[Docs] - Playground I/O, New Project button, and Python version (#2102)
* Doc which components affect Playground appearance (need review here for clarity) * Clearer instructions on where the New Project button is * Clearer instructions on Python >=3.10 version requirement
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@ -35,3 +35,21 @@ As long as you have a flow's environment variables set, you can run it by clicki
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>
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<ReactPlayer playing controls url="/videos/langflow_playground.mp4" />
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</div>
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## Playground I/O
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The Playground's appearance changes depending on what components are in your canvas.
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Adding or removing any of the below components modifies your Playground so you can monitor the inputs and outputs.
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* Chat Input
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* Text Input
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* Chat Output
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* Text Output
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* Records Output
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* Inspect Memory
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You can also select **Options** > **Logs** to see your flow's logs.
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For more information, see [Inputs and Outputs](../components/inputs-and-outputs.mdx).
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@ -6,13 +6,10 @@ import Admonition from "@theme/Admonition";
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# 📦 Install Langflow
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<Admonition type="info">
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Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space
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using this
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link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true),
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to create your own Langflow workspace in minutes.
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Langflow **requires** Python version 3.10 or greater.
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</Admonition>
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Langflow requires [Python >=3.10](https://www.python.org/downloads/release/python-3100/) and [pip](https://pypi.org/project/pip/) or [pipx](https://pipx.pypa.io/stable/installation/) to be installed on your system.
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Langflow **requires** [Python >=3.10](https://www.python.org/downloads/release/python-3100/) and [pip](https://pypi.org/project/pip/) or [pipx](https://pipx.pypa.io/stable/installation/) to be installed on your system.
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Install Langflow with pip:
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@ -10,6 +10,8 @@ This guide demonstrates how to build a basic prompt flow and modify that prompt
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## Prerequisites
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- [Python >=3.10](https://www.python.org/downloads/release/python-3100/) and [pip](https://pypi.org/project/pip/) or [pipx](https://pipx.pypa.io/stable/installation/)
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- [Langflow installed and running](./install-langflow.mdx)
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- [OpenAI API key](https://platform.openai.com)
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@ -13,7 +13,7 @@ In this guide, we will use Astra DB as a vector store to store and retrieve the
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<Admonition type="tip">
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This guide assumes that you have Langflow up and running. If you are new to
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Langflow, you can check out the [Getting Started](/) guide.
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Langflow, you can check out the [Getting Started](../getting-started/install-langflow.mdx) guide.
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</Admonition>
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TLDR;
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@ -75,9 +75,11 @@ Now we are all set to start building our RAG application using Astra DB and Lang
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If you haven't already, now is the time to launch Langflow. To make things easier, you can duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) which sets up a Langflow instance just for you.
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## Open the Vector Store RAG Project
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## Open the Vector Store RAG Project in Langflow
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To get started, click on the **New Project** button and look for the **Vector Store RAG** project. This will open a starter project with the necessary components to run a RAG application using Astra DB.
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Run Langflow and open the UI.
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In the Langflow dashboard, click the **New Project** button and select the **Vector Store RAG** project. This will open a starter project with the necessary components to run a RAG application using Astra DB.
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This project consists of two flows. The simpler one is the **Ingestion Flow** which is responsible for ingesting the documents into the Astra DB database.
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