diff --git a/docs/docs/administration/chat-interface.mdx b/docs/docs/administration/chat-interface.mdx
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-import ThemedImage from "@theme/ThemedImage";
-import useBaseUrl from "@docusaurus/useBaseUrl";
-import ZoomableImage from "/src/theme/ZoomableImage.js";
-import ReactPlayer from "react-player";
-
-# Chat Interface
-
-Langflow’s chat interface provides a user-friendly experience and functionality to interact with the model and customize the prompt. The sidebar brings options that allow users to view and edit pre-defined prompt variables. This feature facilitates quick experimentation by enabling the modification of variable values right in the chat.
-
-{" "}
-
-
-
-Notice that editing variables in the chat interface take place temporarily and won’t change their original value in the components once the chat is closed.
-
-{" "}
-
-
-
-To view the complete prompt in its original, structured format, click the "Display Prompt" option. This feature lets you see the prompt exactly as it entered the model.
-
-{" "}
-
-
-In the chat interface, you can redefine which variable should be interpreted as the chat input. This gives you control over these inputs and allows dynamic and creative interactions.
-
-{" "}
-
diff --git a/docs/docs/administration/collection.mdx b/docs/docs/administration/collection.mdx
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-import ThemedImage from '@theme/ThemedImage';
-import useBaseUrl from '@docusaurus/useBaseUrl';
-import ZoomableImage from '/src/theme/ZoomableImage.js';
-import ReactPlayer from 'react-player';
-
-# Collection
-
-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.
-
-
-
-
diff --git a/docs/docs/administration/components.mdx b/docs/docs/administration/components.mdx
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-import ThemedImage from "@theme/ThemedImage";
-import useBaseUrl from "@docusaurus/useBaseUrl";
-import ZoomableImage from "/src/theme/ZoomableImage.js";
-import ReactPlayer from "react-player";
-
-# Component
-
-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://python.langchain.com/docs/integrations/components) section.
-
-### Component's Features
-
-
- 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).
-
-
-
- For example, if you select a ConversationChain component, you
- will see orange o and purple{" "}
- o input handles. They indicate that
- this component accepts an LLM and a Memory component as inputs. The red
- asterisk * means that at least one input
- of that type is required.
-
-
-{" "}
-
-
-
-
- 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.
-
-
----
-
-### Component's Parameters
-
-Langflow components can be edited in the component settings button. Hide parameters to reduce complexity and keep the canvas clean and intuitive for experimentation.
-
-
-
-
diff --git a/docs/docs/administration/features.mdx b/docs/docs/administration/features.mdx
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-# Features
-
-
- When you click for New Project, you will see on the top left corner of the
- screen, some options such as Import, Export,{" "}
- Code and Save, as displayed in the image
- below:
-
-
-{" "}
-
-
-
-
- Further down, we will explain each of these options.
-
-
----
-
-### Import and Export
-
-Flows can be exported and imported as JSON files.
-
-
-Watch out for API keys being stored in local files.
-
-
-
----
-
-### Code
-
-The Code button shows snippets to use your flow as a Python object or an API.
-
-**Python Code**
-
-Through the Langflow package, you can run your flow from a JSON file. The example below shows how to run a flow from a JSON file.
-
-```python
-from langflow.load import run_flow_from_json
-
-results = run_flow_from_json("path/to/flow.json", input_value="Hello, World!")
-```
-
-**API**
-
-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.
-
-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.
-
-
-
-
-
-import ThemedImage from "@theme/ThemedImage";
-import useBaseUrl from "@docusaurus/useBaseUrl";
-import ZoomableImage from "/src/theme/ZoomableImage.js";
-import ReactPlayer from "react-player";
-import Admonition from "@theme/Admonition";