Merge branch 'dev' into docs-cli-commands
This commit is contained in:
Mendon Kissling
commit
c8240d73bd
229 changed files with 16487 additions and 14983 deletions
2
.github/actions/poetry_caching/action.yml
vendored
2
.github/actions/poetry_caching/action.yml
vendored
|
|
@ -74,7 +74,7 @@ runs:
|
|||
if: steps.cache-bin-poetry.outputs.cache-hit != 'true'
|
||||
shell: bash
|
||||
env:
|
||||
POETRY_VERSION: ${{ inputs.poetry-version }}
|
||||
POETRY_VERSION: ${{ inputs.poetry-version || env.POETRY_VERSION }}
|
||||
PYTHON_VERSION: ${{ inputs.python-version }}
|
||||
# Install poetry using the python version installed by setup-python step.
|
||||
run: |
|
||||
|
|
|
|||
2
.github/workflows/create-release.yml
vendored
2
.github/workflows/create-release.yml
vendored
|
|
@ -25,7 +25,7 @@ jobs:
|
|||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
run: pipx install poetry==${{ env.POETRY_VERSION }}
|
||||
- name: Set up Python 3.12
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
|
|
|
|||
28
.github/workflows/docker-build.yml
vendored
28
.github/workflows/docker-build.yml
vendored
|
|
@ -19,6 +19,8 @@ on:
|
|||
options:
|
||||
- base
|
||||
- main
|
||||
env:
|
||||
POETRY_VERSION: "1.8.2"
|
||||
|
||||
jobs:
|
||||
docker_build:
|
||||
|
|
@ -54,6 +56,28 @@ jobs:
|
|||
tags: ${{ env.TAGS }}
|
||||
- name: Wait for Docker Hub to propagate
|
||||
run: sleep 120
|
||||
- name: Build and push (backend)
|
||||
if: ${{ inputs.release_type == 'main' }}
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./docker/build_and_push_backend.Dockerfile
|
||||
build-args: |
|
||||
LANGFLOW_IMAGE=langflowai/langflow:${{ inputs.version }}
|
||||
tags: |
|
||||
langflowai/langflow-backend:${{ inputs.version }}
|
||||
langflowai/langflow-backend:1.0-alpha
|
||||
- name: Build and push (frontend)
|
||||
if: ${{ inputs.release_type == 'main' }}
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./docker/frontend/build_and_push_frontend.Dockerfile
|
||||
tags: |
|
||||
langflowai/langflow-frontend:${{ inputs.version }}
|
||||
langflowai/langflow-frontend:1.0-alpha
|
||||
|
||||
restart-space:
|
||||
runs-on: ubuntu-latest
|
||||
|
|
@ -76,6 +100,4 @@ jobs:
|
|||
|
||||
- name: Restart HuggingFace Spaces Build
|
||||
run: |
|
||||
poetry run python ./scripts/factory_restart_space.py
|
||||
env:
|
||||
HUGGINGFACE_API_TOKEN: ${{ secrets.HUGGINGFACE_API_TOKEN }}
|
||||
poetry run python ./scripts/factory_restart_space.py --space "Langflow/Langflow-Preview" --token ${{ secrets.HUGGINGFACE_API_TOKEN }}
|
||||
|
|
|
|||
61
.github/workflows/docker_test.yml
vendored
Normal file
61
.github/workflows/docker_test.yml
vendored
Normal file
|
|
@ -0,0 +1,61 @@
|
|||
name: Test Docker images
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
paths:
|
||||
- "docker/**"
|
||||
- "poetry.lock"
|
||||
- "pyproject.toml"
|
||||
- "src/backend/**"
|
||||
pull_request:
|
||||
branches: [dev]
|
||||
paths:
|
||||
- "docker/**"
|
||||
- "poetry.lock"
|
||||
- "pyproject.toml"
|
||||
- "src/**"
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.8.2"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Build image
|
||||
run: |
|
||||
docker build -t langflowai/langflow:latest-dev \
|
||||
-f docker/build_and_push.Dockerfile \
|
||||
.
|
||||
- name: Test image
|
||||
run: |
|
||||
expected_version=$(cat pyproject.toml | grep version | head -n 1 | cut -d '"' -f 2)
|
||||
version=$(docker run --rm --entrypoint bash langflowai/langflow:latest-dev -c 'python -c "from langflow.version import __version__ as langflow_version; print(langflow_version)"')
|
||||
if [ "$expected_version" != "$version" ]; then
|
||||
echo "Expected version: $expected_version"
|
||||
echo "Actual version: $version"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
- name: Build backend image
|
||||
run: |
|
||||
docker build -t langflowai/langflow-backend:latest-dev \
|
||||
--build-arg LANGFLOW_IMAGE=langflowai/langflow:latest-dev \
|
||||
-f docker/build_and_push_backend.Dockerfile \
|
||||
.
|
||||
- name: Test backend image
|
||||
run: |
|
||||
expected_version=$(cat pyproject.toml | grep version | head -n 1 | cut -d '"' -f 2)
|
||||
version=$(docker run --rm --entrypoint bash langflowai/langflow-backend:latest-dev -c 'python -c "from langflow.version import __version__ as langflow_version; print(langflow_version)"')
|
||||
if [ "$expected_version" != "$version" ]; then
|
||||
echo "Expected version: $expected_version"
|
||||
echo "Actual version: $version"
|
||||
exit 1
|
||||
fi
|
||||
- name: Build frontend image
|
||||
run: |
|
||||
docker build -t langflowai/langflow-frontend:latest-dev \
|
||||
-f docker/frontend/build_and_push_frontend.Dockerfile \
|
||||
.
|
||||
2
.github/workflows/pre-release-base.yml
vendored
2
.github/workflows/pre-release-base.yml
vendored
|
|
@ -22,7 +22,7 @@ jobs:
|
|||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
run: pipx install poetry==${{ env.POETRY_VERSION }}
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
|
|
|
|||
24
.github/workflows/pre-release-langflow.yml
vendored
24
.github/workflows/pre-release-langflow.yml
vendored
|
|
@ -26,7 +26,7 @@ jobs:
|
|||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
run: pipx install poetry==${{ env.POETRY_VERSION }}
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
|
|
@ -82,6 +82,28 @@ jobs:
|
|||
tags: |
|
||||
langflowai/langflow:${{ needs.release.outputs.version }}
|
||||
langflowai/langflow:1.0-alpha
|
||||
- name: Build and push (frontend)
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./docker/frontend/build_and_push_frontend.Dockerfile
|
||||
tags: |
|
||||
langflowai/langflow-frontend:${{ needs.release.outputs.version }}
|
||||
langflowai/langflow-frontend:1.0-alpha
|
||||
- name: Wait for Docker Hub to propagate
|
||||
run: sleep 120
|
||||
- name: Build and push (backend)
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./docker/build_and_push_backend.Dockerfile
|
||||
build-args: |
|
||||
LANGFLOW_IMAGE=langflowai/langflow:${{ needs.release.outputs.version }}
|
||||
tags: |
|
||||
langflowai/langflow-backend:${{ needs.release.outputs.version }}
|
||||
langflowai/langflow-backend:1.0-alpha
|
||||
|
||||
create_release:
|
||||
name: Create Release
|
||||
|
|
|
|||
2
.github/workflows/pre-release.yml
vendored
2
.github/workflows/pre-release.yml
vendored
|
|
@ -29,7 +29,7 @@ jobs:
|
|||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
run: pipx install poetry==${{ env.POETRY_VERSION }}
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
|
|
|
|||
24
.github/workflows/release.yml
vendored
24
.github/workflows/release.yml
vendored
|
|
@ -19,7 +19,7 @@ jobs:
|
|||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
run: pipx install poetry==${{ env.POETRY_VERSION }}
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
|
|
@ -54,6 +54,28 @@ jobs:
|
|||
tags: |
|
||||
langflowai/langflow:${{ steps.check-version.outputs.version }}
|
||||
langflowai/langflow:latest
|
||||
- name: Wait for Docker Hub to propagate
|
||||
run: sleep 120
|
||||
- name: Build and push (backend)
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./docker/build_and_push_backend.Dockerfile
|
||||
build-args: |
|
||||
LANGFLOW_IMAGE=langflowai/langflow:${{ steps.check-version.outputs.version }}
|
||||
tags: |
|
||||
langflowai/langflow-backend:${{ steps.check-version.outputs.version }}
|
||||
langflowai/langflow-backend:latest
|
||||
- name: Build and push (frontend)
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: ./docker/frontend/build_and_push_frontend.Dockerfile
|
||||
tags: |
|
||||
langflowai/langflow-frontend:${{ steps.check-version.outputs.version }}
|
||||
langflowai/langflow-frontend:latest
|
||||
- name: Create Release
|
||||
uses: ncipollo/release-action@v1
|
||||
with:
|
||||
|
|
|
|||
171
README.PT.md
Normal file
171
README.PT.md
Normal file
|
|
@ -0,0 +1,171 @@
|
|||
<!-- markdownlint-disable MD030 -->
|
||||
|
||||
# [](https://www.langflow.org)
|
||||
|
||||
<p align="center"><strong>
|
||||
Um framework visual para criar apps de agentes autônomos e RAG
|
||||
</strong></p>
|
||||
<p align="center" style="font-size: 12px;">
|
||||
Open-source, construído em Python, totalmente personalizável, agnóstico em relação a modelos e databases
|
||||
</p>
|
||||
|
||||
<p align="center" style="font-size: 12px;">
|
||||
<a href="https://docs.langflow.org" style="text-decoration: underline;">Docs</a> -
|
||||
<a href="https://discord.com/invite/EqksyE2EX9" style="text-decoration: underline;">Junte-se ao nosso Discord</a> -
|
||||
<a href="https://twitter.com/langflow_ai" style="text-decoration: underline;">Siga-nos no X</a> -
|
||||
<a href="https://huggingface.co/spaces/Langflow/Langflow-Preview" style="text-decoration: underline;">Demonstração</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://github.com/langflow-ai/langflow">
|
||||
<img src="https://img.shields.io/github/stars/langflow-ai/langflow">
|
||||
</a>
|
||||
<a href="https://discord.com/invite/EqksyE2EX9">
|
||||
<img src="https://img.shields.io/discord/1116803230643527710?label=Discord">
|
||||
</a>
|
||||
</p>
|
||||
|
||||
<div align="center">
|
||||
<a href="./README.md"><img alt="README em Inglês" src="https://img.shields.io/badge/English-d9d9d9"></a>
|
||||
<a href="./README.zh_CN.md"><img alt="README em Chinês Simplificado" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
|
||||
</div>
|
||||
|
||||
<p align="center">
|
||||
<img src="./docs/static/img/langflow_basic_howto.gif" alt="Seu GIF" style="border: 3px solid #211C43;">
|
||||
</p>
|
||||
|
||||
# 📝 Conteúdo
|
||||
|
||||
- [📝 Conteúdo](#-conteúdo)
|
||||
- [📦 Introdução](#-introdução)
|
||||
- [🎨 Criar Fluxos](#-criar-fluxos)
|
||||
- [Deploy](#deploy)
|
||||
- [Deploy usando Google Cloud Platform](#deploy-usando-google-cloud-platform)
|
||||
- [Deploy on Railway](#deploy-on-railway)
|
||||
- [Deploy on Render](#deploy-on-render)
|
||||
- [🖥️ Interface de Linha de Comando (CLI)](#️-interface-de-linha-de-comando-cli)
|
||||
- [Uso](#uso)
|
||||
- [Variáveis de Ambiente](#variáveis-de-ambiente)
|
||||
- [👋 Contribuir](#-contribuir)
|
||||
- [🌟 Contribuidores](#-contribuidores)
|
||||
- [📄 Licença](#-licença)
|
||||
|
||||
# 📦 Introdução
|
||||
|
||||
Você pode instalar o Langflow com pip:
|
||||
|
||||
```shell
|
||||
# Certifique-se de ter >=Python 3.10 instalado no seu sistema.
|
||||
# Instale a versão pré-lançamento (recomendada para as atualizações mais recentes)
|
||||
python -m pip install langflow --pre --force-reinstall
|
||||
|
||||
# ou versão estável
|
||||
python -m pip install langflow -U
|
||||
```
|
||||
|
||||
Então, execute o Langflow com:
|
||||
|
||||
```shell
|
||||
python -m langflow run
|
||||
```
|
||||
|
||||
Você também pode visualizar o Langflow no [HuggingFace Spaces](https://huggingface.co/spaces/Langflow/Langflow-Preview). [Clone o Space usando este link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) para criar seu próprio workspace do Langflow em minutos.
|
||||
|
||||
# 🎨 Criar Fluxos
|
||||
|
||||
Criar fluxos com Langflow é fácil. Basta arrastar componentes da barra lateral para o canvas e conectá-los para começar a construir sua aplicação.
|
||||
|
||||
Explore editando os parâmetros do prompt, agrupando componentes e construindo seus próprios componentes personalizados (Custom Components).
|
||||
|
||||
Quando terminar, você pode exportar seu fluxo como um arquivo JSON.
|
||||
|
||||
Carregue o fluxo com:
|
||||
|
||||
```python
|
||||
from langflow.load import run_flow_from_json
|
||||
|
||||
results = run_flow_from_json("path/to/flow.json", input_value="Hello, World!")
|
||||
```
|
||||
|
||||
# Deploy
|
||||
|
||||
## Deploy usando Google Cloud Platform
|
||||
|
||||
Siga nosso passo a passo para fazer deploy do Langflow no Google Cloud Platform (GCP) usando o Google Cloud Shell. O guia está disponível no documento [**Langflow on Google Cloud Platform**](https://github.com/langflow-ai/langflow/blob/dev/docs/docs/deployment/gcp-deployment.md).
|
||||
|
||||
Alternativamente, clique no botão **"Open in Cloud Shell"** abaixo para iniciar o Google Cloud Shell, clonar o repositório do Langflow e começar um **tutorial interativo** que o guiará pelo processo de configuração dos recursos necessários e deploy do Langflow no seu projeto GCP.
|
||||
|
||||
[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md)
|
||||
|
||||
## Deploy on Railway
|
||||
|
||||
Use este template para implantar o Langflow 1.0 Preview no Railway:
|
||||
|
||||
[](https://railway.app/template/UsJ1uB?referralCode=MnPSdg)
|
||||
|
||||
Ou este para implantar o Langflow 0.6.x:
|
||||
|
||||
[](https://railway.app/template/JMXEWp?referralCode=MnPSdg)
|
||||
|
||||
## Deploy on Render
|
||||
|
||||
<a href="https://render.com/deploy?repo=https://github.com/langflow-ai/langflow/tree/dev">
|
||||
<img src="https://render.com/images/deploy-to-render-button.svg" alt="Deploy to Render" />
|
||||
</a>
|
||||
|
||||
# 🖥️ Interface de Linha de Comando (CLI)
|
||||
|
||||
O Langflow fornece uma interface de linha de comando (CLI) para fácil gerenciamento e configuração.
|
||||
|
||||
## Uso
|
||||
|
||||
Você pode executar o Langflow usando o seguinte comando:
|
||||
|
||||
```shell
|
||||
langflow run [OPTIONS]
|
||||
```
|
||||
|
||||
Cada opção é detalhada abaixo:
|
||||
|
||||
- `--help`: Exibe todas as opções disponíveis.
|
||||
- `--host`: Define o host para vincular o servidor. Pode ser configurado usando a variável de ambiente `LANGFLOW_HOST`. O padrão é `127.0.0.1`.
|
||||
- `--workers`: Define o número de processos. Pode ser configurado usando a variável de ambiente `LANGFLOW_WORKERS`. O padrão é `1`.
|
||||
- `--timeout`: Define o tempo limite do worker em segundos. O padrão é `60`.
|
||||
- `--port`: Define a porta para escutar. Pode ser configurado usando a variável de ambiente `LANGFLOW_PORT`. O padrão é `7860`.
|
||||
- `--env-file`: Especifica o caminho para o arquivo .env contendo variáveis de ambiente. O padrão é `.env`.
|
||||
- `--log-level`: Define o nível de log. Pode ser configurado usando a variável de ambiente `LANGFLOW_LOG_LEVEL`. O padrão é `critical`.
|
||||
- `--components-path`: Especifica o caminho para o diretório contendo componentes personalizados. Pode ser configurado usando a variável de ambiente `LANGFLOW_COMPONENTS_PATH`. O padrão é `langflow/components`.
|
||||
- `--log-file`: Especifica o caminho para o arquivo de log. Pode ser configurado usando a variável de ambiente `LANGFLOW_LOG_FILE`. O padrão é `logs/langflow.log`.
|
||||
- `--cache`: Seleciona o tipo de cache a ser usado. As opções são `InMemoryCache` e `SQLiteCache`. Pode ser configurado usando a variável de ambiente `LANGFLOW_LANGCHAIN_CACHE`. O padrão é `SQLiteCache`.
|
||||
- `--dev/--no-dev`: Alterna o modo de desenvolvimento. O padrão é `no-dev`.
|
||||
- `--path`: Especifica o caminho para o diretório frontend contendo os arquivos de build. Esta opção é apenas para fins de desenvolvimento. Pode ser configurado usando a variável de ambiente `LANGFLOW_FRONTEND_PATH`.
|
||||
- `--open-browser/--no-open-browser`: Alterna a opção de abrir o navegador após iniciar o servidor. Pode ser configurado usando a variável de ambiente `LANGFLOW_OPEN_BROWSER`. O padrão é `open-browser`.
|
||||
- `--remove-api-keys/--no-remove-api-keys`: Alterna a opção de remover as chaves de API dos projetos salvos no banco de dados. Pode ser configurado usando a variável de ambiente `LANGFLOW_REMOVE_API_KEYS`. O padrão é `no-remove-api-keys`.
|
||||
- `--install-completion [bash|zsh|fish|powershell|pwsh]`: Instala a conclusão para o shell especificado.
|
||||
- `--show-completion [bash|zsh|fish|powershell|pwsh]`: Exibe a conclusão para o shell especificado, permitindo que você copie ou personalize a instalação.
|
||||
- `--backend-only`: Este parâmetro, com valor padrão `False`, permite executar apenas o servidor backend sem o frontend. Também pode ser configurado usando a variável de ambiente `LANGFLOW_BACKEND_ONLY`.
|
||||
- `--store`: Este parâmetro, com valor padrão `True`, ativa os recursos da loja, use `--no-store` para desativá-los. Pode ser configurado usando a variável de ambiente `LANGFLOW_STORE`.
|
||||
|
||||
Esses parâmetros são importantes para usuários que precisam personalizar o comportamento do Langflow, especialmente em cenários de desenvolvimento ou deploy especializado.
|
||||
|
||||
### Variáveis de Ambiente
|
||||
|
||||
Você pode configurar muitas das opções de CLI usando variáveis de ambiente. Estas podem ser exportadas no seu sistema operacional ou adicionadas a um arquivo `.env` e carregadas usando a opção `--env-file`.
|
||||
|
||||
Um arquivo de exemplo `.env` chamado `.env.example` está incluído no projeto. Copie este arquivo para um novo arquivo chamado `.env` e substitua os valores de exemplo pelas suas configurações reais. Se você estiver definindo valores tanto no seu sistema operacional quanto no arquivo `.env`, as configurações do `.env` terão precedência.
|
||||
|
||||
# 👋 Contribuir
|
||||
|
||||
Aceitamos contribuições de desenvolvedores de todos os níveis para nosso projeto open-source no GitHub. Se você deseja contribuir, por favor, confira nossas [diretrizes de contribuição](./CONTRIBUTING.md) e ajude a tornar o Langflow mais acessível.
|
||||
|
||||
---
|
||||
|
||||
[](https://star-history.com/#langflow-ai/langflow&Date)
|
||||
|
||||
# 🌟 Contribuidores
|
||||
|
||||
[](https://github.com/langflow-ai/langflow/graphs/contributors)
|
||||
|
||||
# 📄 Licença
|
||||
|
||||
O Langflow é lançado sob a licença MIT. Veja o arquivo [LICENSE](LICENSE) para detalhes.
