Merge remote-tracking branch 'origin/dev' into two_edges

docs/docs/deployment/backend-only.md

@@ -0,0 +1,113 @@
+# Backend-only
+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
+
+1. Stop Langflow with Ctrl+C.
+2. 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.
+3. 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.

docs/docs/deployment/docker.md

@@ -0,0 +1,65 @@
+# Docker
+
+This guide will help you get LangFlow up and running using Docker and Docker Compose.
+
+## Prerequisites
+
+- Docker
+- Docker Compose
+
+## Steps
+
+1. Clone the LangFlow repository:
+
+   ```sh
+   git clone https://github.com/langflow-ai/langflow.git
+   ```
+
+2. Navigate to the `docker_example` directory:
+
+   ```sh
+   cd langflow/docker_example
+   ```
+
+3. Run the Docker Compose file:
+
+   ```sh
+   docker compose up
+   ```
+
+LangFlow will now be accessible at [http://localhost:7860/](http://localhost:7860/).
+
+## Docker Compose Configuration
+
+The Docker Compose configuration spins up two services: `langflow` and `postgres`.
+
+### LangFlow Service
+
+The `langflow` service uses the `langflowai/langflow:latest` Docker image and exposes port 7860. It depends on the `postgres` service.
+
+Environment variables:
+
+- `LANGFLOW_DATABASE_URL`: The connection string for the PostgreSQL database.
+- `LANGFLOW_CONFIG_DIR`: The directory where LangFlow stores logs, file storage, monitor data, and secret keys.
+
+Volumes:
+
+- `langflow-data`: This volume is mapped to `/var/lib/langflow` in the container.
+
+### PostgreSQL Service
+
+The `postgres` service uses the `postgres:16` Docker image and exposes port 5432.
+
+Environment variables:
+
+- `POSTGRES_USER`: The username for the PostgreSQL database.
+- `POSTGRES_PASSWORD`: The password for the PostgreSQL database.
+- `POSTGRES_DB`: The name of the PostgreSQL database.
+
+Volumes:
+
+- `langflow-postgres`: This volume is mapped to `/var/lib/postgresql/data` in the container.
+
+## Switching to a Specific LangFlow Version
+
+If you want to use a specific version of LangFlow, you can modify the `image` field under the `langflow` service in the Docker Compose file. For example, to use version 1.0-alpha, change `langflowai/langflow:latest` to `langflowai/langflow:1.0-alpha`.