13fe129e4b* feat: add API endpoint for retrieving user data * feat: add useAddUser hook for adding a user via API * feat: add useGetUserPage hook for retrieving users with pagination * refactor: optimize deletion of messages (#2714) * feat: optimize deletion of messages in SessionView component This commit optimizes the deletion of messages in the SessionView component by using the useDeleteMessages hook from the API queries. It replaces the useRemoveMessages hook that was previously used. The new implementation handles the deletion of messages more efficiently and provides better error handling. The selectedRows state is updated after successful deletion, and a success message is displayed to the user. In case of an error, an error message is shown. Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> * feat: optimize deletion of messages in SessionView component This commit optimizes the deletion of messages in the SessionView component by using the useDeleteMessages hook from the API queries. It replaces the useRemoveMessages hook that was previously used. The new implementation handles the deletion of messages more efficiently and provides better error handling. The selectedRows state is updated after successful deletion, and a success message is displayed to the user. In case of an error, an error message is shown. Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> * refactor: optimize deletion of messages in SessionView component This commit optimizes the deletion of messages in the SessionView component by using the useDeleteMessages hook from the API queries. It replaces the useRemoveMessages hook that was previously used. The new implementation handles the deletion of messages more efficiently and provides better error handling. The selectedRows state is updated after successful deletion, and a success message is displayed to the user. In case of an error, an error message is shown. * [autofix.ci] apply automated fixes --------- Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Lucas Oliveira <lucas.edu.oli@hotmail.com> Co-authored-by: Lucas Oliveira <62335616+lucaseduoli@users.noreply.github.com> * fix: component seems to be clickable (#2731) * Changed card to not have shadow on hover if it is a component * removed unused console.log * feat: add logs field to ResultData and Vertex class (#2732) * feat: add logs to ResultDataResponse in schemas.py * feat(schema.py): add logs field to ResultData class to store log messages for better debugging and monitoring * feat(vertex): add logs attribute to Vertex class to store logs for each vertex operation * feat: add useDeleteUsers hook for deleting users via API * feat: add useUpdateUser hook for updating user data via API * feat: add useResetPassword hook for resetting user password via API * feat: add logout API endpoint and useLogout hook Add the `logout` API endpoint and the `useLogout` hook to handle user logout functionality. The `logout` API endpoint sends a PATCH request to the server to log out the user, while the `useLogout` hook provides a convenient way to call the `logout` API endpoint. This addition allows users to securely log out of the application. * feat: add login API endpoint and useLoginUser hook Add the `login` API endpoint and the `useLoginUser` hook to handle user login functionality. The `login` API endpoint sends a POST request to the server with the user's username and password to authenticate the user. The `useLoginUser` hook provides a convenient way to call the `login` API endpoint. This addition allows users to securely log in to the application. * feat: add autologin API endpoint and useGetAutoLogin hook Add the `autologin` API endpoint and the `useGetAutoLogin` hook to handle automatic login functionality. The `autologin` API endpoint sends a GET request to the server to check if the user is already logged in. The `useGetAutoLogin` hook provides a convenient way to call the `autologin` API endpoint. This addition allows for seamless automatic login for users who have previously logged in to the application. * feat: add REFRESH constant and useRefrshAccessToken hook Add the `REFRESH` constant to the `constants.ts` file and the `useRefrshAccessToken` hook to handle refreshing the access token. The `REFRESH` constant represents the API endpoint for refreshing the access token, and the `useRefrshAccessToken` hook provides a convenient way to call this endpoint. This addition allows for seamless token refreshing for authenticated users. * refactor: fromat code --------- Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org> Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Lucas Oliveira <lucas.edu.oli@hotmail.com> Co-authored-by: Lucas Oliveira <62335616+lucaseduoli@users.noreply.github.com> |
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| .devcontainer | ||
| .github | ||
| .vscode | ||
| deploy | ||
| docker | ||
| docker_example | ||
| docs | ||
| scripts | ||
| src | ||
| tests | ||
| .env.example | ||
| .eslintrc.json | ||
| .gitattributes | ||
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| .pre-commit-config.yaml | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| eslint.config.js | ||
| LICENSE | ||
| Makefile | ||
| poetry.lock | ||
| pyproject.toml | ||
| README.md | ||
| README.PT.md | ||
| README.zh_CN.md | ||
| render.yaml | ||
Langflow 1.0 is OUT! 🎉
Read all about it here!
A visual framework for building multi-agent and RAG applications
Open-source, Python-powered, fully customizable, LLM and vector store agnostic
Docs - Join our Discord - Follow us on X - Live demo
📝 Content
- 📝 Content
- 📦 Get Started
- 🎨 Create Flows
- Deploy
- 🖥️ Command Line Interface (CLI)
- 👋 Contribute
- 🌟 Contributors
- 📄 License
📦 Get Started
You can install Langflow with pip:
# Make sure you have >=Python 3.10 installed on your system.
python -m pip install langflow -U
Or
If you would like to install from your cloned repo, you can build and install Langflow's frontend and backend with:
make install_frontend && make build_frontend && make install_backend
Then, run Langflow with:
python -m langflow run
🎨 Create Flows
Creating flows with Langflow is easy. Simply drag components from the sidebar onto the workspace 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!")
Deploy
DataStax Langflow
DataStax Langflow is a hosted version of Langflow integrated with AstraDB. Be up and running in minutes with no installation or setup required. Sign up for free.
Deploy Langflow on Hugging Face Spaces
You can also preview Langflow in HuggingFace Spaces. Clone the space using this link to create your own Langflow workspace in minutes.
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 on Railway:
Deploy on Render
Deploy on Kubernetes
Follow our step-by-step guide to deploy Langflow on Kubernetes.
🖥️ 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.
👋 Contribute
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.