=api_key))
|
|||
|
||||
## Security Considerations
|
||||
|
||||
- **Visibility**: The API key won't be retrievable again through the UI for security reasons.
|
||||
- **Scope**: The key only allows access to the flows and components of the specific user to whom it was issued.
|
||||
- **Visibility**: For security reasons, the API key cannot be retrieved again through the UI.
|
||||
- **Scope**: The key allows access only to the flows and components of the specific user to whom it was issued.
|
||||
|
||||
## Revoking an API Key
|
||||
|
||||
To revoke an API key, simply delete it from the UI. This will immediately invalidate the key and prevent it from being used again.
|
||||
To revoke an API key, delete it from the UI. This action immediately invalidates the key and prevents it from being used again.
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
# 🖥️ Command Line Interface (CLI)
|
||||
# Command Line Interface (CLI)
|
||||
|
||||
## Overview
|
||||
|
||||
|
|
@ -19,7 +19,6 @@ Each option is detailed below:
|
|||
- `--workers`: Sets the number of worker processes. Can be set using the `LANGFLOW_WORKERS` environment variable. The default is `1`.
|
||||
- `--timeout`: Sets the worker timeout in seconds. The default is `60`.
|
||||
- `--port`: Sets the port to listen on. Can be set using the `LANGFLOW_PORT` environment variable. The default is `7860`.
|
||||
- `--config`: Defines the path to the configuration file. The default is `config.yaml`.
|
||||
- `--env-file`: Specifies the path to the .env file containing environment variables. The default is `.env`.
|
||||
- `--log-level`: Defines the logging level. Can be set using the `LANGFLOW_LOG_LEVEL` environment variable. The default is `critical`.
|
||||
- `--components-path`: Specifies the path to the directory containing custom components. Can be set using the `LANGFLOW_COMPONENTS_PATH` environment variable. The default is `langflow/components`.
|
||||
|
|
|
|||
|
|
@ -391,13 +391,13 @@ The recommended way to load custom components is to set the _`LANGFLOW_COMPONENT
|
|||
|
||||
```bash
|
||||
export LANGFLOW_COMPONENTS_PATH='["/path/to/components"]'
|
||||
langflow
|
||||
langflow run
|
||||
```
|
||||
|
||||
Alternatively, you can specify the path to your custom components using the _`--components-path`_ argument when running the Langflow CLI, as shown below:
|
||||
|
||||
```bash
|
||||
langflow --components-path /path/to/components
|
||||
langflow run --components-path /path/to/components
|
||||
```
|
||||
|
||||
Langflow will attempt to load all of the components found in the specified directory. If a component fails to load due to errors in the component's code, Langflow will print an error message to the console but will continue loading the rest of the components.
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import Admonition from "@theme/Admonition";
|
||||
import ReactPlayer from "react-player";
|
||||
|
||||
# Global environment variables
|
||||
|
||||
|
|
@ -43,3 +44,11 @@ You now have a `openai_api_key` global environment variable for your Langflow pr
|
|||
4. To view and manage your project's global environment variables, visit **Settings** > **Variables and Secrets**.
|
||||
|
||||
For more on variables in HuggingFace Spaces, see [Managing Secrets](https://huggingface.co/docs/hub/spaces-overview#managing-secrets).
|
||||
|
||||
## Video
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_global_variables.mp4" />
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,49 +0,0 @@
|
|||
# Integrating Langfuse with Langflow
|
||||
|
||||
## Introduction
|
||||
|
||||
Langfuse is an open-source tracing and analytics tool designed for LLM applications. Integrating Langfuse with Langflow provides detailed production traces and granular insights into quality, cost, and latency. This integration allows you to monitor and debug your Langflow's chat or APIs easily.
|
||||
|
||||
## Step-by-Step Instructions
|
||||
|
||||
### Step 1: Create a Langfuse account
|
||||
|
||||
1. Go to [Langfuse](https://langfuse.com) and click on the "Sign In" button in the top right corner.
|
||||
2. Click on the "Sign Up" button and create an account.
|
||||
3. Once logged in, click on "Settings" and then on "Create new API keys."
|
||||
4. Copy the Public key and the Secret Key and save them somewhere safe.
|
||||
{/* Add these keys to your environment variables in the following step. */}
|
||||
|
||||
### Step 2: Set up Langfuse in Langflow
|
||||
|
||||
1. **Export the Environment Variables**: You'll need to export the environment variables `LANGFLOW_LANGFUSE_SECRET_KEY` and `LANGFLOW_LANGFUSE_PUBLIC_KEY` with the values obtained in Step 1.
|
||||
|
||||
You can do this by executing the following commands in your terminal:
|
||||
|
||||
```bash
|
||||
export LANGFLOW_LANGFUSE_SECRET_KEY=<your secret key>
|
||||
export LANGFLOW_LANGFUSE_PUBLIC_KEY=<your public key>
|
||||
```
|
||||
|
||||
Alternatively, you can run the Langflow CLI command:
|
||||
|
||||
```bash
|
||||
LANGFLOW_LANGFUSE_SECRET_KEY=<your secret key> LANGFLOW_LANGFUSE_PUBLIC_KEY=<your public key> langflow
|
||||
```
|
||||
|
||||
If you are self-hosting Langfuse, you can also set the environment variable `LANGFLOW_LANGFUSE_HOST` to point to your Langfuse instance. By default, Langfuse points to the cloud instance at `https://cloud.langfuse.com`.
|
||||
|
||||
2. **Verify Integration**: Ensure that the environment variables are set correctly by checking their existence in your environment, for example by running:
|
||||
|
||||
```bash
|
||||
echo $LANGFLOW_LANGFUSE_SECRET_KEY
|
||||
echo $LANGFLOW_LANGFUSE_PUBLIC_KEY
|
||||
```
|
||||
|
||||
3. **Monitor Langflow**: Now, whenever you use Langflow's chat or API, you will be able to see the tracing of your conversations in Langfuse.
|
||||
|
||||
That's it! You have successfully integrated Langfuse with Langflow, enhancing observability and debugging capabilities for your LLM application.
|
||||
|
||||
---
|
||||
|
||||
Note: For more details or customized configurations, please refer to the official [Langfuse documentation](https://langfuse.com/docs/integrations/langchain).
|
||||
|
|
@ -14,7 +14,7 @@ It even works for flows hosted on the Langflow store!
|
|||
|
||||
As long as you have a flow's environment variables set, you can run it by clicking the **Playground** button.
|
||||
|
||||
1. From your **Collections** page, click **Playground** in one of your flows.
|
||||
1. From your **Collections** page, click the **Playground** in one of your flows.
|
||||
The **Playground** window opens.
|
||||
|
||||
<ZoomableImage
|
||||
|
|
@ -27,3 +27,11 @@ As long as you have a flow's environment variables set, you can run it by clicki
|
|||
/>
|
||||
|
||||
2. Chat with your bot as you normally would, all without having to open the editor.
|
||||
|
||||
## Video
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_playground.mp4" />
|
||||
</div>
|
||||
|
|
|
|||
217
docs/docs/getting-started/canvas.mdx
Normal file
|
|
@ -0,0 +1,217 @@
|
|||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import ReactPlayer from "react-player";
|
||||
import Admonition from "@theme/Admonition";
|
||||
|
||||
# 🎨 Langflow canvas
|
||||
|
||||
The **Langflow canvas** is the central hub of Langflow, where you'll assemble new flows from components, run them, and see the results.
|
||||
|
||||
To get a feel for the canvas, we'll examine a basic prompting flow.
|
||||
You can either build this flow yourself, or select **New Project** > **Basic prompting** to open a canvas with the flow pre-built.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/basic-prompting.png",
|
||||
dark: "img/basic-prompting.png",
|
||||
}}
|
||||
style={{ width: "30%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
For more on the difference between flows, components, collections, and projects, see [Flows, collections, components, and projects](./flows-components-collections.mdx).
|
||||
|
||||
## Components
|
||||
|
||||
A component is a building block of a flow.
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
During the flow creation process, you will notice handles (colored circles)
|
||||
attached to one or both sides of a component. These handles represent the
|
||||
availability to connect to other components. Hover over a handle to see
|
||||
connection details.
|
||||
</div>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
For example, if you select a <code>ConversationChain</code> component, you
|
||||
will see orange <span style={{ color: "orange" }}>o</span> and purple{" "}
|
||||
<span style={{ color: "purple" }}>o</span> input handles. They indicate that
|
||||
this component accepts an LLM and a Memory component as inputs. The red
|
||||
asterisk <span style={{ color: "red" }}>*</span> means that at least one input
|
||||
of that type is required.
|
||||
</div>
|
||||
|
||||
{" "}
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/single-component.png"),
|
||||
dark: useBaseUrl("img/single-component.png"),
|
||||
}}
|
||||
style={{ width: "50%", maxWidth: "800px", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
In the top right corner of the component, you'll find the component status icon ().
|
||||
Run the flow by clicking the **Playground** button at the bottom right of the canvas.
|
||||
|
||||
Once the validation is complete, the status of each validated component should turn green ().
|
||||
To debug, hover over the component status to see the outputs.
