jyapayne/langflow
1
0
Fork 0
Code Issues Pull requests Projects Releases 1 Packages Wiki Activity Actions

Fix and Enhance Modal, Button, and Layout Functionality (#2064)

Browse source 
#### Description

This pull request introduces several fixes and enhancements related to
modals, buttons, and layout elements within the application. The changes
improve the user experience by addressing bugs, enhancing functionality,
and refining UI components.

#### Summary of Changes

- **Modals:**
  - Added Submit buttons to every modal, except confirmation modals.
  - Fixed submitting issues on `storeApiKeyModal`.
  - Added a close button when the submit button is present.
  - Fixed padding on `deleteConfirmationModal`.

- **Node and Component Enhancements:**
  - Removed the pencil icon from the node name.
- Made node description editable by clicking once and changed the cursor
type.
  - Changed empty component behavior to open the New Project modal.
  - Fixed the node toolbar to allow moving the nodes.
  - Fixed Endpoint Name labeling.
  - Passed duplicate flow function to the main page.
  - Made folders visually more pleasing.
  - Fixed the tooltip that no longer needs removal of the portal.

- **UI and Layout Adjustments:**
  - Fixed bottom padding on settings pages.
  - Fixed scrolling not working in the global variables dropdown.
  - Disabled accordion when it is empty.
  - Removed shadow from card elements.
  - Added a description column to the advanced tab.
  - Implemented unselect on escape.
- Fixed classes and layout for sidebar buttons, ensuring they don't look
strange and behave consistently.
- Fixed button classes to allow loading indicators and ensure proper
sizing and functionality.
  - Modularized loading on buttons.

- **General Fixes and Improvements:**
  - Changed message of the terminal to "Run Langflow".
- Fixed save functionality to use user-provided API keys instead of
default ones.
- Ensured button components can handle multiple children and look
correct.
  - Added icons to various UI elements.
  - Fixed ID scrolling issue when clicking from Store.
  - Removed extra space caused by an unnecessary div element.
- Returned the loader to default settings and ensured buttons work with
`asChild`.

#### Additional Changes
- Merged the remote-tracking branch `origin/dev` into `fix/minor_bugs`
on multiple occasions to keep the branch up-to-date with the latest
developments.

#### Notes

- Please review the changes related to button classes carefully, as they
impact multiple components.
- Further UI enhancements are planned for the next iteration.
This commit is contained in:
Lucas Oliveira 2024-06-05 19:14:32 +02:00 • committed by GitHub
commit 6b41460bf2
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
154 changed files with 14303 additions and 14226 deletions
Download patch file Download diff file Expand all files Collapse all files

