langflow-ai / langflow

⛓️ Langflow is a dynamic graph where each node is an executable unit. Its modular and interactive design fosters rapid experimentation and prototyping, pushing hard on the limits of creativity.
http://www.langflow.org
MIT License
17.86k stars 2.68k forks source link
chatgpt langchain large-language-models react-flow

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:

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

Use this template to deploy Langflow 1.0 Preview on Railway:

Deploy 1.0 Preview on Railway

Or this one to deploy Langflow 0.6.x:

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.


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🌟 Contributors

langflow contributors

📄 License

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