open-index/open-npm huggingface dataset:
npm package: @neurarank/neurarank-framework
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.0.1

# pieces-framework

This library was generated with [Nx](https://nx.dev).

## Building

Run `nx build pieces-framework` to build the library.

## Running unit tests

Run `nx test pieces-framework` to execute the unit tests via [Jest](https://jestjs.io).
npm package: @neurarank/node-assemblyai
Description: Use the AssemblyAI piece for Activepieces to use AssemblyAI's models to [transcribe audio with Speech-to-Text models](https://www.assemblyai.com/products/speech-to-text?utm_source=activepieces), analyze audio with [audio intelligence models](https://www.a
Latest version: 1.0.8

# AssemblyAI piece for Activepieces

Use the AssemblyAI piece for Activepieces to use AssemblyAI's models to
[transcribe audio with Speech-to-Text models](https://www.assemblyai.com/products/speech-to-text?utm_source=activepieces), analyze audio with [audio intelligence models](https://www.assemblyai.com/products/speech-understanding?utm_source=activepieces), build generative AI features on top of audio with LLMs using [LeMUR](https://www.assemblyai.com/blog/lemur/?utm_source=activepieces).

Learn more about this piece:

- [Activepieces Integrations](https://www.activepieces.com/pieces/assemblyai)
- [AssemblyAI Documentation](https://www.assemblyai.com/docs/integrations/activepieces)

This library was built upon the [AssemblyAI JavaScript SDK](https://github.com/AssemblyAI/assemblyai-node-sdk).

## Building

Run `nx build pieces-assemblyai` to build the library.

## Generating props

- Copy `assemblyai.env.sample` to `assemblyai.env`
- In `assemblyai.env`, update the `OPENAPI_SPEC_LOCATION` variable to the path or URL of AssemblyAI's OpenAPI spec
- Run `nx generate-params pieces-assemblyai`

You can find [AssemblyAI's OpenAPI spec on GitHub](https://github.com/AssemblyAI/assemblyai-api-spec/blob/main/openapi.yml).
npm package: @neurarank/node-browserless
Description: Browserless is a cloud-based browser automation platform that allows you to run full Chrome sessions remotely for tasks like taking screenshots, scraping data, converting pages to PDFs, and more without writing scraping code or managing servers.
Latest version: 0.0.3

# Browserless

Browserless is a cloud-based browser automation platform that allows you to run full Chrome sessions remotely for tasks like taking screenshots, scraping data, converting pages to PDFs, and more without writing scraping code or managing servers.

## Actions

- **Capture Screenshot**: Take a screenshot of a web page
- **Generate PDF**: Convert a web page to PDF format
- **Scrape URL**: Extract content from a web page using CSS selectors
- **Run BQL Query**: Execute Browser Query Language (BQL) code
- **Get Website Performance**: Analyze website performance metrics using Lighthouse

## Authentication

To use this piece, you'll need:

1. A Browserless account (sign up for free at https://www.browserless.io/)
2. Your API token from the dashboard
3. Your API endpoint URL (typically https://your-api-key.browserless.io)

## Getting Started

1. Sign up for a free account at https://www.browserless.io/
2. Get your API token from your dashboard
3. Use your API endpoint URL in the format: `https://your-api-key.browserless.io`
4. Configure the authentication in Activepieces with your token and base URL

## Documentation

For more information about Browserless API capabilities, visit:
- [Browserless Documentation](https://docs.browserless.io/)
- [REST API Reference](https://docs.browserless.io/rest-apis/intro)
npm package: @neurarank/node-cometapi
Description: This is a Comet API integration for Activepieces that allows users to access multiple AI models through a unified interface.
Latest version: 0.0.2

# Comet API Piece for Activepieces

This is a Comet API integration for Activepieces that allows users to access multiple AI models through a unified interface.

## Features

- ✅ Support for multiple AI models (GPT, Claude, Gemini, DeepSeek, etc.)
- ✅ Dynamic model list loading
- ✅ Complete parameter configuration (temperature, max_tokens, top_p)
- ✅ Detailed error handling
- ✅ Custom API call support
- ✅ API key validation

## Supported Models

### GPT Series
- gpt-5-chat-latest
- chatgpt-4o-latest
- gpt-4o-mini
- gpt-5-mini
- gpt-5-nano

### Claude Series
- claude-opus-4-1-20250805
- claude-sonnet-4-20250514
- claude-3-7-sonnet-latest
- claude-3-5-haiku-latest

### Gemini Series
- gemini-2.5-pro
- gemini-2.5-flash
- gemini-2.0-flash

### Other Models
- DeepSeek series (deepseek-v3.1, deepseek-v3, deepseek-r1-0528)
- Grok series (grok-4-0709, grok-3, grok-3-mini)
- Qwen series (qwen3-30b-a3b, qwen3-coder-plus-2025-07-22)