77
docs/docs/components/custom.mdx
View file

@ -3,7 +3,8 @@ import Admonition from "@theme/Admonition";
# Custom Components
<Admonition type="info" label="Tip">
Read the [Custom Component Guidelines](../administration/custom-component) for detailed information on custom components.
Read the [Custom Component Guidelines](../administration/custom-component) for
detailed information on custom components.
</Admonition>
Custom components let you extend Langflow by creating reusable and configurable components from a Python script.
@ -31,57 +32,60 @@ This class is the foundation for creating custom components. It allows users to
The following types are supported in the build method:
| Supported Types |
| --------------------------------------------------------- |
| _`str`_, _`int`_, _`float`_, _`bool`_, _`list`_, _`dict`_ |
| _`langflow.field_typing.NestedDict`_ |
| _`langflow.field_typing.Prompt`_ |
| _`langchain.chains.base.Chain`_ |
| _`langchain.PromptTemplate`_ |
| Supported Types |
| ----------------------------------------------------------------- |
| _`str`_, _`int`_, _`float`_, _`bool`_, _`list`_, _`dict`_ |
| _`langflow.field_typing.NestedDict`_ |
| _`langflow.field_typing.Prompt`_ |
| _`langchain.chains.base.Chain`_ |
| _`langchain.PromptTemplate`_ |
| _`from langchain.schema.language_model import BaseLanguageModel`_ |
| _`langchain.Tool`_ |
| _`langchain.document_loaders.base.BaseLoader`_ |
| _`langchain.schema.Document`_ |
| _`langchain.text_splitters.TextSplitter`_ |
| _`langchain.vectorstores.base.VectorStore`_ |
| _`langchain.embeddings.base.Embeddings`_ |
| _`langchain.schema.BaseRetriever`_ |
| _`langchain.Tool`_ |
| _`langchain.document_loaders.base.BaseLoader`_ |
| _`langchain.schema.Document`_ |
| _`langchain.text_splitters.TextSplitter`_ |
| _`langchain.vectorstores.base.VectorStore`_ |
| _`langchain.embeddings.base.Embeddings`_ |
| _`langchain.schema.BaseRetriever`_ |
The difference between _`dict`_ and _`langflow.field_typing.NestedDict`_ is that one adds a simple key-value pair field, while the other opens a more robust dictionary editor.
<Admonition type="info">
Use the `Prompt` type by adding **kwargs to the build method.
If you want to add the values of the variables to the template you defined, format the `PromptTemplate` inside the `CustomComponent` class.
Use the `Prompt` type by adding **kwargs to the build method. If you want to
add the values of the variables to the template you defined, format the
`PromptTemplate` inside the `CustomComponent` class.
</Admonition>
<Admonition type="info">
Use base Python types without a handle by default. To add handles, use the `input_types` key in the `build_config` method.
Use base Python types without a handle by default. To add handles, use the
`input_types` key in the `build_config` method.
</Admonition>
**build_config:** Defines the configuration fields of the component. This method returns a dictionary where each key represents a field name and each value defines the field's behavior.
Supported keys for configuring fields:
| Key | Description |
| --------------------- | --------------------------------------------------- |
| `is_list` | Boolean indicating if the field can hold multiple values. |
| `options` | Dropdown menu options. |
| `multiline` | Boolean indicating if a field allows multiline input. |
| `input_types` | Allows connection handles for string fields. |
| `display_name` | Field name displayed in the UI. |
| `advanced` | Hides the field in the default UI view. |
| `password` | Masks input, useful for sensitive data. |
| `required` | Overrides the default behavior to make a field mandatory. |
| `info` | Tooltip for the field. |
| `file_types` | Accepted file types, useful for file fields. |
| `range_spec` | Defines valid ranges for float fields. |
| `title_case` | Boolean that controls field name capitalization. |
| `refresh_button` | Adds a refresh button that updates field values. |
| `real_time_refresh` | Updates the configuration as field values change. |
| `field_type` | Automatically set based on the build method's type hint. |
| Key | Description |
| ------------------- | --------------------------------------------------------- |
| `is_list` | Boolean indicating if the field can hold multiple values. |
| `options` | Dropdown menu options. |
| `multiline` | Boolean indicating if a field allows multiline input. |
| `input_types` | Allows connection handles for string fields. |
| `display_name` | Field name displayed in the UI. |
| `advanced` | Hides the field in the default UI view. |
| `password` | Masks input, useful for sensitive data. |
| `required` | Overrides the default behavior to make a field mandatory. |
| `info` | Tooltip for the field. |
| `file_types` | Accepted file types, useful for file fields. |
| `range_spec` | Defines valid ranges for float fields. |
| `title_case` | Boolean that controls field name capitalization. |
| `refresh_button` | Adds a refresh button that updates field values. |
| `real_time_refresh` | Updates the configuration as field values change. |
| `field_type` | Automatically set based on the build method's type hint. |
<Admonition type="info" label="Tip">
Use the `update_build_config` method to dynamically update configurations based on field values.
Use the `update_build_config` method to dynamically update configurations
based on field values.
</Admonition>
## Additional methods and attributes
@ -99,4 +103,3 @@ The `CustomComponent` class also provides helpful methods for specific tasks (e.
- `status`: Shows values from the `build` method, useful for debugging.
- `field_order`: Controls the display order of fields.
- `icon`: Sets the canvas display icon.

2
docs/docs/examples/chat-memory.mdx
View file

@ -14,4 +14,4 @@ This component is available under the **Helpers** tab of the Langflow preview.
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/chat_memory.mp4" />
</div>
</div>

2
docs/docs/examples/combine-text.mdx
View file

@ -18,4 +18,4 @@ This component is available under the **Helpers** tab of the Langflow preview.
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/combine_text.mp4" />
</div>
</div>

2
docs/docs/examples/create-record.mdx
View file

@ -14,4 +14,4 @@ The **Create Record** component allows you to dynamically create a `Record` from
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/create_record.mp4" />
</div>
</div>

2
docs/docs/examples/pass.mdx
View file

@ -14,4 +14,4 @@ The **Pass** component enables you to ignore one input and move forward with ano
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/pass.mp4" />
</div>
</div>

2
docs/docs/examples/store-message.mdx
View file

@ -14,4 +14,4 @@ The **Message History** component can then be used to retrieve stored messages.
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/store_message.mp4" />
</div>
</div>

2
docs/docs/examples/sub-flow.mdx
View file

@ -12,4 +12,4 @@ The **Sub Flow** component enables a user to select a previously built flow and
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/sub_flow.mp4" />
</div>
</div>

2
docs/docs/examples/text-operator.mdx
View file

@ -12,4 +12,4 @@ The **Text Operator** component simplifies logic. It evaluates the results from
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/text_operator.mp4" />
</div>
</div>

