Visual UI Integration

Flowfile provides a web-based visual interface that can be launched directly from Python, so you can move a code-built pipeline into the visual editor and back.

Starting the Web UI

Quick Start

import flowfile as ff

# Start the web UI (opens browser automatically)
ff.start_web_ui()

# Start without opening browser
ff.start_web_ui(open_browser=False)

Command Line

# Start with default settings
flowfile run ui

# Start without opening browser
flowfile run ui --no-browser

Unified Mode

The web UI runs in unified mode: one process hosting the Core API, the Worker, and the UI. No separate services or Docker involved.

Opening Pipelines in the Editor

Basic Usage

import flowfile as ff

# Build a pipeline in code
df = ff.FlowFrame({
    "product": ["Widget", "Gadget", "Tool"],
    "price": [19.99, 39.99, 15.99],
    "quantity": [100, 50, 200]
})

result = df.filter(ff.col("price") > 20).with_columns([
    (ff.col("price") * ff.col("quantity")).alias("revenue")
])

# Open in visual editor (auto-starts server if needed)
ff.open_graph_in_editor(result.flow_graph)

What Happens Behind the Scenes

When you call open_graph_in_editor():

1. Saves the graph to a temporary .yaml flow file
2. Checks if the server is running by probing http://localhost:63578
3. Starts the server if needed using flowfile run ui --no-browser
4. Imports the flow via an API endpoint
5. Opens a browser tab at http://localhost:63578/ui/flow/{id}

Advanced Options

# Save to a specific location instead of a temp file
ff.open_graph_in_editor(
    result.flow_graph,
    storage_location="./my_pipeline.yaml"
)

# Don't automatically open browser
ff.open_graph_in_editor(
    result.flow_graph,
    automatically_open_browser=False
)

# Use custom module name (for development)
ff.open_graph_in_editor(
    result.flow_graph,
    module_name="my_custom_flowfile"
)

Server Management

Checking Server Status

# All server management functions are in flowfile.api
from flowfile.api import (
    is_flowfile_running,
    start_flowfile_server_process, 
    stop_flowfile_server_process,
    get_auth_token
)

if is_flowfile_running():
    print("Server is running")
else:
    print("Server is not running")

Manual Server Control

from flowfile.api import start_flowfile_server_process, stop_flowfile_server_process

# Start server manually
success, single_mode = start_flowfile_server_process()

# Stop server when done
stop_flowfile_server_process()

Auto-cleanup

The server process is automatically stopped when your Python script exits. No need to manually stop it unless you want to free resources earlier.

Configuration

The web UI is hard-locked to 127.0.0.1:63578 — start_server raises NotImplementedError for any other host or port, so there is no environment variable that relocates it. The FLOWFILE_MODULE_NAME variable (default flowfile) selects which module the launcher runs.

URLs and Endpoints

Once running, the following are available:

• Web UI: http://localhost:63578/ui
• API Docs: http://localhost:63578/docs

is_flowfile_running() treats a reachable /docs as "server up" — it is the readiness probe the client library uses, not a dedicated health endpoint.

Troubleshooting

Server Won't Start

The UI is fixed to port 63578; if a previous session holds it, free it (lsof -i :63578 / netstat -ano | findstr :63578) and retry. If the server starts but no tab opens, navigate to http://localhost:63578/ui manually.

Import Fails

# Verify authentication is working
from flowfile.api import get_auth_token

token = get_auth_token()
if token:
    print("Auth successful")
else:
    print("Auth failed - check server logs")

Poetry Environment Issues

If using Poetry for development:

# Force Poetry detection
import os
os.environ["FORCE_POETRY"] = "1"

# Or specify Poetry path
os.environ["POETRY_PATH"] = "/path/to/poetry"

ff.open_graph_in_editor(df.flow_graph)

The server is a singleton: the first open_graph_in_editor() call starts it, and every later call reuses it — there is no need to start it yourself or to manage the temporary flow files it writes (pass storage_location only when you want to keep the .yaml).

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