## Usage

### 1. Get API Key
1. Visit: https://www.cometapi.com/
2. Register an account and login
3. Go to API settings page to get your API key

### 2. Configure in Activepieces
1. Create a new flow in Activepieces
2. Add the "Comet API" piece
3. Configure your API key
4. Select the AI model to use
5. Enter your prompt

### 3. Available Actions

#### Ask Comet API
Send prompts to any AI model supported by Comet API.

**Parameters:**
- **Model**: The AI model to use
- **Prompt**: The prompt text to send to the AI
- **System Message** (optional): System message to set AI behavior
- **Temperature** (optional): Controls randomness (0-2)
- **Max Tokens** (optional): Maximum tokens to generate
- **Top P** (optional): Nucleus sampling parameter (0-1)

#### Custom API Call
Directly call any endpoint of the Comet API.

## Build

Run `nx build pieces-cometapi` to build the library.
npm package: @neurarank/node-convertkit
Description: ## Untested pieces
Latest version: 0.2.6

# Notes

## Untested pieces

The following webhook trigger event types (https://developers.convertkit.com/#webhooks) have been implemented but not yet fully tested.

- subscriber.subscriber_complain

- subscriber.product_purchase

- purchase.purchase_create

<!-- If you run into problems with these events, please create an issue and tag/message me (gunther@mailcraft.co). -->

## No debounce in form fields

I have not implemented a debounce in any form fields. This means that calls to the ConvertKit API will be triggered on every keystroke for certain fields.

I have raised an issue here: https://github.com/activepieces/activepieces/issues/3142

# Building

Run `nx build pieces-convertkit` to build the library.

# ToDo

- Versioning of piece https://www.activepieces.com/docs/developers/piece-reference/piece-versioning
- Debounce on form fields
- Add tests(?)
npm package: @neurarank/node-customer-io
Description: - Track Custom API (https://www.customer.io/docs/api/track/) - Base Custom API (https://customer.io/docs/api/app/#section/Overview) - Create  Event
Latest version: 0.2.7

# pieces-customer-io

- Track Custom API (https://www.customer.io/docs/api/track/)
- Base Custom API (https://customer.io/docs/api/app/#section/Overview)
- Create  Event

## Building

Run `nx build pieces-customer-io` to build the library.
npm package: @neurarank/node-cyberark
Description: This piece provides integration with CyberArk PTA (Privileged Threat Analytics) for authentication and monitoring.
Latest version: 0.0.2

# CyberArk Piece

This piece provides integration with CyberArk PTA (Privileged Threat Analytics) for authentication and monitoring.

## Features

### PTA Authentication
- **Get Authentication Token**: Retrieve an authentication token from CyberArk PTA server for system health monitoring

## Authentication

The CyberArk piece uses custom authentication with the following required fields:

- **PTA Server URL**: The PTA server URL (e.g., `https://pta-server:8443`)
- **Username**: The username for authentication (typically `Administrator`)
- **Password**: The password for authentication

## API Reference

### PTA Get Authentication Token

**Endpoint**: `POST /api/getauthtoken/`

**Description**: This method enables a user to get a token upon Web application authentication. You can use this method to monitor the PTA system health.

**Request Format**: `application/x-www-form-urlencoded`

**Parameters**:
- `username`: The user name (required)
- `password`: The user password (required)

**Response**:
- `Token`: An authorized token string

## URL Guidelines

- Make sure there are no spaces in the URL
- The following characters are not supported in URL values: `+`, `&`, `%`
- If the URL includes a dot (.), add a forward slash (/) at the end of the URL

## Return Codes

The following table lists all the return codes that are returned from the REST APIs:

| Return Code | Code Number | Description |
|-------------|-------------|-------------|
| Success | 200 | The request succeeded. The actual response will depend on the request method used. |
| Created | 201 | The request was fulfilled and resulted in a new resource being created. |
| No Content | 204 | The server successfully processed the request and is not returning any content (no response body). This code is typically returned by DELETE requests. |
| Bad request | 400 | The request could not be understood by the server due to incorrect syntax. |
| Unauthorized | 401 | The request requires user authentication. |
| Forbidden | 403 | The server received and understood the request, but will not fulfill it. Authorization will not help and the request MUST NOT be repeated. |
| Not Found | 404 | The server did not find anything that matches the Request-URI. No indication is given of whether the condition is temporary or permanent. |
| Conflict | 409 | The request could not be completed due to a conflict with the current state of the resource. |
| Too Many Requests | 429 | The user has sent too many requests in a given amount of time ("rate limiting"). |
| Internal Server Error | 500 | The server encountered an unexpected condition which prevented it from fulfilling the request. |
| Not Implemented | 501 | The server does not support this operation due to version incompatibility. |

## Building

Run `nx build pieces-cyberark` to build the library.
npm package: @neurarank/node-datadog
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.0.4

# pieces-datadog

This library was generated with [Nx](https://nx.dev).

