refactor: remove some preview references

This commit is contained in:
Rodrigo 2024-06-24 01:04:24 -03:00 • committed by Gabriel Luiz Freitas Almeida
commit 4e01178d1c
10 changed files with 26 additions and 57 deletions

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@ -8,7 +8,7 @@ import Admonition from "@theme/Admonition";
The **Chat Memory** component restores previous messages given a Session ID, which can be any string. The **Chat Memory** component restores previous messages given a Session ID, which can be any string.
This component is available under the **Helpers** tab of the Langflow preview. This component is available under the **Helpers** tab of the Langflow sidebar.
<div <div
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }} style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}

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@ -12,7 +12,7 @@ The **Combine Text** component concatenates two text inputs into a single chunk
Also, check out **Combine Texts (Unsorted)** as a similar alternative. Also, check out **Combine Texts (Unsorted)** as a similar alternative.
This component is available under the **Helpers** tab of the Langflow preview. This component is available under the **Helpers** tab of the Langflow sidebar.
<div <div
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }} style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}

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@ -19,9 +19,8 @@ In this guide, we will use Astra DB as a vector store to store and retrieve the
TLDR; TLDR;
- [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account) - [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account)
- Duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
- Create a new database, get a **Token** and the **API Endpoint** - Create a new database, get a **Token** and the **API Endpoint**
- Click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components - Start Langflow and click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components
- Import the project into Langflow by dropping it on the Workspace or My Collection page - Import the project into Langflow by dropping it on the Workspace or My Collection page
- Update the **Token** and **API Endpoint** in the **Astra DB** components - Update the **Token** and **API Endpoint** in the **Astra DB** components
- Update the OpenAI API key in the **OpenAI** components - Update the OpenAI API key in the **OpenAI** components
@ -71,16 +70,12 @@ Once your database is initialized, to the right of the page, you will see the _D
Now we are all set to start building our RAG application using Astra DB and Langflow. Now we are all set to start building our RAG application using Astra DB and Langflow.
## (Optional) Duplicate the Langflow 1.0 HuggingFace Space
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.
## Open the Vector Store RAG Project ## Open the Vector Store RAG Project
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. 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.
<ZoomableImage <ZoomableImage
alt="Docusaurus themed image" alt="Drag-and-drop"
sources={{ sources={{
light: "img/drag-and-drop-flow.png", light: "img/drag-and-drop-flow.png",
dark: "img/drag-and-drop-flow.png", dark: "img/drag-and-drop-flow.png",
@ -100,7 +95,7 @@ The ingestion flow consists of:
- **Astra DB** component that stores the text chunks in the Astra DB database - **Astra DB** component that stores the text chunks in the Astra DB database
<ZoomableImage <ZoomableImage
alt="Docusaurus themed image" alt="Astra Ingestion"
sources={{ sources={{
light: "img/astra-ingestion-flow.png", light: "img/astra-ingestion-flow.png",
dark: "img/astra-ingestion-flow.png", dark: "img/astra-ingestion-flow.png",
@ -122,7 +117,7 @@ Now, let's update the **Astra DB** and **Astra DB Search** components with the *
And run it! This will ingest the Text data from your file into the Astra DB database. And run it! This will ingest the Text data from your file into the Astra DB database.
<ZoomableImage <ZoomableImage
alt="Docusaurus themed image" alt="Astra Run"
sources={{ sources={{
light: "img/astra-ingestion-run.png", light: "img/astra-ingestion-run.png",
dark: "img/astra-ingestion-run.png", dark: "img/astra-ingestion-run.png",
@ -155,7 +150,7 @@ The RAG flow is a bit more complex. It consists of:
To run it all we have to do is click on the ⚡ _Run_ button and start interacting with your RAG application. To run it all we have to do is click on the ⚡ _Run_ button and start interacting with your RAG application.
<ZoomableImage <ZoomableImage
alt="Docusaurus themed image" alt="Astra RAG"
sources={{ sources={{
light: "img/astra-rag-flow-run.png", light: "img/astra-rag-flow-run.png",
dark: "img/astra-rag-flow-run.png", dark: "img/astra-rag-flow-run.png",
@ -168,7 +163,7 @@ This opens the Playground where you can chat your data.
Because this flow has a **Chat Input** and a **Text Output** component, the Panel displays a chat input at the bottom and the Extracted Chunks section on the left. Because this flow has a **Chat Input** and a **Text Output** component, the Panel displays a chat input at the bottom and the Extracted Chunks section on the left.
<ZoomableImage <ZoomableImage
alt="Docusaurus themed image" alt="Playground"
sources={{ sources={{
light: "img/astra-rag-flow-interaction-panel.png", light: "img/astra-rag-flow-interaction-panel.png",
dark: "img/astra-rag-flow-interaction-panel.png", dark: "img/astra-rag-flow-interaction-panel.png",
@ -179,7 +174,7 @@ Because this flow has a **Chat Input** and a **Text Output** component, the Pane
Once we interact with it we get a response and the Extracted Chunks section is updated with the retrieved data. Once we interact with it we get a response and the Extracted Chunks section is updated with the retrieved data.
<ZoomableImage <ZoomableImage
alt="Docusaurus themed image" alt="Astra Playground"
sources={{ sources={{
light: "img/astra-rag-flow-interaction-panel-interaction.png", light: "img/astra-rag-flow-interaction-panel-interaction.png",
dark: "img/astra-rag-flow-interaction-panel-interaction.png", dark: "img/astra-rag-flow-interaction-panel-interaction.png",

