Skip to main content

A Python package with a built-in web application

Project description

Langflow

Langflow is a new, visual way to build, iterate and deploy AI apps.

⚡️ Documentation and Community

📦 Installation

You can install Langflow with pip:

# Make sure you have Python 3.10 installed on your system.
# Install the pre-release version
python -m pip install langflow --pre --force-reinstall

# or stable version
python -m pip install langflow -U

Then, run Langflow with:

python -m langflow run

You can also preview Langflow in HuggingFace Spaces. Clone the space using this link, to create your own Langflow workspace in minutes.

🎨 Creating Flows

Creating flows with Langflow is easy. Simply drag components from the sidebar onto the canvas and connect them to start building your application.

Explore by editing prompt parameters, grouping components into a single high-level component, and building your own Custom Components.

Once you’re done, you can export your flow as a JSON file.

Load the flow with:

from langflow.load import run_flow_from_json

results = run_flow_from_json("path/to/flow.json", input_value="Hello, World!")

🖥️ Command Line Interface (CLI)

Langflow provides a command-line interface (CLI) for easy management and configuration.

Usage

You can run the Langflow using the following command:

langflow run [OPTIONS]

Each option is detailed below:

  • --help: Displays all available options.
  • --host: Defines the host to bind the server to. Can be set using the LANGFLOW_HOST environment variable. The default is 127.0.0.1.
  • --workers: Sets the number of worker processes. Can be set using the LANGFLOW_WORKERS environment variable. The default is 1.
  • --timeout: Sets the worker timeout in seconds. The default is 60.
  • --port: Sets the port to listen on. Can be set using the LANGFLOW_PORT environment variable. The default is 7860.
  • --config: Defines the path to the configuration file. The default is config.yaml.
  • --env-file: Specifies the path to the .env file containing environment variables. The default is .env.
  • --log-level: Defines the logging level. Can be set using the LANGFLOW_LOG_LEVEL environment variable. The default is critical.
  • --components-path: Specifies the path to the directory containing custom components. Can be set using the LANGFLOW_COMPONENTS_PATH environment variable. The default is langflow/components.
  • --log-file: Specifies the path to the log file. Can be set using the LANGFLOW_LOG_FILE environment variable. The default is logs/langflow.log.
  • --cache: Selects the type of cache to use. Options are InMemoryCache and SQLiteCache. Can be set using the LANGFLOW_LANGCHAIN_CACHE environment variable. The default is SQLiteCache.
  • --dev/--no-dev: Toggles the development mode. The default is no-dev.
  • --path: Specifies the path to the frontend directory containing build files. This option is for development purposes only. Can be set using the LANGFLOW_FRONTEND_PATH environment variable.
  • --open-browser/--no-open-browser: Toggles the option to open the browser after starting the server. Can be set using the LANGFLOW_OPEN_BROWSER environment variable. The default is open-browser.
  • --remove-api-keys/--no-remove-api-keys: Toggles the option to remove API keys from the projects saved in the database. Can be set using the LANGFLOW_REMOVE_API_KEYS environment variable. The default is no-remove-api-keys.
  • --install-completion [bash|zsh|fish|powershell|pwsh]: Installs completion for the specified shell.
  • --show-completion [bash|zsh|fish|powershell|pwsh]: Shows completion for the specified shell, allowing you to copy it or customize the installation.
  • --backend-only: This parameter, with a default value of False, allows running only the backend server without the frontend. It can also be set using the LANGFLOW_BACKEND_ONLY environment variable.
  • --store: This parameter, with a default value of True, enables the store features, use --no-store to deactivate it. It can be configured using the LANGFLOW_STORE environment variable.

These parameters are important for users who need to customize the behavior of Langflow, especially in development or specialized deployment scenarios.

Environment Variables

You can configure many of the CLI options using environment variables. These can be exported in your operating system or added to a .env file and loaded using the --env-file option.

A sample .env file named .env.example is included with the project. Copy this file to a new file named .env and replace the example values with your actual settings. If you're setting values in both your OS and the .env file, the .env settings will take precedence.

Deployment

Deploy Langflow on Google Cloud Platform

Follow our step-by-step guide to deploy Langflow on Google Cloud Platform (GCP) using Google Cloud Shell. The guide is available in the Langflow in Google Cloud Platform document.

Alternatively, click the "Open in Cloud Shell" button below to launch Google Cloud Shell, clone the Langflow repository, and start an interactive tutorial that will guide you through the process of setting up the necessary resources and deploying Langflow on your GCP project.

Open in Cloud Shell

Deploy on Railway

Deploy on Railway

Deploy on Render

Deploy to Render

👋 Contributing

We welcome contributions from developers of all levels to our open-source project on GitHub. If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.


Star History Chart

🌟 Contributors

langflow contributors

📄 License

Langflow is released under the MIT License. See the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bflower-1.0.0a33.tar.gz (6.8 kB view details)

Uploaded Source

Built Distribution

bflower-1.0.0a33-py3-none-any.whl (6.3 kB view details)

Uploaded Python 3

File details

Details for the file bflower-1.0.0a33.tar.gz.

File metadata

  • Download URL: bflower-1.0.0a33.tar.gz
  • Upload date:
  • Size: 6.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.10.14 Linux/6.5.0-1021-azure

File hashes

Hashes for bflower-1.0.0a33.tar.gz
Algorithm Hash digest
SHA256 2be391b1d42fe356e5d0f3162d3f55e99823231f1f2b40ba3120e42b8f125181
MD5 b9aeefcc533f61589f7e98ac4aa4f25a
BLAKE2b-256 cb7bebe382c25d0a33caad322ac9913cced61627adf48542c306d04093ae057e

See more details on using hashes here.

File details

Details for the file bflower-1.0.0a33-py3-none-any.whl.

File metadata

  • Download URL: bflower-1.0.0a33-py3-none-any.whl
  • Upload date:
  • Size: 6.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.10.14 Linux/6.5.0-1021-azure

File hashes

Hashes for bflower-1.0.0a33-py3-none-any.whl
Algorithm Hash digest
SHA256 73cdedc0b91abf8add974957261088206fac2c47b2180a434c8fa6f64820696c
MD5 deee1ae0deba48b8e9e75aa0f5d8a3ef
BLAKE2b-256 1ee51b916a7d40aa95778039e1da12dc87698004a3614f557abab944c57ac4a5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page