18
docs/docs/getting-started/canvas.mdx
View file

@ -56,7 +56,8 @@ Components are the building blocks of flows. They consist of inputs, outputs, an
<div style={{ marginBottom: "20px" }}>
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. Hover over a handle to see connection details.
availability to connect to other components. Hover over a handle to see
connection details.
</div>
<div style={{ marginBottom: "20px" }}>
@ -85,6 +86,7 @@ Build the flow by clicking the **![Playground icon](/logos/botmessage.svg)Playgr
Once the validation is complete, the status of each validated component should turn green (![Status icon](/logos/greencheck.svg)).
To debug, hover over the component status to see the outputs.
</div>
---
@ -196,6 +198,7 @@ curl -X POST \
```
Result:
```
{"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"}]}]}%
```
@ -231,9 +234,10 @@ A collection is a snapshot of flows available in a database.
Collections can be downloaded to local storage and uploaded for future use.
<div style={{ marginBottom: '20px', display: 'flex', justifyContent: 'center' }}>
<ReactPlayer playing controls url='/videos/langflow_collection.mp4'
/>
<div
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
>
<ReactPlayer playing controls url="/videos/langflow_collection.mp4" />
</div>
## Project
@ -276,9 +280,3 @@ To see options for your project, in the upper left corner of the canvas, select
**Export** - Download your current project to your local machine as a `.json` file.
**Undo** or **Redo** - Undo or redo your last action.

14
docs/docs/getting-started/flows-components-collections.mdx
View file

@ -1,7 +1,7 @@
import ThemedImage from '@theme/ThemedImage';
import useBaseUrl from '@docusaurus/useBaseUrl';
import ZoomableImage from '/src/theme/ZoomableImage.js';
import ReactPlayer from 'react-player';
import ThemedImage from "@theme/ThemedImage";
import useBaseUrl from "@docusaurus/useBaseUrl";
import ZoomableImage from "/src/theme/ZoomableImage.js";
import ReactPlayer from "react-player";
# 🖥️ Flows, components, collections, and projects
@ -17,10 +17,4 @@ A [project](#project) can be a component or a flow. Projects are saved as part o
For example, the **OpenAI LLM** is a **component** of the **Basic prompting** flow, and the **flow** is stored in a **collection**.
## Component

15
docs/docs/getting-started/install-langflow.mdx
View file

@ -6,33 +6,40 @@ import Admonition from "@theme/Admonition";
# 📦 Install Langflow
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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 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.
Install Langflow with pip:
```bash
python -m pip install langflow -U
```
Install Langflow with pipx:
```bash
pipx install langflow --python python3.10 --fetch-missing-python
```
Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually.
Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually.
## Install Langflow pre-release
To install a pre-release version of Langflow:
pip:
```bash
python -m pip install langflow --pre --force-reinstall
```
pipx:
```bash
pipx install langflow --python python3.10 --fetch-missing-python --pip-args="--pre --force-reinstall"
```
@ -52,11 +59,13 @@ python -m langflow --help
## ⛓️ Run Langflow
1. To run Langflow, enter the following command.
```bash
python -m langflow run
```
2. Confirm that a local Langflow instance starts by visiting `http://127.0.0.1:7860` in a Chromium-based browser.
```bash
│ Welcome to ⛓ Langflow │
│ │
@ -83,4 +92,4 @@ You'll be presented with the following screen:
style={{ width: "100%", margin: "20px auto" }}
/>
Name your Space, define the visibility (Public or Private), and click on **Duplicate Space** to start the installation process. When installation is finished, you'll be redirected to the Space's main page to start using Langflow right away!
Name your Space, define the visibility (Public or Private), and click on **Duplicate Space** to start the installation process. When installation is finished, you'll be redirected to the Space's main page to start using Langflow right away!

33
docs/docs/getting-started/quickstart.mdx
View file

@ -10,12 +10,15 @@ This guide demonstrates how to build a basic prompt flow and modify that prompt
## Prerequisites
* [Langflow installed and running](./install-langflow.mdx)
- [Langflow installed and running](./install-langflow.mdx)
* [OpenAI API key](https://platform.openai.com)
- [OpenAI API key](https://platform.openai.com)
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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>
## Hello World - Basic Prompting
@ -44,25 +47,25 @@ Examine the **Prompt** component. The **Template** field instructs the LLM to `A
This should be interesting...
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
## Run the basic prompting flow
1. Click the **Run** button.
The **Interaction Panel** opens, where you can chat with your bot.
The **Interaction Panel** opens, where you can chat with your bot.
2. Type a message and press Enter.
And... Ahoy! 🏴‍☠️
The bot responds in a piratical manner!
And... Ahoy! 🏴‍☠️
The bot responds in a piratical manner!
## Modify the prompt for a different result
1. To modify your prompt results, in the **Prompt** template, click the **Template** field.
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.`
3. Run the basic prompting flow again.
The response will be markedly different.
The response will be markedly different.
## Next steps
@ -72,8 +75,6 @@ By adding Langflow components to your flow, you can create all sorts of interest
Here are a couple of examples:
* [Memory chatbot](/starter-projects/memory-chatbot.mdx)
* [Blog writer](/starter-projects/blog-writer.mdx)
* [Document QA](/starter-projects/document-qa.mdx)
- [Memory chatbot](/starter-projects/memory-chatbot.mdx)
- [Blog writer](/starter-projects/blog-writer.mdx)
- [Document QA](/starter-projects/document-qa.mdx)