|
||||
|
|
@ -25,13 +25,18 @@
|
|||
</a>
|
||||
</p>
|
||||
|
||||
<div align="center">
|
||||
<a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
|
||||
<a href="./README.PT.md"><img alt="README in Portuguese" src="https://img.shields.io/badge/Portuguese-d9d9d9"></a>
|
||||
<a href="./README.zh_CN.md"><img alt="README in Simplified Chinese" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
|
||||
</div>
|
||||
|
||||
<p align="center">
|
||||
<img src="./docs/static/img/langflow_basic_howto.gif" alt="Your GIF" style="border: 3px solid #211C43;">
|
||||
</p>
|
||||
|
||||
# 📝 Content
|
||||
|
||||
- [](#)
|
||||
- [📝 Content](#-content)
|
||||
- [📦 Get Started](#-get-started)
|
||||
- [🎨 Create Flows](#-create-flows)
|
||||
|
|
|
|||
172
README.zh_CN.md
Normal file
172
README.zh_CN.md
Normal file
|
|
@ -0,0 +1,172 @@
|
|||
<!-- markdownlint-disable MD030 -->
|
||||
|
||||
# [](https://www.langflow.org)
|
||||
|
||||
<p align="center"><strong>
|
||||
一种用于构建多智能体和RAG应用的可视化框架
|
||||
</strong></p>
|
||||
<p align="center" style="font-size: 12px;">
|
||||
开源、Python驱动、完全可定制、大模型且不依赖于特定的向量存储
|
||||
</p>
|
||||
|
||||
<p align="center" style="font-size: 12px;">
|
||||
<a href="https://docs.langflow.org" style="text-decoration: underline;">文档</a> -
|
||||
<a href="https://discord.com/invite/EqksyE2EX9" style="text-decoration: underline;">加入我们的Discord社区</a> -
|
||||
<a href="https://twitter.com/langflow_ai" style="text-decoration: underline;">在X上关注我们</a> -
|
||||
<a href="https://huggingface.co/spaces/Langflow/Langflow-Preview" style="text-decoration: underline;">在线体验</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://github.com/langflow-ai/langflow">
|
||||
<img src="https://img.shields.io/github/stars/langflow-ai/langflow">
|
||||
</a>
|
||||
<a href="https://discord.com/invite/EqksyE2EX9">
|
||||
<img src="https://img.shields.io/discord/1116803230643527710?label=Discord">
|
||||
</a>
|
||||
</p>
|
||||
|
||||
<div align="center">
|
||||
<a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/英文-d9d9d9"></a>
|
||||
<a href="./README.zh_CN.md"><img alt="README in Simplified Chinese" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
|
||||
</div>
|
||||
|
||||
<p align="center">
|
||||
<img src="./docs/static/img/langflow_basic_howto.gif" alt="Your GIF" style="border: 3px solid #211C43;">
|
||||
</p>
|
||||
|
||||
# 📝 目录
|
||||
|
||||
- [📝 目录](#-目录)
|
||||
- [📦 快速开始](#-快速开始)
|
||||
- [🎨 创建工作流](#-创建工作流)
|
||||
- [部署](#部署)
|
||||
- [在Google Cloud Platform上部署Langflow](#在google-cloud-platform上部署langflow)
|
||||
- [在Railway上部署](#在railway上部署)
|
||||
- [在Render上部署](#在render上部署)
|
||||
- [🖥️ 命令行界面 (CLI)](#️-命令行界面-cli)
|
||||
- [用法](#用法)
|
||||
- [环境变量](#环境变量)
|
||||
- [👋 贡献](#-贡献)
|
||||
- [🌟 贡献者](#-贡献者)
|
||||
- [📄 许可证](#-许可证)
|
||||
|
||||
# 📦 快速开始
|
||||
|
||||
使用 pip 安装 Langflow：
|
||||
|
||||
```shell
|
||||
# 确保您的系统已经安装上>=Python 3.10
|
||||
# 安装Langflow预发布版本
|
||||
python -m pip install langflow --pre --force-reinstall
|
||||
|
||||
# 安装Langflow稳定版本
|
||||
python -m pip install langflow -U
|
||||
```
|
||||
|
||||
然后运行Langflow：
|
||||
|
||||
```shell
|
||||
python -m langflow run
|
||||
```
|
||||
|
||||
您可以在[HuggingFace Spaces](https://huggingface.co/spaces/Langflow/Langflow-Preview)中在线体验 Langflow，也可以使用该链接[克隆空间](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)，在几分钟内创建您自己的 Langflow 运行工作空间。
|
||||
|
||||
# 🎨 创建工作流
|
||||
|
||||
使用 Langflow 来创建工作流非常简单。只需从侧边栏拖动组件到画布上，然后连接组件即可开始构建应用程序。
|
||||
|
||||
您可以通过编辑提示参数、将组件分组到单个高级组件中以及构建您自己的自定义组件来展开探索。
|
||||
|
||||
完成后，可以将工作流导出为 JSON 文件。
|
||||
|
||||
然后使用以下脚本加载工作流：
|
||||
|
||||
```python
|
||||
from langflow.load import run_flow_from_json
|
||||
|
||||
results = run_flow_from_json("path/to/flow.json", input_value="Hello, World!")
|
||||
```
|
||||
|
||||
# 部署
|
||||
|
||||
## 在Google Cloud Platform上部署Langflow
|
||||
|
||||
请按照我们的分步指南使用 Google Cloud Shell 在 Google Cloud Platform (GCP) 上部署 Langflow。该指南在 [**Langflow in Google Cloud Platform**](GCP_DEPLOYMENT.md) 文档中提供。
|
||||
|
||||
或者，点击下面的 "Open in Cloud Shell" 按钮，启动 Google Cloud Shell，克隆 Langflow 仓库，并开始一个互动教程，该教程将指导您设置必要的资源并在 GCP 项目中部署 Langflow。
|
||||
|
||||
[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md)
|
||||
|
||||
## 在Railway上部署
|
||||
|
||||
使用此模板在 Railway 上部署 Langflow 1.0 预览版：
|
||||
|
||||
[](https://railway.app/template/UsJ1uB?referralCode=MnPSdg)
|
||||
|
||||
或者使用此模板部署 Langflow 0.6.x：
|
||||
|
||||
[](https://railway.app/template/JMXEWp?referralCode=MnPSdg)
|
||||
|
||||
## 在Render上部署
|
||||
|
||||
<a href="https://render.com/deploy?repo=https://github.com/langflow-ai/langflow/tree/dev">
|
||||
<img src="https://render.com/images/deploy-to-render-button.svg" alt="Deploy to Render" />
|
||||
</a>
|
||||
|
||||
# 🖥️ 命令行界面 (CLI)
|
||||
|
||||
Langflow提供了一个命令行界面以便于平台的管理和配置。
|
||||
|
||||
## 用法
|
||||
|
||||
您可以使用以下命令运行Langflow：
|
||||
|
||||
```shell
|
||||
langflow run [OPTIONS]
|
||||
```
|
||||
|
||||
命令行参数的详细说明：
|
||||
|
||||
- `--help`: 显示所有可用参数。
|
||||
- `--host`: 定义绑定服务器的主机host参数，可以使用 LANGFLOW_HOST 环境变量设置，默认值为 127.0.0.1。
|
||||
- `--workers`: 设置工作进程的数量，可以使用 LANGFLOW_WORKERS 环境变量设置，默认值为 1。
|
||||
- `--timeout`: 设置工作进程的超时时间（秒），默认值为 60。
|
||||
- `--port`: 设置服务监听的端口，可以使用 LANGFLOW_PORT 环境变量设置，默认值为 7860。
|
||||
- `--config`: 定义配置文件的路径，默认值为 config.yaml。
|
||||
- `--env-file`: 指定包含环境变量的 .env 文件路径，默认值为 .env。
|
||||
- `--log-level`: 定义日志记录级别，可以使用 LANGFLOW_LOG_LEVEL 环境变量设置，默认值为 critical。
|
||||
- `--components-path`: 指定包含自定义组件的目录路径，可以使用 LANGFLOW_COMPONENTS_PATH 环境变量设置，默认值为 langflow/components。
|
||||
- `--log-file`: 指定日志文件的路径，可以使用 LANGFLOW_LOG_FILE 环境变量设置，默认值为 logs/langflow.log。
|
||||
- `--cache`: 选择要使用的缓存类型，可选项为 InMemoryCache 和 SQLiteCache，可以使用 LANGFLOW_LANGCHAIN_CACHE 环境变量设置，默认值为 SQLiteCache。
|
||||
- `--dev/--no-dev`: 切换开发/非开发模式，默认值为 no-dev即非开发模式。
|
||||
- `--path`: 指定包含前端构建文件的目录路径，此参数仅用于开发目的，可以使用 LANGFLOW_FRONTEND_PATH 环境变量设置。
|
||||
- `--open-browser/--no-open-browser`: 切换启动服务器后是否打开浏览器，可以使用 LANGFLOW_OPEN_BROWSER 环境变量设置，默认值为 open-browser即启动后打开浏览器。
|
||||
- `--remove-api-keys/--no-remove-api-keys`: 切换是否从数据库中保存的项目中移除 API 密钥，可以使用 LANGFLOW_REMOVE_API_KEYS 环境变量设置，默认值为 no-remove-api-keys。
|
||||
- `--install-completion [bash|zsh|fish|powershell|pwsh]`: 为指定的 shell 安装自动补全。
|
||||
- `--show-completion [bash|zsh|fish|powershell|pwsh]`: 显示指定 shell 的自动补全，使您可以复制或自定义安装。
|
||||
- `--backend-only`: 此参数默认为 False，允许仅运行后端服务器而不运行前端，也可以使用 LANGFLOW_BACKEND_ONLY 环境变量设置。
|
||||
- `--store`: 此参数默认为 True，启用存储功能，使用 --no-store 可禁用它，可以使用 LANGFLOW_STORE 环境变量配置。
|
||||
|
||||
这些参数对于需要定制 Langflow 行为的用户尤其重要，特别是在开发或者特殊部署场景中。
|
||||
|
||||
### 环境变量
|
||||
|
||||
您可以使用环境变量配置许多 CLI 参数选项。这些变量可以在操作系统中导出，或添加到 .env 文件中，并使用 --env-file 参数加载。
|
||||
|
||||
项目中包含一个名为 .env.example 的示例 .env 文件。将此文件复制为新文件 .env，并用实际设置值替换示例值。如果同时在操作系统和 .env 文件中设置值，则 .env 设置优先。
|
||||
|
||||
# 👋 贡献
|
||||
|
||||
我们欢迎各级开发者为我们的 GitHub 开源项目做出贡献，并帮助 Langflow 更加易用，如果您想参与贡献，请查看我们的贡献指南 [contributing guidelines](./CONTRIBUTING.md) 。
|
||||
|
||||
---
|
||||
|
||||
[](https://star-history.com/#langflow-ai/langflow&Date)
|
||||
|
||||
# 🌟 贡献者
|
||||
|
||||
[](https://github.com/langflow-ai/langflow/graphs/contributors)
|
||||
|
||||
# 📄 许可证
|
||||
|
||||
Langflow 以 MIT 许可证发布。有关详细信息，请参阅 [LICENSE](LICENSE) 文件。
|
||||
|
|
@ -1,21 +1,13 @@
|
|||
|
||||
|
||||
# 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
|
||||
# BUILDER-BASE
|
||||
# Used to build deps + create our virtual environment
|
||||
################################
|
||||
FROM python:3.12-slim as python-base
|
||||
FROM python:3.12-slim as builder-base
|
||||
|
||||
# python
|
||||
ENV PYTHONUNBUFFERED=1 \
|
||||
# prevents python creating .pyc files
|
||||
PYTHONDONTWRITEBYTECODE=1 \
|
||||
ENV PYTHONDONTWRITEBYTECODE=1 \
|
||||
\
|
||||
# pip
|
||||
PIP_DISABLE_PIP_VERSION_CHECK=on \
|
||||
|
|
@ -37,56 +29,49 @@ ENV PYTHONUNBUFFERED=1 \
|
|||
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 \
|
||||
# npm
|
||||
npm \
|
||||
build-essential npm \
|
||||
# gcc
|
||||
gcc \
|
||||
&& apt-get clean \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
|
||||
|
||||
# Now we need to copy the entire project into the image
|
||||
WORKDIR /app
|
||||
COPY pyproject.toml poetry.lock ./
|
||||
COPY src ./src
|
||||
COPY scripts ./scripts
|
||||
COPY Makefile ./
|
||||
COPY README.md ./
|
||||
RUN --mount=type=cache,target=/root/.cache \
|
||||
curl -sSL https://install.python-poetry.org | python3 -
|
||||
RUN useradd -m -u 1000 user && \
|
||||
mkdir -p /app/langflow && \
|
||||
chown -R user:user /app && \
|
||||
chmod -R u+w /app/langflow
|
||||
|
||||
# Update PATH with home/user/.local/bin
|
||||
ENV PATH="/home/user/.local/bin:${PATH}"
|
||||
RUN python -m pip install requests && cd ./scripts && python update_dependencies.py
|
||||
RUN $POETRY_HOME/bin/poetry lock
|
||||
RUN $POETRY_HOME/bin/poetry build
|
||||
WORKDIR /app
|
||||
COPY pyproject.toml poetry.lock README.md ./
|
||||
COPY src/ ./src
|
||||
COPY scripts/ ./scripts
|
||||
|
||||
RUN python -m pip install requests --user && cd ./scripts && python update_dependencies.py
|
||||
RUN $POETRY_HOME/bin/poetry lock --no-update \
|
||||
&& $POETRY_HOME/bin/poetry install --no-interaction --no-ansi -E deploy \
|
||||
&& $POETRY_HOME/bin/poetry build -f wheel \
|
||||
&& $POETRY_HOME/bin/poetry run pip install dist/*.whl
|
||||
|
||||
################################
|
||||
# RUNTIME
|
||||
# Setup user, utilities and copy the virtual environment only
|
||||
################################
|
||||
FROM python:3.12-slim as runtime
|
||||
|
||||
LABEL org.opencontainers.image.title=langflow
|
||||
LABEL org.opencontainers.image.authors=['Langflow']
|
||||
LABEL org.opencontainers.image.licenses=MIT
|
||||
LABEL org.opencontainers.image.url=https://github.com/langflow-ai/langflow
|
||||
LABEL org.opencontainers.image.source=https://github.com/langflow-ai/langflow
|
||||
|
||||
RUN useradd user -u 1000 -g 0 --no-create-home --home-dir /app/data
|
||||
COPY --from=builder-base --chown=1000 /app/.venv /app/.venv
|
||||
ENV PATH="/app/.venv/bin:${PATH}"
|
||||
|
||||
# Copy virtual environment and built .tar.gz from builder base
|
||||
USER user
|
||||
# Install the package from the .tar.gz
|
||||
RUN python -m pip install /app/dist/*.tar.gz --user
|
||||
WORKDIR /app
|
||||
|
||||
ENTRYPOINT ["python", "-m", "langflow", "run"]
|
||||
CMD ["--host", "0.0.0.0", "--port", "7860"]
|
||||
CMD ["--host", "0.0.0.0", "--port", "7860"]
|
||||
8
docker/build_and_push_backend.Dockerfile
Normal file
8
docker/build_and_push_backend.Dockerfile
Normal file
|
|
@ -0,0 +1,8 @@
|
|||
# syntax=docker/dockerfile:1
|
||||
# Keep this syntax directive! It's used to enable Docker BuildKit
|
||||
|
||||
ARG LANGFLOW_IMAGE
|
||||
FROM $LANGFLOW_IMAGE
|
||||
|
||||
RUN rm -rf /app/.venv/langflow/frontend
|
||||
CMD ["--host", "0.0.0.0", "--port", "7860", "--backend-only"]
|
||||
27
docker/frontend/build_and_push_frontend.Dockerfile
Normal file
27
docker/frontend/build_and_push_frontend.Dockerfile
Normal file
|
|
@ -0,0 +1,27 @@
|
|||
# syntax=docker/dockerfile:1
|
||||
# Keep this syntax directive! It's used to enable Docker BuildKit
|
||||
|
||||
################################
|
||||
# BUILDER-BASE
|
||||
################################
|
||||
FROM node:lts-bookworm-slim as builder-base
|
||||
COPY src/frontend /frontend
|
||||
|
||||
RUN cd /frontend && npm install && npm run build
|
||||
|
||||
################################
|
||||
# RUNTIME
|
||||
################################
|
||||
FROM nginxinc/nginx-unprivileged:stable-bookworm-perl as runtime
|
||||
|
||||
LABEL org.opencontainers.image.title=langflow-frontend
|
||||
LABEL org.opencontainers.image.authors=['Langflow']
|
||||
LABEL org.opencontainers.image.licenses=MIT
|
||||
LABEL org.opencontainers.image.url=https://github.com/langflow-ai/langflow
|
||||
LABEL org.opencontainers.image.source=https://github.com/langflow-ai/langflow
|
||||
|
||||
COPY --from=builder-base --chown=nginx /frontend/build /usr/share/nginx/html
|
||||
COPY --chown=nginx ./docker/frontend/nginx.conf /etc/nginx/conf.d/default.conf
|
||||
COPY --chown=nginx ./docker/frontend/start-nginx.sh /start-nginx.sh
|
||||
RUN chmod +x /start-nginx.sh
|
||||
ENTRYPOINT ["/start-nginx.sh"]
|
||||
22
docker/frontend/nginx.conf
Normal file
22
docker/frontend/nginx.conf
Normal file
|
|
@ -0,0 +1,22 @@
|
|||
server {
|
||||
gzip on;
|
||||
gzip_comp_level 2;
|
||||
gzip_min_length 1000;
|
||||
gzip_types text/xml text/css;
|
||||
gzip_http_version 1.1;
|
||||
gzip_vary on;
|
||||
gzip_disable "MSIE [4-6] \.";
|
||||
|
||||
listen 80;
|
||||
|
||||
location / {
|
||||
root /usr/share/nginx/html;
|
||||
index index.html index.htm;
|
||||
try_files $uri $uri/ /index.html =404;
|
||||
}
|
||||
location /api {
|
||||
proxy_pass __BACKEND_URL__;
|
||||
}
|
||||
|
||||
include /etc/nginx/extra-conf.d/*.conf;
|
||||
}
|
||||
16
docker/frontend/start-nginx.sh
Normal file
16
docker/frontend/start-nginx.sh
Normal file
|
|
@ -0,0 +1,16 @@
|
|||
#!/bin/sh
|
||||
set -e
|
||||
trap 'kill -TERM $PID' TERM INT
|
||||
if [ -z "$BACKEND_URL" ]; then
|
||||
BACKEND_URL="$1"
|
||||
fi
|
||||
if [ -z "$BACKEND_URL" ]; then
|
||||
echo "BACKEND_URL must be set as an environment variable or as first parameter. (e.g. http://localhost:7860)"
|
||||
exit 1
|
||||
fi
|
||||
sed -i "s|__BACKEND_URL__|$BACKEND_URL|g" /etc/nginx/conf.d/default.conf
|
||||
cat /etc/nginx/conf.d/default.conf
|
||||
|
||||
|
||||
# Start nginx
|
||||
exec nginx -g 'daemon off;'
|
||||
|
|
@ -1,31 +1,39 @@
|
|||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import Admonition from "@theme/Admonition";
|
||||
import ReactPlayer from "react-player";
|
||||
import Admonition from "@theme/Admonition";
|
||||
|
||||
# Global Environment Variables
|
||||
# Global Variables
|
||||
|
||||
Langflow 1.0 alpha includes the option to add **Global Environment Variables** for your application.
|
||||
Global Variables are a useful feature of Langflow, allowing you to define reusable variables accessed from any Text field in your project.
|
||||
|
||||
## Add a global variable to a project
|
||||
## TL;DR
|
||||
|
||||
In this example, you'll add the `openai_api_key` credential as a global environment variable to the **Basic Prompting** starter project.
|
||||
- Global Variables are reusable variables accessible from any Text field in your project.
|
||||
- To create one, click the 🌐 button in a Text field and then **+ Add New Variable**.
|
||||
- Define the **Name**, **Type**, and **Value** of the variable.
|
||||
- Click **Save Variable** to create it.
|
||||
- All Credential Global Variables are encrypted and accessible only by you.
|
||||
- Set _`LANGFLOW_STORE_ENVIRONMENT_VARIABLES`_ to _`true`_ in your `.env` file to add all variables in _`LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT`_ to your user's Global Variables.
|
||||
|
||||
For more information on the starter flow, see [Basic prompting](../starter-projects/basic-prompting.mdx).
|
||||
## Creating and Adding a Global Variable
|
||||
|
||||
1. From the Langflow dashboard, click **New Project**.
|
||||
2. Select **Basic Prompting**.
|
||||
To create and add a global variable, click the 🌐 button in a Text field, and then click **+ Add New Variable**.
|
||||
|
||||
The **Basic Prompting** flow is created.
|
||||
Text fields are where you write text without opening a Text area, and are identified with the 🌐 icon.
|
||||
|
||||
3. To create an environment variable for the **OpenAI** component:
|
||||
1. In the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
2. In the **Variable Name** field, enter `openai_api_key`.
|
||||
3. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
4. For the variable **Type**, select **Credential**.
|
||||
5. In the **Apply to Fields** field, select **OpenAI API Key** to apply this variable to all fields named **OpenAI API Key**.
|
||||
6. Click **Save Variable**.
|
||||
For example, to create an environment variable for the **OpenAI** component:
|
||||
|
||||
1. In the **OpenAI API Key** text field, click the 🌐 button, then **Add New Variable**.
|
||||
2. Enter `openai_api_key` in the **Variable Name** field.
|
||||
3. Paste your OpenAI API Key (`sk-...`) in the **Value** field.
|
||||
4. Select **Credential** for the **Type**.
|
||||
5. Choose **OpenAI API Key** in the **Apply to Fields** field to apply this variable to all fields named **OpenAI API Key**.
|
||||
6. Click **Save Variable**.
|
||||
|
||||
You now have a `openai_api_key` global environment variable for your Langflow project.
|
||||
Subsequently, clicking the 🌐 button in a Text field will display the new variable in the dropdown.