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
### Component menu
|
||||
|
||||
Each component is a little unique, but they will all have a menu bar on top that looks something like this.
|
||||
The menu options are **Code**, **Save**, **Duplicate**, and **More**.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/chat-input-with-menu.png",
|
||||
dark: "img/chat-input-with-menu.png",
|
||||
}}
|
||||
style={{ width: "30%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
#### Code
|
||||
|
||||
The **Code** button displays your component's Python code.
|
||||
You can modify the code and save it.
|
||||
|
||||
#### Save
|
||||
|
||||
Save your component to the **Saved** components folder for re-use.
|
||||
|
||||
#### Duplicate
|
||||
|
||||
Duplicate your component in the canvas.
|
||||
|
||||
#### More
|
||||
|
||||
**Advanced** - modify the parameters of your component.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_parameters.mp4" />
|
||||
</div>
|
||||
|
||||
**Copy** - copy your component.
|
||||
|
||||
**Share** - share your component to the Langflow store.
|
||||
|
||||
**Docs** - view documentation for your component.
|
||||
|
||||
**Delete** - delete your component.
|
||||
|
||||
### Group multiple components
|
||||
|
||||
Components without input or output nodes can be grouped into a single component for re-use.
|
||||
This is useful for combining large flows into single components (like RAG with a vector database, for example) and saves space in the canvas.
|
||||
|
||||
1. Hold **Shift** and drag to select the **Prompt** and **OpenAI** components.
|
||||
2. Select **Group**.
|
||||
3. The components merge into a single component.
|
||||
4. To save the new component, select **Save**. It can now be re-used from the **Saved** components folder.
|
||||
|
||||
## Playground
|
||||
|
||||
Run your flow by clicking the **Playground** button.
|
||||
|
||||
For more, see [Playground](../administration/playground.mdx).
|
||||
|
||||
## API
|
||||
|
||||
The **API** button opens the API window, where Langflow presents code for integrating your flow into external applications.
|
||||
|
||||
Modify the call's parameters in the **Tweaks** window, click the **Copy Code** or **Download** buttons, and paste your code where you want to use it.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/api-window.png",
|
||||
dark: "img/api-window.png",
|
||||
}}
|
||||
style={{ width: "50%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
### curl
|
||||
|
||||
The **curl** tab displays sample code for posting a query to your flow.
|
||||
Modify the `input_value` to change your input message.
|
||||
|
||||
```curl
|
||||
curl -X POST \
|
||||
http://127.0.0.1:7863/api/v1/run/f2eefd80-bb91-4190-9279-0d6ffafeaac4\?stream\=false \
|
||||
-H 'Content-Type: application/json'\
|
||||
-d '{"input_value": "is anybody there?",
|
||||
"output_type": "chat",
|
||||
"input_type": "chat",
|
||||
"tweaks": {
|
||||
"Prompt-uxBqP": {},
|
||||
"OpenAIModel-k39HS": {},
|
||||
"ChatOutput-njtka": {},
|
||||
"ChatInput-P3fgL": {}
|
||||
}}'
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```
|
||||
{"session_id":"f2eefd80-bb91-4190-9279-0d6ffafeaac4:53856a772b8e1cfcb3dd2e71576b5215399e95bae318d3c02101c81b7c252da3","outputs":[{"inputs":{"input_value":"is anybody there?"},"outputs":[{"results":{"result":"Arrr, me hearties! Aye, this be Captain [Your Name] speakin'. What be ye needin', matey?"},"artifacts":{"message":"Arrr, me hearties! Aye, this be Captain [Your Name] speakin'. What be ye needin', matey?","sender":"Machine","sender_name":"AI"},"messages":[{"message":"Arrr, me hearties! Aye, this be Captain [Your Name] speakin'. What be ye needin', matey?","sender":"Machine","sender_name":"AI","component_id":"ChatOutput-njtka"}],"component_display_name":"Chat Output","component_id":"ChatOutput-njtka"}]}]}%
|
||||
```
|
||||
|
||||
### Python API
|
||||
|
||||
The **Python API** tab displays code to interact with your flow using the Python HTTP requests library.
|
||||
|
||||
### Python Code
|
||||
|
||||
The **Python Code** tab displays code to interact with your flow's `.json` file using the Langflow runtime.
|
||||
|
||||
### Chat Widget HTML
|
||||
|
||||
The **Chat Widget HTML** tab displays code that can be inserted in the `<body>` of your HTML to interact with your flow.
|
||||
For more, see the [Chat widget documentation](../administration/chat-widget.mdx).
|
||||
|
||||
### Tweaks
|
||||
|
||||
The **Tweaks** tab displays the available parameters for your flow.
|
||||
Modifying the parameters changes the code parameters across all windows.
|
||||
For example, changing the **Chat Input** component's `input_value` will change that value across all API calls.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_api.mp4" />
|
||||
</div>
|
||||
|
||||
## Project options menu
|
||||
|
||||
To see options for your project, in the upper left corner of the canvas, select the dropdown menu.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/project-options-menu.png",
|
||||
dark: "img/project-options-menu.png",
|
||||
}}
|
||||
style={{ width: "30%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
**New** - Start a new project.
|
||||
|
||||
**Duplicate** - Duplicate the current flow as a new project.
|
||||
|
||||
**Settings** - Modify the project's **Name** or **Description**.
|
||||
|
||||
**Import** - Upload a flow `.json` file from your local machine.
|
||||
|
||||
**Export** - Download your current project to your local machine as a `.json` file.
|
||||
|
||||
**Undo** or **Redo** - Undo or redo your last action.
|
||||
115
docs/docs/getting-started/flows-components-collections.mdx
Normal file
|
|
@ -0,0 +1,115 @@
|
|||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import ReactPlayer from "react-player";
|
||||
|
||||
# 🖥️ Flows, components, collections, and projects
|
||||
|
||||
## TL;DR
|
||||
|
||||
A [flow](#flow) is a pipeline of components connected together in the Langflow canvas.
|
||||
|
||||
A [component](#component) is a single building block within a flow. A component has inputs, outputs, and parameters that define its functionality.
|
||||
|
||||
A [collection](#collection) is a snapshot of the flows available in your database. Collections can be downloaded to local storage and uploaded for future use.
|
||||
|
||||
A [project](#project) can be a component or a flow. Projects are saved as part of your collection.
|
||||
|
||||
For example, the **OpenAI LLM** is a **component** of the **Basic prompting** flow, and the **flow** is stored in a **collection**.
|
||||
|
||||
## Flow
|
||||
|
||||
A **flow** is a pipeline of components connected together in the Langflow canvas.
|
||||
|
||||
For example, the [Basic prompting](../starter-projects/basic-prompting.mdx) flow is a pipeline of four components:
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/basic-prompting.png",
|
||||
dark: "img/basic-prompting.png",
|
||||
}}
|
||||
style={{ width: "80%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
For example, the **OpenAI LLM component** receives input (left side) and produces output (right side) - in this case, receiving input from the **Chat Input** and **Prompt** components and producing output to the **Chat Output** component.
|
||||
|
||||
## Component
|
||||
|
||||
Components are the building blocks of flows. They consist of inputs, outputs, and parameters that define their functionality. These elements provide a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the LangChain [documentation](https://python.langchain.com/docs/integrations/components).
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
During the flow creation process, you will notice handles (colored circles)
|
||||
attached to one or both sides of a component. These handles represent the
|
||||
availability to connect to other components. Hover over a handle to see
|
||||
connection details.
|
||||
</div>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
For example, if you select a <code>ConversationChain</code> component, you
|
||||
will see orange <span style={{ color: "orange" }}>o</span> and purple{" "}
|
||||
<span style={{ color: "purple" }}>o</span> input handles. They indicate that
|
||||
this component accepts an LLM and a Memory component as inputs. The red
|
||||
asterisk <span style={{ color: "red" }}>*</span> means that at least one input
|
||||
of that type is required.
|
||||
</div>
|
||||
|
||||
{" "}
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/single-component.png"),
|
||||
dark: useBaseUrl("img/single-component.png"),
|
||||
}}
|
||||
style={{ width: "50%", maxWidth: "800px", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
In the top right corner of the component, you'll find the component status icon ().
|
||||
Build the flow by clicking the **Playground** at the bottom right of the canvas.
|
||||
|
||||
Once the validation is complete, the status of each validated component should turn green ().
|
||||
To debug, hover over the component status to see the outputs.
