organized folders, added components tab, adjusted mendable style.
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docs/docs/guidelines/collection.mdx
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docs/docs/guidelines/collection.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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# Collection
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A collection is a snapshot of the flows available in the database. You can download your entire collection for local storage and upload it anytime 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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docs/docs/guidelines/components.mdx
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docs/docs/guidelines/components.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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# Component
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Components are the building blocks of the flows. They are made of inputs, outputs, and parameters that define their functionality, providing a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the LangChain [documentation](https://docs.langchain.com/docs/category/components) section.
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### Component's Features
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<div style={{ marginBottom: '20px' }}>
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During the flow creation process, you will notice handles (colored circles) attached to one or both sides of a component. These handles represent the availability to connect to other components, while their colors are type hints (hover over a handle to see connection details).</div>
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<div style={{ marginBottom: '20px' }}>
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For example, if you select a <code>ConversationChain</code> component, you will see orange <span style={{ color: 'orange' }}>o</span> and purple <span style={{ color: 'purple' }}>o</span> input handles. They indicate that this component accepts an LLM and a Memory component as inputs. The red asterisk <span style={{ color: 'red' }}>*</span> means that at least one input of that type is required.
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</div>
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<div style={{ marginBottom: '20px', display: 'flex', justifyContent: 'center' }}>
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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-compenent.png'),
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}}
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style={{ width: '100%', maxWidth: '800px', margin: '0 auto' }}
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/>
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</div>
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<div style={{ marginBottom: '20px' }}>
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On the top right corner, you will find the component status icon 🔴. Make the necessary connections, build the flow (⚡ zap icon on the bottom right of the canvas) and once the validation is completed, the status of each validated component should light green 🟢. Hover over the component status to reveal the outputs going through it in case of success, or the detected error in case of failure.
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</div>
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---
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### Component's Parameters
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LangFlow components can be edited in the component settings button. Hide parameters to reduce complexity and keep the canvas clean and intuitive for experimentation.
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<div style={{ marginBottom: '20px', display: 'flex', justifyContent: 'center' }}>
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<ReactPlayer playing controls url='/videos/langflow_parameters.mp4'
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/>
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</div>
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docs/docs/guidelines/features.mdx
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docs/docs/guidelines/features.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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# Features
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<div style={{ marginBottom: '20px' }}>
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When you click for New Project, you will see on the top left corner of the screen, some options such as <strong>Import</strong>, <strong>Export</strong>, <strong>Code</strong> and <strong>Save</strong>, as displayed in the image below:
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</div>
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<div style={{ marginBottom: '20px', display: 'flex', justifyContent: 'center' }}>
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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/features.png'),
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}}
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style={{ width: '100%', maxWidth: '800px', margin: '0 auto' }}
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/>
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</div>
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<div style={{ marginBottom: '20px' }}>
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Further down, we will explain each of these options.
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</div>
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---
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### Import and Export
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Flows can be exported and imported as JSON files.
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:::caution
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Watch out for API keys being stored in local files.
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:::
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---
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### Code
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The Code button shows snippets to use your flow as a Python object or an API.
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**Python Code**
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Through the LangFlow package, you can load a flow from a JSON file and use it as a LangChain object.
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```py
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from langflow import load_flow_from_json
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flow = load_flow_from_json("path/to/flow.json")
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# Now you can use it like any chain
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flow("Hey, have you heard of LangFlow?")
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```
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**API**
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Once you save a flow, the API endpoint is created with your latest changes. Click the "code" button to use that flow as an API. You can post-adjust component parameters using the global variable TWEAKS.
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The example below shows a Python script making a POST request to a local API endpoint, which gets a prediction based on the message input.
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<div style={{ marginBottom: '20px', display: 'flex', justifyContent: 'center' }}>
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<ReactPlayer playing controls url='/videos/langflow_api.mp4'
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/>
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</div>
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