|
||||
|
||||
<Admonition type="tip">
|
||||
You can also create global variables in **Settings** > **Variables and
|
||||
|
|
@ -41,10 +49,55 @@ You now have a `openai_api_key` global environment variable for your Langflow pr
|
|||
style={{ width: "40%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
4. To view and manage your project's global environment variables, visit **Settings** > **Variables and Secrets**.
|
||||
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).
|
||||
|
||||
{/* All variables are encrypted */}
|
||||
|
||||
<Admonition type="warning">
|
||||
All Credential Global Variables are encrypted and accessible only by you.
|
||||
</Admonition>
|
||||
|
||||
## Configuring Environment Variables in your .env file
|
||||
|
||||
Setting `LANGFLOW_STORE_ENVIRONMENT_VARIABLES` to `true` in your `.env` file (default) adds all variables in `LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT` to your user's Global Variables.
|
||||
|
||||
These variables are accessible like any other Global Variable.
|
||||
|
||||
<Admonition type="tip">
|
||||
To prevent this behavior, set `LANGFLOW_STORE_ENVIRONMENT_VARIABLES` to
|
||||
`false` in your `.env` file.
|
||||
</Admonition>
|
||||
|
||||
You can specify variables to get from the environment by listing them in `LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT`.
|
||||
|
||||
Specify variables as a comma-separated list (e.g., _`"VARIABLE1, VARIABLE2"`_) or a JSON-encoded string (e.g., _`'["VARIABLE1", "VARIABLE2"]'`_).
|
||||
|
||||
The default list of variables includes:
|
||||
|
||||
- ANTHROPIC_API_KEY
|
||||
- ASTRA_DB_API_ENDPOINT
|
||||
- ASTRA_DB_APPLICATION_TOKEN
|
||||
- AZURE_OPENAI_API_KEY
|
||||
- AZURE_OPENAI_API_DEPLOYMENT_NAME
|
||||
- AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME
|
||||
- AZURE_OPENAI_API_INSTANCE_NAME
|
||||
- AZURE_OPENAI_API_VERSION
|
||||
- COHERE_API_KEY
|
||||
- GOOGLE_API_KEY
|
||||
- GROQ_API_KEY
|
||||
- HUGGINGFACEHUB_API_TOKEN
|
||||
- OPENAI_API_KEY
|
||||
- PINECONE_API_KEY
|
||||
- SEARCHAPI_API_KEY
|
||||
- SERPAPI_API_KEY
|
||||
- UPSTASH_VECTOR_REST_URL
|
||||
- UPSTASH_VECTOR_REST_TOKEN
|
||||
- VECTARA_CUSTOMER_ID
|
||||
- VECTARA_CORPUS_ID
|
||||
- VECTARA_API_KEY
|
||||
|
||||
## Video
|
||||
|
||||
<div
|
||||
|
|
|
|||
|
|
@ -3,7 +3,8 @@ import Admonition from "@theme/Admonition";
|
|||
# Custom Components
|
||||
|
||||
<Admonition type="info" label="Tip">
|
||||
Read the [Custom Component Guidelines](../administration/custom-component) for detailed information on custom components.
|
||||
Read the [Custom Component Guidelines](../administration/custom-component) for
|
||||
detailed information on custom components.
|
||||
</Admonition>
|
||||
|
||||
Custom components let you extend Langflow by creating reusable and configurable components from a Python script.
|
||||
|
|
@ -31,57 +32,60 @@ This class is the foundation for creating custom components. It allows users to
|
|||
|
||||
The following types are supported in the build method:
|
||||
|
||||
| Supported Types |
|
||||
| --------------------------------------------------------- |
|
||||
| _`str`_, _`int`_, _`float`_, _`bool`_, _`list`_, _`dict`_ |
|
||||
| _`langflow.field_typing.NestedDict`_ |
|
||||
| _`langflow.field_typing.Prompt`_ |
|
||||
| _`langchain.chains.base.Chain`_ |
|
||||
| _`langchain.PromptTemplate`_ |
|
||||
| Supported Types |
|
||||
| ----------------------------------------------------------------- |
|
||||
| _`str`_, _`int`_, _`float`_, _`bool`_, _`list`_, _`dict`_ |
|
||||
| _`langflow.field_typing.NestedDict`_ |
|
||||
| _`langflow.field_typing.Prompt`_ |
|
||||
| _`langchain.chains.base.Chain`_ |
|
||||
| _`langchain.PromptTemplate`_ |
|
||||
| _`from langchain.schema.language_model import BaseLanguageModel`_ |
|
||||
| _`langchain.Tool`_ |
|
||||
| _`langchain.document_loaders.base.BaseLoader`_ |
|
||||
| _`langchain.schema.Document`_ |
|
||||
| _`langchain.text_splitters.TextSplitter`_ |
|
||||
| _`langchain.vectorstores.base.VectorStore`_ |
|
||||
| _`langchain.embeddings.base.Embeddings`_ |
|
||||
| _`langchain.schema.BaseRetriever`_ |
|
||||
| _`langchain.Tool`_ |
|
||||
| _`langchain.document_loaders.base.BaseLoader`_ |
|
||||
| _`langchain.schema.Document`_ |
|
||||
| _`langchain.text_splitters.TextSplitter`_ |
|
||||
| _`langchain.vectorstores.base.VectorStore`_ |
|
||||
| _`langchain.embeddings.base.Embeddings`_ |
|
||||
| _`langchain.schema.BaseRetriever`_ |
|
||||
|
||||
The difference between _`dict`_ and _`langflow.field_typing.NestedDict`_ is that one adds a simple key-value pair field, while the other opens a more robust dictionary editor.
|
||||
|
||||
<Admonition type="info">
|
||||
Use the `Prompt` type by adding **kwargs to the build method.
|
||||
If you want to add the values of the variables to the template you defined, format the `PromptTemplate` inside the `CustomComponent` class.
|
||||
Use the `Prompt` type by adding **kwargs to the build method. If you want to
|
||||
add the values of the variables to the template you defined, format the
|
||||
`PromptTemplate` inside the `CustomComponent` class.
|
||||
</Admonition>
|
||||
|
||||
<Admonition type="info">
|
||||
Use base Python types without a handle by default. To add handles, use the `input_types` key in the `build_config` method.
|
||||
Use base Python types without a handle by default. To add handles, use the
|
||||
`input_types` key in the `build_config` method.
|
||||
</Admonition>
|
||||
|
||||
**build_config:** Defines the configuration fields of the component. This method returns a dictionary where each key represents a field name and each value defines the field's behavior.
|
||||
|
||||
Supported keys for configuring fields:
|
||||
|
||||
| Key | Description |
|
||||
| --------------------- | --------------------------------------------------- |
|
||||
| `is_list` | Boolean indicating if the field can hold multiple values. |
|
||||
| `options` | Dropdown menu options. |
|
||||
| `multiline` | Boolean indicating if a field allows multiline input. |
|
||||
| `input_types` | Allows connection handles for string fields. |
|
||||
| `display_name` | Field name displayed in the UI. |
|
||||
| `advanced` | Hides the field in the default UI view. |
|
||||
| `password` | Masks input, useful for sensitive data. |
|
||||
| `required` | Overrides the default behavior to make a field mandatory. |
|
||||
| `info` | Tooltip for the field. |
|
||||
| `file_types` | Accepted file types, useful for file fields. |
|
||||
| `range_spec` | Defines valid ranges for float fields. |
|
||||
| `title_case` | Boolean that controls field name capitalization. |
|
||||
| `refresh_button` | Adds a refresh button that updates field values. |
|
||||
| `real_time_refresh` | Updates the configuration as field values change. |
|
||||
| `field_type` | Automatically set based on the build method's type hint. |
|
||||
| Key | Description |
|
||||
| ------------------- | --------------------------------------------------------- |
|
||||
| `is_list` | Boolean indicating if the field can hold multiple values. |
|
||||
| `options` | Dropdown menu options. |
|
||||
| `multiline` | Boolean indicating if a field allows multiline input. |
|
||||
| `input_types` | Allows connection handles for string fields. |
|
||||
| `display_name` | Field name displayed in the UI. |
|
||||
| `advanced` | Hides the field in the default UI view. |
|
||||
| `password` | Masks input, useful for sensitive data. |
|
||||
| `required` | Overrides the default behavior to make a field mandatory. |
|
||||
| `info` | Tooltip for the field. |
|
||||
| `file_types` | Accepted file types, useful for file fields. |
|
||||
| `range_spec` | Defines valid ranges for float fields. |
|
||||
| `title_case` | Boolean that controls field name capitalization. |
|
||||
| `refresh_button` | Adds a refresh button that updates field values. |
|
||||
| `real_time_refresh` | Updates the configuration as field values change. |
|
||||
| `field_type` | Automatically set based on the build method's type hint. |
|
||||
|
||||
<Admonition type="info" label="Tip">
|
||||
Use the `update_build_config` method to dynamically update configurations based on field values.
|
||||
Use the `update_build_config` method to dynamically update configurations
|
||||
based on field values.
|
||||
</Admonition>
|
||||
|
||||
## Additional methods and attributes
|
||||
|
|
@ -99,4 +103,3 @@ The `CustomComponent` class also provides helpful methods for specific tasks (e.
|
|||
- `status`: Shows values from the `build` method, useful for debugging.
|
||||
- `field_order`: Controls the display order of fields.
|
||||
- `icon`: Sets the canvas display icon.
|
||||
|
||||
|
|
|
|||
161
docs/docs/components/inputs-and-outputs.mdx
Normal file
161
docs/docs/components/inputs-and-outputs.mdx
Normal file
|
|
@ -0,0 +1,161 @@
|
|||
import Admonition from "@theme/Admonition";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
|
||||
# Inputs and Outputs
|
||||
|
||||
TL;DR: Inputs and Outputs are a category of components that are used to define where data comes in and out of your flow.
|
||||
They also dynamically change the Playground and can be renamed to facilitate building and maintaining your flows.
|
||||
|
||||
## Inputs
|
||||
|
||||
Inputs are components used to define where data enters your flow. They can receive data from the user, a database, or any other source that can be converted to Text or Record.
|
||||
|
||||
The difference between Chat Input and other Input components is the output format, the number of configurable fields, and the way they are displayed in the Playground.
|
||||
|
||||
Chat Input components can output `Text` or `Record`. When you want to pass the sender name or sender to the next component, use the `Record` output. To pass only the message, use the `Text` output, useful when saving the message to a database or memory system like Zep.
|
||||
|
||||
You can find out more about Chat Input and other Inputs [here](#chat-input).
|
||||
|
||||
### Chat Input
|
||||
|
||||
This component collects user input from the chat.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Sender Type:** Specifies the sender type. Defaults to `User`. Options are `Machine` and `User`.
|
||||
- **Sender Name:** Specifies the name of the sender. Defaults to `User`.
|
||||
- **Message:** Specifies the message text. It is a multiline text input.
|
||||
- **Session ID:** Specifies the session ID of the chat history. If provided, the message will be saved in the Message History.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
If `As Record` is `true` and the `Message` is a `Record`, the data of the
|
||||
`Record` will be updated with the `Sender`, `Sender Name`, and `Session ID`.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/chat-input-expanded.png",
|
||||
dark: "img/chat-input-expanded.png",
|
||||
}}
|
||||
style={{ width: "40%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
One significant capability of the Chat Input component is its ability to transform the Playground into a chat window. This feature is particularly valuable for scenarios requiring user input to initiate or influence the flow.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/interaction-panel-with-chat-input.png",
|
||||
dark: "img/interaction-panel-with-chat-input.png",
|
||||
}}
|
||||
style={{ width: "50%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
### Text Input
|
||||
|
||||
The **Text Input** component adds an **Input** field on the Playground. This enables you to define parameters while running and testing your flow.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Value:** Specifies the text input value. This is where the user inputs text data that will be passed to the next component in the sequence. If no value is provided, it defaults to an empty string.
|
||||
- **Record Template:** Specifies how a `Record` should be converted into `Text`.
|
||||
|
||||
The **Record Template** field is used to specify how a `Record` should be converted into `Text`. This is particularly useful when you want to extract specific information from a `Record` and pass it as text to the next component in the sequence.
|
||||
|
||||
For example, if you have a `Record` with the following structure:
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "John Doe",
|
||||
"age": 30,
|
||||
"email": "johndoe@email.com"
|
||||
}
|
||||
```
|
||||
|
||||
A template with `Name: {name}, Age: {age}` will convert the `Record` into a text string of `Name: John Doe, Age: 30`.
|
||||
|
||||
If you pass more than one `Record`, the text will be concatenated with a new line separator.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/text-input-expanded.png",
|
||||
dark: "img/text-input-expanded.png",
|
||||
}}
|
||||
style={{ width: "50%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
## Outputs
|
||||
|
||||
Outputs are components that are used to define where data comes out of your flow. They can be used to send data to the user, to the Playground, or to define how the data will be displayed in the Playground.
|
||||
|
||||
The Chat Output works similarly to the Chat Input but does not have a field that allows for written input. It is used as an Output definition and can be used to send data to the user.
|
||||
|
||||
You can find out more about it and the other Outputs [here](#chat-output).
|
||||
|
||||
### Chat Output
|
||||
|
||||
This component sends a message to the chat.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Sender Type:** Specifies the sender type. Default is `"Machine"`. Options are `"Machine"` and `"User"`.
|
||||
|
||||
- **Sender Name:** Specifies the sender's name. Default is `"AI"`.
|
||||
|
||||
- **Session ID:** Specifies the session ID of the chat history. If provided, messages are saved in the Message History.
|
||||
|
||||
- **Message:** Specifies the text of the message.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
If `As Record` is `true` and the `Message` is a `Record`, the data in the
|
||||
`Record` is updated with the `Sender`, `Sender Name`, and `Session ID`.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
### Text Output
|
||||
|
||||
This component displays text data to the user. It is useful when you want to show text without sending it to the chat.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Value:** Specifies the text data to be displayed. Defaults to an empty string.
|
||||
|
||||
The `TextOutput` component provides a simple way to display text data. It allows textual data to be visible in the chat window during your interaction flow.
|
||||
|
||||
## Prompts
|
||||
|
||||
A prompt is the input provided to a language model, consisting of multiple components and can be parameterized using prompt templates. A prompt template offers a reproducible method for generating prompts, enabling easy customization through input variables.
|
||||
|
||||
### Prompt
|
||||
|
||||
This component creates a prompt template with dynamic variables. This is useful for structuring prompts and passing dynamic data to a language model.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Template:** The template for the prompt. This field allows you to create other fields dynamically by using curly brackets `{}`. For example, if you have a template like `Hello {name}, how are you?`, a new field called `name` will be created. Prompt variables can be created with any name inside curly brackets, e.g. `{variable_name}`.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/prompt-with-template.png",
|
||||
dark: "img/prompt-with-template.png",
|
||||
}}
|
||||
style={{ width: "50%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
### PromptTemplate
|
||||
|
||||
The `PromptTemplate` component enables users to create prompts and define variables that control how the model is instructed. Users can input a set of variables which the template uses to generate the prompt when a conversation starts.
|
||||
|
||||
<Admonition type="info">
|
||||
After defining a variable in the prompt template, it acts as its own component
|
||||
input. See [Prompt Customization](../administration/prompt-customization) for
|
||||
more details.
|
||||
</Admonition>
|
||||
|
||||
- **template:** The template used to format an individual request.
|
||||
|
|
@ -1,99 +0,0 @@
|
|||
import Admonition from '@theme/Admonition';
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
|
||||
# Inputs
|
||||
|
||||
## Chat Input
|
||||
|
||||
This component obtains user input from the chat.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Sender Type:** Specifies the sender type. Defaults to `User`. Options are `Machine` and `User`.
|
||||
- **Sender Name:** Specifies the name of the sender. Defaults to `User`.
|
||||
- **Message:** Specifies the message text. It is a multiline text input.
|
||||
- **Session ID:** Specifies the session ID of the chat history. If provided, the message will be saved in the Message History.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
If `As Record` is `true` and the `Message` is a `Record`, the data
|
||||
of the `Record` will be updated with the `Sender`, `Sender Name`, and
|
||||
`Session ID`.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/chat-input-expanded.png",
|
||||
dark: "img/chat-input-expanded.png",
|
||||
}}
|
||||
style={{ width: "40%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
One significant capability of the Chat Input component is its ability to transform the Playground into a chat window. This feature is particularly valuable for scenarios requiring user input to initiate or influence the flow.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/interaction-panel-with-chat-input.png",
|
||||
dark: "img/interaction-panel-with-chat-input.png",
|
||||
}}
|
||||
style={{ width: "50%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
---
|
||||
|
||||
## Prompt
|
||||
|
||||
This component creates a prompt template with dynamic variables. This is useful for structuring prompts and passing dynamic data to a language model.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Template:** The template for the prompt. This field allows you to create other fields dynamically by using curly brackets `{}`. For example, if you have a template like `Hello {name}, how are you?`, a new field called `name` will be created. Prompt variables can be created with any name inside curly brackets, e.g. `{variable_name}`.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/prompt-with-template.png",
|
||||
dark: "img/prompt-with-template.png",
|
||||
}}
|
||||
style={{ width: "50%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
---
|
||||
|
||||
## Text Input
|
||||
|
||||
The **Text Input** component adds an **Input** field on the Playground. This enables you to define parameters while running and testing your flow.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Value:** Specifies the text input value. This is where the user inputs text data that will be passed to the next component in the sequence. If no value is provided, it defaults to an empty string.
|
||||
- **Record Template:** Specifies how a `Record` should be converted into `Text`.
|
||||
|
||||
The **Record Template** field is used to specify how a `Record` should be converted into `Text`. This is particularly useful when you want to extract specific information from a `Record` and pass it as text to the next component in the sequence.
|
||||
|
||||
For example, if you have a `Record` with the following structure:
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "John Doe",
|
||||
"age": 30,
|
||||
"email": "johndoe@email.com"
|
||||
}
|
||||
```
|
||||
|
||||
A template with `Name: {name}, Age: {age}` will convert the `Record` into a text string of `Name: John Doe, Age: 30`.
|
||||
|
||||
If you pass more than one `Record`, the text will be concatenated with a new line separator.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/text-input-expanded.png",
|
||||
dark: "img/text-input-expanded.png",
|
||||
}}
|
||||
style={{ width: "50%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
|
|
@ -1,34 +0,0 @@
|
|||
import Admonition from '@theme/Admonition';
|
||||
|
||||
# Outputs
|
||||
|
||||
## Chat Output
|
||||
|
||||
This component sends a message to the chat.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Sender Type:** Specifies the sender type. Default is `"Machine"`. Options are `"Machine"` and `"User"`.
|
||||
|
||||
- **Sender Name:** Specifies the sender's name. Default is `"AI"`.
|
||||
|
||||
- **Session ID:** Specifies the session ID of the chat history. If provided, messages are saved in the Message History.
|
||||
|
||||
- **Message:** Specifies the text of the message.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
If `As Record` is `true` and the `Message` is a `Record`, the data in the `Record` is updated with the `Sender`, `Sender Name`, and `Session ID`.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
## Text Output
|
||||
|
||||
This component displays text data to the user. It is useful when you want to show text without sending it to the chat.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Value:** Specifies the text data to be displayed. Defaults to an empty string.
|
||||
|
||||
|
||||
The `TextOutput` component provides a simple way to display text data. It allows textual data to be visible in the chat window during your interaction flow.
|
||||
|
|
@ -1,25 +0,0 @@
|
|||
import Admonition from "@theme/Admonition";
|
||||
|
||||
# Prompts
|
||||
|
||||
<Admonition type="caution" icon="🚧" title="Zone Under Construction">
|
||||
<p>
|
||||
Thank you for your patience as we refine our documentation. It may
|
||||
still have some areas under development. Please share your feedback or report any issues to help us improve!