5
docs/docs/index.mdx
View file

@ -29,7 +29,10 @@ Its intuitive interface allows for easy manipulation of AI building blocks, enab
- [Langflow Canvas](/getting-started/canvas) - Learn more about the Langflow canvas.
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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>
## Learn more about Langflow 1.0

10
docs/docs/integrations/notion/add-content-to-page.md
View file

@ -16,7 +16,7 @@ The `AddContentToPage` component enables you to:
- Convert markdown text to Notion blocks.
- Append the converted blocks to a specified Notion page.
- Seamlessly integrate Notion content creation into Langflow workflows.
</Admonition>
</Admonition>
## Component Usage
@ -105,12 +105,12 @@ class NotionPageCreator(CustomComponent):
Example of using the `AddContentToPage` component in a Langflow flow using Markdown as input:
<ZoomableImage
alt="NotionDatabaseProperties Flow Example"
sources={{
alt="NotionDatabaseProperties Flow Example"
sources={{
light: "img/notion/AddContentToPage_flow_example.png",
dark: "img/notion/AddContentToPage_flow_example.png",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
In this example, the `AddContentToPage` component connects to a `MarkdownLoader` component to provide the markdown text input. The converted Notion blocks are appended to the specified Notion page using the provided `block_id` and `notion_secret`.
@ -131,8 +131,8 @@ The `AddContentToPage` component is a powerful tool for integrating Notion conte
## Troubleshooting
If you encounter any issues while using the `AddContentToPage` component, consider the following:
- Verify the Notion integration token’s validity and permissions.
- Check the Notion API documentation for updates.
- Ensure markdown text is properly formatted.
- Double-check the `block_id` for correctness.

6
docs/docs/integrations/notion/intro.md
View file

@ -8,12 +8,12 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
The Notion integration in Langflow enables seamless connectivity with Notion databases, pages, and users, facilitating automation and improving productivity.
<ZoomableImage
alt="Notion Components in Langflow"
sources={{
alt="Notion Components in Langflow"
sources={{
light: "img/notion/notion_bundle.jpg",
dark: "img/notion/notion_bundle.jpg",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
#### <a target="\_blank" href="json_files/Notion_Components_bundle.json" download>Download Notion Components Bundle</a>

6
docs/docs/integrations/notion/list-database-properties.md
View file

@ -41,7 +41,7 @@ class NotionDatabaseProperties(CustomComponent):
description = "Retrieve properties of a Notion database."
documentation: str = "https://docs.langflow.org/integrations/notion/list-database-properties"
icon = "NotionDirectoryLoader"
def build_config(self):
return {
"database_id": {
@ -80,6 +80,7 @@ class NotionDatabaseProperties(CustomComponent):
```
## Example Usage
<Admonition type="info" title="Example Usage">
Here's an example of how you can use the `NotionDatabaseProperties` component in a Langflow flow:
@ -110,6 +111,7 @@ Feel free to explore the capabilities of the `NotionDatabaseProperties` componen
## Troubleshooting
If you encounter any issues while using the `NotionDatabaseProperties` component, consider the following:
- Verify that the Notion integration token is valid and has the required permissions.
- Check the database ID to ensure it matches the intended Notion database.
- Inspect the response from the Notion API for any error messages or status codes that may indicate the cause of the issue.
- Inspect the response from the Notion API for any error messages or status codes that may indicate the cause of the issue.

13
docs/docs/integrations/notion/list-pages.md
View file

@ -140,16 +140,17 @@ class NotionListPages(CustomComponent):
<Admonition type="info" title="Example Usage">
## Example Usage
Here's an example of how you can use the `NotionListPages` component in a Langflow flow and passing to the Prompt component:
<ZoomableImage
alt="NotionListPages
Flow Example"
sources={{
alt="NotionListPages
Flow Example"
sources={{
light: "img/notion/NotionListPages_flow_example.png",
dark: "img/notion/NotionListPages_flow_example_dark.png",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
In this example, the `NotionListPages` component is used to retrieve specific pages from a Notion database based on the provided filters and sorting options. The retrieved data can then be processed further in the subsequent components of the flow.
@ -157,7 +158,7 @@ In this example, the `NotionListPages` component is used to retrieve specific pa
## Best Practices
When using the `NotionListPages
When using the `NotionListPages
` component, consider the following best practices:
- Ensure that you have a valid Notion integration token with the necessary permissions to query the desired database.
@ -171,7 +172,7 @@ We encourage you to explore the capabilities of the `NotionListPages
## Troubleshooting
If you encounter any issues while using the `NotionListPages` component, consider the following:
If you encounter any issues while using the `NotionListPages` component, consider the following:
- Double-check that the `notion_secret` and `database_id` are correct and valid.
- Verify that the `query_payload` JSON string is properly formatted and contains valid filtering and sorting options.

16
docs/docs/integrations/notion/list-users.md
View file

@ -15,7 +15,7 @@ The `NotionUserList` component retrieves users from Notion. It provides a conven
- Retrieve user data from Notion
- Access user information such as ID, type, name, and avatar URL
- Integrate Notion user data seamlessly into your Langflow workflows
</Admonition>
</Admonition>
## Component Usage
@ -94,34 +94,34 @@ class NotionUserList(CustomComponent):
```
## Example Usage
<Admonition type="info" title="Example Usage">
Here's an example of how you can use the `NotionUserList` component in a Langflow flow and passing the outputs to the Prompt component:
<ZoomableImage
alt="NotionUserList Flow Example"
sources={{
alt="NotionUserList Flow Example"
sources={{
light: "img/notion/NotionUserList_flow_example.png",
dark: "img/notion/NotionUserList_flow_example_dark.png",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
</Admonition>
## Best Practices
When using the `NotionUserList` component, consider the following best practices:
When using the `NotionUserList` component, consider the following best practices:
- Ensure that you have a valid Notion integration token with the necessary permissions to retrieve user data.
- Handle the retrieved user data securely and in compliance with Notion's API usage guidelines.
The `NotionUserList` component provides a seamless way to integrate Notion user data into your Langflow workflows. By leveraging this component, you can easily retrieve and utilize user information from Notion, enhancing the capabilities of your Langflow applications. Feel free to explore and experiment with the `NotionUserList` component to unlock new possibilities in your Langflow projects!
## Troubleshooting
If you encounter any issues while using the `NotionUserList` component, consider the following:
If you encounter any issues while using the `NotionUserList` component, consider the following:
- Double-check that your Notion integration token is valid and has the required permissions.
- Verify that you have installed the necessary dependencies (`requests`) for the component to function properly.
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.

