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import ThemedImage from "@theme/ThemedImage";
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import ZoomableImage from "/src/theme/ZoomableImage.js";
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import ReactPlayer from "react-player";
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# 🎨 Creating Flows
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## Compose
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Creating flows with Langflow is easy. Drag sidebar components onto the canvas and connect them together to create your pipeline.
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Langflow provides a range of Components to choose from, including **Chat Input**, **Chat Output**, **API Request** and **Prompt**.
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/langflow_canvas.png",
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dark: "img/langflow_canvas.png",
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}}
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style={{
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width: "70%",
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margin: "20px auto",
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display: "flex",
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justifyContent: "center",
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}}
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/>
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## Starter Flows
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Langflow provides a range of starter flows to help you get started. These flows are pre-built and can be used as a starting point for your own flows.
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<div
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style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
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>
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<ReactPlayer playing controls url="/videos/langflow_fork.mp4" />
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</div>
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## Defining Inputs and Outputs
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Each flow can have multiple inputs and outputs. These can be defined by placing **Inputs** and **Outputs** components on the canvas.
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The **Inputs** components define the inputs to the flow.
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Whenever you place an Input component on the canvas, it will allow you to interactively define change its value
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from the Interactive Panel.
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The **Text Input** component allows you to define a text input, and the **Chat Input** component allows you to use the chat input from the Interactive Panel.
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The **Outputs** components define the outputs of the flow and work similarly to the Inputs components.
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Both Inputs and Outputs components can be connected to other components on the canvas and are used to define how the API works too.
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<div
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style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
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>
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<ReactPlayer playing controls url="/videos/langflow_build.mp4" />
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</div>
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@ -1,44 +0,0 @@
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import Admonition from "@theme/Admonition";
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# Async API
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## Introduction
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<Admonition type="info" caption="In development">
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This implementation is still in development. Contributions are welcome!
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</Admonition>
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The Async API is an implementation of the Langflow API that uses [Celery](https://docs.celeryproject.org/en/stable/)
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to run the tasks asynchronously, using a message broker to send and receive messages, a result backend to store the results and a cache to store the task states and session data.
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### Configuration
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The folder _`./deploy`_ in the [Github repository](https://github.com/logspace-ai/langflow) contains a _`.env.example`_ file that can be used to configure a Langflow deployment.
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The file contains the variables required to configure a Celery worker queue, Redis cache and result backend and a RabbitMQ message broker.
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To set it up locally you can copy the file to _`.env`_ and run the following command:
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```bash
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docker compose up -d
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```
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This will set up the following containers:
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- Langflow API
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- Celery worker
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- RabbitMQ message broker
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- Redis cache
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- PostgreSQL database
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- PGAdmin
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- Flower
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- Traefik
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- Grafana
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- Prometheus
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### Testing
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To run the tests for the Async API, you can run the following command:
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```bash
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docker compose -f docker-compose.with_tests.yml up --exit-code-from tests tests result_backend broker celeryworker db --build
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```
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@ -61,11 +61,11 @@ We wanted to create start projects that would help you learn about new features
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For now, we have:
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- **[Basic Prompting (Ahoy World!)](/starter-projects/basic-prompting)**: A simple flow that shows you how to use the Prompt Component and how to talk like a pirate.
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- **[Vector Store RAG](/starter-projects/rag-with-astradb)**: A flow that shows you how to ingest data into a Vector Store and then use it to run a RAG application.
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- **[Memory Chatbot](/starter-projects/memory-chatbot)**: This one shows you how to create a simple chatbot that can remember things about the user.
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- **[Document QA](/starter-projects/document-qa)**: This flow shows you how to build a simple flow that helps you get answers about a document.
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- **[Blog Writer](/starter-projects/blog-writer)**: Shows you how you can expand on the Prompt variables and be creative about what inputs you add to it.
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- **[Basic Prompting (Ahoy World!)](/getting-started/basic-prompting)**: A simple flow that shows you how to use the Prompt Component and how to talk like a pirate.
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- **[Vector Store RAG](/getting-started/rag-with-astradb)**: A flow that shows you how to ingest data into a Vector Store and then use it to run a RAG application.
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- **[Memory Chatbot](/getting-started/memory-chatbot)**: This one shows you how to create a simple chatbot that can remember things about the user.
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- **[Document QA](/getting-started/document-qa)**: This flow shows you how to build a simple flow that helps you get answers about a document.
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- **[Blog Writer](/getting-started/blog-writer)**: Shows you how you can expand on the Prompt variables and be creative about what inputs you add to it.
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As always, your feedback is invaluable, so please let us know what you think of the new starter projects and what you would like to see in the future.
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