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
A prompt is the input provided to a language model, consisting of multiple components and can be parameterized using prompt templates. A prompt template offers a reproducible method for generating prompts, enabling easy customization through input variables.
|
||||
|
||||
---
|
||||
|
||||
### PromptTemplate
|
||||
|
||||
The `PromptTemplate` component enables users to create prompts and define variables that control how the model is instructed. Users can input a set of variables which the template uses to generate the prompt when a conversation starts.
|
||||
|
||||
<Admonition type="info">
|
||||
After defining a variable in the prompt template, it acts as its own component
|
||||
input. See [Prompt Customization](../administration/prompt-customization) for more details.
|
||||
</Admonition>
|
||||
|
||||
- **template:** The template used to format an individual request.
|
||||
49
docs/docs/components/text-and-record.mdx
Normal file
49
docs/docs/components/text-and-record.mdx
Normal file
|
|
@ -0,0 +1,49 @@
|
|||
# Text and Record
|
||||
|
||||
In Langflow 1.0, we added two main input and output types: `Text` and `Record`.
|
||||
|
||||
`Text` is a simple string input and output type, while `Record` is a structure very similar to a dictionary in Python. It is a key-value pair data structure.
|
||||
|
||||
We've created a few components to help you work with these types. Let's see how a few of them work.
|
||||
|
||||
## Records To Text
|
||||
|
||||
This is a component that takes in Records and outputs a `Text`. It does this using a template string and concatenating the values of the `Record`, one per line.
|
||||
|
||||
If we have the following Records:
|
||||
|
||||
```json
|
||||
{
|
||||
"sender_name": "Alice",
|
||||
"message": "Hello!"
|
||||
}
|
||||
{
|
||||
"sender_name": "John",
|
||||
"message": "Hi!"
|
||||
}
|
||||
```
|
||||
|
||||
And the template string is: _`{sender_name}: {message}`_
|
||||
|
||||
The output is:
|
||||
|
||||
```
|
||||
Alice: Hello!
|
||||
John: Hi!
|
||||
```
|
||||
|
||||
## Create Record
|
||||
|
||||
This component allows you to create a `Record` from a number of inputs. You can add as many key-value pairs as you want (as long as it is less than 15). Once you've picked that number you'll need to write the name of the Key and can pass `Text` values from other components to it.
|
||||
|
||||
## Documents To Records
|
||||
|
||||
This component takes in a LangChain `Document` and outputs a `Record`. It does this by extracting the `page_content` and the `metadata` from the `Document` and adding them to the `Record` as text and data respectively.
|
||||
|
||||
## Why is this useful?
|
||||
|
||||
The idea was to create a unified way to work with complex data in Langflow and to make it easier to work with data that is not just a simple string. This way you can create more complex workflows and use the data in more ways.
|
||||
|
||||
## What's next?
|
||||
|
||||
We are planning to integrate an array of modalities to Langflow, such as images, audio, and video. This will allow you to create even more complex workflows and use cases. Stay tuned for more updates! 🚀
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import Admonition from "@theme/Admonition";
|
||||
|
||||
# Vector Stores Documentation
|
||||
# Vector Stores
|
||||
|
||||
### Astra DB
|
||||
|
||||
|
|
|
|||
|
|
@ -14,4 +14,4 @@ This component is available under the **Helpers** tab of the Langflow preview.
|
|||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/chat_memory.mp4" />
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -18,4 +18,4 @@ This component is available under the **Helpers** tab of the Langflow preview.
|
|||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/combine_text.mp4" />
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -14,4 +14,4 @@ The **Create Record** component allows you to dynamically create a `Record` from
|
|||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/create_record.mp4" />
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -14,4 +14,4 @@ The **Pass** component enables you to ignore one input and move forward with ano
|
|||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/pass.mp4" />
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -14,4 +14,4 @@ The **Message History** component can then be used to retrieve stored messages.
|
|||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/store_message.mp4" />
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -12,4 +12,4 @@ The **Sub Flow** component enables a user to select a previously built flow and
|
|||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/sub_flow.mp4" />
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -12,4 +12,4 @@ The **Text Operator** component simplifies logic. It evaluates the results from
|
|||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/text_operator.mp4" />
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -56,7 +56,8 @@ Components are the building blocks of flows. They consist of inputs, outputs, an
|
|||
<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.
|
||||
availability to connect to other components. Hover over a handle to see
|
||||
connection details.
|
||||
</div>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
|
|
@ -85,6 +86,7 @@ Build the flow by clicking the **Playgr
|
|||
|
||||
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>
|
||||
|
||||
---
|
||||
|
|
@ -196,6 +198,7 @@ curl -X POST \
|
|||
```
|
||||
|
||||
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"}]}]}%
|
||||
```
|
||||
|
|
@ -231,9 +234,10 @@ 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
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_collection.mp4" />
|
||||
</div>
|
||||
|
||||
## Project
|
||||
|
|
@ -276,9 +280,3 @@ To see options for your project, in the upper left corner of the canvas, select
|
|||
**Export** - Download your current project to your local machine as a `.json` file.
|
||||
|
||||
**Undo** or **Redo** - Undo or redo your last action.
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import ThemedImage from '@theme/ThemedImage';
|
||||
import useBaseUrl from '@docusaurus/useBaseUrl';
|
||||
import ZoomableImage from '/src/theme/ZoomableImage.js';
|
||||
import ReactPlayer from 'react-player';
|
||||
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
|
||||
|
||||
|
|
@ -17,10 +17,4 @@ A [project](#project) can be a component or a flow. Projects are saved as part o
|
|||
|
||||
For example, the **OpenAI LLM** is a **component** of the **Basic prompting** flow, and the **flow** is stored in a **collection**.
|
||||
|
||||
|
||||
|
||||
## Component
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -6,33 +6,40 @@ import Admonition from "@theme/Admonition";
|
|||
# 📦 Install Langflow
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true), to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true),
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
Langflow requires [Python >=3.10](https://www.python.org/downloads/release/python-3100/) and [pip](https://pypi.org/project/pip/) or [pipx](https://pipx.pypa.io/stable/installation/) to be installed on your system.
|
||||
|
||||
Install Langflow with pip:
|
||||
|
||||
```bash
|
||||
python -m pip install langflow -U
|
||||
```
|
||||
|
||||
Install Langflow with pipx:
|
||||
|
||||
```bash
|
||||
pipx install langflow --python python3.10 --fetch-missing-python
|
||||
```
|
||||
Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually.
|
||||
|
||||
Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually.
|
||||
|
||||
## Install Langflow pre-release
|
||||
|
||||
To install a pre-release version of Langflow:
|
||||
|
||||
pip:
|
||||
|
||||
```bash
|
||||
python -m pip install langflow --pre --force-reinstall
|
||||
```
|
||||
|
||||
pipx:
|
||||
|
||||
```bash
|
||||
pipx install langflow --python python3.10 --fetch-missing-python --pip-args="--pre --force-reinstall"
|
||||
```
|
||||
|
|
@ -52,11 +59,13 @@ python -m langflow --help
|
|||
## ⛓️ Run Langflow
|
||||
|
||||
1. To run Langflow, enter the following command.
|
||||
|
||||
```bash
|
||||
python -m langflow run
|
||||
```
|
||||
|
||||
2. Confirm that a local Langflow instance starts by visiting `http://127.0.0.1:7860` in a Chromium-based browser.
|
||||
|
||||
```bash
|
||||
│ Welcome to ⛓ Langflow │
|
||||
│ │
|
||||
|
|
@ -83,4 +92,4 @@ You'll be presented with the following screen:
|
|||
style={{ width: "100%", margin: "20px auto" }}
|
||||
/>
|
||||
|
||||
Name your Space, define the visibility (Public or Private), and click on **Duplicate Space** to start the installation process. When installation is finished, you'll be redirected to the Space's main page to start using Langflow right away!
|
||||
Name your Space, define the visibility (Public or Private), and click on **Duplicate Space** to start the installation process. When installation is finished, you'll be redirected to the Space's main page to start using Langflow right away!
|
||||
|
|
|
|||
|
|
@ -10,12 +10,15 @@ This guide demonstrates how to build a basic prompt flow and modify that prompt
|
|||
|
||||
## Prerequisites
|
||||
|
||||
* [Langflow installed and running](./install-langflow.mdx)
|
||||
- [Langflow installed and running](./install-langflow.mdx)
|
||||
|
||||
* [OpenAI API key](https://platform.openai.com)
|
||||
- [OpenAI API key](https://platform.openai.com)
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
## Hello World - Basic Prompting
|
||||
|
|
@ -44,25 +47,25 @@ Examine the **Prompt** component. The **Template** field instructs the LLM to `A
|
|||
This should be interesting...
|
||||
|
||||
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
## Run the basic prompting flow
|
||||
|
||||
1. Click the **Run** button.
|
||||
The **Interaction Panel** opens, where you can chat with your bot.
|
||||
The **Interaction Panel** opens, where you can chat with your bot.
|
||||
2. Type a message and press Enter.
|
||||
And... Ahoy! 🏴☠️
|
||||
The bot responds in a piratical manner!
|
||||
And... Ahoy! 🏴☠️
|
||||
The bot responds in a piratical manner!
|
||||
|
||||
## Modify the prompt for a different result
|
||||
|
||||
1. To modify your prompt results, in the **Prompt** template, click the **Template** field.
|
||||
The **Edit Prompt** window opens.
|
||||
The **Edit Prompt** window opens.
|
||||
2. Change `Answer the user as if you were a pirate` to a different character, perhaps `Answer the user as if you were Harold Abelson.`
|
||||
3. Run the basic prompting flow again.
|
||||
The response will be markedly different.
|
||||
The response will be markedly different.
|
||||
|
||||
## Next steps
|
||||
|
||||
|
|
@ -72,8 +75,6 @@ By adding Langflow components to your flow, you can create all sorts of interest
|
|||
|
||||
Here are a couple of examples:
|
||||
|
||||
* [Memory chatbot](/starter-projects/memory-chatbot.mdx)
|
||||
* [Blog writer](/starter-projects/blog-writer.mdx)
|
||||
* [Document QA](/starter-projects/document-qa.mdx)
|
||||
|
||||
|
||||
- [Memory chatbot](/starter-projects/memory-chatbot.mdx)
|
||||
- [Blog writer](/starter-projects/blog-writer.mdx)
|
||||
- [Document QA](/starter-projects/document-qa.mdx)
|
||||
|
|
|
|||
|
|
@ -29,7 +29,10 @@ Its intuitive interface allows for easy manipulation of AI building blocks, enab
|
|||
- [Langflow Canvas](/getting-started/canvas) - Learn more about the Langflow canvas.
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
## Learn more about Langflow 1.0
|
||||
|
|
|
|||
|
|
@ -9,14 +9,11 @@ The `AddContentToPage` component converts markdown text to Notion blocks and app
|
|||
|
||||
[Notion Reference](https://developers.notion.com/reference/patch-block-children)
|
||||
|
||||
<Admonition type="tip" title="Component Functionality">
|
||||
|
||||
The `AddContentToPage` component enables you to:
|
||||
|
||||
- Convert markdown text to Notion blocks.
|
||||
- Append the converted blocks to a specified Notion page.
|
||||
- Seamlessly integrate Notion content creation into Langflow workflows.
|
||||
</Admonition>
|
||||
|
||||
## Component Usage
|
||||
|
||||
|
|
@ -100,23 +97,19 @@ class NotionPageCreator(CustomComponent):
|
|||
|
||||
## Example Usage
|
||||
|
||||
<Admonition type="info" title="Example Usage">
|
||||
|
||||
Example of using the `AddContentToPage` component in a Langflow flow using Markdown as input:
|
||||
|
||||
<ZoomableImage
|
||||
alt="NotionDatabaseProperties Flow Example"
|
||||
sources={{
|
||||
alt="NotionDatabaseProperties Flow Example"
|
||||
sources={{
|
||||
light: "img/notion/AddContentToPage_flow_example.png",
|
||||
dark: "img/notion/AddContentToPage_flow_example.png",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
|
||||
In this example, the `AddContentToPage` component connects to a `MarkdownLoader` component to provide the markdown text input. The converted Notion blocks are appended to the specified Notion page using the provided `block_id` and `notion_secret`.
|
||||
|
||||
</Admonition>
|
||||
|
||||
## Best Practices
|
||||
|
||||
When using the `AddContentToPage` component:
|
||||
|
|
@ -131,8 +124,8 @@ The `AddContentToPage` component is a powerful tool for integrating Notion conte
|
|||
## Troubleshooting
|
||||
|
||||
If you encounter any issues while using the `AddContentToPage` component, consider the following:
|
||||
|
||||
- Verify the Notion integration token’s validity and permissions.
|
||||
- Check the Notion API documentation for updates.
|
||||
- Ensure markdown text is properly formatted.
|
||||
- Double-check the `block_id` for correctness.
|
||||
|
||||
|
|
|
|||
|
|
@ -8,12 +8,12 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
The Notion integration in Langflow enables seamless connectivity with Notion databases, pages, and users, facilitating automation and improving productivity.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Notion Components in Langflow"
|
||||
sources={{
|
||||
alt="Notion Components in Langflow"
|
||||
sources={{
|
||||
light: "img/notion/notion_bundle.jpg",
|
||||
dark: "img/notion/notion_bundle.jpg",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/Notion_Components_bundle.json" download>Download Notion Components Bundle</a>
|
||||
|
|
|
|||
|
|
@ -41,7 +41,7 @@ class NotionDatabaseProperties(CustomComponent):
|
|||
description = "Retrieve properties of a Notion database."
|
||||
documentation: str = "https://docs.langflow.org/integrations/notion/list-database-properties"
|
||||
icon = "NotionDirectoryLoader"
|
||||
|
||||
|
||||
def build_config(self):
|
||||
return {
|
||||
"database_id": {
|
||||
|
|
@ -80,6 +80,7 @@ class NotionDatabaseProperties(CustomComponent):
|
|||
```
|
||||
|
||||
## Example Usage
|
||||
|
||||
<Admonition type="info" title="Example Usage">
|
||||
Here's an example of how you can use the `NotionDatabaseProperties` component in a Langflow flow:
|
||||
|
||||
|
|
@ -110,6 +111,7 @@ Feel free to explore the capabilities of the `NotionDatabaseProperties` componen
|
|||
## Troubleshooting
|
||||
|
||||
If you encounter any issues while using the `NotionDatabaseProperties` component, consider the following:
|
||||
|
||||
- Verify that the Notion integration token is valid and has the required permissions.
|
||||
- Check the database ID to ensure it matches the intended Notion database.
|
||||
- Inspect the response from the Notion API for any error messages or status codes that may indicate the cause of the issue.
|
||||
- Inspect the response from the Notion API for any error messages or status codes that may indicate the cause of the issue.
|
||||
|
|
|
|||
|
|
@ -140,16 +140,17 @@ class NotionListPages(CustomComponent):
|
|||
<Admonition type="info" title="Example Usage">
|
||||
|
||||
## Example Usage
|
||||
|
||||
Here's an example of how you can use the `NotionListPages` component in a Langflow flow and passing to the Prompt component:
|
||||
|
||||
<ZoomableImage
|
||||
alt="NotionListPages
|
||||
Flow Example"
|
||||
sources={{
|
||||
alt="NotionListPages
|
||||
Flow Example"
|
||||
sources={{
|
||||
light: "img/notion/NotionListPages_flow_example.png",
|
||||
dark: "img/notion/NotionListPages_flow_example_dark.png",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
|
||||
In this example, the `NotionListPages` component is used to retrieve specific pages from a Notion database based on the provided filters and sorting options. The retrieved data can then be processed further in the subsequent components of the flow.
|
||||
|
|
@ -157,7 +158,7 @@ In this example, the `NotionListPages` component is used to retrieve specific pa
|
|||
|
||||
## Best Practices
|
||||
|
||||
When using the `NotionListPages
|
||||
When using the `NotionListPages
|
||||
` component, consider the following best practices:
|
||||
|
||||
- Ensure that you have a valid Notion integration token with the necessary permissions to query the desired database.
|
||||
|
|
@ -171,7 +172,7 @@ We encourage you to explore the capabilities of the `NotionListPages
|
|||
|
||||
## Troubleshooting
|
||||
|
||||
If you encounter any issues while using the `NotionListPages` component, consider the following:
|
||||
If you encounter any issues while using the `NotionListPages` component, consider the following:
|
||||
|
||||
- Double-check that the `notion_secret` and `database_id` are correct and valid.
|
||||
- Verify that the `query_payload` JSON string is properly formatted and contains valid filtering and sorting options.
|
||||
|
|
|
|||
|
|
@ -9,13 +9,11 @@ The `NotionUserList` component retrieves users from Notion. It provides a conven
|
|||
|
||||
[Notion Reference](https://developers.notion.com/reference/get-users)
|
||||
|
||||
<Admonition type="tip" title="Component Functionality">
|
||||
The `NotionUserList` component enables you to:
|
||||
|
||||
- Retrieve user data from Notion
|
||||
- Access user information such as ID, type, name, and avatar URL
|
||||
- Integrate Notion user data seamlessly into your Langflow workflows
|
||||
</Admonition>
|
||||
|
||||
## Component Usage
|
||||
|
||||
|
|
@ -94,34 +92,31 @@ class NotionUserList(CustomComponent):
|
|||
```
|
||||
|
||||
## Example Usage
|
||||
<Admonition type="info" title="Example Usage">
|
||||
|
||||
Here's an example of how you can use the `NotionUserList` component in a Langflow flow and passing the outputs to the Prompt component:
|
||||
|
||||
<ZoomableImage
|
||||
alt="NotionUserList Flow Example"
|
||||
sources={{
|
||||
alt="NotionUserList Flow Example"
|
||||
sources={{
|
||||
light: "img/notion/NotionUserList_flow_example.png",
|
||||
dark: "img/notion/NotionUserList_flow_example_dark.png",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
|
||||
</Admonition>
|
||||
|
||||
## Best Practices
|
||||
|
||||
When using the `NotionUserList` component, consider the following best practices:
|
||||
When using the `NotionUserList` component, consider the following best practices:
|
||||
|
||||
- Ensure that you have a valid Notion integration token with the necessary permissions to retrieve user data.
|
||||
- Handle the retrieved user data securely and in compliance with Notion's API usage guidelines.
|
||||
|
||||
The `NotionUserList` component provides a seamless way to integrate Notion user data into your Langflow workflows. By leveraging this component, you can easily retrieve and utilize user information from Notion, enhancing the capabilities of your Langflow applications. Feel free to explore and experiment with the `NotionUserList` component to unlock new possibilities in your Langflow projects!
|
||||
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
If you encounter any issues while using the `NotionUserList` component, consider the following:
|
||||
If you encounter any issues while using the `NotionUserList` component, consider the following:
|
||||
|
||||
- Double-check that your Notion integration token is valid and has the required permissions.
|
||||
- Verify that you have installed the necessary dependencies (`requests`) for the component to function properly.
|
||||
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.
|
||||
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@ The `NotionPageContent` component retrieves the content of a Notion page as plai
|
|||
|
||||
<Admonition type="tip" title="Component Functionality">
|
||||
|
||||
The `NotionPageContent` component enables you to:
|
||||
The `NotionPageContent` component enables you to:
|
||||
|
||||
- Retrieve the content of a Notion page as plain text
|
||||
- Extract text from various block types, including paragraphs, headings, lists, and more
|
||||
|
|
@ -114,18 +114,18 @@ class NotionPageContent(CustomComponent):
|
|||
Here's an example of how you can use the `NotionPageContent` component in a Langflow flow:
|
||||
|
||||
<ZoomableImage
|
||||
alt="NotionPageContent Flow Example"
|
||||
sources={{
|
||||
alt="NotionPageContent Flow Example"
|
||||
sources={{
|
||||
light: "img/notion/NotionPageContent_flow_example.png",
|
||||
dark: "img/notion/NotionPageContent_flow_example_dark.png",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
</Admonition>
|
||||
|
||||
## Best Practices
|
||||
|
||||
When using the `NotionPageContent` component, consider the following best practices:
|
||||
When using the `NotionPageContent` component, consider the following best practices:
|
||||
|
||||
- Ensure that you have the necessary permissions to access the Notion page you want to retrieve.
|
||||
- Keep your Notion integration token secure and avoid sharing it publicly.
|
||||
|
|
@ -135,7 +135,7 @@ The `NotionPageContent` component provides a seamless way to integrate Notion pa
|
|||
|
||||
## Troubleshooting
|
||||
|
||||
If you encounter any issues while using the `NotionPageContent` component, consider the following:
|
||||
If you encounter any issues while using the `NotionPageContent` component, consider the following:
|
||||
|
||||
- Double-check that you have provided the correct Notion page ID.
|
||||
- Verify that your Notion integration token is valid and has the necessary permissions.
|
||||
|
|
|
|||
|
|
@ -97,16 +97,17 @@ class NotionPageCreator(CustomComponent):
|
|||
```
|
||||
|
||||
## Example Usage
|
||||
|
||||
<Admonition type="info" title="Example Usage">
|
||||
Here's an example of how to use the `NotionPageCreator` component in a Langflow flow:
|
||||
|
||||
<ZoomableImage
|
||||
alt="NotionPageCreator Flow Example"
|
||||
sources={{
|
||||
alt="NotionPageCreator Flow Example"
|
||||
sources={{
|
||||
light: "img/notion/NotionPageCreator_flow_example.png",
|
||||
dark: "img/notion/NotionPageCreator_flow_example_dark.png",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
</Admonition>
|
||||
|
||||
|
|
@ -124,6 +125,7 @@ The `NotionPageCreator` component simplifies the process of creating pages in a
|
|||
## Troubleshooting
|
||||
|
||||
If you encounter any issues while using the `NotionPageCreator` component, consider the following:
|
||||
|
||||
- Double-check that the `database_id` and `notion_secret` inputs are correct and valid.
|
||||
- Verify that the `properties` input is properly formatted as a JSON string and matches the structure of your Notion database.
|
||||
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.
|
||||
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.
|
||||
|
|
|
|||
|
|
@ -109,12 +109,12 @@ Let's break down the key parts of this component:
|
|||
Here's an example of how to use the `NotionPageUpdate` component in a Langflow flow using:
|
||||
|
||||
<ZoomableImage
|
||||
alt="NotionPageUpdate Flow Example"
|
||||
sources={{
|
||||
alt="NotionPageUpdate Flow Example"
|
||||
sources={{
|
||||
light: "img/notion/NotionPageUpdate_flow_example.png",
|
||||
dark: "img/notion/NotionPageUpdate_flow_example_dark.png",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
</Admonition>
|
||||
|
||||
|
|
@ -128,7 +128,6 @@ When using the `NotionPageUpdate` component, consider the following best practic
|
|||
|
||||
By leveraging the `NotionPageUpdate` component in Langflow, you can easily integrate updating Notion page properties into your language model workflows and build powerful applications that extend Langflow's capabilities.
