Sharing my collection locally with my research team

[flefevre]

Dear Langflow team,
If i install a local instance of langflow, and I have multiple users in my research laboratory.
How can they share the different workflows they have created?
Is it possible to have a local collection shared additionnaly to "Community examples" ?
Thanks for your help
François
NB: i was not sure if i have to ask here or in discord, tell me your preference for next time

[dosubot[bot]]

Yes, it is possible to have a local collection shared among multiple users in addition to the "Community examples" when installing a local instance of Langflow. You can achieve this by configuring the database to be stored in a shared location.

To do this, set the LANGFLOW_SAVE_DB_IN_CONFIG_DIR to true and specify a shared directory for LANGFLOW_CONFIG_DIR in the .env file. This way, the database will be stored in the specified config directory, which can be accessed by multiple users.

Here is an example configuration in the .env file:

# Config directory
# Directory where files, logs and database will be stored
# Example: LANGFLOW_CONFIG_DIR=/path/to/shared/directory
LANGFLOW_CONFIG_DIR=/path/to/shared/directory

# Save database in the config directory
# Values: true, false
# If false, the database will be saved in Langflow's root directory
# This means that the database will be deleted when Langflow is uninstalled
# and that the database will not be shared between different virtual environments
# Example: LANGFLOW_SAVE_DB_IN_CONFIG_DIR=true
LANGFLOW_SAVE_DB_IN_CONFIG_DIR=true

Make sure that the shared directory specified in LANGFLOW_CONFIG_DIR is accessible to all users who need to share the local collection.

Additionally, you can utilize the create_or_update_starter_projects function to load and update starter projects in the shared database. This function ensures that the starter projects are up-to-date and available for all users:

def create_or_update_starter_projects():
    components_paths = get_settings_service().settings.components_path
    try:
        all_types_dict = get_all_components(components_paths, as_dict=True)
    except Exception as e:
        logger.exception(f"Error loading components: {e}")
        raise e
    with session_scope() as session:
        new_folder = create_starter_folder(session)
        starter_projects = load_starter_projects()
        delete_start_projects(session, new_folder.id)
        for project_path, project in starter_projects:
            (
                project_name,
                project_description,
                project_is_component,
                updated_at_datetime,
                project_data,
                project_icon,
                project_icon_bg_color,
            ) = get_project_data(project)
            updated_project_data = update_projects_components_with_latest_component_versions(
                project_data, all_types_dict
            )
            if updated_project_data != project_data:
                project_data = updated_project_data
                # We also need to update the project data in the file

                update_project_file(project_path, project, updated_project_data)
            if project_name and project_data:
                for existing_project in get_all_flows_similar_to_project(session, new_folder.id):
                    session.delete(existing_project)

                create_new_project(
                    session,
                    project_name,
                    project_description,
                    project_is_component,
                    updated_at_datetime,
                    project_data,
                    project_icon,
                    project_icon_bg_color,
                    new_folder.id,
                )

This function will help maintain a consistent set of starter projects that can be shared among multiple users ^[1][2].

To continue talking to Dosu, mention @dosu.

[flefevre]

Thanks for your answer. I will test it but just to be sure, the LANGFLOW_SAVE_DB_IN_CONFIG_DIR Could be used also LANGFLOW_DATABASE_URL environment variable? I am a little confused. #Database, configuration FAILED #1432 - DB_USER=${DB_USER} - DB_PASSWORD=${DB_PASSWORD} - DB_HOST=${DB_HOST} - DB_PORT=${DB_PORT} - DB_NAME=${DB_NAME} - LANGFLOW_DATABASE_URL=postgresql://${DB_USER}:${DB_PASSWORD}@ ${DB_HOST}:${DB_PORT}/${DB_NAME} # This variable defines Le mar. 11 juin 2024, 13:01, dosubot[bot] ***@***.***> a écrit :