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
### Component Parameters
|
||||
|
||||
Langflow components can be edited by clicking the component settings button. Hide parameters to reduce complexity and keep the canvas clean and intuitive for experimentation.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_parameters.mp4" />
|
||||
</div>
|
||||
|
||||
## Collection
|
||||
|
||||
A collection is a snapshot of flows available in a database.
|
||||
|
||||
Collections can be downloaded to local storage and uploaded for future use.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_collection.mp4" />
|
||||
</div>
|
||||
|
||||
## Project
|
||||
|
||||
A **Project** can be a flow or a component. To view your saved projects, select **My Collection**.
|
||||
|
||||
Your **Projects** are displayed.
|
||||
|
||||
Click the ** Playground** button to run a flow from the **My Collection** screen.
|
||||
|
||||
In the top left corner of the screen are options for **Download Collection**, **Upload Collection**, and **New Project**.
|
||||
|
||||
Select **Download Collection** to save your project to your local machine. This downloads all flows and components as a `.json` file.
|
||||
|
||||
Select **Upload Collection** to upload a flow or component `.json` file from your local machine.
|
||||
|
||||
Select **New Project** to create a new project. In addition to a blank canvas, [starter projects](../starter-projects/basic-prompting.mdx) are also available.
|
||||
|
|
@ -1,4 +1,4 @@
|
|||
# Common Installation Issues
|
||||
# ❗️ Common Installation Issues
|
||||
|
||||
This is a list of possible issues that you may encounter when installing Langflow 1.0 alpha and how to solve them.
|
||||
|
||||
|
|
@ -25,11 +25,11 @@ ModuleNotFoundError: No module named 'langflow.__main__'
|
|||
There are two possible reasons for this error:
|
||||
|
||||
1. You've installed Langflow using _`pip install langflow`_ but you already had a previous version of Langflow installed in your system.
|
||||
In this case, you might be running the wrong executable.
|
||||
To solve this issue, run the correct executable by running _`python -m langflow run`_ instead of _`langflow run`_.
|
||||
If that doesn't work, try uninstalling and reinstalling Langflow with _`python -m pip install langflow --pre -U`_.
|
||||
In this case, you might be running the wrong executable.
|
||||
To solve this issue, run the correct executable by running _`python -m langflow run`_ instead of _`langflow run`_.
|
||||
If that doesn't work, try uninstalling and reinstalling Langflow with _`python -m pip install langflow --pre -U`_.
|
||||
2. Some version conflicts might have occurred during the installation process.
|
||||
Run _`python -m pip install langflow --pre -U --force-reinstall`_ to reinstall Langflow and its dependencies.
|
||||
Run _`python -m pip install langflow --pre -U --force-reinstall`_ to reinstall Langflow and its dependencies.
|
||||
|
||||
## _`Something went wrong running migrations. Please, run 'langflow migration --fix'`_
|
||||
|
||||
|
|
@ -45,4 +45,3 @@ There are two possible reasons for this error:
|
|||
This error can occur during Langflow upgrades when the new version can't override `langflow-pre.db` in `.cache/langflow/`. Clearing the cache removes this file but will also erase your settings.
|
||||
|
||||
If you wish to retain your files, back them up before clearing the folder.
|
||||
|
||||
|
|
|
|||
|
|
@ -15,6 +15,9 @@ module.exports = {
|
|||
"getting-started/install-langflow",
|
||||
"getting-started/quickstart",
|
||||
"getting-started/huggingface-spaces",
|
||||
"getting-started/canvas",
|
||||
"getting-started/flows-components-collections",
|
||||
"migration/possible-installation-issues",
|
||||
"getting-started/new-to-llms",
|
||||
],
|
||||
},
|
||||
|
|
@ -35,15 +38,12 @@ module.exports = {
|
|||
label: "Administration",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"administration/login",
|
||||
"administration/api",
|
||||
"administration/login",
|
||||
"administration/cli",
|
||||
"administration/playground",
|
||||
"administration/global-env",
|
||||
"administration/components",
|
||||
"administration/collection",
|
||||
"administration/prompt-customization",
|
||||
"administration/langfuse_integration",
|
||||
"administration/chat-widget",
|
||||
],
|
||||
},
|
||||
{
|
||||
|
|
|
|||
6506
docs/static/data/AstraDB-RAG-Flows.json
vendored
BIN
docs/static/img/api-window.png
vendored
Normal file
|
After Width: | Height: | Size: 277 KiB |
BIN
docs/static/img/chat-input-with-menu.png
vendored
Normal file
|
After Width: | Height: | Size: 72 KiB |
BIN
docs/static/img/features.png
vendored
|
Before Width: | Height: | Size: 3.2 KiB |
BIN
docs/static/img/project-options-menu.png
vendored
Normal file
|
After Width: | Height: | Size: 43 KiB |
BIN
docs/static/img/single-component.png
vendored
Normal file
|
After Width: | Height: | Size: 61 KiB |
8
docs/static/logos/botmessage.svg
vendored
Normal file
|
|
@ -0,0 +1,8 @@
|
|||
<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="white" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-bot-message-square">
|
||||
<path d="M12 6V2H8" />
|
||||
<path d="m8 18-4 4V8a2 2 0 0 1 2-2h12a2 2 0 0 1 2 2v8a2 2 0 0 1-2 2Z" />
|
||||
<path d="M2 12h2" />
|
||||
<path d="M9 11v2" />
|
||||
<path d="M15 11v2" />
|
||||
<path d="M20 12h2" />
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 417 B |
11
docs/static/logos/greencheck.svg
vendored
Normal file
|
|
@ -0,0 +1,11 @@
|
|||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
fill="none"
|
||||
viewBox="0 0 24 24"
|
||||
stroke="green"
|
||||
stroke-width="1.5"
|
||||
stroke-linecap="round"
|
||||
stroke-linejoin="round"
|
||||
>
|
||||
<path d="M20 6 9 17l-5-5" />
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 207 B |
11
docs/static/logos/playbutton.svg
vendored
Normal file
|
|
@ -0,0 +1,11 @@
|
|||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
fill="none"
|
||||
viewBox="0 0 24 24"
|
||||
stroke="white"
|
||||
stroke-width="2"
|
||||
stroke-linecap="round"
|
||||
stroke-linejoin="round"
|
||||
>
|
||||
<polygon points="5,3 19,12 5,21 5,3" fill="currentColor" />
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 236 B |
BIN
docs/static/videos/langflow_global_variables.mp4
vendored
Normal file
BIN
docs/static/videos/langflow_playground.mp4
vendored
Normal file
932
package-lock.json
generated
|
|
@ -1,932 +0,0 @@
|
|||
{
|
||||
"name": "langflow",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"dependencies": {
|
||||
"@radix-ui/react-popover": "^1.0.7",
|
||||
"cmdk": "^0.2.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@babel/runtime": {
|
||||
"version": "7.23.2",
|
||||
"resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.23.2.tgz",
|
||||
"integrity": "sha512-mM8eg4yl5D6i3lu2QKPuPH4FArvJ8KhTofbE7jwMUv9KX5mBvwPAqnV3MlyBNqdp9RyRKP6Yck8TrfYrPvX3bg==",
|
||||
"dependencies": {
|
||||
"regenerator-runtime": "^0.14.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=6.9.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@floating-ui/core": {
|
||||
"version": "1.5.0",
|
||||
"resolved": "https://registry.npmjs.org/@floating-ui/core/-/core-1.5.0.tgz",
|
||||
"integrity": "sha512-kK1h4m36DQ0UHGj5Ah4db7R0rHemTqqO0QLvUqi1/mUUp3LuAWbWxdxSIf/XsnH9VS6rRVPLJCncjRzUvyCLXg==",
|
||||
"dependencies": {
|
||||
"@floating-ui/utils": "^0.1.3"
|
||||
}
|
||||
},
|
||||
"node_modules/@floating-ui/dom": {
|
||||