|
||||
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
If you encounter any issues while using the `NotionPageUpdate` component, consider the following:
|
||||
|
|
|
|||
|
|
@ -146,16 +146,17 @@ class NotionSearch(CustomComponent):
|
|||
```
|
||||
|
||||
## Example Usage
|
||||
|
||||
<Admonition type="info" title="Example Usage">
|
||||
Here's an example of how you can use the `NotionSearch` component in a Langflow flow:
|
||||
|
||||
<ZoomableImage
|
||||
alt="NotionSearch Flow Example"
|
||||
sources={{
|
||||
alt="NotionSearch Flow Example"
|
||||
sources={{
|
||||
light: "img/notion/NotionSearch_flow_example.png",
|
||||
dark: "img/notion/NotionSearch_flow_example_dark.png",
|
||||
}}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
style={{ width: "100%", margin: "20px 0" }}
|
||||
/>
|
||||
|
||||
In this example, the `NotionSearch` component is used to search for pages and databases in Notion based on the provided query and filter criteria. The retrieved data can then be processed further in the subsequent components of the flow.
|
||||
|
|
|
|||
|
|
@ -76,4 +76,3 @@ Refer to the individual component documentation for more details on how to use e
|
|||
- [Notion Integration Capabilities](https://developers.notion.com/reference/capabilities)
|
||||
|
||||
If you encounter any issues or have questions, please reach out to our support team or consult the Langflow community forums.
|
||||
|
||||
|
|
|
|||
|
|
@ -1,118 +0,0 @@
|
|||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import Admonition from "@theme/Admonition";
|
||||
|
||||
# Global Variables
|
||||
|
||||
## TLDR;
|
||||
|
||||
- Global Variables are reusable variables that can be accessed from any Text field in your project.
|
||||
- To create a Global Variable, click on the 🌐 button in a Text field and then **+ Add New Variable**.
|
||||
- Define the **Name**, **Type**, and **Value** of the variable.
|
||||
- Click on **Save Variable** to create the variable.
|
||||
- All Credential Global Variables are encrypted and cannot be accessed by anyone but you.
|
||||
- Set _`LANGFLOW_STORE_ENVIRONMENT_VARIABLES`_ to _`true`_ in your `.env` file to add all variables in _`LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT`_ to your user's Global Variables.
|
||||
|
||||
Global Variables are a really useful feature of Langflow.
|
||||
They allow you to define reusable variables that can be accessed from any Text field in your project.
|
||||
|
||||
The first thing you need to do is find a **Text field** in a Component, so let's talk about what a Text field is.
|
||||
|
||||
## Text Fields
|
||||
|
||||
Text fields are the fields in a Component where you can write text but that does not allow you to open a Text Area.
|
||||
|
||||
The easiest way to find fields that are Text fields, though, is to look for fields that have a 🌐 button.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/ollama-gv.png",
|
||||
dark: "img/ollama-gv.png",
|
||||
}}
|
||||
style={{ width: "50%" }}
|
||||
/>
|
||||
|
||||
## Creating a Global Variable
|
||||
|
||||
To create a Global Variable, you need to click on the 🌐 button in a Text field and that will open a dropdown showing your currently available variables and at the end of it **+ Add New Variable**.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/add-new-variable.png",
|
||||
dark: "img/add-new-variable.png",
|
||||
}}
|
||||
style={{ width: "60%" }}
|
||||
/>
|
||||
|
||||
Click on **+ Add New Variable** and a window will open where you can define your new Global Variable.
|
||||
|
||||
In it, you can define the **Name** of the variable, the optional **Type** of the variable, and the **Value** of the variable.
|
||||
|
||||
The **Name** is the name that you will use to refer to the variable in your Text fields.
|
||||
|
||||
The **Type** is optional for now but will be used in the future to allow for more advanced features.
|
||||
|
||||
The **Value** is the value that the variable will have.
|
||||
{/* say that all variables are encrypted */}
|
||||
|
||||
<Admonition type="warning">
|
||||
All Credential Global Variables are encrypted and cannot be accessed by anyone
|
||||
but you.
|
||||
</Admonition>
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/create-variable-window.png",
|
||||
dark: "img/create-variable-window.png",
|
||||
}}
|
||||
style={{ width: "60%" }}
|
||||
/>
|
||||
|
||||
After you have defined your variable, click on **Save Variable** and your variable will be created.
|
||||
|
||||
After that, once you click on the 🌐 button in a Text field, you will see your new variable in the dropdown.
|
||||
|
||||
## Environment Variables
|
||||
|
||||
If you set _`LANGFLOW_STORE_ENVIRONMENT_VARIABLES`_ to _`true`_ (which is the default value) in your `.env` file, all variables in _`LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT`_ will be added to your user's Global Variables.
|
||||
|
||||
All of these variables can be used in your project as any other Global Variable.
|
||||
|
||||
<Admonition type="tip">
|
||||
You can set _`LANGFLOW_STORE_ENVIRONMENT_VARIABLES`_ to _`false`_ in your
|
||||
`.env` file to prevent this behavior.
|
||||
</Admonition>
|
||||
|
||||
You can also set _`LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT`_ to a list of variables that you want to get from the environment.
|
||||
|
||||
The default list at the moment is:
|
||||
|
||||
- ANTHROPIC_API_KEY
|
||||
- ASTRA_DB_API_ENDPOINT
|
||||
- ASTRA_DB_APPLICATION_TOKEN
|
||||
- AZURE_OPENAI_API_KEY
|
||||
- AZURE_OPENAI_API_DEPLOYMENT_NAME
|
||||
- AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME
|
||||
- AZURE_OPENAI_API_INSTANCE_NAME
|
||||
- AZURE_OPENAI_API_VERSION
|
||||
- COHERE_API_KEY
|
||||
- GOOGLE_API_KEY
|
||||
- GROQ_API_KEY
|
||||
- HUGGINGFACEHUB_API_TOKEN
|
||||
- OPENAI_API_KEY
|
||||
- PINECONE_API_KEY
|
||||
- SEARCHAPI_API_KEY
|
||||
- SERPAPI_API_KEY
|
||||
- UPSTASH_VECTOR_REST_URL
|
||||
- UPSTASH_VECTOR_REST_TOKEN
|
||||
- VECTARA_CUSTOMER_ID
|
||||
- VECTARA_CORPUS_ID
|
||||
- VECTARA_API_KEY
|
||||
|
||||
<Admonition type="tip">
|
||||
Set _`LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT`_ as a comma-separated list
|
||||
of variables (e.g. _`"VARIABLE1, VARIABLE2"`_) or as a JSON-encoded string
|
||||
(e.g. _`'["VARIABLE1", "VARIABLE2"]'`_).
|
||||
</Admonition>
|
||||
|
|
@ -1,36 +0,0 @@
|
|||
# Inputs and Outputs
|
||||
|
||||
TL;DR: Inputs and Outputs are a category of components that are used to define where data comes in and out of your flow. They also
|
||||
dynamically change the Playground and can be renamed to make it easier to build and maintain your flows.
|
||||
|
||||
## Introduction
|
||||
|
||||
Langflow 1.0 introduces new categories of components called Inputs and Outputs. They are used to make it easier to understand and interact with your flows.
|
||||
|
||||
Let's start with what they have in common:
|
||||
|
||||
- Components in these categories connect to components that have Text or Record inputs or outputs. Some can connect to both but you have to pick what type of data you want to output or input.
|
||||
- They can be renamed to help you identify them more easily in the Playground and while using the API.
|
||||
- They dynamically change the Playground to make it easier to understand and interact with your flows.
|
||||
|
||||
Native Langflow Components were created to be powerful tools that work around Langflow's features. They are designed to be easy to use and understand, and to help you build your flows faster.
|
||||
|
||||
Let's dive into Inputs and Outputs.
|
||||
|
||||
## Inputs
|
||||
|
||||
Inputs are components that are used to define where data comes into your flow. They can be used to receive data from the user, from a database, or from any other source that can be converted to Text or Record.
|
||||
|
||||
The difference between Chat Input and other Input components is the format of the output, the number of configurable fields, and the way they are displayed in the Playground.
|
||||
|
||||
Chat Input components can output Text or Record. When you want to pass the sender name, or sender to the next component, you can use the Record output, and when you want to pass the message only you can use the Text output. This is useful when saving the message to a database or a memory system like Zep.
|
||||
|
||||
You can find out more about it and the other Inputs [here](../components/inputs).
|
||||
|
||||
## Outputs
|
||||
|
||||
Outputs are components that are used to define where data comes out of your flow. They can be used to send data to the user, to the Playground, or to define how the data will be displayed in the Playground.
|
||||
|
||||
The Chat Output works similarly to the Chat Input but does not have a field that allows for written input. It is used as an Output definition and can be used to send data to the user.
|
||||
|
||||
You can find out more about it and the other Outputs [here](../components/outputs).
|
||||
|
|
@ -41,7 +41,7 @@ We have a special channel in our Discord server dedicated to Langflow 1.0 migrat
|
|||
|
||||
Langflow 1.0 introduces adds the concept of Inputs and Outputs to flows, allowing a clear definition of the data flow between components. Discover how to use Inputs and Outputs to pass data between components and create more dynamic flows.
|
||||
|
||||
[Learn more about Inputs and Outputs of Components](../migration/inputs-and-outputs)
|
||||
[Learn more about Inputs and Outputs of Components](../components/inputs-and-outputs)
|
||||
|
||||
## To Compose or Not to Compose: the choice is yours
|
||||
|
||||
|
|
@ -71,7 +71,7 @@ Langflow 1.0 introduces many new native categories, including Inputs, Outputs, H
|
|||
|
||||
With the introduction of Text and Record types connections between Components are more intuitive and easier to understand. This is the first step in a series of improvements to the way you interact with Langflow. Learn how to use Text, and Record and how they help you build better flows.
|
||||
|
||||
[Learn more about Text and Record](../migration/text-and-record)
|
||||
[Learn more about Text and Record](../components/text-and-record)
|
||||
|
||||
## CustomComponent for All Components
|
||||
|
||||
|
|
@ -119,7 +119,7 @@ Things got a whole lot easier. You can now pass tweaks and inputs in the API by
|
|||
|
||||
Global Variables can be used in any Text Field across your projects. Learn how to define and utilize Global Variables to streamline your workflow.
|
||||
|
||||
[Learn more about Global Variables](../migration/global-variables)
|
||||
[Learn more about Global Variables](../administration/global-env.mdx)
|
||||
|
||||
## Experimental Components
|
||||
|
||||
|
|
|
|||
|
|
@ -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.
|
||||
|
||||
|
|
|
|||
|
|
@ -1,45 +0,0 @@
|
|||
# Text and Record
|
||||
|
||||
In Langflow 1.0 we added two main input and output types: Text and Record. Text is a simple string input and output type, while Record is a structure very similar to a dictionary in Python. It is a key-value pair data structure.
|
||||
|
||||
We've created a few components to help you work with these types. Let's see how a few of them work.
|
||||
|
||||
### Records To Text
|
||||
|
||||
This is a Component that takes in Records and outputs a Text. It does this using a template string and concatenating the values of the Record, one per line.
|
||||
|
||||
If we have the following Records:
|
||||
|
||||
```json
|
||||
{
|
||||
"sender_name": "Alice",
|
||||
"message": "Hello!"
|
||||
}
|
||||
{
|
||||
"sender_name": "John",
|
||||
"message": "Hi!"
|
||||
}
|
||||
```
|
||||
|
||||
And the template string is: _`{sender_name}: {message}`_
|
||||
|
||||
```
|
||||
Alice: Hello!
|
||||
John: Hi!
|
||||
```
|
||||
|
||||
### Create Record
|
||||
|
||||
This Component allows you to create a Record from a number of inputs. You can add as many key-value pairs as you want (as long as it is less than 15 😅). Once you've picked that number you'll need to write the name of the Key and can pass Text values from other components to it.
|
||||
|
||||
### Documents To Records
|
||||
|
||||
This Component takes in a [LangChain](https://langchain.com) Document and outputs a Record. It does this by extracting the _`page_content`_ and the _`metadata`_ from the Document and adding them to the Record as _`text`_ and _`data`_ respectively.
|
||||
|
||||
## Why is this useful?
|
||||
|
||||
The idea was to create a unified way to work with complex data in Langflow, and to make it easier to work with data that is not just a simple string. This way you can create more complex workflows and use the data in more ways.
|
||||
|
||||
## What's next?
|
||||
|
||||
We are planning to integrate an array of modalities to Langflow, such as images, audio, and video. This will allow you to create even more complex workflows and use cases. Stay tuned for more updates! 🚀
|
||||
|
|
@ -14,12 +14,15 @@ This article demonstrates how to use Langflow's prompt tools to issue basic prom
|
|||
|
||||
## Prerequisites
|
||||
|
||||
* [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
- [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
|
||||
* [OpenAI API key created](https://platform.openai.com)
|
||||
- [OpenAI API key created](https://platform.openai.com)
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
## Create the basic prompting project
|
||||
|
|
@ -42,25 +45,21 @@ Examine the **Prompt** component. The **Template** field instructs the LLM to `A
|
|||
This should be interesting...
|
||||
|
||||
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
## Run the basic prompting flow
|
||||
|
||||
1. Click the **Run** button.
|
||||
The **Interaction Panel** opens, where you can converse with your bot.
|
||||
The **Interaction Panel** opens, where you can converse with your bot.
|
||||
2. Type a message and press Enter.
|
||||
The bot responds in a markedly piratical manner!
|
||||
The bot responds in a markedly piratical manner!
|
||||
|
||||
## Modify the prompt for a different result
|
||||
|
||||
1. To modify your prompt results, in the **Prompt** template, click the **Template** field.
|
||||
The **Edit Prompt** window opens.
|
||||
The **Edit Prompt** window opens.
|
||||
2. Change `Answer the user as if you were a pirate` to a different character, perhaps `Answer the user as if you were Harold Abelson.`
|
||||
3. Run the basic prompting flow again.
|
||||
The response will be markedly different.
|
||||
|
||||
|
||||
|
||||
|
||||
The response will be markedly different.
|
||||
|
|
|
|||
|
|
@ -10,12 +10,15 @@ Build a blog writer with OpenAI that uses URLs for reference content.
|
|||
|
||||
## Prerequisites
|
||||
|
||||
* [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
- [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
|
||||
* [OpenAI API key created](https://platform.openai.com)
|
||||
- [OpenAI API key created](https://platform.openai.com)
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
## Create the Blog Writer project
|
||||
|
|
@ -36,6 +39,7 @@ Build a blog writer with OpenAI that uses URLs for reference content.
|
|||
This flow creates a one-shot prompt flow with **Prompt**, **OpenAI**, and **Chat Output** components, and augments the flow with reference content and instructions from the **URL** and **Instructions** components.
|
||||
|
||||
The **Prompt** component's default **Template** field looks like this:
|
||||
|
||||
```bash
|
||||
Reference 1:
|
||||
|
||||
|
|
@ -59,16 +63,16 @@ The `{instructions}` value is received from the **Value** field of the **Instruc
|
|||
The `reference_1` and `reference_2` values are received from the **URL** fields of the **URL** components.
|
||||
|
||||
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
## Run the Blog Writer flow
|
||||
|
||||
1. Click the **Run** button.
|
||||
The **Interaction Panel** opens, where you can run your one-shot flow.
|
||||
The **Interaction Panel** opens, where you can run your one-shot flow.
|
||||
2. Click the **Lighting Bolt** icon to run your flow.
|
||||
3. The **OpenAI** component constructs a blog post with the **URL** items as context.
|
||||
The default **URL** values are for web pages at `promptingguide.ai`, so your blog post will be about prompting LLMs.
|
||||
The default **URL** values are for web pages at `promptingguide.ai`, so your blog post will be about prompting LLMs.
|
||||
|
||||
To write about something different, change the values in the **URL** components, and see what the LLM constructs.
|
||||
To write about something different, change the values in the **URL** components, and see what the LLM constructs.
|
||||
|
|
|
|||
|
|
@ -10,12 +10,15 @@ Build a question-and-answer chatbot with a document loaded from local memory.
|
|||
|
||||
## Prerequisites
|
||||
|
||||
* [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
- [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
|
||||
* [OpenAI API key created](https://platform.openai.com)
|
||||
- [OpenAI API key created](https://platform.openai.com)
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
## Create the Document QA project
|
||||
|
|
@ -39,24 +42,27 @@ The **Prompt** component is instructed to answer questions based on the contents
|
|||
Including a file with the prompt gives the **OpenAI** component context it may not otherwise have access to.
|
||||
|
||||
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
5. To select a document to load, in the **Files** component, click within the **Path** field.
|
||||
1. Select a local file, and then click **Open**.
|
||||
2. The file name appears in the field.
|
||||
<Admonition type="tip">
|
||||
The file must be of an extension type listed [here](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/base/data/utils.py#L13).
|
||||
</Admonition>
|
||||
1. Select a local file, and then click **Open**.
|
||||
2. The file name appears in the field.
|
||||
<Admonition type="tip">
|
||||
The file must be of an extension type listed
|
||||
[here](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/base/data/utils.py#L13).
|
||||
</Admonition>
|
||||
|
||||
## Run the Document QA flow
|
||||
|
||||
1. Click the **Run** button.
|
||||
The **Interaction Panel** opens, where you can converse with your bot.
|
||||
The **Interaction Panel** opens, where you can converse with your bot.
|
||||
2. Type a message and press Enter.
|
||||
For this example, we loaded an error log `.txt` file and asked, "What went wrong?"
|
||||
The bot responded:
|
||||
For this example, we loaded an error log `.txt` file and asked, "What went wrong?"
|
||||
The bot responded:
|
||||
|
||||
```
|
||||
The issue occurred during the execution of migrations in the application. Specifically, an error was raised by the Alembic library, indicating that new upgrade operations were detected that had not been accounted for in the existing migration scripts. The operation in question involved modifying the nullable property of a column (apikey, created_at) in the database, with details about the existing type (DATETIME()), existing server default, and other properties.
|
||||
```
|
||||
|
|
|
|||
|
|
@ -10,12 +10,15 @@ This flow extends the [basic prompting flow](./basic-prompting.mdx) to include c
|
|||
|
||||
## Prerequisites
|
||||
|
||||
* [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
- [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
|
||||
* [OpenAI API key created](https://platform.openai.com)
|
||||
- [OpenAI API key created](https://platform.openai.com)
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
## Create the memory chatbot project
|
||||
|
|
@ -43,16 +46,16 @@ This chatbot is augmented with the **Chat Memory** component, which stores messa
|
|||
The **Chat History** component gives the **OpenAI** component a memory of previous questions.
|
||||
|
||||
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
## Run the memory chatbot flow
|
||||
|
||||
1. Click the **Run** button.
|
||||
The **Interaction Panel** opens, where you can converse with your bot.
|
||||
The **Interaction Panel** opens, where you can converse with your bot.
|
||||
2. Type a message and press Enter.
|
||||
The bot will respond according to the template in the **Prompt** component.
|
||||
The bot will respond according to the template in the **Prompt** component.
|
||||
3. Type more questions. In the **Outputs** log, your queries are logged in order. Up to 5 queries are stored by default. Try asking `What is the first subject I asked you about?` to see where the LLM's memory disappears.
|
||||
|
||||
## Modify the Session ID field to have multiple conversations
|
||||
|
|
@ -65,11 +68,11 @@ You can demonstrate this by modifying the **Session ID** value to switch between
|
|||
|
||||
1. In the **Session ID** field of the **Chat Memory** and **Chat Input** components, change the **Session ID** value from `MySessionID` to `AnotherSessionID`.
|
||||
2. Click the **Run** button to run your flow.
|
||||
In the **Interaction Panel**, you will have a new conversation. (You may need to clear the cache with the **Eraser** button).
|
||||
In the **Interaction Panel**, you will have a new conversation. (You may need to clear the cache with the **Eraser** button).
|
||||
3. Type a few questions to your bot.
|
||||
4. In the **Session ID** field of the **Chat Memory** and **Chat Input** components, change the **Session ID** value back to `MySessionID`.
|
||||
5. Run your flow.
|
||||
The **Outputs** log of the **Interaction Panel** displays the history from your initial chat with `MySessionID`.
|
||||
The **Outputs** log of the **Interaction Panel** displays the history from your initial chat with `MySessionID`.
|
||||
|
||||
## Store Session ID as a Langflow variable
|
||||
|
||||
|
|
@ -79,4 +82,3 @@ To store **Session ID** as a Langflow variable, in the **Session ID** field, cli
|
|||
2. In the **Value** field, enter a value like `1B5EBD79-6E9C-4533-B2C8-7E4FF29E983B`.
|
||||
3. Click **Save Variable**.
|
||||
4. Apply this variable to **Chat Input**.
|
||||
|
||||
|
|
|
|||
|
|
@ -17,16 +17,19 @@ We've chosen [Astra DB](https://astra.datastax.com/signup?utm_source=langflow-pr
|
|||
## Prerequisites
|
||||
|
||||
<Admonition type="info">
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes.