…

Yes, it is possible to have a local collection shared among multiple users in addition to the "Community examples" when installing a local instance of Langflow. You can achieve this by configuring the database to be stored in a shared location. To do this, set the LANGFLOW_SAVE_DB_IN_CONFIG_DIR to true and specify a shared directory for LANGFLOW_CONFIG_DIR in the .env file. This way, the database will be stored in the specified config directory, which can be accessed by multiple users. Here is an example configuration in the .env file: # Config directory# Directory where files, logs and database will be stored# Example: LANGFLOW_CONFIG_DIR=/path/to/shared/directoryLANGFLOW_CONFIG_DIR=/path/to/shared/directory # Save database in the config directory# Values: true, false# If false, the database will be saved in Langflow's root directory# This means that the database will be deleted when Langflow is uninstalled# and that the database will not be shared between different virtual environments# Example: LANGFLOW_SAVE_DB_IN_CONFIG_DIR=trueLANGFLOW_SAVE_DB_IN_CONFIG_DIR=true Make sure that the shared directory specified in LANGFLOW_CONFIG_DIR is accessible to all users who need to share the local collection. Additionally, you can utilize the create_or_update_starter_projects function to load and update starter projects in the shared database. This function ensures that the starter projects are up-to-date and available for all users: def create_or_update_starter_projects(): components_paths = get_settings_service().settings.components_path try: all_types_dict = get_all_components(components_paths, as_dict=True) except Exception as e: logger.exception(f"Error loading components: {e}") raise e with session_scope() as session: new_folder = create_starter_folder(session) starter_projects = load_starter_projects() delete_start_projects(session, new_folder.id) for project_path, project in starter_projects: ( project_name, project_description, project_is_component, updated_at_datetime, project_data, project_icon, project_icon_bg_color, ) = get_project_data(project) updated_project_data = update_projects_components_with_latest_component_versions( project_data, all_types_dict ) if updated_project_data != project_data: project_data = updated_project_data # We also need to update the project data in the file update_project_file(project_path, project, updated_project_data) if project_name and project_data: for existing_project in get_all_flows_similar_to_project(session, new_folder.id): session.delete(existing_project) create_new_project( session, project_name, project_description, project_is_component, updated_at_datetime, project_data, project_icon, project_icon_bg_color, new_folder.id, ) This function will help maintain a consistent set of starter projects that can be shared among multiple users [1] <https://github.com/langflow-ai/langflow/blob/dev/.env.example>[2] <https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/initial_setup/setup.py> . *To continue talking to Dosu <https://dosu.dev>, mention @dosu <https://github.com/dosu>.* — Reply to this email directly, view it on GitHub <#2135 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABKZRFFV2PK5WRG7SNBFNDTZG3KKHAVCNFSM6AAAAABJDUBPFCVHI2DSMVQWIX3LMV43SRDJONRXK43TNFXW4Q3PNVWWK3TUHM4TOMZXHAYDE> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[dosubot[bot]]

Yes, you can use the LANGFLOW_DATABASE_URL environment variable instead of LANGFLOW_SAVE_DB_IN_CONFIG_DIR. The LANGFLOW_DATABASE_URL environment variable is checked and used if provided, and it takes precedence over the default SQLite database configuration.

To configure it for a shared database setup, set the LANGFLOW_DATABASE_URL environment variable to the URL of your shared database. Here is an example:

export LANGFLOW_DATABASE_URL="postgresql://user:password@hostname:port/dbname"

This ensures that Langflow uses the specified shared database instead of the default SQLite database. You can find more configuration options in the .env.example file:

# Database URL
# Postgres example: LANGFLOW_DATABASE_URL=postgresql://postgres:postgres@localhost:5432/langflow
# SQLite example:
LANGFLOW_DATABASE_URL=sqlite:///./langflow.db

Make sure to copy the .env.example file to .env and modify the values according to your needs ^[1][2].

For a Docker setup, you can refer to the docker_example/docker-compose.yml file. Here is an example configuration:

version: "3.8"

services:
  langflow:
    image: langflowai/langflow:latest
    ports:
      - "7860:7860"
    depends_on:
      - postgres
    environment:
      - LANGFLOW_DATABASE_URL=postgresql://langflow:langflow@postgres:5432/langflow
      - LANGFLOW_CONFIG_DIR=/var/lib/langflow
    volumes:
      - langflow-data:/var/lib/langflow

  postgres:
    image: postgres:16
    environment:
      POSTGRES_USER: langflow
      POSTGRES_PASSWORD: langflow
      POSTGRES_DB: langflow
    ports:
      - "5432:5432"
    volumes:
      - langflow-postgres:/var/lib/postgresql/data

volumes:
  langflow-postgres:
  langflow-data:

This configuration sets up a Langflow service that connects to a PostgreSQL database using the LANGFLOW_DATABASE_URL environment variable ^[3].

To continue talking to Dosu, mention @dosu.