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@ -29,11 +29,13 @@ Its intuitive interface allows for easy manipulation of AI building blocks, enab
- [Langflow Workspace](/getting-started/workspace) - Learn more about the Langflow Workspace. - [Langflow Workspace](/getting-started/workspace) - Learn more about the Langflow Workspace.
<Admonition type="info"> {/* Mentions wrong link */}
Langflow is also available in HuggingFace Spaces. [Clone the space using this {/\* <Admonition type="info">
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) Langflow is also available in HuggingFace Spaces. [Clone the space using this
to run your own Langflow instance in minutes. link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
</Admonition> to run your own Langflow instance in minutes.
</Admonition> */}
## Learn more about Langflow 1.0 ## Learn more about Langflow 1.0

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@ -18,13 +18,6 @@ This article demonstrates how to use Langflow's prompt tools to issue basic prom
- [OpenAI API key created](https://platform.openai.com) - [OpenAI API key created](https://platform.openai.com)
<Admonition type="info">
Langflow is also available in HuggingFace Spaces. [Clone the space
using this
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
to create your own Langflow workspace in minutes.
</Admonition>
## Create the basic prompting project ## Create the basic prompting project
1. From the Langflow dashboard, click **New Project**. 1. From the Langflow dashboard, click **New Project**.
@ -62,4 +55,4 @@ This should be interesting...
The **Edit Prompt** window opens. The **Edit Prompt** window opens.
2. Change `Answer the user as if you were a pirate` to a different character, perhaps `Answer the user as if you were Harold Abelson.` 2. Change `Answer the user as if you were a pirate` to a different character, perhaps `Answer the user as if you were Harold Abelson.`
3. Run the basic prompting flow again. 3. Run the basic prompting flow again.
The response will be markedly different. The response will be markedly different.

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@ -14,12 +14,13 @@ Build a blog writer with OpenAI that uses URLs for reference content.
- [OpenAI API key created](https://platform.openai.com) - [OpenAI API key created](https://platform.openai.com)
<Admonition type="info"> {/\* <Admonition type="info">
Langflow is also available in HuggingFace Spaces. [Clone the space Langflow is also available in HuggingFace Spaces. [Clone the space
using this using this
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
to create your own Langflow workspace in minutes. to create your own Langflow workspace in minutes.
</Admonition>
</Admonition> */}
## Create the Blog Writer project ## Create the Blog Writer project

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@ -14,13 +14,6 @@ Build a question-and-answer chatbot with a document loaded from local memory.
- [OpenAI API key created](https://platform.openai.com) - [OpenAI API key created](https://platform.openai.com)
<Admonition type="info">
Langflow is also available in HuggingFace Spaces. [Clone the space
using this
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
to create your own Langflow workspace in minutes.
</Admonition>
## Create the Document QA project ## Create the Document QA project
1. From the Langflow dashboard, click **New Project**. 1. From the Langflow dashboard, click **New Project**.

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@ -14,13 +14,6 @@ This flow extends the [basic prompting flow](./basic-prompting) to include chat
- [OpenAI API key created](https://platform.openai.com) - [OpenAI API key created](https://platform.openai.com)
<Admonition type="info">
Langflow is also available in HuggingFace Spaces. [Clone the space
using this
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
to create your own Langflow workspace in minutes.
</Admonition>
## Create the memory chatbot project ## Create the memory chatbot project
1. From the Langflow dashboard, click **New Project**. 1. From the Langflow dashboard, click **New Project**.
@ -81,4 +74,4 @@ To store **Session ID** as a Langflow variable, in the **Session ID** field, cli
1. In the **Variable Name** field, enter a name like `customer_chat_emea`. 1. In the **Variable Name** field, enter a name like `customer_chat_emea`.
2. In the **Value** field, enter a value like `1B5EBD79-6E9C-4533-B2C8-7E4FF29E983B`. 2. In the **Value** field, enter a value like `1B5EBD79-6E9C-4533-B2C8-7E4FF29E983B`.
3. Click **Save Variable**. 3. Click **Save Variable**.
4. Apply this variable to **Chat Input**. 4. Apply this variable to **Chat Input**.

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@ -16,13 +16,6 @@ We've chosen [Astra DB](https://astra.datastax.com/signup?utm_source=langflow-pr
## Prerequisites ## Prerequisites
<Admonition type="info">
Langflow is also available in HuggingFace Spaces. [Clone the space
using this
link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
to create your own Langflow workspace in minutes.
</Admonition>
- [Langflow installed and running](../getting-started/install-langflow) - [Langflow installed and running](../getting-started/install-langflow)
- [OpenAI API key](https://platform.openai.com) - [OpenAI API key](https://platform.openai.com)

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@ -20,9 +20,8 @@ In this guide, we will use Astra DB as a vector store to store and retrieve the
TLDR; TLDR;
- [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account) - [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account)
- Duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true)
- Create a new database, get a **Token** and the **API Endpoint** - Create a new database, get a **Token** and the **API Endpoint**
- Click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components - Start Langflow and click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components
- Import the project into Langflow by dropping it on the Workspace or My Collection page - Import the project into Langflow by dropping it on the Workspace or My Collection page
- Update the **Token** and **API Endpoint** in the **Astra DB** components - Update the **Token** and **API Endpoint** in the **Astra DB** components
- Update the OpenAI API key in the **OpenAI** components - Update the OpenAI API key in the **OpenAI** components