"version": "1.5.3",
|
||||
"resolved": "https://registry.npmjs.org/@floating-ui/dom/-/dom-1.5.3.tgz",
|
||||
"integrity": "sha512-ClAbQnEqJAKCJOEbbLo5IUlZHkNszqhuxS4fHAVxRPXPya6Ysf2G8KypnYcOTpx6I8xcgF9bbHb6g/2KpbV8qA==",
|
||||
"dependencies": {
|
||||
"@floating-ui/core": "^1.4.2",
|
||||
"@floating-ui/utils": "^0.1.3"
|
||||
}
|
||||
},
|
||||
"node_modules/@floating-ui/react-dom": {
|
||||
"version": "2.0.4",
|
||||
"resolved": "https://registry.npmjs.org/@floating-ui/react-dom/-/react-dom-2.0.4.tgz",
|
||||
"integrity": "sha512-CF8k2rgKeh/49UrnIBs4BdxPUV6vize/Db1d/YbCLyp9GiVZ0BEwf5AiDSxJRCr6yOkGqTFHtmrULxkEfYZ7dQ==",
|
||||
"dependencies": {
|
||||
"@floating-ui/dom": "^1.5.1"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"react": ">=16.8.0",
|
||||
"react-dom": ">=16.8.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@floating-ui/utils": {
|
||||
"version": "0.1.6",
|
||||
"resolved": "https://registry.npmjs.org/@floating-ui/utils/-/utils-0.1.6.tgz",
|
||||
"integrity": "sha512-OfX7E2oUDYxtBvsuS4e/jSn4Q9Qb6DzgeYtsAdkPZ47znpoNsMgZw0+tVijiv3uGNR6dgNlty6r9rzIzHjtd/A=="
|
||||
},
|
||||
"node_modules/@radix-ui/primitive": {
|
||||
"version": "1.0.1",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/primitive/-/primitive-1.0.1.tgz",
|
||||
"integrity": "sha512-yQ8oGX2GVsEYMWGxcovu1uGWPCxV5BFfeeYxqPmuAzUyLT9qmaMXSAhXpb0WrspIeqYzdJpkh2vHModJPgRIaw==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10"
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-arrow": {
|
||||
"version": "1.0.3",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-arrow/-/react-arrow-1.0.3.tgz",
|
||||
"integrity": "sha512-wSP+pHsB/jQRaL6voubsQ/ZlrGBHHrOjmBnr19hxYgtS0WvAFwZhK2WP/YY5yF9uKECCEEDGxuLxq1NBK51wFA==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10",
|
||||
"@radix-ui/react-primitive": "1.0.3"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@types/react": "*",
|
||||
"@types/react-dom": "*",
|
||||
"react": "^16.8 || ^17.0 || ^18.0",
|
||||
"react-dom": "^16.8 || ^17.0 || ^18.0"
|
||||
},
|
||||
"peerDependenciesMeta": {
|
||||
"@types/react": {
|
||||
"optional": true
|
||||
},
|
||||
"@types/react-dom": {
|
||||
"optional": true
|
||||
}
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-compose-refs": {
|
||||
"version": "1.0.1",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-compose-refs/-/react-compose-refs-1.0.1.tgz",
|
||||
"integrity": "sha512-fDSBgd44FKHa1FRMU59qBMPFcl2PZE+2nmqunj+BWFyYYjnhIDWL2ItDs3rrbJDQOtzt5nIebLCQc4QRfz6LJw==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@types/react": "*",
|
||||
"react": "^16.8 || ^17.0 || ^18.0"
|
||||
},
|
||||
"peerDependenciesMeta": {
|
||||
"@types/react": {
|
||||
"optional": true
|
||||
}
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-context": {
|
||||
"version": "1.0.1",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-context/-/react-context-1.0.1.tgz",
|
||||
"integrity": "sha512-ebbrdFoYTcuZ0v4wG5tedGnp9tzcV8awzsxYph7gXUyvnNLuTIcCk1q17JEbnVhXAKG9oX3KtchwiMIAYp9NLg==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@types/react": "*",
|
||||
"react": "^16.8 || ^17.0 || ^18.0"
|
||||
},
|
||||
"peerDependenciesMeta": {
|
||||
"@types/react": {
|
||||
"optional": true
|
||||
}
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-dialog": {
|
||||
"version": "1.0.0",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-dialog/-/react-dialog-1.0.0.tgz",
|
||||
"integrity": "sha512-Yn9YU+QlHYLWwV1XfKiqnGVpWYWk6MeBVM6x/bcoyPvxgjQGoeT35482viLPctTMWoMw0PoHgqfSox7Ig+957Q==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10",
|
||||
"@radix-ui/primitive": "1.0.0",
|
||||
"@radix-ui/react-compose-refs": "1.0.0",
|
||||
"@radix-ui/react-context": "1.0.0",
|
||||
"@radix-ui/react-dismissable-layer": "1.0.0",
|
||||
"@radix-ui/react-focus-guards": "1.0.0",
|
||||
"@radix-ui/react-focus-scope": "1.0.0",
|
||||
"@radix-ui/react-id": "1.0.0",
|
||||
"@radix-ui/react-portal": "1.0.0",
|
||||
"@radix-ui/react-presence": "1.0.0",
|
||||
"@radix-ui/react-primitive": "1.0.0",
|
||||
"@radix-ui/react-slot": "1.0.0",
|
||||
"@radix-ui/react-use-controllable-state": "1.0.0",
|
||||
"aria-hidden": "^1.1.1",
|
||||
"react-remove-scroll": "2.5.4"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"react": "^16.8 || ^17.0 || ^18.0",
|
||||
"react-dom": "^16.8 || ^17.0 || ^18.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-dialog/node_modules/@radix-ui/primitive": {
|
||||
"version": "1.0.0",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/primitive/-/primitive-1.0.0.tgz",
|
||||
"integrity": "sha512-3e7rn8FDMin4CgeL7Z/49smCA3rFYY3Ha2rUQ7HRWFadS5iCRw08ZgVT1LaNTCNqgvrUiyczLflrVrF0SRQtNA==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10"
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-dialog/node_modules/@radix-ui/react-compose-refs": {
|
||||
"version": "1.0.0",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-compose-refs/-/react-compose-refs-1.0.0.tgz",
|
||||
"integrity": "sha512-0KaSv6sx787/hK3eF53iOkiSLwAGlFMx5lotrqD2pTjB18KbybKoEIgkNZTKC60YECDQTKGTRcDBILwZVqVKvA==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"react": "^16.8 || ^17.0 || ^18.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-dialog/node_modules/@radix-ui/react-context": {
|
||||
"version": "1.0.0",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-context/-/react-context-1.0.0.tgz",
|
||||
"integrity": "sha512-1pVM9RfOQ+n/N5PJK33kRSKsr1glNxomxONs5c49MliinBY6Yw2Q995qfBUUo0/Mbg05B/sGA0gkgPI7kmSHBg==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"react": "^16.8 || ^17.0 || ^18.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-dialog/node_modules/@radix-ui/react-dismissable-layer": {
|
||||
"version": "1.0.0",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-dismissable-layer/-/react-dismissable-layer-1.0.0.tgz",
|
||||
"integrity": "sha512-n7kDRfx+LB1zLueRDvZ1Pd0bxdJWDUZNQ/GWoxDn2prnuJKRdxsjulejX/ePkOsLi2tTm6P24mDqlMSgQpsT6g==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10",
|
||||
"@radix-ui/primitive": "1.0.0",
|
||||
"@radix-ui/react-compose-refs": "1.0.0",
|
||||
"@radix-ui/react-primitive": "1.0.0",
|
||||
"@radix-ui/react-use-callback-ref": "1.0.0",
|
||||
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"integrity": "sha512-AEYxH93jGFPn/a2iVAwW87VuUIkR1FVUKB77NwMF7nBTDkDrrT/Hpt/IrCJ0QXhW27jTBDcf5ZY7w6RiqTMw2Q=="
|
||||
},
|
||||
"node_modules/use-callback-ref": {
|
||||
"version": "1.3.0",
|
||||
"resolved": "https://registry.npmjs.org/use-callback-ref/-/use-callback-ref-1.3.0.tgz",
|
||||
"integrity": "sha512-3FT9PRuRdbB9HfXhEq35u4oZkvpJ5kuYbpqhCfmiZyReuRgpnhDlbr2ZEnnuS0RrJAPn6l23xjFg9kpDM+Ms7w==",
|
||||
"dependencies": {
|
||||
"tslib": "^2.0.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=10"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@types/react": "^16.8.0 || ^17.0.0 || ^18.0.0",
|
||||
"react": "^16.8.0 || ^17.0.0 || ^18.0.0"
|
||||
},
|
||||
"peerDependenciesMeta": {
|
||||
"@types/react": {
|
||||
"optional": true
|
||||
}
|
||||
}
|
||||
},
|
||||
"node_modules/use-sidecar": {
|
||||
"version": "1.1.2",
|
||||
"resolved": "https://registry.npmjs.org/use-sidecar/-/use-sidecar-1.1.2.tgz",
|
||||
"integrity": "sha512-epTbsLuzZ7lPClpz2TyryBfztm7m+28DlEv2ZCQ3MDr5ssiwyOwGH/e5F9CkfWjJ1t4clvI58yF822/GUkjjhw==",
|
||||
"dependencies": {
|
||||
"detect-node-es": "^1.1.0",
|
||||
"tslib": "^2.0.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=10"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@types/react": "^16.9.0 || ^17.0.0 || ^18.0.0",