12
docs/docs/integrations/notion/page-content-viewer.md
View file

@ -11,7 +11,7 @@ The `NotionPageContent` component retrieves the content of a Notion page as plai
<Admonition type="tip" title="Component Functionality">
The `NotionPageContent` component enables you to:
The `NotionPageContent` component enables you to:
- Retrieve the content of a Notion page as plain text
- Extract text from various block types, including paragraphs, headings, lists, and more
@ -114,18 +114,18 @@ class NotionPageContent(CustomComponent):
Here's an example of how you can use the `NotionPageContent` component in a Langflow flow:
<ZoomableImage
alt="NotionPageContent Flow Example"
sources={{
alt="NotionPageContent Flow Example"
sources={{
light: "img/notion/NotionPageContent_flow_example.png",
dark: "img/notion/NotionPageContent_flow_example_dark.png",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
</Admonition>
## Best Practices
When using the `NotionPageContent` component, consider the following best practices:
When using the `NotionPageContent` component, consider the following best practices:
- Ensure that you have the necessary permissions to access the Notion page you want to retrieve.
- Keep your Notion integration token secure and avoid sharing it publicly.
@ -135,7 +135,7 @@ The `NotionPageContent` component provides a seamless way to integrate Notion pa
## Troubleshooting
If you encounter any issues while using the `NotionPageContent` component, consider the following:
If you encounter any issues while using the `NotionPageContent` component, consider the following:
- Double-check that you have provided the correct Notion page ID.
- Verify that your Notion integration token is valid and has the necessary permissions.

10
docs/docs/integrations/notion/page-create.md
View file

@ -97,16 +97,17 @@ class NotionPageCreator(CustomComponent):
```
## Example Usage
<Admonition type="info" title="Example Usage">
Here's an example of how to use the `NotionPageCreator` component in a Langflow flow:
<ZoomableImage
alt="NotionPageCreator Flow Example"
sources={{
alt="NotionPageCreator Flow Example"
sources={{
light: "img/notion/NotionPageCreator_flow_example.png",
dark: "img/notion/NotionPageCreator_flow_example_dark.png",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
</Admonition>
@ -124,6 +125,7 @@ The `NotionPageCreator` component simplifies the process of creating pages in a
## Troubleshooting
If you encounter any issues while using the `NotionPageCreator` component, consider the following:
- Double-check that the `database_id` and `notion_secret` inputs are correct and valid.
- Verify that the `properties` input is properly formatted as a JSON string and matches the structure of your Notion database.
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.
- Check the Notion API documentation for any updates or changes that may affect the component's functionality.

7
docs/docs/integrations/notion/page-update.md
View file

@ -109,12 +109,12 @@ Let's break down the key parts of this component:
Here's an example of how to use the `NotionPageUpdate` component in a Langflow flow using:
<ZoomableImage
alt="NotionPageUpdate Flow Example"
sources={{
alt="NotionPageUpdate Flow Example"
sources={{
light: "img/notion/NotionPageUpdate_flow_example.png",
dark: "img/notion/NotionPageUpdate_flow_example_dark.png",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
</Admonition>
@ -128,7 +128,6 @@ When using the `NotionPageUpdate` component, consider the following best practic
By leveraging the `NotionPageUpdate` component in Langflow, you can easily integrate updating Notion page properties into your language model workflows and build powerful applications that extend Langflow's capabilities.
## Troubleshooting
If you encounter any issues while using the `NotionPageUpdate` component, consider the following:

7
docs/docs/integrations/notion/search.md
View file

@ -146,16 +146,17 @@ class NotionSearch(CustomComponent):
```
## Example Usage
<Admonition type="info" title="Example Usage">
Here's an example of how you can use the `NotionSearch` component in a Langflow flow:
<ZoomableImage
alt="NotionSearch Flow Example"
sources={{
alt="NotionSearch Flow Example"
sources={{
light: "img/notion/NotionSearch_flow_example.png",
dark: "img/notion/NotionSearch_flow_example_dark.png",
}}
style={{ width: "100%", margin: "20px 0" }}
style={{ width: "100%", margin: "20px 0" }}
/>
In this example, the `NotionSearch` component is used to search for pages and databases in Notion based on the provided query and filter criteria. The retrieved data can then be processed further in the subsequent components of the flow.

