129 lines
5.1 KiB
Text
129 lines
5.1 KiB
Text
import Admonition from "@theme/Admonition";
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# Backend-only
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<Admonition type="warning" title="warning">
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This page may contain outdated information. It will be updated as soon as possible.
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</Admonition>
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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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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
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- [Langflow installed](../getting-started/install-langflow)
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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
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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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It will look something like this:
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```curl
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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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-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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}}'
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```
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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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## 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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You should get a result like this:
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```bash
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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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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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## Download your flow's Python API call
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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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```python
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import requests
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from typing import Optional
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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 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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"""
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Run a flow with a given message and optional tweaks.
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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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```
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3. Run your Python app:
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```python
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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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```bash
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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](../administration/api) for more ways to interact with your headless Langflow server.
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