[Docs] - Administration folder (#1969)
* video-content * consolidate-pages * api * remove-langfuse-integration * playground-svg * update-component-png * consolidate-items * status-svgs * factor-flows-components-collections-docs * cleanup-page * component-content * api-calls * move-docs * migration-issues --------- Co-authored-by: ogabrielluiz <gabriel@langflow.org>
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Mendon Kissling
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docs/docs/getting-started/canvas.mdx
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docs/docs/getting-started/canvas.mdx
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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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import Admonition from "@theme/Admonition";
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# 🎨 Langflow canvas
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The **Langflow canvas** is the central hub of Langflow, where you'll assemble new flows from components, run them, and see the results.
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To get a feel for the canvas, we'll examine a basic prompting flow.
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You can either build this flow yourself, or select **New Project** > **Basic prompting** to open a canvas with the flow pre-built.
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/basic-prompting.png",
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dark: "img/basic-prompting.png",
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}}
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style={{ width: "30%", margin: "20px auto" }}
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/>
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For more on the difference between flows, components, collections, and projects, see [Flows, collections, components, and projects](./flows-components-collections.mdx).
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## Components
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A component is a building block of a flow.
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<div style={{ marginBottom: "20px" }}>
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During the flow creation process, you will notice handles (colored circles)
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attached to one or both sides of a component. These handles represent the
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availability to connect to other components. Hover over a handle to see connection details.
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</div>
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<div style={{ marginBottom: "20px" }}>
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For example, if you select a <code>ConversationChain</code> component, you
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will see orange <span style={{ color: "orange" }}>o</span> and purple{" "}
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<span style={{ color: "purple" }}>o</span> input handles. They indicate that
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this component accepts an LLM and a Memory component as inputs. The red
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asterisk <span style={{ color: "red" }}>*</span> means that at least one input
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of that type is required.
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</div>
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{" "}
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: useBaseUrl("img/single-component.png"),
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dark: useBaseUrl("img/single-component.png"),
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}}
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style={{ width: "50%", maxWidth: "800px", margin: "20px auto" }}
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/>
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<div style={{ marginBottom: "20px" }}>
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In the top right corner of the component, you'll find the component status icon ().
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Run the flow by clicking the **Playground** button at the bottom right of the canvas.
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Once the validation is complete, the status of each validated component should turn green ().
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To debug, hover over the component status to see the outputs.
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</div>
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---
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### Component menu
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Each component is a little unique, but they will all have a menu bar on top that looks something like this.
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The menu options are **Code**, **Save**, **Duplicate**, and **More**.
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/chat-input-with-menu.png",
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dark: "img/chat-input-with-menu.png",
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}}
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style={{ width: "30%", margin: "20px auto" }}
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/>
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#### Code
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The **Code** button displays your component's Python code.
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You can modify the code and save it.
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#### Save
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Save your component to the **Saved** components folder for re-use.
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#### Duplicate
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Duplicate your component in the canvas.
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#### More
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**Advanced** - modify the parameters of your component.
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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_parameters.mp4" />
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</div>
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**Copy** - copy your component.
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**Share** - share your component to the Langflow store.
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**Docs** - view documentation for your component.
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**Delete** - delete your component.
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### Group multiple components
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Components without input or output nodes can be grouped into a single component for re-use.
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This is useful for combining large flows into single components (like RAG with a vector database, for example) and saves space in the canvas.
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1. Hold **Shift** and drag to select the **Prompt** and **OpenAI** components.
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2. Select **Group**.
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3. The components merge into a single component.
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4. To save the new component, select **Save**. It can now be re-used from the **Saved** components folder.
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## Playground
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Run your flow by clicking the **Playground** button.
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For more, see [Playground](../administration/playground.mdx).
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## API
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The **API** button opens the API window, where Langflow presents code for integrating your flow into external applications.
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Modify the call's parameters in the **Tweaks** window, click the **Copy Code** or **Download** buttons, and paste your code where you want to use it.
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/api-window.png",
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dark: "img/api-window.png",
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}}
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style={{ width: "50%", margin: "20px auto" }}
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/>
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### curl
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The **curl** tab displays sample code for posting a query to your flow.
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Modify the `input_value` to change your input message.
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```curl
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curl -X POST \
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http://127.0.0.1:7863/api/v1/run/f2eefd80-bb91-4190-9279-0d6ffafeaac4\?stream\=false \
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-H 'Content-Type: application/json'\
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-d '{"input_value": "is anybody there?",
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"output_type": "chat",
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"input_type": "chat",
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"tweaks": {
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"Prompt-uxBqP": {},
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"OpenAIModel-k39HS": {},
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"ChatOutput-njtka": {},
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"ChatInput-P3fgL": {}
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}}'
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```
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Result:
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```
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{"session_id":"f2eefd80-bb91-4190-9279-0d6ffafeaac4:53856a772b8e1cfcb3dd2e71576b5215399e95bae318d3c02101c81b7c252da3","outputs":[{"inputs":{"input_value":"is anybody there?"},"outputs":[{"results":{"result":"Arrr, me hearties! Aye, this be Captain [Your Name] speakin'. What be ye needin', matey?"},"artifacts":{"message":"Arrr, me hearties! Aye, this be Captain [Your Name] speakin'. What be ye needin', matey?","sender":"Machine","sender_name":"AI"},"messages":[{"message":"Arrr, me hearties! Aye, this be Captain [Your Name] speakin'. What be ye needin', matey?","sender":"Machine","sender_name":"AI","component_id":"ChatOutput-njtka"}],"component_display_name":"Chat Output","component_id":"ChatOutput-njtka"}]}]}%
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```
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### Python API
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The **Python API** tab displays code to interact with your flow using the Python HTTP requests library.