1
docs/docs/integrations/notion/setup.md
View file

@ -76,4 +76,3 @@ Refer to the individual component documentation for more details on how to use e
- [Notion Integration Capabilities](https://developers.notion.com/reference/capabilities)
If you encounter any issues or have questions, please reach out to our support team or consult the Langflow community forums.

9
docs/docs/migration/possible-installation-issues.mdx
View file

@ -25,11 +25,11 @@ ModuleNotFoundError: No module named 'langflow.__main__'
There are two possible reasons for this error:
1. You've installed Langflow using _`pip install langflow`_ but you already had a previous version of Langflow installed in your system.
In this case, you might be running the wrong executable.
To solve this issue, run the correct executable by running _`python -m langflow run`_ instead of _`langflow run`_.
If that doesn't work, try uninstalling and reinstalling Langflow with _`python -m pip install langflow --pre -U`_.
In this case, you might be running the wrong executable.
To solve this issue, run the correct executable by running _`python -m langflow run`_ instead of _`langflow run`_.
If that doesn't work, try uninstalling and reinstalling Langflow with _`python -m pip install langflow --pre -U`_.
2. Some version conflicts might have occurred during the installation process.
Run _`python -m pip install langflow --pre -U --force-reinstall`_ to reinstall Langflow and its dependencies.
Run _`python -m pip install langflow --pre -U --force-reinstall`_ to reinstall Langflow and its dependencies.
## _`Something went wrong running migrations. Please, run 'langflow migration --fix'`_
@ -45,4 +45,3 @@ There are two possible reasons for this error:
This error can occur during Langflow upgrades when the new version can't override `langflow-pre.db` in `.cache/langflow/`. Clearing the cache removes this file but will also erase your settings.
If you wish to retain your files, back them up before clearing the folder.

27
docs/docs/starter-projects/basic-prompting.mdx
View file

@ -14,12 +14,15 @@ This article demonstrates how to use Langflow's prompt tools to issue basic prom
## Prerequisites
* [Langflow installed and running](../getting-started/install-langflow.mdx)
- [Langflow installed and running](../getting-started/install-langflow.mdx)
* [OpenAI API key created](https://platform.openai.com)
- [OpenAI API key created](https://platform.openai.com)
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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
@ -42,25 +45,21 @@ Examine the **Prompt** component. The **Template** field instructs the LLM to `A
This should be interesting...
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
## Run the basic prompting flow
1. Click the **Run** button.
The **Interaction Panel** opens, where you can converse with your bot.
The **Interaction Panel** opens, where you can converse with your bot.
2. Type a message and press Enter.
The bot responds in a markedly piratical manner!
The bot responds in a markedly piratical manner!
## Modify the prompt for a different result
1. To modify your prompt results, in the **Prompt** template, click the **Template** field.
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.`
3. Run the basic prompting flow again.
The response will be markedly different.
The response will be markedly different.

