Docs: backend only mode (#4405)
* initial-cleanup-and-test * better-flow * config * Apply suggestions from code review Co-authored-by: KimberlyFields <46325568+KimberlyFields@users.noreply.github.com> * more-why-clarity * cleanup * code-review-and-tech-review --------- Co-authored-by: KimberlyFields <46325568+KimberlyFields@users.noreply.github.com>
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Mendon Kissling
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---
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title: Backend-Only
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title: Run Langflow in backend-only mode
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sidebar_position: 4
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slug: /configuration-backend-only
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---
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Langflow can run in `--backend-only` mode to expose a Langflow app as an API endpoint, without running the frontend UI.
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This is also known as "headless" mode. Running Langflow without the frontend is useful for automation, testing, and situations where you just need to serve a flow as a workload without creating a new flow in the UI.
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To run Langflow in backend-only mode, pass the `--backend-only` flag at startup.
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:::info
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```python
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python3 -m langflow run --backend-only
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```
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This page may contain outdated information. It will be updated as soon as possible.
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The terminal prints `Welcome to ⛓ Langflow`, and Langflow will now serve requests to its API without the frontend running.
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:::
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## Set up a basic prompting flow in backend-only mode
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This example shows you how to set up a [Basic Prompting flow](/starter-projects-basic-prompting) as an endpoint in backend-only mode.
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However, you can use these same instructions as guidelines for using any type of flow in backend-only mode.
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### Prerequisites
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- [Langflow is installed](/getting-started-installation)
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- [You have an OpenAI API key](https://platform.openai.com/)
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- [You have a Langflow Basic Prompting flow](/starter-projects-basic-prompting)
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You can run Langflow in `--backend-only` mode to expose your Langflow app as an API, without running the frontend UI.
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### Get your flow's ID
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This guide assumes you have created a [Basic Prompting flow](/starter-projects-basic-prompting) or have another working flow available.
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Start langflow in backend-only mode with `python3 -m langflow run --backend-only`.
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The terminal prints `Welcome to ⛓ Langflow`, and a blank window opens at `http://127.0.0.1:7864/all`.
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Langflow will now serve requests to its API without the frontend running.
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## Prerequisites {#81dfa9407ed648889081b9d08b0e5cfe}
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- [Langflow installed](/getting-started-installation)
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- [OpenAI API key](https://platform.openai.com/)
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- [A Langflow flow created](/starter-projects-basic-prompting)
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## Download your flow's curl call {#d2cf1b694e4741eca07fd9806516007b}
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1. Click API.
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2. Click **curl** > **Copy code** and save the code to your local machine.
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1. In the Langflow UI, click **API**.
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2. Click **curl** > **Copy code** to copy the curl command.
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This command will POST input to your flow's endpoint.
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It will look something like this:
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```text
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curl -X POST \\
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"<http://127.0.0.1:7864/api/v1/run/ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef?stream=false>" \\
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-H 'Content-Type: application/json'\\
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curl -X POST \
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"http://127.0.0.1:7861/api/v1/run/fff8dcaa-f0f6-4136-9df0-b7cb38de42e0?stream=false" \
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-H 'Content-Type: application/json'\
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-d '{"input_value": "message",
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"output_type": "chat",
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"input_type": "chat",
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"tweaks": {
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"Prompt-kvo86": {},
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"OpenAIModel-MilkD": {},
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"ChatOutput-ktwdw": {},
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"ChatInput-xXC4F": {}
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"ChatInput-8a86T": {},
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"Prompt-pKfl9": {},
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"ChatOutput-WcGpD": {},
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"OpenAIModel-5UyvQ": {}
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}}'
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```
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The flow ID in this example is `fff8dcaa-f0f6-4136-9df0-b7cb38de42e0`, a UUID generated by Langflow and used in the endpoint URL.
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See [Project & General Settings](/settings-project-general-settings) to change the endpoint.
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Note the flow ID of `ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef`. You can find this ID in the UI as well to ensure you're querying the right flow.
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3. To stop Langflow, press **Ctrl+C**.
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### Start Langflow in backend-only mode
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## Start Langflow in backend-only mode {#f0ba018daf3041c39c0d226dadf78d35}
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1. Start Langflow in backend-only mode.
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1. Stop Langflow with Ctrl+C.
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2. Start langflow in backend-only mode with `python3 -m langflow run --backend-only`.
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The terminal prints `Welcome to ⛓ Langflow`, and a blank window opens at `http://127.0.0.1:7864/all`.
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Langflow will now serve requests to its API.
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3. Run the curl code you copied from the UI.
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```python
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python3 -m langflow run --backend-only
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```
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The terminal prints `Welcome to ⛓ Langflow`.
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Langflow is now serving requests to its API.
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2. Run the curl code you copied from the UI.