|
||||
Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
|
||||
using this
|
||||
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
|
||||
to create your own Langflow workspace in minutes.
|
||||
</Admonition>
|
||||
|
||||
* [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
- [Langflow installed and running](../getting-started/install-langflow.mdx)
|
||||
|
||||
* [OpenAI API key](https://platform.openai.com)
|
||||
- [OpenAI API key](https://platform.openai.com)
|
||||
|
||||
* [An Astra DB vector database created](https://docs.datastax.com/en/astra-db-serverless/get-started/quickstart.html) with:
|
||||
* Application token (`AstraCS:WSnyFUhRxsrg…`)
|
||||
* API endpoint (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`)
|
||||
- [An Astra DB vector database created](https://docs.datastax.com/en/astra-db-serverless/get-started/quickstart.html) with:
|
||||
- Application token (`AstraCS:WSnyFUhRxsrg…`)
|
||||
- API endpoint (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`)
|
||||
|
||||
## Create the vector store RAG project
|
||||
|
||||
|
|
@ -49,38 +52,40 @@ The **ingestion** flow (bottom of the screen) populates the vector store with da
|
|||
It ingests data from a file (**File**), splits it into chunks (**Recursive Character Text Splitter**), indexes it in Astra DB (**Astra DB**), and computes embeddings for the chunks (**OpenAI Embeddings**).
|
||||
This forms a "brain" for the query flow.
|
||||
|
||||
The **query** flow (top of the screen) allows users to chat with the embedded vector store data. It's a little more complex:
|
||||
The **query** flow (top of the screen) allows users to chat with the embedded vector store data. It's a little more complex:
|
||||
|
||||
* **Chat Input** component defines where to put the user input coming from the Playground.
|
||||
* **OpenAI Embeddings** component generates embeddings from the user input.
|
||||
* **Astra DB Search** component retrieves the most relevant Records from the Astra DB database.
|
||||
* **Text Output** component turns the Records into Text by concatenating them and also displays it in the Playground.
|
||||
* **Prompt** component takes in the user input and the retrieved Records as text and builds a prompt for the OpenAI model.
|
||||
* **OpenAI** component generates a response to the prompt.
|
||||
* **Chat Output** component displays the response in the Playground.
|
||||
- **Chat Input** component defines where to put the user input coming from the Playground.
|
||||
- **OpenAI Embeddings** component generates embeddings from the user input.
|
||||
- **Astra DB Search** component retrieves the most relevant Records from the Astra DB database.
|
||||
- **Text Output** component turns the Records into Text by concatenating them and also displays it in the Playground.
|
||||
- **Prompt** component takes in the user input and the retrieved Records as text and builds a prompt for the OpenAI model.
|
||||
- **OpenAI** component generates a response to the prompt.
|
||||
- **Chat Output** component displays the response in the Playground.
|
||||
|
||||
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
4. To create environment variables for the **Astra DB** and **Astra DB Search** components:
|
||||
1. In the **Token** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
2. In the **Variable Name** field, enter `astra_token`.
|
||||
3. In the **Value** field, paste your Astra application token (`AstraCS:WSnyFUhRxsrg…`).
|
||||
4. Click **Save Variable**.
|
||||
5. Repeat the above steps for the **API Endpoint** field, pasting your Astra API Endpoint instead (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`).
|
||||
6. Add the global variable to both the **Astra DB** and **Astra DB Search** components.
|
||||
1. In the **Variable Name** field, enter `openai_api_key`.
|
||||
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
|
||||
3. Click **Save Variable**.
|
||||
|
||||
5. To create environment variables for the **Astra DB** and **Astra DB Search** components:
|
||||
1. In the **Token** field, click the **Globe** button, and then click **Add New Variable**.
|
||||
2. In the **Variable Name** field, enter `astra_token`.
|
||||
3. In the **Value** field, paste your Astra application token (`AstraCS:WSnyFUhRxsrg…`).
|
||||
4. Click **Save Variable**.
|
||||
5. Repeat the above steps for the **API Endpoint** field, pasting your Astra API Endpoint instead (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`).
|
||||
6. Add the global variable to both the **Astra DB** and **Astra DB Search** components.
|
||||
|
||||
## Run the vector store RAG flow
|
||||
|
||||
1. Click the **Playground** button.
|
||||
The **Playground** opens, where you can chat with your data.
|
||||
The **Playground** opens, where you can chat with your data.
|
||||
2. Type a message and press Enter. (Try something like "What topics do you know about?")
|
||||
3. The bot will respond with a summary of the data you've embedded.
|
||||
|
||||
For example, we embedded a PDF of an engine maintenance manual and asked, "How do I change the oil?"
|
||||
The bot responds:
|
||||
|
||||
```
|
||||
To change the oil in the engine, follow these steps:
|
||||
|
||||
|
|
@ -102,7 +107,3 @@ You should use a 3/8 inch wrench to remove the oil drain cap.
|
|||
```
|
||||
|
||||
This is the size the engine manual lists as well. This confirms our flow works, because the query returns the unique knowledge we embedded from the Astra vector store.
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -41,7 +41,7 @@ By having a clear definition of Inputs and Outputs, we could build the experienc
|
|||
When building a project testing and debugging is crucial. The Playground is a tool that changes dynamically based on the Inputs and Outputs you defined in your project.
|
||||
|
||||
For example, let's say you are building a simple RAG application. Generally, you have an Input, some references that come from a Vector Store Search, a Prompt and the answer.
|
||||
Now, you could plug the output of your Prompt into a [Text Output](../components/outputs#Text-Output), rename that to "Prompt Result" and see the output of your Prompt in the Playground.
|
||||
Now, you could plug the output of your Prompt into a [Text Output](../components/inputs-and-outputs), rename that to "Prompt Result" and see the output of your Prompt in the Playground.
|
||||
|
||||
{/* Add image here of the described above */}
|
||||
|
||||
|
|
|
|||
|
|
@ -49,8 +49,8 @@ module.exports = {
|
|||
label: "Core Components",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"components/inputs",
|
||||
"components/outputs",
|
||||
"components/inputs-and-outputs",
|
||||
"components/text-and-record",
|
||||
"components/data",
|
||||
"components/models",
|
||||
"components/helpers",
|
||||
|
|
@ -91,15 +91,12 @@ module.exports = {
|
|||
},
|
||||
{
|
||||
type: "category",
|
||||
label: "Migration Guides",
|
||||
label: "Migration",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"migration/possible-installation-issues",
|
||||
"migration/migrating-to-one-point-zero",
|
||||
"migration/inputs-and-outputs",
|
||||
"migration/text-and-record",
|
||||
"migration/compatibility",
|
||||
"migration/global-variables",
|
||||
],
|
||||
},
|
||||
{
|
||||
|
|
|
|||
6504
docs/static/data/AstraDB-RAG-Flows.json
vendored
6504
docs/static/data/AstraDB-RAG-Flows.json
vendored
File diff suppressed because one or more lines are too long
882
docs/static/json_files/Notion_Components_bundle.json
vendored
882
docs/static/json_files/Notion_Components_bundle.json
vendored
File diff suppressed because one or more lines are too long
122
poetry.lock
generated
122
poetry.lock
generated
|
|
@ -471,17 +471,17 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "boto3"
|
||||
version = "1.34.117"
|
||||
version = "1.34.116"
|
||||
description = "The AWS SDK for Python"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "boto3-1.34.117-py3-none-any.whl", hash = "sha256:1506589e30566bbb2f4997b60968ff7d4ef8a998836c31eedd36437ac3b7408a"},
|
||||
{file = "boto3-1.34.117.tar.gz", hash = "sha256:c8a383b904d6faaf7eed0c06e31b423db128e4c09ce7bd2afc39d1cd07030a51"},
|
||||
{file = "boto3-1.34.116-py3-none-any.whl", hash = "sha256:e7f5ab2d1f1b90971a2b9369760c2c6bae49dae98c084a5c3f5c78e3968ace15"},
|
||||
{file = "boto3-1.34.116.tar.gz", hash = "sha256:53cb8aeb405afa1cd2b25421e27a951aeb568026675dec020587861fac96ac87"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
botocore = ">=1.34.117,<1.35.0"
|
||||
botocore = ">=1.34.116,<1.35.0"
|
||||
jmespath = ">=0.7.1,<2.0.0"
|
||||
s3transfer = ">=0.10.0,<0.11.0"
|
||||
|
||||
|
|
@ -490,13 +490,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
|
|||
|
||||
[[package]]
|
||||
name = "botocore"
|
||||
version = "1.34.117"
|
||||
version = "1.34.116"
|
||||
description = "Low-level, data-driven core of boto 3."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "botocore-1.34.117-py3-none-any.whl", hash = "sha256:26a431997f882bcdd1e835f44c24b2a1752b1c4e5183c2ce62999ce95d518d6c"},
|
||||
{file = "botocore-1.34.117.tar.gz", hash = "sha256:4637ca42e6c51aebc4d9a2d92f97bf4bdb042e3f7985ff31a659a11e4c170e73"},
|
||||
{file = "botocore-1.34.116-py3-none-any.whl", hash = "sha256:ec4d42c816e9b2d87a2439ad277e7dda16a4a614ef6839cf66f4c1a58afa547c"},
|
||||
{file = "botocore-1.34.116.tar.gz", hash = "sha256:269cae7ba99081519a9f87d7298e238d9e68ba94eb4f8ddfa906224c34cb8b6c"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2882,13 +2882,13 @@ grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
|
|||
|
||||
[[package]]
|
||||
name = "gotrue"
|
||||
version = "2.4.3"
|
||||
version = "2.4.2"
|
||||
description = "Python Client Library for Supabase Auth"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8"
|
||||
files = [
|
||||
{file = "gotrue-2.4.3-py3-none-any.whl", hash = "sha256:1e1679890c6a7bbfb10999b817e134d593dec4f7ff2ea05d48a78c2f384355ed"},
|
||||
{file = "gotrue-2.4.3.tar.gz", hash = "sha256:f93953654408aa35230317c1670ae1435e01ee5a461f2bfbc541fafd59b99c6b"},
|
||||
{file = "gotrue-2.4.2-py3-none-any.whl", hash = "sha256:64cd40933d1f0a5d5cc4f4bd93bc51d730b94812447b6600f774790a4901e455"},
|
||||
{file = "gotrue-2.4.2.tar.gz", hash = "sha256:e100745161f1c58dd05b9c1ef8bcd4cd78cdfb38d8d2c253ade63143a3dc6aeb"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4058,19 +4058,19 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "langchain-anthropic"
|
||||
version = "0.1.15"
|
||||
version = "0.1.13"
|
||||
description = "An integration package connecting AnthropicMessages and LangChain"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_anthropic-0.1.15-py3-none-any.whl", hash = "sha256:7cceea526f473e4d514f39295dc128eec57da628a4bbb54850d11dda7aa959fc"},
|
||||
{file = "langchain_anthropic-0.1.15.tar.gz", hash = "sha256:c5c3c6eaccb11ed99a63886e50873ac21eaf8e9441e0f75c7ae7cd8cdef65155"},
|
||||
{file = "langchain_anthropic-0.1.13-py3-none-any.whl", hash = "sha256:121f6f480da7685c239573d98322adb94fe486d40651ac341637f65da36881de"},
|
||||
{file = "langchain_anthropic-0.1.13.tar.gz", hash = "sha256:32e7ac51e1874c47e1a20493e75f5bfc88b0ffeaf5f1aed6091547e1ae44bb85"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
anthropic = ">=0.28.0,<1"
|
||||
anthropic = ">=0.26.0,<1"
|
||||
defusedxml = ">=0.7.1,<0.8.0"
|
||||
langchain-core = ">=0.2.2rc1,<0.3"
|
||||
langchain-core = ">=0.1.43,<0.3"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-astradb"
|
||||
|
|
@ -4322,7 +4322,7 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "langflow-base"
|
||||
version = "0.0.55"
|
||||
version = "0.0.54"
|
||||
description = "A Python package with a built-in web application"
|
||||
optional = false
|
||||
python-versions = ">=3.10,<3.13"
|
||||
|
|
@ -4365,7 +4365,7 @@ rich = "^13.7.0"
|
|||
sqlmodel = "^0.0.18"
|
||||
typer = "^0.12.0"
|
||||
uncurl = "^0.0.11"
|
||||
uvicorn = "^0.30.0"
|
||||
uvicorn = "^0.29.0"
|
||||
websockets = "*"
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -4419,13 +4419,13 @@ requests = ">=2,<3"
|
|||
|
||||
[[package]]
|
||||
name = "litellm"
|
||||
version = "1.40.0"
|
||||
version = "1.39.5"
|
||||
description = "Library to easily interface with LLM API providers"
|
||||
optional = false
|
||||
python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
|
||||
files = [
|
||||
{file = "litellm-1.40.0-py3-none-any.whl", hash = "sha256:c3055767ae144585699fdb07b3ad678e66738c2eff19abd7761c8fe22d6e636f"},
|
||||
{file = "litellm-1.40.0.tar.gz", hash = "sha256:12b4c0ad850ede5aebdb2f48e3a8e898efb25df5bc915ff89929ad963cb92f54"},
|
||||
{file = "litellm-1.39.5-py3-none-any.whl", hash = "sha256:1e8dd43c5d257fa8d7a0039b20aed7aeed4463d53608d1ba4ac233f1967a5330"},
|
||||
{file = "litellm-1.39.5.tar.gz", hash = "sha256:8f4ea9fe21d67890e81a578e12c30b4172260ff35971dc7c3edf7eb69167d3be"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -6182,13 +6182,13 @@ tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "p
|
|||
|
||||
[[package]]
|
||||
name = "postgrest"
|
||||
version = "0.16.7"
|
||||
version = "0.16.4"
|
||||
description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8"
|
||||
files = [
|
||||
{file = "postgrest-0.16.7-py3-none-any.whl", hash = "sha256:0727dbdbc4e00fd98244596812e7dba6261019f3ec09138be291479a76d9fe99"},
|
||||
{file = "postgrest-0.16.7.tar.gz", hash = "sha256:779e20bd34f3c14e1e99129407612f85d7bb1d80b5cee2f54e50194b4488c658"},
|
||||
{file = "postgrest-0.16.4-py3-none-any.whl", hash = "sha256:304425381eb38e31018832a524943d7d1f07687be80c3c7397d8ae69ca56cb88"},
|
||||
{file = "postgrest-0.16.4.tar.gz", hash = "sha256:e16973155be1464101d18a51cc060707cd177b918f4b01ea8afa51746ca870ef"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -6834,17 +6834,17 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
|
|||
|
||||
[[package]]
|
||||
name = "pydantic-settings"
|
||||
version = "2.3.0"
|
||||
version = "2.2.1"
|
||||
description = "Settings management using Pydantic"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "pydantic_settings-2.3.0-py3-none-any.whl", hash = "sha256:26eeed27370a9c5e3f64e4a7d6602573cbedf05ed940f1d5b11c3f178427af7a"},
|
||||
{file = "pydantic_settings-2.3.0.tar.gz", hash = "sha256:78db28855a71503cfe47f39500a1dece523c640afd5280edb5c5c9c9cfa534c9"},
|
||||
{file = "pydantic_settings-2.2.1-py3-none-any.whl", hash = "sha256:0235391d26db4d2190cb9b31051c4b46882d28a51533f97440867f012d4da091"},
|
||||
{file = "pydantic_settings-2.2.1.tar.gz", hash = "sha256:00b9f6a5e95553590434c0fa01ead0b216c3e10bc54ae02e37f359948643c5ed"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
pydantic = ">=2.7.0"
|
||||
pydantic = ">=2.3.0"
|
||||
python-dotenv = ">=0.21.0"
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -7763,28 +7763,28 @@ pyasn1 = ">=0.1.3"
|
|||
|
||||
[[package]]
|
||||
name = "ruff"
|
||||
version = "0.4.7"
|
||||
version = "0.4.6"
|
||||
description = "An extremely fast Python linter and code formatter, written in Rust."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "ruff-0.4.7-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:e089371c67892a73b6bb1525608e89a2aca1b77b5440acf7a71dda5dac958f9e"},
|
||||
{file = "ruff-0.4.7-py3-none-macosx_11_0_arm64.whl", hash = "sha256:10f973d521d910e5f9c72ab27e409e839089f955be8a4c8826601a6323a89753"},
|
||||
{file = "ruff-0.4.7-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:59c3d110970001dfa494bcd95478e62286c751126dfb15c3c46e7915fc49694f"},
|
||||
{file = "ruff-0.4.7-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fa9773c6c00f4958f73b317bc0fd125295110c3776089f6ef318f4b775f0abe4"},
|
||||
{file = "ruff-0.4.7-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:07fc80bbb61e42b3b23b10fda6a2a0f5a067f810180a3760c5ef1b456c21b9db"},
|
||||
{file = "ruff-0.4.7-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:fa4dafe3fe66d90e2e2b63fa1591dd6e3f090ca2128daa0be33db894e6c18648"},
|
||||
{file = "ruff-0.4.7-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a7c0083febdec17571455903b184a10026603a1de078428ba155e7ce9358c5f6"},
|
||||
{file = "ruff-0.4.7-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ad1b20e66a44057c326168437d680a2166c177c939346b19c0d6b08a62a37589"},
|
||||
{file = "ruff-0.4.7-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cbf5d818553add7511c38b05532d94a407f499d1a76ebb0cad0374e32bc67202"},
|
||||
{file = "ruff-0.4.7-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:50e9651578b629baec3d1513b2534de0ac7ed7753e1382272b8d609997e27e83"},
|
||||
{file = "ruff-0.4.7-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:8874a9df7766cb956b218a0a239e0a5d23d9e843e4da1e113ae1d27ee420877a"},
|
||||
{file = "ruff-0.4.7-py3-none-musllinux_1_2_i686.whl", hash = "sha256:b9de9a6e49f7d529decd09381c0860c3f82fa0b0ea00ea78409b785d2308a567"},
|
||||
{file = "ruff-0.4.7-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:13a1768b0691619822ae6d446132dbdfd568b700ecd3652b20d4e8bc1e498f78"},
|
||||
{file = "ruff-0.4.7-py3-none-win32.whl", hash = "sha256:769e5a51df61e07e887b81e6f039e7ed3573316ab7dd9f635c5afaa310e4030e"},
|
||||
{file = "ruff-0.4.7-py3-none-win_amd64.whl", hash = "sha256:9e3ab684ad403a9ed1226894c32c3ab9c2e0718440f6f50c7c5829932bc9e054"},
|
||||
{file = "ruff-0.4.7-py3-none-win_arm64.whl", hash = "sha256:10f2204b9a613988e3484194c2c9e96a22079206b22b787605c255f130db5ed7"},
|
||||
{file = "ruff-0.4.7.tar.gz", hash = "sha256:2331d2b051dc77a289a653fcc6a42cce357087c5975738157cd966590b18b5e1"},
|
||||
{file = "ruff-0.4.6-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:ef995583a038cd4a7edf1422c9e19118e2511b8ba0b015861b4abd26ec5367c5"},
|
||||
{file = "ruff-0.4.6-py3-none-macosx_11_0_arm64.whl", hash = "sha256:602ebd7ad909eab6e7da65d3c091547781bb06f5f826974a53dbe563d357e53c"},
|
||||
{file = "ruff-0.4.6-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3f9ced5cbb7510fd7525448eeb204e0a22cabb6e99a3cb160272262817d49786"},
|
||||
{file = "ruff-0.4.6-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:04a80acfc862e0e1630c8b738e70dcca03f350bad9e106968a8108379e12b31f"},
|
||||
{file = "ruff-0.4.6-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:be47700ecb004dfa3fd4dcdddf7322d4e632de3c06cd05329d69c45c0280e618"},
|
||||
{file = "ruff-0.4.6-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:1ff930d6e05f444090a0139e4e13e1e2e1f02bd51bb4547734823c760c621e79"},
|
||||
{file = "ruff-0.4.6-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f13410aabd3b5776f9c5699f42b37a3a348d65498c4310589bc6e5c548dc8a2f"},
|
||||
{file = "ruff-0.4.6-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0cf5cc02d3ae52dfb0c8a946eb7a1d6ffe4d91846ffc8ce388baa8f627e3bd50"},
|
||||
{file = "ruff-0.4.6-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ea3424793c29906407e3cf417f28fc33f689dacbbadfb52b7e9a809dd535dcef"},
|
||||