22
docs/docs/starter-projects/blog-writer.mdx
View file

@ -10,12 +10,15 @@ Build a blog writer with OpenAI that uses URLs for reference content.
## Prerequisites
* [Langflow installed and running](../getting-started/install-langflow.mdx)
- [Langflow installed and running](../getting-started/install-langflow.mdx)
* [OpenAI API key created](https://platform.openai.com)
- [OpenAI API key created](https://platform.openai.com)
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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 Blog Writer project
@ -36,6 +39,7 @@ Build a blog writer with OpenAI that uses URLs for reference content.
This flow creates a one-shot prompt flow with **Prompt**, **OpenAI**, and **Chat Output** components, and augments the flow with reference content and instructions from the **URL** and **Instructions** components.
The **Prompt** component's default **Template** field looks like this:
```bash
Reference 1:
@ -59,16 +63,16 @@ The `{instructions}` value is received from the **Value** field of the **Instruc
The `reference_1` and `reference_2` values are received from the **URL** fields of the **URL** components.
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
## Run the Blog Writer flow
1. Click the **Run** button.
The **Interaction Panel** opens, where you can run your one-shot flow.
The **Interaction Panel** opens, where you can run your one-shot flow.
2. Click the **Lighting Bolt** icon to run your flow.
3. The **OpenAI** component constructs a blog post with the **URL** items as context.
The default **URL** values are for web pages at `promptingguide.ai`, so your blog post will be about prompting LLMs.
The default **URL** values are for web pages at `promptingguide.ai`, so your blog post will be about prompting LLMs.
To write about something different, change the values in the **URL** components, and see what the LLM constructs.
To write about something different, change the values in the **URL** components, and see what the LLM constructs.

34
docs/docs/starter-projects/document-qa.mdx
View file

@ -10,12 +10,15 @@ Build a question-and-answer chatbot with a document loaded from local memory.
## Prerequisites
* [Langflow installed and running](../getting-started/install-langflow.mdx)
- [Langflow installed and running](../getting-started/install-langflow.mdx)
* [OpenAI API key created](https://platform.openai.com)
- [OpenAI API key created](https://platform.openai.com)
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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
@ -39,24 +42,27 @@ The **Prompt** component is instructed to answer questions based on the contents
Including a file with the prompt gives the **OpenAI** component context it may not otherwise have access to.
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
5. To select a document to load, in the **Files** component, click within the **Path** field.
1. Select a local file, and then click **Open**.
2. The file name appears in the field.
<Admonition type="tip">
The file must be of an extension type listed [here](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/base/data/utils.py#L13).
</Admonition>
1. Select a local file, and then click **Open**.
2. The file name appears in the field.
<Admonition type="tip">
The file must be of an extension type listed
[here](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/base/data/utils.py#L13).
</Admonition>
## Run the Document QA flow
1. Click the **Run** button.
The **Interaction Panel** opens, where you can converse with your bot.
The **Interaction Panel** opens, where you can converse with your bot.
2. Type a message and press Enter.
For this example, we loaded an error log `.txt` file and asked, "What went wrong?"
The bot responded:
For this example, we loaded an error log `.txt` file and asked, "What went wrong?"
The bot responded:
```
The issue occurred during the execution of migrations in the application. Specifically, an error was raised by the Alembic library, indicating that new upgrade operations were detected that had not been accounted for in the existing migration scripts. The operation in question involved modifying the nullable property of a column (apikey, created_at) in the database, with details about the existing type (DATETIME()), existing server default, and other properties.
```

24
docs/docs/starter-projects/memory-chatbot.mdx
View file

@ -10,12 +10,15 @@ This flow extends the [basic prompting flow](./basic-prompting.mdx) to include c
## Prerequisites
* [Langflow installed and running](../getting-started/install-langflow.mdx)
- [Langflow installed and running](../getting-started/install-langflow.mdx)
* [OpenAI API key created](https://platform.openai.com)
- [OpenAI API key created](https://platform.openai.com)
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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
@ -43,16 +46,16 @@ This chatbot is augmented with the **Chat Memory** component, which stores messa
The **Chat History** component gives the **OpenAI** component a memory of previous questions.
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
## Run the memory chatbot flow
1. Click the **Run** button.
The **Interaction Panel** opens, where you can converse with your bot.
The **Interaction Panel** opens, where you can converse with your bot.
2. Type a message and press Enter.
The bot will respond according to the template in the **Prompt** component.
The bot will respond according to the template in the **Prompt** component.
3. Type more questions. In the **Outputs** log, your queries are logged in order. Up to 5 queries are stored by default. Try asking `What is the first subject I asked you about?` to see where the LLM's memory disappears.
## Modify the Session ID field to have multiple conversations
@ -65,11 +68,11 @@ You can demonstrate this by modifying the **Session ID** value to switch between
1. In the **Session ID** field of the **Chat Memory** and **Chat Input** components, change the **Session ID** value from `MySessionID` to `AnotherSessionID`.
2. Click the **Run** button to run your flow.
In the **Interaction Panel**, you will have a new conversation. (You may need to clear the cache with the **Eraser** button).