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You should get a result like this:
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```shell
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{"session_id":"ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef:bf81d898868ac87e1b4edbd96c131c5dee801ea2971122cc91352d144a45b880","outputs":[{"inputs":{"input_value":"hi, are you there?"},"outputs":[{"results":{"result":"Arrr, ahoy matey! Aye, I be here. What be ye needin', me hearty?"},"artifacts":{"message":"Arrr, ahoy matey! Aye, I be here. What be ye needin', me hearty?","sender":"Machine","sender_name":"AI"},"messages":[{"message":"Arrr, ahoy matey! Aye, I be here. What be ye needin', me hearty?","sender":"Machine","sender_name":"AI","component_id":"ChatOutput-ktwdw"}],"component_display_name":"Chat Output","component_id":"ChatOutput-ktwdw","used_frozen_result":false}]}]}%
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```
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This confirms Langflow is receiving your POST request, running the flow, and returning the result without running the frontend.
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Again, note that the flow ID matches.
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Langflow is receiving your POST request, running the flow, and returning the result, all without running the frontend. Cool!
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You can interact with this endpoint using the other options in the **API** menu, including the Python and Javascript APIs.
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### Query the Langflow endpoint with a Python script
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## Download your flow's Python API call {#5923ff9dc40843c7a22a72fa6c66540c}
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Using the same flow ID, run a Python sample script to send a query and get a prettified JSON response back.
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Instead of using curl, you can download your flow as a Python API call instead.
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1. Click API.
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2. Click **Python API** > **Copy code** and save the code to your local machine.
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The code will look something like this:
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1. Create a Python file and name it `langflow_api_demo.py`.
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```python
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import requests
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from typing import Optional
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import json
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BASE_API_URL = "<http://127.0.0.1:7864/api/v1/run>"
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FLOW_ID = "ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef"
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# You can tweak the flow by adding a tweaks dictionary
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# e.g {"OpenAI-XXXXX": {"model_name": "gpt-4"}}
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def query_langflow(message):
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url = "http://127.0.0.1:7861/api/v1/run/fff8dcaa-f0f6-4136-9df0-b7cb38de42e0"
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headers = {"Content-Type": "application/json"}
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data = {"input_value": message}
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def run_flow(message: str,
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flow_id: str,
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output_type: str = "chat",
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input_type: str = "chat",
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tweaks: Optional[dict] = None,
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api_key: Optional[str] = None) -> dict:
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"""Run a flow with a given message and optional tweaks.
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response = requests.post(url, headers=headers, json=data)
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return response.json()
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:param message: The message to send to the flow
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:param flow_id: The ID of the flow to run
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:param tweaks: Optional tweaks to customize the flow
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:return: The JSON response from the flow
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"""
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api_url = f"{BASE_API_URL}/{flow_id}"
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payload = {
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"input_value": message,
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"output_type": output_type,
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"input_type": input_type,
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}
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headers = None
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if tweaks:
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payload["tweaks"] = tweaks
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if api_key:
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headers = {"x-api-key": api_key}
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response = requests.post(api_url, json=payload, headers=headers)
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return response.json()
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# Setup any tweaks you want to apply to the flow
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message = "message"
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print(run_flow(message=message, flow_id=FLOW_ID))
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user_input = input("Enter your message: ")
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result = query_langflow(user_input)
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print(json.dumps(result, indent=2))
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```
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2. Run the script.
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```python
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python langflow_api_demo.py
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```
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3. Enter your message when prompted.
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You will get a prettified JSON response back containing a response to your message.
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### Configure host and ports in backend-only mode
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To change the host and port, pass the values as additional flags.
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```python
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python -m langflow run --host 127.0.0.1 --port 7860 --backend-only
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```
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3. Run your Python app:
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```shell
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python3 app.py
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```
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The result is similar to the curl call:
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```json
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{'session_id': 'ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef:bf81d898868ac87e1b4edbd96c131c5dee801ea2971122cc91352d144a45b880', 'outputs': [{'inputs': {'input_value': 'message'}, 'outputs': [{'results': {'result': "Arrr matey! What be yer message for this ol' pirate? Speak up or walk the plank!"}, 'artifacts': {'message': "Arrr matey! What be yer message for this ol' pirate? Speak up or walk the plank!", 'sender': 'Machine', 'sender_name': 'AI'}, 'messages': [{'message': "Arrr matey! What be yer message for this ol' pirate? Speak up or walk the plank!", 'sender': 'Machine', 'sender_name': 'AI', 'component_id': 'ChatOutput-ktwdw'}], 'component_display_name': 'Chat Output', 'component_id': 'ChatOutput-ktwdw', 'used_frozen_result': False}]}]}
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```
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Your Python app POSTs to your Langflow server, and the server runs the flow and returns the result.
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See [API](https://www.notion.so/administration/api) for more ways to interact with your headless Langflow server.
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