{file = "ruff-0.4.6-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:1fa8561489fadf483ffbb091ea94b9c39a00ed63efacd426aae2f197a45e67fc"},
|
||||
{file = "ruff-0.4.6-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:4d5b914818d8047270308fe3e85d9d7f4a31ec86c6475c9f418fbd1624d198e0"},
|
||||
{file = "ruff-0.4.6-py3-none-musllinux_1_2_i686.whl", hash = "sha256:4f02284335c766678778475e7698b7ab83abaf2f9ff0554a07b6f28df3b5c259"},
|
||||
{file = "ruff-0.4.6-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:3a6a0a4f4b5f54fff7c860010ab3dd81425445e37d35701a965c0248819dde7a"},
|
||||
{file = "ruff-0.4.6-py3-none-win32.whl", hash = "sha256:9018bf59b3aa8ad4fba2b1dc0299a6e4e60a4c3bc62bbeaea222679865453062"},
|
||||
{file = "ruff-0.4.6-py3-none-win_amd64.whl", hash = "sha256:a769ae07ac74ff1a019d6bd529426427c3e30d75bdf1e08bb3d46ac8f417326a"},
|
||||
{file = "ruff-0.4.6-py3-none-win_arm64.whl", hash = "sha256:735a16407a1a8f58e4c5b913ad6102722e80b562dd17acb88887685ff6f20cf6"},
|
||||
{file = "ruff-0.4.6.tar.gz", hash = "sha256:a797a87da50603f71e6d0765282098245aca6e3b94b7c17473115167d8dfb0b7"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -9013,13 +9013,13 @@ types-pyOpenSSL = "*"
|
|||
|
||||
[[package]]
|
||||
name = "types-requests"
|
||||
version = "2.32.0.20240602"
|
||||
version = "2.32.0.20240523"
|
||||
description = "Typing stubs for requests"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "types-requests-2.32.0.20240602.tar.gz", hash = "sha256:3f98d7bbd0dd94ebd10ff43a7fbe20c3b8528acace6d8efafef0b6a184793f06"},
|
||||
{file = "types_requests-2.32.0.20240602-py3-none-any.whl", hash = "sha256:ed3946063ea9fbc6b5fc0c44fa279188bae42d582cb63760be6cb4b9d06c3de8"},
|
||||
{file = "types-requests-2.32.0.20240523.tar.gz", hash = "sha256:26b8a6de32d9f561192b9942b41c0ab2d8010df5677ca8aa146289d11d505f57"},
|
||||
{file = "types_requests-2.32.0.20240523-py3-none-any.whl", hash = "sha256:f19ed0e2daa74302069bbbbf9e82902854ffa780bc790742a810a9aaa52f65ec"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -9038,13 +9038,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.12.1"
|
||||
version = "4.12.0"
|
||||
description = "Backported and Experimental Type Hints for Python 3.8+"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "typing_extensions-4.12.1-py3-none-any.whl", hash = "sha256:6024b58b69089e5a89c347397254e35f1bf02a907728ec7fee9bf0fe837d203a"},
|
||||
{file = "typing_extensions-4.12.1.tar.gz", hash = "sha256:915f5e35ff76f56588223f15fdd5938f9a1cf9195c0de25130c627e4d597f6d1"},
|
||||
{file = "typing_extensions-4.12.0-py3-none-any.whl", hash = "sha256:b349c66bea9016ac22978d800cfff206d5f9816951f12a7d0ec5578b0a819594"},
|
||||
{file = "typing_extensions-4.12.0.tar.gz", hash = "sha256:8cbcdc8606ebcb0d95453ad7dc5065e6237b6aa230a31e81d0f440c30fed5fd8"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -9230,13 +9230,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "uvicorn"
|
||||
version = "0.30.1"
|
||||
version = "0.29.0"
|
||||
description = "The lightning-fast ASGI server."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "uvicorn-0.30.1-py3-none-any.whl", hash = "sha256:cd17daa7f3b9d7a24de3617820e634d0933b69eed8e33a516071174427238c81"},
|
||||
{file = "uvicorn-0.30.1.tar.gz", hash = "sha256:d46cd8e0fd80240baffbcd9ec1012a712938754afcf81bce56c024c1656aece8"},
|
||||
{file = "uvicorn-0.29.0-py3-none-any.whl", hash = "sha256:2c2aac7ff4f4365c206fd773a39bf4ebd1047c238f8b8268ad996829323473de"},
|
||||
{file = "uvicorn-0.29.0.tar.gz", hash = "sha256:6a69214c0b6a087462412670b3ef21224fa48cae0e452b5883e8e8bdfdd11dd0"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -9300,13 +9300,13 @@ test = ["Cython (>=0.29.36,<0.30.0)", "aiohttp (==3.9.0b0)", "aiohttp (>=3.8.1)"
|
|||
|
||||
[[package]]
|
||||
name = "validators"
|
||||
version = "0.28.3"
|
||||
version = "0.28.1"
|
||||
description = "Python Data Validation for Humans™"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "validators-0.28.3-py3-none-any.whl", hash = "sha256:53cafa854f13850156259d9cc479b864ee901f6a96e6b109e6fc33f98f37d99f"},
|
||||
{file = "validators-0.28.3.tar.gz", hash = "sha256:c6c79840bcde9ba77b19f6218f7738188115e27830cbaff43264bc4ed24c429d"},
|
||||
{file = "validators-0.28.1-py3-none-any.whl", hash = "sha256:890c98789ad884037f059af6ea915ec2d667129d509180c2c590b8009a4c4219"},
|
||||
{file = "validators-0.28.1.tar.gz", hash = "sha256:5ac88e7916c3405f0ce38ac2ac82a477fcf4d90dbbeddd04c8193171fc17f7dc"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -9454,13 +9454,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "weaviate-client"
|
||||
version = "4.6.4"
|
||||
version = "4.6.3"
|
||||
description = "A python native Weaviate client"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "weaviate_client-4.6.4-py3-none-any.whl", hash = "sha256:19b76fb923a5f0b6fcb7471ef3cd990d2791ede71731e53429e1066a9dbf2af2"},
|
||||
{file = "weaviate_client-4.6.4.tar.gz", hash = "sha256:5378db8a33bf1d48adff3f9efa572d9fb04eaeb36444817cab56f1ba3c595500"},
|
||||
{file = "weaviate_client-4.6.3-py3-none-any.whl", hash = "sha256:b2921f9aea84a4eccb1c75d55dd2857a87241e5536540fb96ffdf4737ed4fe8a"},
|
||||
{file = "weaviate_client-4.6.3.tar.gz", hash = "sha256:a6e638f746f91c310fe6680cffa77949718f17d8b40b966f7037028cacfd94e0"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -9471,7 +9471,7 @@ grpcio-tools = ">=1.57.0,<2.0.0"
|
|||
httpx = ">=0.25.0,<=0.27.0"
|
||||
pydantic = ">=2.5.0,<3.0.0"
|
||||
requests = ">=2.30.0,<3.0.0"
|
||||
validators = "0.28.3"
|
||||
validators = "0.28.1"
|
||||
|
||||
[[package]]
|
||||
name = "websocket-client"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow"
|
||||
version = "1.0.0a44"
|
||||
version = "1.0.0a43"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Langflow <contact@langflow.org>"]
|
||||
maintainers = [
|
||||
|
|
@ -140,7 +140,7 @@ testpaths = ["tests", "integration"]
|
|||
console_output_style = "progress"
|
||||
filterwarnings = ["ignore::DeprecationWarning"]
|
||||
log_cli = true
|
||||
markers = ["async_test", "api_key_required"]
|
||||
markers = ["async_test"]
|
||||
|
||||
|
||||
[tool.ruff]
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
import os
|
||||
import argparse
|
||||
|
||||
from huggingface_hub import HfApi, list_models
|
||||
from rich import print
|
||||
|
|
@ -6,11 +6,27 @@ from rich import print
|
|||
# Use root method
|
||||
models = list_models()
|
||||
|
||||
args = argparse.ArgumentParser(description="Restart a space in the Hugging Face Hub.")
|
||||
args.add_argument("--space", type=str, help="The space to restart.")
|
||||
args.add_argument("--token", type=str, help="The Hugging Face API token.")
|
||||
|
||||
parsed_args = args.parse_args()
|
||||
|
||||
space = parsed_args.space
|
||||
|
||||
if not space:
|
||||
print("Please provide a space to restart.")
|
||||
exit()
|
||||
|
||||
if not parsed_args.token:
|
||||
print("Please provide an API token.")
|
||||
exit()
|
||||
|
||||
# Or configure a HfApi client
|
||||
hf_api = HfApi(
|
||||
endpoint="https://huggingface.co", # Can be a Private Hub endpoint.
|
||||
token=os.getenv("HUGGINFACE_API_TOKEN"),
|
||||
token=parsed_args.token,
|
||||
)
|
||||
|
||||
space_runtime = hf_api.restart_space("Langflow/Langflow-Preview", factory_reboot=True)
|
||||
space_runtime = hf_api.restart_space(space, factory_reboot=True)
|
||||
print(space_runtime)
|
||||
|
|
|
|||
|
|
@ -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 |
|
||||
| ------------------ | --------------------- | ---------------------- | ------------------------------ | ------------------------------- | -------------------------------------------------------------------------- |
|
||||
|
|
|
|||
|
|
@ -121,7 +121,7 @@ def run(
|
|||
),
|
||||
):
|
||||
"""
|
||||
Run the Langflow.
|
||||
Run Langflow.
|
||||
"""
|
||||
|
||||
configure(log_level=log_level, log_file=log_file)
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ from loguru import logger
|
|||
from sqlmodel import Session, col, select
|
||||
|
||||
from langflow.api.utils import remove_api_keys, validate_is_component
|
||||
from langflow.api.v1.schemas import FlowListCreate, FlowListIds, FlowListRead
|
||||
from langflow.api.v1.schemas import FlowListCreate, FlowListRead
|
||||
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 import Flow, FlowCreate, FlowRead, FlowUpdate
|
||||
|
|
@ -258,9 +258,9 @@ async def download_file(
|
|||
return FlowListRead(flows=flows)
|
||||
|
||||
|
||||
@router.post("/multiple_delete/")
|
||||
@router.delete("/")
|
||||
async def delete_multiple_flows(
|
||||
flow_ids: FlowListIds, user: User = Depends(get_current_active_user), db: Session = Depends(get_session)
|
||||
flow_ids: List[UUID], user: User = Depends(get_current_active_user), db: Session = Depends(get_session)
|
||||
):
|
||||
"""
|
||||
Delete multiple flows by their IDs.
|
||||
|
|
@ -274,9 +274,7 @@ async def delete_multiple_flows(
|
|||
|
||||
"""
|
||||
try:
|
||||
deleted_flows = db.exec(
|
||||
select(Flow).where(col(Flow.id).in_(flow_ids.flow_ids)).where(Flow.user_id == user.id)
|
||||
).all()
|
||||
deleted_flows = db.exec(select(Flow).where(col(Flow.id).in_(flow_ids)).where(Flow.user_id == user.id)).all()
|
||||
for flow in deleted_flows:
|
||||
db.delete(flow)
|
||||
db.commit()
|
||||
|
|
|
|||
|
|
@ -1,9 +1,10 @@
|
|||
from typing import List, Optional
|
||||
|
||||
from uuid import UUID
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
|
||||
from langflow.services.deps import get_monitor_service
|
||||
from langflow.services.monitor.schema import (
|
||||
MessageModelRequest,
|
||||
MessageModelResponse,
|
||||
TransactionModelResponse,
|
||||
VertexBuildMapModel,
|
||||
|
|
@ -66,6 +67,44 @@ async def get_messages(
|
|||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.delete("/messages", status_code=204)
|
||||
async def delete_messages(
|
||||
message_ids: List[int],
|
||||
monitor_service: MonitorService = Depends(get_monitor_service),
|
||||
):
|
||||
try:
|
||||
monitor_service.delete_messages(message_ids=message_ids)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.post("/messages/{message_id}", response_model=MessageModelResponse)
|
||||
async def update_message(
|
||||
message_id: str,
|
||||
message: MessageModelRequest,
|
||||
monitor_service: MonitorService = Depends(get_monitor_service),
|
||||
):
|
||||
try:
|
||||
message_dict = message.model_dump(exclude_none=True)
|
||||
message_dict.pop("index", None)
|
||||
monitor_service.update_message(message_id=message_id, **message_dict)
|
||||
return MessageModelResponse(index=message_id, **message_dict)
|
||||
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.delete("/messages/session/{session_id}", status_code=204)
|
||||
async def delete_messages_session(
|
||||
session_id: str,
|
||||
monitor_service: MonitorService = Depends(get_monitor_service),
|
||||
):
|
||||
try:
|
||||
monitor_service.delete_messages_session(session_id=session_id)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.get("/transactions", response_model=List[TransactionModelResponse])
|
||||
async def get_transactions(
|
||||
source: Optional[str] = Query(None),
|
||||
|
|
|
|||
|
|
@ -15,10 +15,25 @@ import shlex
|
|||
from collections import OrderedDict, namedtuple
|
||||
from http.cookies import SimpleCookie
|
||||
|
||||
from uncurl.api import parser # type: ignore
|
||||
|
||||
parser.add_argument("-x", "--proxy", default={})
|
||||
parser.add_argument("-U", "--proxy-user", default="")
|
||||
ParsedArgs = namedtuple(
|
||||
"ParsedContext",
|
||||
[
|
||||
"command",
|
||||
"url",
|
||||
"data",
|
||||
"data_binary",
|
||||
"method",
|
||||
"headers",
|
||||
"compressed",
|
||||
"insecure",
|
||||
"user",
|
||||
"include",
|
||||
"silent",
|
||||
"proxy",
|
||||
"proxy_user",
|
||||
"cookies",
|
||||
],
|
||||
)
|
||||
|
||||
ParsedContext = namedtuple("ParsedContext", ["method", "url", "data", "headers", "cookies", "verify", "auth", "proxy"])
|
||||
|
||||
|
|
@ -27,24 +42,89 @@ def normalize_newlines(multiline_text):
|
|||
return multiline_text.replace(" \\\n", " ")
|
||||
|
||||
|
||||
def parse_curl_command(curl_command):
|
||||
tokens = shlex.split(normalize_newlines(curl_command))
|
||||
tokens = [token for token in tokens if token and token != " "]
|
||||
if "curl" not in tokens[0]:
|
||||
raise ValueError("Invalid curl command")
|
||||
args_template = {
|
||||
"command": None,
|
||||
"url": None,
|
||||
"data": None,
|
||||
"data_binary": None,
|
||||
"method": "get",
|
||||
"headers": [],
|
||||
"compressed": False,
|
||||
"insecure": False,
|
||||
"user": (),
|
||||
"include": False,
|
||||
"silent": False,
|
||||
"proxy": None,
|
||||
"proxy_user": None,
|
||||
"cookies": {},
|
||||
}
|
||||
args = args_template.copy()
|
||||
|
||||
i = 0
|
||||
while i < len(tokens):
|
||||
token = tokens[i]
|
||||
if token == "-X":
|
||||
i += 1
|
||||
args["method"] = tokens[i].lower()
|
||||
elif token in ("-d", "--data"):
|
||||
i += 1
|
||||
args["data"] = tokens[i]
|
||||
args["method"] = "post"
|
||||
elif token in ("-b", "--data-binary", "--data-raw"):
|
||||
i += 1
|
||||
args["data_binary"] = tokens[i]
|
||||
args["method"] = "post"
|
||||
elif token in ("-H", "--header"):
|
||||
i += 1
|
||||
args["headers"].append(tokens[i])
|
||||
elif token == "--compressed":
|
||||
args["compressed"] = True
|
||||
elif token in ("-k", "--insecure"):
|
||||
args["insecure"] = True
|
||||
elif token in ("-u", "--user"):
|
||||
i += 1
|
||||
args["user"] = tuple(tokens[i].split(":"))
|
||||
elif token in ("-I", "--include"):
|
||||
args["include"] = True
|
||||
elif token in ("-s", "--silent"):
|
||||
args["silent"] = True
|
||||
elif token in ("-x", "--proxy"):
|
||||
i += 1
|
||||
args["proxy"] = tokens[i]
|
||||
elif token in ("-U", "--proxy-user"):
|
||||
i += 1
|
||||
args["proxy_user"] = tokens[i]
|
||||
elif not token.startswith("-"):
|
||||
if args["command"] is None:
|
||||
args["command"] = token
|
||||
else:
|
||||
args["url"] = token
|
||||
i += 1
|
||||
|
||||
return ParsedArgs(**args)
|
||||
|
||||
|
||||
def parse_context(curl_command):
|
||||
method = "get"
|
||||
|
||||
tokens = shlex.split(normalize_newlines(curl_command))
|
||||
tokens = [token for token in tokens if token and token != " "]
|
||||
parsed_args = parser.parse_args(tokens)
|
||||
parsed_args: ParsedArgs = parse_curl_command(curl_command)
|
||||
|
||||
post_data = parsed_args.data or parsed_args.data_binary
|
||||
if post_data:
|
||||
method = "post"
|
||||
|
||||
if parsed_args.X:
|
||||
method = parsed_args.X.lower()
|
||||
if parsed_args.method:
|
||||
method = parsed_args.method.lower()
|
||||
|
||||
cookie_dict = OrderedDict()
|
||||
quoted_headers = OrderedDict()
|
||||
|
||||
for curl_header in parsed_args.header:
|
||||
for curl_header in parsed_args.headers:
|
||||
if curl_header.startswith(":"):
|
||||
occurrence = [m.start() for m in re.finditer(":", curl_header)]
|
||||
header_key, header_value = curl_header[: occurrence[1]], curl_header[occurrence[1] + 1 :]
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@ import xml.etree.ElementTree as ET
|
|||
from concurrent import futures
|
||||
from pathlib import Path
|
||||
from typing import Callable, List, Optional, Text
|
||||
|
||||
import chardet
|
||||
import yaml
|
||||
|
||||
from langflow.schema.schema import Record
|
||||
|
|
@ -89,7 +89,12 @@ def retrieve_file_paths(
|
|||
|
||||
|
||||
def read_text_file(file_path: str) -> str:
|
||||
with open(file_path, "r") as f:
|
||||
with open(file_path, "rb") as f:
|
||||
raw_data = f.read()
|
||||
result = chardet.detect(raw_data)
|
||||
encoding = result['encoding']
|
||||
|
||||
with open(file_path, "r", encoding=encoding) as f:
|
||||
return f.read()
|
||||
|
||||
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load diff
File diff suppressed because it is too large
Load diff
File diff suppressed because it is too large
Load diff
File diff suppressed because it is too large
Load diff
File diff suppressed because it is too large
Load diff
File diff suppressed because one or more lines are too long
|
|
@ -1,3 +1,4 @@
|
|||
from .load import load_flow_from_json, run_flow_from_json # noqa: F401
|
||||
from .load import load_flow_from_json, run_flow_from_json
|
||||
from .utils import upload_file, get_flow
|
||||
|
||||
__all__ = ["load_flow_from_json", "run_flow_from_json"]
|
||||
__all__ = ["load_flow_from_json", "run_flow_from_json", "upload_file", "get_flow"]
|
||||
|
|
|
|||
89
src/backend/base/langflow/load/utils.py
Normal file
89
src/backend/base/langflow/load/utils.py
Normal file
|
|
@ -0,0 +1,89 @@
|
|||
import httpx
|
||||
|
||||
from langflow.services.database.models.flow.model import FlowBase
|
||||
|
||||
|
||||
def upload(file_path, host, flow_id):
|
||||
"""
|
||||
Upload a file to Langflow and return the file path.
|
||||
|
||||
Args:
|
||||
file_path (str): The path to the file to be uploaded.
|
||||
host (str): The host URL of Langflow.
|
||||
flow_id (UUID): The ID of the flow to which the file belongs.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary containing the file path.
|
||||
|
||||
Raises:
|
||||
Exception: If an error occurs during the upload process.
|
||||
"""
|
||||
try:
|
||||
url = f"{host}/api/v1/upload/{flow_id}"
|
||||
response = httpx.post(url, files={"file": open(file_path, "rb")})
|
||||
if response.status_code == 200:
|
||||
return response.json()
|
||||
else:
|
||||
raise Exception(f"Error uploading file: {response.status_code}")
|
||||
except Exception as e:
|
||||
raise Exception(f"Error uploading file: {e}")
|
||||
|
||||
|
||||
def upload_file(file_path, host, flow_id, components, tweaks={}):
|
||||
"""
|
||||
Upload a file to Langflow and return the file path.
|
||||
|
||||
Args:
|
||||
file_path (str): The path to the file to be uploaded.
|
||||
host (str): The host URL of Langflow.
|
||||
port (int): The port number of Langflow.
|
||||
flow_id (UUID): The ID of the flow to which the file belongs.
|
||||
components (str): List of component IDs or names that need the file.
|
||||
tweaks (dict): A dictionary of tweaks to be applied to the file.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary containing the file path and any tweaks that were applied.
|
||||
|
||||
Raises:
|
||||
Exception: If an error occurs during the upload process.
|
||||
"""
|
||||
try:
|
||||
response = upload(file_path, host, flow_id)
|
||||
if response["file_path"]:
|
||||
for component in components:
|
||||
if isinstance(component, str):
|
||||
tweaks[component] = {"file_path": response["file_path"]}
|
||||
else:
|
||||
raise ValueError(f"Component ID or name must be a string. Got {type(component)}")
|
||||
return tweaks
|
||||
else:
|
||||
raise ValueError("Error uploading file")
|
||||
except Exception as e:
|
||||
raise ValueError(f"Error uploading file: {e}")
|
||||
|
||||
|
||||
def get_flow(url: str, flow_id: str):
|
||||
"""Get the details of a flow from Langflow.