|
||||
"react": "^16.8.0 || ^17.0.0 || ^18.0.0"
|
||||
},
|
||||
"peerDependenciesMeta": {
|
||||
"@types/react": {
|
||||
"optional": true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -1,6 +0,0 @@
|
|||
{
|
||||
"dependencies": {
|
||||
"@radix-ui/react-popover": "^1.0.7",
|
||||
"cmdk": "^0.2.0"
|
||||
}
|
||||
}
|
||||
1108
poetry.lock
generated
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow"
|
||||
version = "1.0.0a36"
|
||||
version = "1.0.0a38"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Langflow <contact@langflow.org>"]
|
||||
maintainers = [
|
||||
|
|
@ -29,20 +29,20 @@ python = ">=3.10,<3.13"
|
|||
langflow-base = { path = "./src/backend/base", develop = true }
|
||||
beautifulsoup4 = "^4.12.2"
|
||||
google-search-results = "^2.4.1"
|
||||
google-api-python-client = "^2.118.0"
|
||||
google-api-python-client = "^2.130.0"
|
||||
huggingface-hub = { version = "^0.20.0", extras = ["inference"] }
|
||||
llama-cpp-python = { version = "~0.2.0", optional = true }
|
||||
networkx = "^3.1"
|
||||
fake-useragent = "^1.4.0"
|
||||
fake-useragent = "^1.5.0"
|
||||
psycopg2-binary = "^2.9.6"
|
||||
pyarrow = "^14.0.0"
|
||||
wikipedia = "^1.4.0"
|
||||
qdrant-client = "^1.7.0"
|
||||
qdrant-client = "^1.9.0"
|
||||
weaviate-client = "*"
|
||||
sentence-transformers = { version = "^2.3.1", optional = true }
|
||||
ctransformers = { version = "^0.2.10", optional = true }
|
||||
cohere = "^5.1.7"
|
||||
faiss-cpu = "^1.7.4"
|
||||
cohere = "^5.5.3"
|
||||
faiss-cpu = "^1.8.0"
|
||||
types-cachetools = "^5.3.0.5"
|
||||
pinecone-client = "^3.0.3"
|
||||
pymongo = "^4.6.0"
|
||||
|
|
@ -56,7 +56,7 @@ redis = { version = "^5.0.1", optional = true }
|
|||
flower = { version = "^2.0.0", optional = true }
|
||||
metaphor-python = "^0.1.11"
|
||||
pywin32 = { version = "^306", markers = "sys_platform == 'win32'" }
|
||||
langfuse = "^2.9.0"
|
||||
langfuse = "^2.33.0"
|
||||
metal-sdk = "^2.5.0"
|
||||
markupsafe = "^2.1.3"
|
||||
# jq is not available for windows
|
||||
|
|
@ -69,14 +69,12 @@ langchain-google-genai = "^1.0.1"
|
|||
langchain-cohere = "^0.1.0rc1"
|
||||
elasticsearch = "^8.12.0"
|
||||
pytube = "^15.0.0"
|
||||
llama-index = "^0.10.13"
|
||||
# unstructured = { extras = ["md"], version = "^0.12.4" }
|
||||
dspy-ai = "^2.4.0"
|
||||
assemblyai = "^0.23.1"
|
||||
litellm = "^1.34.22"
|
||||
chromadb = "^0.4.24"
|
||||
assemblyai = "^0.26.0"
|
||||
litellm = "^1.38.0"
|
||||
chromadb = "^0.5.0"
|
||||
langchain-anthropic = "^0.1.6"
|
||||
langchain-astradb = "^0.1.0"
|
||||
langchain-astradb = "^0.3.0"
|
||||
langchain-openai = "^0.1.1"
|
||||
zep-python = { version = "^2.0.0rc5", allow-prereleases = true }
|
||||
langchain-google-vertexai = "^1.0.3"
|
||||
|
|
@ -84,26 +82,29 @@ langchain-groq = "^0.1.3"
|
|||
langchain-pinecone = "^0.1.0"
|
||||
langchain-mistralai = "^0.1.6"
|
||||
couchbase = "^4.2.1"
|
||||
youtube-transcript-api = "^0.6.2"
|
||||
markdown = "^3.6"
|
||||
langchain-chroma = "^0.1.1"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
types-redis = "^4.6.0.5"
|
||||
ipykernel = "^6.29.0"
|
||||
mypy = "^1.9.0"
|
||||
ruff = "^0.3.5"
|
||||
mypy = "^1.10.0"
|
||||
ruff = "^0.4.5"
|
||||
httpx = "*"
|
||||
pytest = "^8.1.0"
|
||||
types-requests = "^2.31.0"
|
||||
requests = "^2.31.0"
|
||||
pytest-cov = "^4.1.0"
|
||||
pytest = "^8.2.0"
|
||||
types-requests = "^2.32.0"
|
||||
requests = "^2.32.0"
|
||||
pytest-cov = "^5.0.0"
|
||||
pandas-stubs = "^2.1.4.231227"
|
||||
types-pillow = "^10.2.0.20240213"
|
||||
types-pyyaml = "^6.0.12.8"
|
||||
types-python-jose = "^3.3.4.8"
|
||||
types-passlib = "^1.7.7.13"
|
||||
locust = "^2.23.1"
|
||||
pytest-mock = "^3.12.0"
|
||||
pytest-xdist = "^3.5.0"
|
||||
pytest-mock = "^3.14.0"
|
||||
pytest-xdist = "^3.6.0"
|
||||
types-pywin32 = "^306.0.0.4"
|
||||
types-google-cloud-ndb = "^2.2.0.0"
|
||||
pytest-sugar = "^1.0.0"
|
||||
|
|
@ -112,6 +113,7 @@ pytest-instafail = "^0.5.0"
|
|||
pytest-asyncio = "^0.23.0"
|
||||
pytest-profiling = "^1.7.0"
|
||||
pre-commit = "^3.7.0"
|
||||
vulture = "^2.11"
|
||||
|
||||
[tool.poetry.extras]
|
||||
deploy = ["celery", "redis", "flower"]
|
||||
|
|
@ -132,7 +134,7 @@ ignore-regex = '.*(Stati Uniti|Tense=Pres).*'
|
|||
|
||||
[tool.pytest.ini_options]
|
||||
minversion = "6.0"
|
||||
addopts = "-ra"
|
||||
addopts = "-ra -n auto"
|
||||
testpaths = ["tests", "integration"]
|
||||
console_output_style = "progress"
|
||||
filterwarnings = ["ignore::DeprecationWarning"]
|
||||
|
|
|
|||
|
|
@ -3,9 +3,9 @@ services:
|
|||
- type: web
|
||||
name: langflow
|
||||
runtime: docker
|
||||
dockerfilePath: ./Dockerfile
|
||||
dockerfilePath: ./docker/render.Dockerfile
|
||||
repo: https://github.com/langflow-ai/langflow
|
||||
branch: main
|
||||
branch: dev
|
||||
healthCheckPath: /health
|
||||
autoDeploy: false
|
||||
envVars:
|
||||
|
|
|
|||
|
|
@ -20,8 +20,7 @@ When running as a [spot (preemptible) instance](https://cloud.google.com/compute
|
|||
|
||||
## Pricing (approximate)
|
||||
|
||||
> For a more accurate breakdown of costs, please use the [**GCP Pricing Calculator**](https://cloud.google.com/products/calculator)
|
||||
> <br>
|
||||
> For a more accurate breakdown of costs, please use the [**GCP Pricing Calculator**](https://cloud.google.com/products/calculator) > <br>
|
||||
|
||||
| Component | Regular Cost (Hourly) | Regular Cost (Monthly) | Spot/Preemptible Cost (Hourly) | Spot/Preemptible Cost (Monthly) | Notes |
|
||||
| ------------------ | --------------------- | ---------------------- | ------------------------------ | ------------------------------- | -------------------------------------------------------------------------- |
|
||||
|
|
@ -22,7 +22,8 @@ from sqlmodel import select
|
|||
from langflow.main import setup_app
|
||||
from langflow.services.database.models.folder.utils import create_default_folder_if_it_doesnt_exist
|
||||
from langflow.services.database.utils import session_getter
|
||||
from langflow.services.deps import get_db_service
|
||||
from langflow.services.deps import get_db_service, get_settings_service, session_scope
|
||||
from langflow.services.settings.constants import DEFAULT_SUPERUSER
|
||||
from langflow.services.utils import initialize_services
|
||||
from langflow.utils.logger import configure, logger
|
||||
from langflow.utils.util import update_settings
|
||||
|
|
@ -83,7 +84,6 @@ def run(
|
|||
help="Path to the directory containing custom components.",
|
||||
envvar="LANGFLOW_COMPONENTS_PATH",
|
||||
),
|
||||
config: str = typer.Option(Path(__file__).parent / "config.yaml", help="Path to the configuration file."),
|
||||
# .env file param
|
||||
env_file: Path = typer.Option(None, help="Path to the .env file containing environment variables."),
|
||||
log_level: str = typer.Option("critical", help="Logging level.", envvar="LANGFLOW_LOG_LEVEL"),
|
||||
|
|
@ -132,7 +132,6 @@ def run(
|
|||
load_dotenv(env_file, override=True)
|
||||
|
||||
update_settings(
|
||||
config,
|
||||
dev=dev,
|
||||
remove_api_keys=remove_api_keys,
|
||||
cache=cache,
|
||||
|
|
@ -510,6 +509,66 @@ def migration(
|
|||
display_results(results)
|
||||
|
||||
|
||||
@app.command()
|
||||
def api_key(
|
||||
log_level: str = typer.Option("error", help="Logging level.", envvar="LANGFLOW_LOG_LEVEL"),
|
||||
):
|
||||
"""
|
||||
Creates an API key for the default superuser if AUTO_LOGIN is enabled.
