e5986ec727
* Refactor code to remove console.log statements * Refactor code to remove console.log statements * ⬆️ (pyproject.toml): upgrade uncurl dependency to version 0.0.11 * 📝 (flows.py): Add docstring to the read_flows function to provide information about its purpose, arguments, and return value 📝 (parse.py): Add comments and docstrings to the parse_context function to explain its purpose and how it works 📝 (APIRequest.py): Add a new method update_build_config to handle parsing of curl commands and update build configuration based on the parsed context * refactor: Improve value change detection logic in DictComponent * refactor: Improve value change detection logic in DictAreaModal * refactor: Update APIRequest to handle parsing of curl commands and update build configuration This commit updates the APIRequest class in APIRequest.py to handle parsing of curl commands and update the build configuration based on the parsed context. It introduces a new method, update_build_config, which parses the curl command using the parse_context function and updates the build configuration with the parsed information. Additionally, it handles JSON decoding errors when parsing the data field of the curl command. This improvement enhances the functionality and flexibility of the APIRequest component. * feat: Add support for handling headers as dictionaries in APIRequest * refactor: Parse curl commands and update build configuration in APIRequest This commit refactors the APIRequest class in APIRequest.py to handle parsing of curl commands and update the build configuration based on the parsed context. It introduces a new method, update_build_config, which parses the curl command using the parse_context function and updates the build configuration with the parsed information. Additionally, it handles JSON decoding errors when parsing the data field of the curl command. This improvement enhances the functionality and flexibility of the APIRequest component. * ✨ (test_data_components.py): add new test case to parse curl command into build configuration for API requests * 🐛 (src/backend/base/langflow/components/data/APIRequest.py): fix type hinting issue for bodies variable in APIRequest class
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 theLANGFLOW_HOSTenvironment variable. The default is127.0.0.1.--workers: Sets the number of worker processes. Can be set using theLANGFLOW_WORKERSenvironment variable. The default is1.--timeout: Sets the worker timeout in seconds. The default is60.--port: Sets the port to listen on. Can be set using theLANGFLOW_PORTenvironment variable. The default is7860.--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 theLANGFLOW_LOG_LEVELenvironment variable. The default iscritical.--components-path: Specifies the path to the directory containing custom components. Can be set using theLANGFLOW_COMPONENTS_PATHenvironment variable. The default islangflow/components.--log-file: Specifies the path to the log file. Can be set using theLANGFLOW_LOG_FILEenvironment variable. The default islogs/langflow.log.--cache: Selects the type of cache to use. Options areInMemoryCacheandSQLiteCache. Can be set using theLANGFLOW_LANGCHAIN_CACHEenvironment variable. The default isSQLiteCache.--dev/--no-dev: Toggles the development mode. The default isno-dev.--path: Specifies the path to the frontend directory containing build files. This option is for development purposes only. Can be set using theLANGFLOW_FRONTEND_PATHenvironment variable.--open-browser/--no-open-browser: Toggles the option to open the browser after starting the server. Can be set using theLANGFLOW_OPEN_BROWSERenvironment variable. The default isopen-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 theLANGFLOW_REMOVE_API_KEYSenvironment variable. The default isno-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 ofFalse, allows running only the backend server without the frontend. It can also be set using theLANGFLOW_BACKEND_ONLYenvironment variable.--store: This parameter, with a default value ofTrue, enables the store features, use--no-storeto deactivate it. It can be configured using theLANGFLOW_STOREenvironment 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.
Deploy on Railway
Use this template to deploy Langflow 1.0 Preview on Railway:
Or this one to deploy Langflow 0.6.x:
Deploy on 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.
🌟 Contributors
📄 License
Langflow is released under the MIT License. See the LICENSE file for details.