|
||||
|
||||
Args:
|
||||
url (str): The host URL of Langflow.
|
||||
port (int): The port number of Langflow.
|
||||
flow_id (UUID): The ID of the flow to retrieve.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary containing the details of the flow.
|
||||
|
||||
Raises:
|
||||
Exception: If an error occurs during the retrieval process.
|
||||
"""
|
||||
try:
|
||||
flow_url = f"{url}/api/v1/flows/{flow_id}"
|
||||
response = httpx.get(flow_url)
|
||||
if response.status_code == 200:
|
||||
json_response = response.json()
|
||||
flow = FlowBase(**json_response).model_dump()
|
||||
return flow
|
||||
else:
|
||||
raise Exception(f"Error retrieving flow: {response.status_code}")
|
||||
except Exception as e:
|
||||
raise Exception(f"Error retrieving flow: {e}")
|
||||
|
|
@ -29,7 +29,6 @@ class FlowBase(SQLModel):
|
|||
is_component: Optional[bool] = Field(default=False, nullable=True)
|
||||
updated_at: Optional[datetime] = Field(default_factory=lambda: datetime.now(timezone.utc), nullable=True)
|
||||
webhook: Optional[bool] = Field(default=False, nullable=True, description="Can be used on the webhook endpoint")
|
||||
folder_id: Optional[UUID] = Field(default=None, nullable=True)
|
||||
endpoint_name: Optional[str] = Field(default=None, nullable=True, index=True)
|
||||
|
||||
@field_validator("endpoint_name")
|
||||
|
|
|
|||
|
|
@ -122,6 +122,13 @@ class MessageModelResponse(MessageModel):
|
|||
return v
|
||||
|
||||
|
||||
class MessageModelRequest(MessageModel):
|
||||
message: str = Field(default="")
|
||||
sender: str = Field(default="")
|
||||
sender_name: str = Field(default="")
|
||||
session_id: str = Field(default="")
|
||||
|
||||
|
||||
class VertexBuildModel(BaseModel):
|
||||
index: Optional[int] = Field(default=None, alias="index", exclude=True)
|
||||
id: Optional[str] = Field(default=None, alias="id")
|
||||
|
|
|
|||
|
|
@ -32,6 +32,10 @@ class MonitorService(Service):
|
|||
except Exception as e:
|
||||
logger.exception(f"Error initializing monitor service: {e}")
|
||||
|
||||
def exec_query(self, query: str):
|
||||
with duckdb.connect(str(self.db_path)) as conn:
|
||||
return conn.execute(query).df()
|
||||
|
||||
def to_df(self, table_name):
|
||||
return self.load_table_as_dataframe(table_name)
|
||||
|
||||
|
|
@ -69,7 +73,7 @@ class MonitorService(Service):
|
|||
valid: Optional[bool] = None,
|
||||
order_by: Optional[str] = "timestamp",
|
||||
):
|
||||
query = "SELECT index,flow_id, valid, params, data, artifacts, timestamp FROM vertex_builds"
|
||||
query = "SELECT id, index,flow_id, valid, params, data, artifacts, timestamp FROM vertex_builds"
|
||||
conditions = []
|
||||
if flow_id:
|
||||
conditions.append(f"flow_id = '{flow_id}'")
|
||||
|
|
@ -88,6 +92,8 @@ class MonitorService(Service):
|
|||
with duckdb.connect(str(self.db_path)) as conn:
|
||||
df = conn.execute(query).df()
|
||||
|
||||
print(query)
|
||||
|
||||
return df.to_dict(orient="records")
|
||||
|
||||
def delete_vertex_builds(self, flow_id: Optional[str] = None):
|
||||
|
|
@ -98,11 +104,20 @@ class MonitorService(Service):
|
|||
with duckdb.connect(str(self.db_path)) as conn:
|
||||
conn.execute(query)
|
||||
|
||||
def delete_messages(self, session_id: str):
|
||||
def delete_messages_session(self, session_id: str):
|
||||
query = f"DELETE FROM messages WHERE session_id = '{session_id}'"
|
||||
|
||||
with duckdb.connect(str(self.db_path)) as conn:
|
||||
conn.execute(query)
|
||||
return self.exec_query(query)
|
||||
|
||||
def delete_messages(self, message_ids: list[int]):
|
||||
query = f"DELETE FROM messages WHERE index IN ({','.join(map(str, message_ids))})"
|
||||
|
||||
return self.exec_query(query)
|
||||
|
||||
def update_message(self, message_id: int, **kwargs):
|
||||
query = f"""UPDATE messages SET {', '.join(f"{k} = '{v}'" for k, v in kwargs.items())} WHERE index = {message_id}"""
|
||||
|
||||
return self.exec_query(query)
|
||||
|
||||
def add_message(self, message: MessageModel):
|
||||
self.add_row("messages", message)
|
||||
|
|
|
|||
280
src/backend/base/poetry.lock
generated
280
src/backend/base/poetry.lock
generated
|
|
@ -463,43 +463,43 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "cryptography"
|
||||
version = "42.0.7"
|
||||
version = "42.0.8"
|
||||
description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
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||||
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|
||||
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||||
{file = "cryptography-42.0.8.tar.gz", hash = "sha256:8d09d05439ce7baa8e9e95b07ec5b6c886f548deb7e0f69ef25f64b3bce842f2"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1159,13 +1159,13 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "0.2.1"
|
||||
version = "0.2.2"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain-0.2.1-py3-none-any.whl", hash = "sha256:3e13bf97c5717bce2c281f5117e8778823e8ccf62d949e73d3869448962b1c97"},
|
||||
{file = "langchain-0.2.1.tar.gz", hash = "sha256:5758a315e1ac92eb26dafec5ad0fafa03cafa686aba197d5bb0b1dd28cc03ebe"},
|
||||
{file = "langchain-0.2.2-py3-none-any.whl", hash = "sha256:58ca0c47bcdd156da66f50a0a4fcedc49bf6950827f4a6b06c8c4842d55805f3"},
|
||||
{file = "langchain-0.2.2.tar.gz", hash = "sha256:9d61e50e9cdc2bea659bc5e6c03650ba048fda63a307490ae368e539f61a0d3a"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1197,13 +1197,13 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "langchain-community"
|
||||
version = "0.2.1"
|
||||
version = "0.2.3"
|
||||
description = "Community contributed LangChain integrations."
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_community-0.2.1-py3-none-any.whl", hash = "sha256:b834e2c5ded6903b839fcaf566eee90a0ffae53405a0f7748202725e701d39cd"},
|
||||
{file = "langchain_community-0.2.1.tar.gz", hash = "sha256:079942e8f15da975769ccaae19042b7bba5481c42020bbbd7d8cad73a9393261"},
|
||||
{file = "langchain_community-0.2.3-py3-none-any.whl", hash = "sha256:aa895545be2f3f4aa2fea36f6da2e3b4ec50ce61ec986e8f146901a1e9138138"},
|
||||
{file = "langchain_community-0.2.3.tar.gz", hash = "sha256:a3c35af215e47b700e7cb4e548fa8b45c6d46d52b5a5a65af2577c5a0104fc9f"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1220,22 +1220,22 @@ tenacity = ">=8.1.0,<9.0.0"
|
|||
|
||||
[package.extras]
|
||||
cli = ["typer (>=0.9.0,<0.10.0)"]
|
||||
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|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "0.2.3"
|
||||
version = "0.2.4"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
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||||
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||||
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||||
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||||
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
jsonpatch = ">=1.33,<2.0"
|
||||
langsmith = ">=0.1.65,<0.2.0"
|
||||
langsmith = ">=0.1.66,<0.2.0"
|
||||
packaging = ">=23.2,<24.0"
|
||||
pydantic = ">=1,<3"
|
||||
PyYAML = ">=5.3"
|
||||
|
|
@ -1246,13 +1246,13 @@ extended-testing = ["jinja2 (>=3,<4)"]
|
|||
|
||||
[[package]]
|
||||
name = "langchain-experimental"
|
||||
version = "0.0.59"
|
||||
version = "0.0.60"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
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||||
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||||
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|
||||
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|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1264,13 +1264,13 @@ extended-testing = ["faker (>=19.3.1,<20.0.0)", "jinja2 (>=3,<4)", "pandas (>=2.
|
|||
|
||||
[[package]]
|
||||
name = "langchain-text-splitters"
|
||||
version = "0.2.0"
|
||||
version = "0.2.1"
|
||||
description = "LangChain text splitting utilities"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
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||||
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||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1296,13 +1296,13 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.1.67"
|
||||
version = "0.1.72"
|
||||
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
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||||
]
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||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2104,18 +2104,18 @@ files = [
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|
||||
[[package]]
|
||||
name = "pydantic"
|
||||
version = "2.7.2"
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||||
version = "2.7.3"
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description = "Data validation using Python type hints"
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optional = false
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python-versions = ">=3.8"
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files = [
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||||
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||||
|
||||
[package.dependencies]
|
||||
annotated-types = ">=0.4.0"
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||||
pydantic-core = "2.18.3"
|
||||
pydantic-core = "2.18.4"
|
||||
typing-extensions = ">=4.6.1"
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||||
|
||||
[package.extras]
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|
@ -2123,90 +2123,90 @@ email = ["email-validator (>=2.0.0)"]
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||||
[[package]]
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name = "pydantic-core"
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||||
{file = "pydantic_core-2.18.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d323a01da91851a4f17bf592faf46149c9169d68430b3146dcba2bb5e5719abc"},
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||||
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||||
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||||
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||||
{file = "pydantic_core-2.18.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:ab86ce7c8f9bea87b9d12c7f0af71102acbf5ecbc66c17796cff45dae54ef9a5"},
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||||
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||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:51991a89639a912c17bef4b45c87bd83593aee0437d8102556af4885811d59f5"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:293afe532740370aba8c060882f7d26cfd00c94cae32fd2e212a3a6e3b7bc15e"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b48ece5bde2e768197a2d0f6e925f9d7e3e826f0ad2271120f8144a9db18d5c8"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:eae237477a873ab46e8dd748e515c72c0c804fb380fbe6c85533c7de51f23a8f"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:834b5230b5dfc0c1ec37b2fda433b271cbbc0e507560b5d1588e2cc1148cf1ce"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:e858ac0a25074ba4bce653f9b5d0a85b7456eaddadc0ce82d3878c22489fa4ee"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:2fd41f6eff4c20778d717af1cc50eca52f5afe7805ee530a4fbd0bae284f16e9"},
|
||||
{file = "pydantic_core-2.18.4.tar.gz", hash = "sha256:ec3beeada09ff865c344ff3bc2f427f5e6c26401cc6113d77e372c3fdac73864"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2214,13 +2214,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
|
|||
|
||||
[[package]]
|
||||
name = "pydantic-settings"
|
||||
version = "2.3.0"
|
||||
version = "2.3.1"
|
||||
description = "Settings management using Pydantic"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "pydantic_settings-2.3.0-py3-none-any.whl", hash = "sha256:26eeed27370a9c5e3f64e4a7d6602573cbedf05ed940f1d5b11c3f178427af7a"},
|
||||
{file = "pydantic_settings-2.3.0.tar.gz", hash = "sha256:78db28855a71503cfe47f39500a1dece523c640afd5280edb5c5c9c9cfa534c9"},
|
||||
{file = "pydantic_settings-2.3.1-py3-none-any.whl", hash = "sha256:acb2c213140dfff9669f4fe9f8180d43914f51626db28ab2db7308a576cce51a"},
|
||||
{file = "pydantic_settings-2.3.1.tar.gz", hash = "sha256:e34bbd649803a6bb3e2f0f58fb0edff1f0c7f556849fda106cc21bcce12c30ab"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow-base"
|
||||
version = "0.0.55"
|
||||
version = "0.0.57"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Langflow <contact@langflow.org>"]
|
||||
maintainers = [
|
||||
|
|
|
|||
32
src/frontend/package-lock.json
generated
32
src/frontend/package-lock.json
generated
|
|
@ -26,6 +26,7 @@
|
|||
"@radix-ui/react-slot": "^1.0.2",
|
||||
"@radix-ui/react-switch": "^1.0.3",
|
||||
"@radix-ui/react-tabs": "^1.0.4",
|
||||
"@radix-ui/react-toggle": "^1.0.3",
|
||||
"@radix-ui/react-tooltip": "^1.0.6",
|
||||
"@tabler/icons-react": "^2.32.0",
|
||||
"@tailwindcss/forms": "^0.5.6",
|
||||
|
|
@ -40,6 +41,7 @@
|
|||
"class-variance-authority": "^0.6.1",
|
||||
"clsx": "^1.2.1",
|
||||
"cmdk": "^1.0.0",
|
||||
"debounce-promise": "^3.1.2",
|
||||
"dompurify": "^3.0.5",
|
||||
"dotenv": "^16.4.5",
|
||||
"esbuild": "^0.17.19",
|
||||
|
|
@ -2761,6 +2763,31 @@
|
|||
}
|
||||
}
|
||||
},
|
||||
"node_modules/@radix-ui/react-toggle": {
|
||||
"version": "1.0.3",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-toggle/-/react-toggle-1.0.3.tgz",
|
||||
"integrity": "sha512-Pkqg3+Bc98ftZGsl60CLANXQBBQ4W3mTFS9EJvNxKMZ7magklKV69/id1mlAlOFDDfHvlCms0fx8fA4CMKDJHg==",
|
||||
"dependencies": {
|
||||
"@babel/runtime": "^7.13.10",
|
||||
"@radix-ui/primitive": "1.0.1",
|
||||
"@radix-ui/react-primitive": "1.0.3",
|
||||
"@radix-ui/react-use-controllable-state": "1.0.1"
|
||||
},
|
||||
"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-tooltip": {
|
||||
"version": "1.0.7",
|
||||
"resolved": "https://registry.npmjs.org/@radix-ui/react-tooltip/-/react-tooltip-1.0.7.tgz",
|
||||
|
|
@ -5670,6 +5697,11 @@
|
|||
"node": ">=12"
|
||||
}
|
||||
},
|
||||
"node_modules/debounce-promise": {
|
||||
"version": "3.1.2",
|
||||
"resolved": "https://registry.npmjs.org/debounce-promise/-/debounce-promise-3.1.2.tgz",
|
||||
"integrity": "sha512-rZHcgBkbYavBeD9ej6sP56XfG53d51CD4dnaw989YX/nZ/ZJfgRx/9ePKmTNiUiyQvh4mtrMoS3OAWW+yoYtpg=="
|
||||
},
|
||||
"node_modules/debug": {
|
||||
"version": "4.3.4",
|
||||
"resolved": "https://registry.npmjs.org/debug/-/debug-4.3.4.tgz",
|
||||
|
|
|
|||
|
|
@ -21,6 +21,7 @@
|
|||
"@radix-ui/react-slot": "^1.0.2",
|
||||
"@radix-ui/react-switch": "^1.0.3",
|
||||
"@radix-ui/react-tabs": "^1.0.4",
|
||||
"@radix-ui/react-toggle": "^1.0.3",
|
||||
"@radix-ui/react-tooltip": "^1.0.6",
|
||||
"@tabler/icons-react": "^2.32.0",
|
||||
"@tailwindcss/forms": "^0.5.6",
|
||||
|
|
@ -35,6 +36,7 @@
|
|||
"class-variance-authority": "^0.6.1",
|
||||
"clsx": "^1.2.1",
|
||||
"cmdk": "^1.0.0",
|
||||
"debounce-promise": "^3.1.2",
|
||||
"dompurify": "^3.0.5",
|
||||
"dotenv": "^16.4.5",
|
||||
"esbuild": "^0.17.19",
|
||||
|
|
|
|||
|
|
@ -15,7 +15,7 @@ dotenv.config({ path: path.resolve(__dirname, "../../.env") });
|
|||
export default defineConfig({
|
||||
testDir: "./tests",
|
||||
/* Run tests in files in parallel */
|
||||
fullyParallel: true,
|
||||
fullyParallel: false,
|
||||
/* Fail the build on CI if you accidentally left test.only in the source code. */
|
||||
forbidOnly: !!process.env.CI,
|
||||
/* Retry on CI only */
|
||||
|
|
@ -52,18 +52,18 @@ export default defineConfig({
|
|||
},
|
||||
},
|
||||
|
||||
{
|
||||
name: "firefox",
|
||||
use: {
|
||||
...devices["Desktop Firefox"],
|
||||
launchOptions: {
|
||||
firefoxUserPrefs: {
|
||||
"dom.events.asyncClipboard.readText": true,
|
||||
"dom.events.testing.asyncClipboard": true,
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
// {
|
||||
// name: "firefox",
|
||||
// use: {
|
||||
// ...devices["Desktop Firefox"],
|
||||
// launchOptions: {
|
||||
// firefoxUserPrefs: {
|
||||
// "dom.events.asyncClipboard.readText": true,
|
||||
// "dom.events.testing.asyncClipboard": true,
|
||||
// },
|
||||
// },
|
||||
// },
|
||||
// },
|
||||
],
|
||||
webServer: [
|
||||
{
|
||||
|
|
|
|||
|
|
@ -30,10 +30,10 @@ export default function App() {
|
|||
useTrackLastVisitedPath();
|
||||
|
||||
const removeFromTempNotificationList = useAlertStore(
|
||||
(state) => state.removeFromTempNotificationList
|
||||
(state) => state.removeFromTempNotificationList,
|
||||
);
|
||||
const tempNotificationList = useAlertStore(
|
||||
(state) => state.tempNotificationList
|
||||
(state) => state.tempNotificationList,
|
||||
);
|
||||
const [fetchError, setFetchError] = useState(false);
|
||||
const isLoading = useFlowsManagerStore((state) => state.isLoading);
|
||||
|
|
@ -51,7 +51,7 @@ export default function App() {
|
|||
const refreshVersion = useDarkStore((state) => state.refreshVersion);
|
||||
const refreshStars = useDarkStore((state) => state.refreshStars);
|
||||
const setGlobalVariables = useGlobalVariablesStore(
|
||||
(state) => state.setGlobalVariables
|
||||
(state) => state.setGlobalVariables,
|
||||
);
|
||||
const checkHasStore = useStoreStore((state) => state.checkHasStore);
|
||||
const navigate = useNavigate();
|
||||
|
|
@ -222,12 +222,19 @@ export default function App() {
|
|||
id={alert.id}
|
||||
removeAlert={removeAlert}
|
||||
/>
|
||||
) : alert.type === "notice" ? (
|
||||
<NoticeAlert
|
||||
key={alert.id}
|
||||
title={alert.title}
|
||||
link={alert.link}
|
||||
id={alert.id}
|
||||
removeAlert={removeAlert}
|
||||
/>
|
||||
) : (
|
||||
alert.type === "notice" && (
|
||||
<NoticeAlert
|
||||
alert.type === "success" && (
|
||||
<SuccessAlert
|
||||
key={alert.id}
|
||||
title={alert.title}
|
||||
link={alert.link}
|
||||
id={alert.id}
|
||||
removeAlert={removeAlert}
|
||||
/>
|
||||
|
|
@ -236,20 +243,6 @@ export default function App() {
|
|||
</div>
|
||||
))}
|
||||
</div>
|
||||
<div className="z-40 flex flex-col-reverse">
|
||||
{tempNotificationList.map((alert) => (
|
||||
<div key={alert.id}>
|
||||
{alert.type === "success" && (
|
||||
<SuccessAlert
|
||||
key={alert.id}
|
||||
title={alert.title}
|
||||
id={alert.id}
|
||||
removeAlert={removeAlert}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
|
|
|
|||
|
|
@ -16,13 +16,13 @@ export default function AlertDropdown({
|
|||
}: AlertDropdownType): JSX.Element {
|
||||
const notificationList = useAlertStore((state) => state.notificationList);
|
||||
const clearNotificationList = useAlertStore(
|
||||
(state) => state.clearNotificationList
|
||||
(state) => state.clearNotificationList,
|
||||
);
|
||||
const removeFromNotificationList = useAlertStore(
|
||||
(state) => state.removeFromNotificationList
|
||||
(state) => state.removeFromNotificationList,
|
||||
);
|
||||
const setNotificationCenter = useAlertStore(
|
||||
(state) => state.setNotificationCenter
|
||||
(state) => state.setNotificationCenter,
|
||||
);
|
||||
|
||||
const [open, setOpen] = useState(false);
|
||||
|
|
@ -36,7 +36,7 @@ export default function AlertDropdown({
|
|||
}}
|
||||
>
|
||||
<PopoverTrigger>{children}</PopoverTrigger>
|
||||
<PopoverContent className="nocopy nopan nodelete nodrag noundo flex h-[500px] w-[500px] flex-col">
|
||||
<PopoverContent className="nocopy nowheel nopan nodelete nodrag noundo flex h-[500px] w-[500px] flex-col">
|
||||
<div className="text-md flex flex-row justify-between pl-3 font-medium text-foreground">
|
||||
Notifications
|
||||
<div className="flex gap-3 pr-3 ">
|
||||
|
|
|
|||
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Reference in a new issue