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backend-only mode

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docs/docs/deployment/backend-only.md
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# Backend-only Deployment
You can run a flow in `--backend-only` mode to
You can run Langflow in `--backend-only` mode to expose your Langflow app as an API, without running the frontend UI.
Start langflow in backend-only mode with `python3 -m langflow run --backend-only`.
The terminal prints ` Welcome to ⛓ Langflow `, and a blank window opens at `http://127.0.0.1:7864/all`.
Langflow will now serve requests to its API without the frontend running.
## Prerequisites
* [Langflow installed](../getting-started/install-langflow.mdx)
* [OpenAI API key](https://platform.openai.com)
* [A Langflow flow created](../starter-projects/basic-prompting.mdx)
## Download your flow's curl call
1. Click API.
2. Click **curl** > **Copy code** and save the code to your local machine.
It will look something like this:
```curl
curl -X POST \
"http://127.0.0.1:7864/api/v1/run/ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef?stream=false" \
-H 'Content-Type: application/json'\
-d '{"input_value": "message",
"output_type": "chat",
"input_type": "chat",
"tweaks": {
"Prompt-kvo86": {},
"OpenAIModel-MilkD": {},
"ChatOutput-ktwdw": {},
"ChatInput-xXC4F": {}
}}'
```
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.
## Start Langflow in backend-only mode
3. Stop Langflow with Ctrl+C.
4. Start langflow in backend-only mode with `python3 -m langflow run --backend-only`.
The terminal prints ` Welcome to ⛓ Langflow `, and a blank window opens at `http://127.0.0.1:7864/all`.
Langflow will now serve requests to its API.
5. Run the curl code you copied from the UI.
You should get a result like this:
```bash
{"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}]}]}%
```
Again, note that the flow ID matches.
Langflow is receiving your POST request, running the flow, and returning the result, all without running the frontend. Cool!
## Download your flow's Python API call
Instead of using curl, you can download your flow as a Python API call instead.
1. Click API.
2. Click **Python API** > **Copy code** and save the code to your local machine.
The code will look something like this:
```python
import requests
from typing import Optional
BASE_API_URL = "http://127.0.0.1:7864/api/v1/run"
FLOW_ID = "ef7e0554-69e5-4e3e-ab29-ee83bcd8d9ef"
# You can tweak the flow by adding a tweaks dictionary
# e.g {"OpenAI-XXXXX": {"model_name": "gpt-4"}}
def run_flow(message: str,
flow_id: str,
output_type: str = "chat",
input_type: str = "chat",
tweaks: Optional[dict] = None,
api_key: Optional[str] = None) -> dict:
"""
Run a flow with a given message and optional tweaks.
:param message: The message to send to the flow
:param flow_id: The ID of the flow to run
:param tweaks: Optional tweaks to customize the flow
:return: The JSON response from the flow
"""
api_url = f"{BASE_API_URL}/{flow_id}"
payload = {
"input_value": message,
"output_type": output_type,
"input_type": input_type,
}
headers = None
if tweaks:
payload["tweaks"] = tweaks
if api_key:
headers = {"x-api-key": api_key}
response = requests.post(api_url, json=payload, headers=headers)
return response.json()
# Setup any tweaks you want to apply to the flow
message = "message"
print(run_flow(message=message, flow_id=FLOW_ID))
```
3. Run your Python app:
```python
python3 app.py
```
The result is similar to the curl call:
```bash
{'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}]}]}
```
Your Python app POSTs to your Langflow server, and the server runs the flow and returns the result.
See [API](../administration/api.mdx) for more ways to interact with your headless Langflow server.