|
||||
|
||||
Args:
|
||||
log_level (str, optional): Logging level. Defaults to "error".
|
||||
|
||||
Returns:
|
||||
None
|
||||
"""
|
||||
configure(log_level=log_level)
|
||||
initialize_services()
|
||||
settings_service = get_settings_service()
|
||||
auth_settings = settings_service.auth_settings
|
||||
if not auth_settings.AUTO_LOGIN:
|
||||
typer.echo("Auto login is disabled. API keys cannot be created through the CLI.")
|
||||
return
|
||||
with session_scope() as session:
|
||||
from langflow.services.database.models.user.model import User
|
||||
|
||||
superuser = session.exec(select(User).where(User.username == DEFAULT_SUPERUSER)).first()
|
||||
if not superuser:
|
||||
typer.echo("Default superuser not found. This command requires a superuser and AUTO_LOGIN to be enabled.")
|
||||
return
|
||||
from langflow.services.database.models.api_key import ApiKey, ApiKeyCreate
|
||||
from langflow.services.database.models.api_key.crud import create_api_key, delete_api_key
|
||||
|
||||
api_key = session.exec(select(ApiKey).where(ApiKey.user_id == superuser.id)).first()
|
||||
if api_key:
|
||||
delete_api_key(session, api_key.id)
|
||||
|
||||
api_key_create = ApiKeyCreate(name="CLI")
|
||||
unmasked_api_key = create_api_key(session, api_key_create, user_id=superuser.id)
|
||||
session.commit()
|
||||
# Create a banner to display the API key and tell the user it won't be shown again
|
||||
api_key_banner(unmasked_api_key)
|
||||
|
||||
|
||||
def api_key_banner(unmasked_api_key):
|
||||
is_mac = platform.system() == "Darwin"
|
||||
import pyperclip # type: ignore
|
||||
|
||||
pyperclip.copy(unmasked_api_key.api_key)
|
||||
panel = Panel(
|
||||
f"[bold]API Key Created Successfully:[/bold]\n\n"
|
||||
f"[bold blue]{unmasked_api_key.api_key}[/bold blue]\n\n"
|
||||
"This is the only time the API key will be displayed. \n"
|
||||
"Make sure to store it in a secure location. \n\n"
|
||||
f"The API key has been copied to your clipboard. [bold]{['Ctrl','Cmd'][is_mac]} + V[/bold] to paste it.",
|
||||
box=box.ROUNDED,
|
||||
border_style="blue",
|
||||
expand=False,
|
||||
)
|
||||
console = Console()
|
||||
console.print(panel)
|
||||
|
||||
|
||||
def main():
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("ignore")
|
||||
|
|
|
|||
|
|
@ -1,4 +1,3 @@
|
|||
import os
|
||||
import warnings
|
||||
from pathlib import Path
|
||||
from typing import TYPE_CHECKING, Optional
|
||||
|
|
|
|||
|
|
@ -1,13 +1,12 @@
|
|||
from typing import TYPE_CHECKING, Any, Dict, List, Optional
|
||||
from uuid import UUID
|
||||
|
||||
from langchain.schema import AgentAction, AgentFinish
|
||||
from langchain_core.callbacks.base import AsyncCallbackHandler
|
||||
from loguru import logger
|
||||
|
||||
from langflow.api.v1.schemas import ChatResponse, PromptResponse
|
||||
from langflow.services.deps import get_chat_service, get_socket_service
|
||||
from langflow.utils.util import remove_ansi_escape_codes
|
||||
from langchain_core.agents import AgentAction, AgentFinish
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.services.socket.service import SocketIOService
|
||||
|
|
|
|||
|
|
@ -18,10 +18,9 @@ from langflow.api.v1.schemas import (
|
|||
UpdateCustomComponentRequest,
|
||||
UploadFileResponse,
|
||||
)
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.custom.utils import build_custom_component_template
|
||||
from langflow.graph.graph.base import Graph
|
||||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.interface.custom.utils import build_custom_component_template
|
||||
from langflow.processing.process import process_tweaks, run_graph_internal
|
||||
from langflow.schema.graph import Tweaks
|
||||
from langflow.services.auth.utils import api_key_security, get_current_active_user
|
||||
|
|
@ -44,7 +43,7 @@ def get_all(
|
|||
|
||||
logger.debug("Building langchain types dict")
|
||||
try:
|
||||
all_types_dict = get_all_types_dict(settings_service.settings.COMPONENTS_PATH)
|
||||
all_types_dict = get_all_types_dict(settings_service.settings.components_path)
|
||||
return all_types_dict
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
|
|
|
|||
|
|
@ -38,7 +38,10 @@ def create_flow(
|
|||
db_flow.updated_at = datetime.now(timezone.utc)
|
||||
|
||||
if db_flow.folder_id is None:
|
||||
default_folder = session.exec(select(Folder).where(Folder.name == DEFAULT_FOLDER_NAME)).first()
|
||||
# Make sure flows always have a folder
|
||||
default_folder = session.exec(
|
||||
select(Folder).where(Folder.name == DEFAULT_FOLDER_NAME, Folder.user_id == current_user.id)
|
||||
).first()
|
||||
if default_folder:
|
||||
db_flow.folder_id = default_folder.id
|
||||
|
||||
|
|
@ -127,7 +130,7 @@ def update_flow(
|
|||
if not db_flow:
|
||||
raise HTTPException(status_code=404, detail="Flow not found")
|
||||
flow_data = flow.model_dump(exclude_unset=True)
|
||||
if settings_service.settings.REMOVE_API_KEYS:
|
||||
if settings_service.settings.remove_api_keys:
|
||||
flow_data = remove_api_keys(flow_data)
|
||||
for key, value in flow_data.items():
|
||||
if value is not None:
|
||||
|
|
|
|||
|
|
@ -3,12 +3,11 @@ from uuid import UUID
|
|||
|
||||
import orjson
|
||||
from fastapi import APIRouter, Depends, File, HTTPException, Response, UploadFile, status
|
||||
from sqlalchemy import update
|
||||
from sqlalchemy import or_, update
|
||||
from sqlmodel import Session, select
|
||||
|
||||
from langflow.api.v1.flows import create_flows
|
||||
from langflow.api.v1.schemas import FlowListCreate, FlowListReadWithFolderName
|
||||
from langflow.initial_setup.setup import STARTER_FOLDER_NAME
|
||||
from langflow.services.auth.utils import get_current_active_user
|
||||
from langflow.services.database.models.flow.model import Flow, FlowCreate, FlowRead
|
||||
from langflow.services.database.models.folder.constants import DEFAULT_FOLDER_NAME
|
||||
|
|
@ -35,6 +34,18 @@ def create_folder(
|
|||
try:
|
||||
new_folder = Folder.model_validate(folder, from_attributes=True)
|
||||
new_folder.user_id = current_user.id
|
||||
|
||||
folder_results = session.exec(
|
||||
select(Folder).where(
|
||||
Folder.name.like(f"{new_folder.name}%"), # type: ignore
|
||||
Folder.user_id == current_user.id,
|
||||
)
|
||||
)
|
||||
existing_folder_names = [folder.name for folder in folder_results]
|
||||
|
||||
if existing_folder_names:
|
||||
new_folder.name = f"{new_folder.name} ({len(existing_folder_names) + 1})"
|
||||
|
||||
session.add(new_folder)
|
||||
session.commit()
|
||||
session.refresh(new_folder)
|
||||
|
|
@ -63,16 +74,11 @@ def read_folders(
|
|||
current_user: User = Depends(get_current_active_user),
|
||||
):
|
||||
try:
|
||||
folders = session.exec(select(Folder).where(Folder.user_id == current_user.id)).all()
|
||||
return folders
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.get("/starter-projects", response_model=FolderReadWithFlows, status_code=200)
|
||||
def read_starter_folders(*, session: Session = Depends(get_session)):
|
||||
try:
|
||||
folders = session.exec(select(Folder).where(Folder.name == STARTER_FOLDER_NAME)).first()
|
||||
folders = session.exec(
|
||||
select(Folder).where(
|
||||
or_(Folder.user_id == current_user.id, Folder.user_id == None) # type: ignore # noqa: E711
|
||||
)
|
||||
).all()
|
||||
return folders
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
|
|
|||
|
|
@ -54,7 +54,7 @@ def check_if_store_is_enabled(
|
|||
settings_service=Depends(get_settings_service),
|
||||
):
|
||||
return {
|
||||
"enabled": settings_service.settings.STORE,
|
||||
"enabled": settings_service.settings.store,
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,9 +1,9 @@
|
|||
from typing import Optional, Union
|
||||
|
||||
from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
from langflow.helpers.record import records_to_text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.memory import store_message
|
||||
from langflow.schema import Record
|
||||
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
from typing import Optional
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
from langflow.helpers.record import records_to_text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.schema.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
from typing import Optional
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,10 +1,10 @@
|
|||
from fastapi import HTTPException
|
||||
from langchain.prompts import PromptTemplate
|
||||
from loguru import logger
|
||||
|
||||
from langflow.api.v1.base import INVALID_NAMES, check_input_variables
|
||||
from langflow.interface.utils import extract_input_variables_from_prompt
|
||||
from langflow.template.field.prompt import DefaultPromptField
|
||||
from langchain_core.prompts import PromptTemplate
|
||||
|
||||
|
||||
def validate_prompt(prompt_template: str, silent_errors: bool = False) -> list[str]:
|
||||
|
|
|
|||
|
|
@ -1,52 +0,0 @@
|
|||
from typing import Callable, List, Optional, Union
|
||||
|
||||
from langchain.agents import AgentExecutor, AgentType, initialize_agent, types
|
||||
|
||||
from langflow.field_typing import BaseChatMemory, BaseLanguageModel, Tool
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class AgentInitializerComponent(CustomComponent):
|
||||
display_name: str = "Agent Initializer"
|
||||
description: str = "Initialize a Langchain Agent."