In the **Interaction Panel**, you will have a new conversation. (You may need to clear the cache with the **Eraser** button).
3. Type a few questions to your bot.
4. In the **Session ID** field of the **Chat Memory** and **Chat Input** components, change the **Session ID** value back to `MySessionID`.
5. Run your flow.
The **Outputs** log of the **Interaction Panel** displays the history from your initial chat with `MySessionID`.
The **Outputs** log of the **Interaction Panel** displays the history from your initial chat with `MySessionID`.
## Store Session ID as a Langflow variable
@ -79,4 +82,3 @@ To store **Session ID** as a Langflow variable, in the **Session ID** field, cli
2. In the **Value** field, enter a value like `1B5EBD79-6E9C-4533-B2C8-7E4FF29E983B`.
3. Click **Save Variable**.
4. Apply this variable to **Chat Input**.

59
docs/docs/starter-projects/vector-store-rag.mdx
View file

@ -17,16 +17,19 @@ We've chosen [Astra DB](https://astra.datastax.com/signup?utm_source=langflow-pr
## Prerequisites
<Admonition type="info">
Langflow v1.0 alpha 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.
Langflow v1.0 alpha 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.mdx)
- [Langflow installed and running](../getting-started/install-langflow.mdx)
* [OpenAI API key](https://platform.openai.com)
- [OpenAI API key](https://platform.openai.com)
* [An Astra DB vector database created](https://docs.datastax.com/en/astra-db-serverless/get-started/quickstart.html) with:
* Application token (`AstraCS:WSnyFUhRxsrg…​`)
* API endpoint (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`)
- [An Astra DB vector database created](https://docs.datastax.com/en/astra-db-serverless/get-started/quickstart.html) with:
- Application token (`AstraCS:WSnyFUhRxsrg…​`)
- API endpoint (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`)
## Create the vector store RAG project
@ -49,38 +52,40 @@ The **ingestion** flow (bottom of the screen) populates the vector store with da
It ingests data from a file (**File**), splits it into chunks (**Recursive Character Text Splitter**), indexes it in Astra DB (**Astra DB**), and computes embeddings for the chunks (**OpenAI Embeddings**).
This forms a "brain" for the query flow.
The **query** flow (top of the screen) allows users to chat with the embedded vector store data. It's a little more complex:
The **query** flow (top of the screen) allows users to chat with the embedded vector store data. It's a little more complex:
* **Chat Input** component defines where to put the user input coming from the Playground.
* **OpenAI Embeddings** component generates embeddings from the user input.
* **Astra DB Search** component retrieves the most relevant Records from the Astra DB database.
* **Text Output** component turns the Records into Text by concatenating them and also displays it in the Playground.
* **Prompt** component takes in the user input and the retrieved Records as text and builds a prompt for the OpenAI model.
* **OpenAI** component generates a response to the prompt.
* **Chat Output** component displays the response in the Playground.
- **Chat Input** component defines where to put the user input coming from the Playground.
- **OpenAI Embeddings** component generates embeddings from the user input.
- **Astra DB Search** component retrieves the most relevant Records from the Astra DB database.
- **Text Output** component turns the Records into Text by concatenating them and also displays it in the Playground.
- **Prompt** component takes in the user input and the retrieved Records as text and builds a prompt for the OpenAI model.
- **OpenAI** component generates a response to the prompt.
- **Chat Output** component displays the response in the Playground.
4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
4. To create environment variables for the **Astra DB** and **Astra DB Search** components:
1. In the **Token** field, click the **Globe** button, and then click **Add New Variable**.
2. In the **Variable Name** field, enter `astra_token`.
3. In the **Value** field, paste your Astra application token (`AstraCS:WSnyFUhRxsrg…​`).
4. Click **Save Variable**.
5. Repeat the above steps for the **API Endpoint** field, pasting your Astra API Endpoint instead (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`).
6. Add the global variable to both the **Astra DB** and **Astra DB Search** components.
1. In the **Variable Name** field, enter `openai_api_key`.
2. In the **Value** field, paste your OpenAI API Key (`sk-...`).
3. Click **Save Variable**.
5. To create environment variables for the **Astra DB** and **Astra DB Search** components:
1. In the **Token** field, click the **Globe** button, and then click **Add New Variable**.
2. In the **Variable Name** field, enter `astra_token`.
3. In the **Value** field, paste your Astra application token (`AstraCS:WSnyFUhRxsrg…​`).
4. Click **Save Variable**.
5. Repeat the above steps for the **API Endpoint** field, pasting your Astra API Endpoint instead (`https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`).
6. Add the global variable to both the **Astra DB** and **Astra DB Search** components.
## Run the vector store RAG flow
1. Click the **Playground** button.
The **Playground** opens, where you can chat with your data.
The **Playground** opens, where you can chat with your data.
2. Type a message and press Enter. (Try something like "What topics do you know about?")
3. The bot will respond with a summary of the data you've embedded.
For example, we embedded a PDF of an engine maintenance manual and asked, "How do I change the oil?"
The bot responds:
```
To change the oil in the engine, follow these steps:
@ -102,7 +107,3 @@ You should use a 3/8 inch wrench to remove the oil drain cap.
```
This is the size the engine manual lists as well. This confirms our flow works, because the query returns the unique knowledge we embedded from the Astra vector store.

6504
docs/static/data/AstraDB-RAG-Flows.json vendored
View file

File diff suppressed because one or more lines are too long

882
docs/static/json_files/Notion_Components_bundle.json vendored
View file

File diff suppressed because one or more lines are too long