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### Python Code
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The **Python Code** tab displays code to interact with your flow's `.json` file using the Langflow runtime.
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### Chat Widget HTML
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The **Chat Widget HTML** tab displays code that can be inserted in the `<body>` of your HTML to interact with your flow.
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For more, see the [Chat widget documentation](../administration/chat-widget.mdx).
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### Tweaks
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The **Tweaks** tab displays the available parameters for your flow.
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Modifying the parameters changes the code parameters across all windows.
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For example, changing the **Chat Input** component's `input_value` will change that value across all API calls.
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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_api.mp4" />
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</div>
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## Project options menu
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To see options for your project, in the upper left corner of the canvas, select the dropdown menu.
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/project-options-menu.png",
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dark: "img/project-options-menu.png",
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}}
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style={{ width: "30%", margin: "20px auto" }}
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/>
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**New** - Start a new project.
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**Duplicate** - Duplicate the current flow as a new project.
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**Settings** - Modify the project's **Name** or **Description**.
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**Import** - Upload a flow `.json` file from your local machine.
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**Export** - Download your current project to your local machine as a `.json` file.
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**Undo** or **Redo** - Undo or redo your last action.
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113
docs/docs/getting-started/flows-components-collections.mdx
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docs/docs/getting-started/flows-components-collections.mdx
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@ -0,0 +1,113 @@
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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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# 🖥️ Flows, components, collections, and projects
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## TL;DR
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A [flow](#flow) is a pipeline of components connected together in the Langflow canvas.
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A [component](#component) is a single building block within a flow. A component has inputs, outputs, and parameters that define its functionality.
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A [collection](#collection) is a snapshot of the flows available in your database. Collections can be downloaded to local storage and uploaded for future use.
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A [project](#project) can be a component or a flow. Projects are saved as part of your collection.
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For example, the **OpenAI LLM** is a **component** of the **Basic prompting** flow, and the **flow** is stored in a **collection**.
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## Flow
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A **flow** is a pipeline of components connected together in the Langflow canvas.
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For example, the [Basic prompting](../starter-projects/basic-prompting.mdx) flow is a pipeline of four components:
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/basic-prompting.png",
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dark: "img/basic-prompting.png",
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}}
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style={{ width: "80%", margin: "20px auto" }}
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/>
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For example, the **OpenAI LLM component** receives input (left side) and produces output (right side) - in this case, receiving input from the **Chat Input** and **Prompt** components and producing output to the **Chat Output** component.
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## Component
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Components are the building blocks of flows. They consist of inputs, outputs, and parameters that define their functionality. These elements provide a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the LangChain [documentation](https://python.langchain.com/docs/integrations/components).
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<div style={{ marginBottom: "20px" }}>
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During the flow creation process, you will notice handles (colored circles)
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attached to one or both sides of a component. These handles represent the
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availability to connect to other components. Hover over a handle to see connection details.
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</div>
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<div style={{ marginBottom: "20px" }}>
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For example, if you select a <code>ConversationChain</code> component, you
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will see orange <span style={{ color: "orange" }}>o</span> and purple{" "}
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<span style={{ color: "purple" }}>o</span> input handles. They indicate that
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this component accepts an LLM and a Memory component as inputs. The red
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asterisk <span style={{ color: "red" }}>*</span> means that at least one input
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of that type is required.
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</div>
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{" "}
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: useBaseUrl("img/single-component.png"),
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dark: useBaseUrl("img/single-component.png"),
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}}
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style={{ width: "50%", maxWidth: "800px", margin: "20px auto" }}
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/>
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<div style={{ marginBottom: "20px" }}>
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In the top right corner of the component, you'll find the component status icon ().
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Build the flow by clicking the **Playground** at the bottom right of the canvas.
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Once the validation is complete, the status of each validated component should turn green ().
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To debug, hover over the component status to see the outputs.
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</div>
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---
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### Component Parameters
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Langflow components can be edited by clicking the component settings button. Hide parameters to reduce complexity and keep the canvas clean and intuitive for experimentation.
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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_parameters.mp4" />
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</div>
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## Collection
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A collection is a snapshot of flows available in a database.
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Collections can be downloaded to local storage and uploaded for future use.
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<div style={{ marginBottom: '20px', display: 'flex', justifyContent: 'center' }}>
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<ReactPlayer playing controls url='/videos/langflow_collection.mp4'
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/>
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</div>
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## Project
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A **Project** can be a flow or a component. To view your saved projects, select **My Collection**.
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Your **Projects** are displayed.
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Click the ** Playground** button to run a flow from the **My Collection** screen.
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In the top left corner of the screen are options for **Download Collection**, **Upload Collection**, and **New Project**.
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Select **Download Collection** to save your project to your local machine. This downloads all flows and components as a `.json` file.
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Select **Upload Collection** to upload a flow or component `.json` file from your local machine.
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Select **New Project** to create a new project. In addition to a blank canvas, [starter projects](../starter-projects/basic-prompting.mdx) are also available.
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