|
||||
documentation: str = "https://python.langchain.com/docs/modules/agents/agent_types/"
|
||||
|
||||
def build_config(self):
|
||||
agents = list(types.AGENT_TO_CLASS.keys())
|
||||
# field_type and required are optional
|
||||
return {
|
||||
"agent": {"options": agents, "value": agents[0], "display_name": "Agent Type"},
|
||||
"max_iterations": {"display_name": "Max Iterations", "value": 10},
|
||||
"memory": {"display_name": "Memory"},
|
||||
"tools": {"display_name": "Tools"},
|
||||
"llm": {"display_name": "Language Model"},
|
||||
"code": {"advanced": True},
|
||||
}
|
||||
|
||||
def build(
|
||||
self,
|
||||
agent: str,
|
||||
llm: BaseLanguageModel,
|
||||
tools: List[Tool],
|
||||
max_iterations: int,
|
||||
memory: Optional[BaseChatMemory] = None,
|
||||
) -> Union[AgentExecutor, Callable]:
|
||||
agent = AgentType(agent)
|
||||
if memory:
|
||||
return initialize_agent(
|
||||
tools=tools,
|
||||
llm=llm,
|
||||
agent=agent,
|
||||
memory=memory,
|
||||
return_intermediate_steps=True,
|
||||
handle_parsing_errors=True,
|
||||
max_iterations=max_iterations,
|
||||
)
|
||||
return initialize_agent(
|
||||
tools=tools,
|
||||
llm=llm,
|
||||
agent=agent,
|
||||
return_intermediate_steps=True,
|
||||
handle_parsing_errors=True,
|
||||
max_iterations=max_iterations,
|
||||
)
|
||||
|
|
@ -1,10 +1,9 @@
|
|||
from langchain.agents import AgentExecutor, create_json_agent
|
||||
from langchain.agents import AgentExecutor
|
||||
from langchain_community.agent_toolkits import create_json_agent
|
||||
from langchain_community.agent_toolkits.json.toolkit import JsonToolkit
|
||||
|
||||
from langflow.field_typing import (
|
||||
BaseLanguageModel,
|
||||
)
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel
|
||||
|
||||
|
||||
class JsonAgentComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,102 +0,0 @@
|
|||
from typing import List, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.conversational_retrieval.openai_functions import _get_default_system_message
|
||||
from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
|
||||
from langchain.memory.token_buffer import ConversationTokenBufferMemory
|
||||
from langchain.prompts import SystemMessagePromptTemplate
|
||||
from langchain.prompts.chat import MessagesPlaceholder
|
||||
from langchain.schema.memory import BaseMemory
|
||||
from langchain.tools import Tool
|
||||
from langchain_openai import ChatOpenAI
|
||||
|
||||
from langflow.field_typing.range_spec import RangeSpec
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from pydantic.v1 import SecretStr
|
||||
|
||||
|
||||
class ConversationalAgent(CustomComponent):
|
||||
display_name: str = "OpenAI Conversational Agent"
|
||||
description: str = "Conversational Agent that can use OpenAI's function calling API"
|
||||
icon = "OpenAI"
|
||||
|
||||
def build_config(self):
|
||||
openai_function_models = [
|
||||
"gpt-4-turbo-preview",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-vision-preview",
|
||||
"gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo-1106",
|
||||
]
|
||||
return {
|
||||
"tools": {"display_name": "Tools"},
|
||||
"memory": {"display_name": "Memory"},
|
||||
"system_message": {"display_name": "System Message"},
|
||||
"max_token_limit": {"display_name": "Max Token Limit"},
|
||||
"model_name": {
|
||||
"display_name": "Model Name",
|
||||
"options": openai_function_models,
|
||||
"value": openai_function_models[0],
|
||||
},
|
||||
"code": {"show": False},
|
||||
"temperature": {
|
||||
"display_name": "Temperature",
|
||||
"value": 0.2,
|
||||
"rangeSpec": RangeSpec(min=0, max=2, step=0.1),
|
||||
},
|
||||
}
|
||||
|
||||
def build(
|
||||
self,
|
||||
model_name: str,
|
||||
openai_api_key: str,
|
||||
tools: List[Tool],
|
||||
openai_api_base: Optional[str] = None,
|
||||
memory: Optional[BaseMemory] = None,
|
||||
system_message: Optional[SystemMessagePromptTemplate] = None,
|
||||
max_token_limit: int = 2000,
|
||||
temperature: float = 0.9,
|
||||
) -> AgentExecutor:
|
||||
if openai_api_key:
|
||||
api_key = SecretStr(openai_api_key)
|
||||
else:
|
||||
api_key = None
|
||||
|
||||
llm = ChatOpenAI(
|
||||
model=model_name,
|
||||
api_key=api_key,
|
||||
base_url=openai_api_base,
|
||||
max_tokens=max_token_limit,
|
||||
temperature=temperature,
|
||||
)
|
||||
if not memory:
|
||||
memory_key = "chat_history"
|
||||
memory = ConversationTokenBufferMemory(
|
||||
memory_key=memory_key,
|
||||
return_messages=True,
|
||||
output_key="output",
|
||||
llm=llm,
|
||||
max_token_limit=max_token_limit,
|
||||
)
|
||||
else:
|
||||
memory_key = memory.memory_key # type: ignore
|
||||
|
||||
_system_message = system_message or _get_default_system_message()
|
||||
prompt = OpenAIFunctionsAgent.create_prompt(
|
||||
system_message=_system_message, # type: ignore
|
||||
extra_prompt_messages=[MessagesPlaceholder(variable_name=memory_key)],
|
||||
)
|
||||
agent = OpenAIFunctionsAgent(
|
||||
llm=llm,
|
||||
tools=tools,
|
||||
prompt=prompt, # type: ignore
|
||||
)
|
||||
return AgentExecutor(
|
||||
agent=agent,
|
||||
tools=tools, # type: ignore
|
||||
memory=memory,
|
||||
verbose=True,
|
||||
return_intermediate_steps=True,
|
||||
handle_parsing_errors=True,
|
||||
)
|
||||
|
|
@ -1,12 +1,12 @@
|
|||
from typing import Callable, Union
|
||||
|
||||
from langchain.agents import AgentExecutor
|
||||
from langchain_community.utilities import SQLDatabase
|
||||
from langchain_community.agent_toolkits import SQLDatabaseToolkit
|
||||
from langchain_community.agent_toolkits.sql.base import create_sql_agent
|
||||
from langchain_community.utilities import SQLDatabase
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class SQLAgentComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -3,8 +3,8 @@ from typing import Callable, Union
|
|||
from langchain.agents import AgentExecutor, create_vectorstore_agent
|
||||
from langchain.agents.agent_toolkits.vectorstore.toolkit import VectorStoreToolkit
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class VectorStoreAgentComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@ from langchain.agents import create_vectorstore_router_agent
|
|||
from langchain.agents.agent_toolkits.vectorstore.toolkit import VectorStoreRouterToolkit
|
||||
from langchain_core.language_models.base import BaseLanguageModel
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
|
||||
|
||||
class VectorStoreRouterAgentComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,17 +1,13 @@
|
|||
from .AgentInitializer import AgentInitializerComponent
|
||||
from .CSVAgent import CSVAgentComponent
|
||||
from .JsonAgent import JsonAgentComponent
|
||||
from .OpenAIConversationalAgent import ConversationalAgent
|
||||
from .SQLAgent import SQLAgentComponent
|
||||
from .VectorStoreAgent import VectorStoreAgentComponent
|
||||
from .VectorStoreRouterAgent import VectorStoreRouterAgentComponent
|
||||
from .XMLAgent import XMLAgentComponent
|
||||
|
||||
__all__ = [
|
||||
"AgentInitializerComponent",
|
||||
"CSVAgentComponent",
|
||||
"JsonAgentComponent",
|
||||
"ConversationalAgent",
|
||||
"SQLAgentComponent",
|
||||
"VectorStoreAgentComponent",
|
||||
"VectorStoreRouterAgentComponent",
|
||||
|
|
|
|||
|
|
@ -2,8 +2,8 @@ from typing import Optional
|
|||
|
||||
from langchain.chains import ConversationChain
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel, BaseMemory, Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class ConversationChainComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,11 +1,11 @@
|
|||
from typing import Optional
|
||||
|
||||
from langchain.chains.llm import LLMChain
|
||||
|
||||
from langflow.field_typing import BaseLanguageModel, BaseMemory, Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langchain_core.prompts import PromptTemplate
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel, BaseMemory, Text
|
||||
|
||||
|
||||
class LLMChainComponent(CustomComponent):
|
||||
display_name = "LLMChain"
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
from langchain.chains import LLMCheckerChain
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel, Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class LLMCheckerChainComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -2,8 +2,8 @@ from typing import Optional
|
|||
|
||||
from langchain.chains import LLMChain, LLMMathChain
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel, BaseMemory, Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class LLMMathChainComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -3,8 +3,8 @@ from typing import Optional
|
|||
from langchain.chains.retrieval_qa.base import RetrievalQA
|
||||
from langchain_core.documents import Document
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel, BaseMemory, BaseRetriever, Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.schema.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -3,8 +3,8 @@ from typing import Optional
|
|||
from langchain.chains import RetrievalQAWithSourcesChain
|
||||
from langchain_core.documents import Document
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel, BaseMemory, BaseRetriever, Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class RetrievalQAWithSourcesChainComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -5,8 +5,8 @@ from langchain_community.utilities.sql_database import SQLDatabase
|
|||
from langchain_core.prompts import PromptTemplate
|
||||
from langchain_core.runnables import Runnable
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import BaseLanguageModel, Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class SQLGeneratorComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -3,7 +3,8 @@ import json
|
|||
from typing import List, Optional
|
||||
|
||||
import httpx
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from langflow.base.data.utils import parallel_load_records, parse_text_file_to_record, retrieve_file_paths
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@ from pathlib import Path
|
|||
from typing import Any, Dict
|
||||
|
||||
from langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_record
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@ from typing import Any, Dict
|
|||
|
||||
from langchain_community.document_loaders.web_base import WebBaseLoader
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,9 +1,9 @@
|
|||
from typing import Optional
|
||||
|
||||
from langchain.embeddings.base import Embeddings
|
||||
from langchain_community.embeddings import BedrockEmbeddings
|
||||
from langchain_core.embeddings import Embeddings
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
|
||||
|
||||
class AmazonBedrockEmeddingsComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,7 +1,8 @@
|
|||
from langchain.embeddings.base import Embeddings
|
||||
from langchain_community.embeddings import AzureOpenAIEmbeddings
|
||||
from langchain_core.embeddings import Embeddings
|
||||
from langchain_openai import AzureOpenAIEmbeddings
|
||||
from pydantic.v1 import SecretStr
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
|
||||
|
||||
class AzureOpenAIEmbeddingsComponent(CustomComponent):
|
||||
|
|
@ -52,12 +53,16 @@ class AzureOpenAIEmbeddingsComponent(CustomComponent):
|
|||
api_version: str,
|
||||
api_key: str,
|
||||
) -> Embeddings:
|
||||
if api_key:
|
||||
azure_api_key = SecretStr(api_key)
|
||||
else:
|
||||
azure_api_key = None
|
||||
try:
|
||||
embeddings = AzureOpenAIEmbeddings(
|
||||
azure_endpoint=azure_endpoint,
|
||||
azure_deployment=azure_deployment,
|
||||
api_version=api_version,
|
||||
api_key=api_key,
|
||||
api_key=azure_api_key,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@ from typing import Dict, Optional
|
|||
|
||||
from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
|
||||
|
||||
class HuggingFaceEmbeddingsComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@ from typing import Dict, Optional
|
|||
from langchain_community.embeddings.huggingface import HuggingFaceInferenceAPIEmbeddings
|
||||
from pydantic.v1.types import SecretStr
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
|
||||
|
||||
class HuggingFaceInferenceAPIEmbeddingsComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
from langchain_mistralai.embeddings import MistralAIEmbeddings
|
||||
from pydantic.v1 import SecretStr
|
||||
|
||||
from langchain_mistralai.embeddings import MistralAIEmbeddings
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Embeddings
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,9 +1,9 @@
|
|||
from typing import Optional
|
||||
|
||||
from langchain.embeddings.base import Embeddings
|
||||
from langchain_community.embeddings import OllamaEmbeddings
|
||||
from langchain_core.embeddings import Embeddings
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
|
||||
|
||||
class OllamaEmbeddingsComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,10 +1,10 @@
|
|||
from typing import Any, Dict, List, Optional
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
from langchain_openai.embeddings.base import OpenAIEmbeddings
|
||||
from pydantic.v1 import SecretStr
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Embeddings, NestedDict
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class OpenAIEmbeddingsComponent(CustomComponent):
|
||||
|
|
@ -94,7 +94,6 @@ class OpenAIEmbeddingsComponent(CustomComponent):
|
|||
allowed_special: List[str] = [],
|
||||
disallowed_special: List[str] = ["all"],
|
||||
chunk_size: int = 1000,
|
||||
client: Optional[Any] = None,
|
||||
deployment: str = "text-embedding-ada-002",
|
||||
embedding_ctx_length: int = 8191,
|
||||
max_retries: int = 6,
|
||||
|
|
@ -126,7 +125,6 @@ class OpenAIEmbeddingsComponent(CustomComponent):
|
|||
allowed_special=set(allowed_special),
|
||||
disallowed_special="all",
|
||||
chunk_size=chunk_size,
|
||||
client=client,
|
||||
deployment=deployment,
|
||||
embedding_ctx_length=embedding_ctx_length,
|
||||
max_retries=max_retries,
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@ from typing import List, Optional
|
|||
|
||||
from langchain_google_vertexai import VertexAIEmbeddings
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
|
||||
|
||||
class VertexAIEmbeddingsComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.memory import delete_messages, get_messages
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
from typing import List
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
from typing import Optional
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +1,8 @@
|
|||
from typing import Union
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
class PassComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
from typing import Callable
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.custom.utils import get_function
|
||||
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):
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
from langchain_core.runnables import Runnable
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class RunnableExecComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
from langchain_community.tools.sql_database.tool import QuerySQLDataBaseTool
|
||||
from langchain_community.utilities import SQLDatabase
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class SQLExecutorComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
from typing import Optional
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.schema import Record
|
||||
from langflow.utils.util import unescape_string
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
from typing import List, Optional
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.memory import get_messages, store_message
|
||||
from langflow.schema import Record
|
||||
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
from typing import Optional, Union
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.schema import Record
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
from langflow.schema import Record
|
||||
|
||||
|
||||
class TextOperatorComponent(CustomComponent):
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Text
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
# from langflow.field_typing import Data
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.schema import Record
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class Component(CustomComponent):
|
||||
|
|
|
|||