## Building

- Run `nx build pieces-datadog` to build the library.
- Add `datadog` to `AP_DEV_PIECES` environment variable to test

## Adding new actions

- Check the [Datadog API documentation](https://docs.datadoghq.com/api/latest/) to see the available endpoints and parameters. 
- Prefer using the typescript SDK ([`@datadog/datadog-api-client`](https://github.com/DataDog/datadog-api-client-typescript)) over the HTTP API for better type safety and documentation.
npm package: @neurarank/node-dittofeed
Description: This piece provides integration with [Dittofeed](https://dittofeed.com/), a customer data platform for user analytics and tracking.
Latest version: 0.0.3

# Dittofeed Piece for ActivePieces

This piece provides integration with [Dittofeed](https://dittofeed.com/), a customer data platform for user analytics and tracking.

## Authentication

To use the Dittofeed piece, you need to provide:

1. **API Key**: Your Dittofeed API key for authentication
2. **Base URL**: The base URL of your Dittofeed instance (e.g., `https://api.dittofeed.com` or your self-hosted instance URL)

## Actions

### Identify User

Identify a user in Dittofeed with their unique ID and traits.

**Parameters:**
- **User ID** (required): A unique identifier for the user
- **User Traits** (optional): An object containing user properties like name, email, etc.

**Example:**
```json
{
  "userId": "user123",
  "traits": {
    "name": "John Doe",
    "email": "john@example.com",
    "plan": "premium"
  }
}
```

### Track Event

Track a user event in Dittofeed.

**Parameters:**
- **User ID** (required): A unique identifier for the user
- **Event** (required): The name of the event to track
- **Properties** (optional): An object containing event properties

**Example:**
```json
{
  "userId": "user123",
  "event": "purchase_completed",
  "properties": {
    "product": "Premium Plan",
    "price": 99.99,
    "currency": "USD"
  }
}
```

### Screen View

Track a screen view event in Dittofeed.

**Parameters:**
- **User ID** (required): A unique identifier for the user
- **Name** (required): The name of the screen viewed
- **Properties** (optional): An object containing screen view properties

**Example:**
```json
{
  "userId": "user123",
  "name": "checkout_page",
  "properties": {
    "referrer": "product_page",
    "device": "mobile"
  }
}
```

## Troubleshooting

### Common Errors

1. **Authentication failed**: Check that your API key is correct and has the necessary permissions.
2. **API endpoint not found**: Verify that your base URL is correct and points to a valid Dittofeed instance.
3. **Rate limit exceeded**: You've made too many requests in a short period. Wait and try again later.
4. **Invalid input**: Ensure that your User ID is not empty and that traits/properties are valid objects.

### Best Practices

1. Use consistent User IDs across all actions to ensure proper user tracking.
2. Keep event names consistent and descriptive for better analytics.
3. Include relevant properties with events and screen views to capture valuable context.

## Building

Run `nx build pieces-dittofeed` to build the library.
npm package: @neurarank/node-gcloud-pubsub
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.0.10

# pieces-gcloud-pubsub

This library was generated with [Nx](https://nx.dev).

## Running lint

Run `nx lint pieces-gcoud-pubsub` to execute the lint via [ESLint](https://eslint.org/).
npm package: @neurarank/node-google-my-business
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.0.14

# pieces-google-my-business

This library was generated with [Nx](https://nx.dev).

## Running lint

Run `nx lint pieces-google-my-business` to execute the lint via [ESLint](https://eslint.org/).
npm package: @neurarank/node-hedy
Description: AI-powered meeting intelligence integration for ActivePieces.
Latest version: 0.0.2

# Hedy Piece for ActivePieces

AI-powered meeting intelligence integration for ActivePieces.

## Features
- Retrieve meeting sessions, highlights, todos, and topics from Hedy.
- Trigger flows when sessions end, highlights are created, or todos are exported.
- Support for pagination and Zapier-compatible response formatting.
- Optional webhook signature verification for additional security.

## Authentication
1. Sign in to your Hedy dashboard.
2. Navigate to **Settings → API**.
3. Generate a new API key (it starts with `hedy_live_`).
4. Paste the key into the Hedy piece connection in ActivePieces.

## Example Automations
- **Post Session Recaps** – Trigger on `Session Ended` and send meeting notes to Slack, Microsoft Teams, or email.
- **Sync Todos** – When a todo is exported from Hedy, automatically create matching tasks in Asana, Todoist, or ClickUp.
- **Daily Digest** – Schedule a flow that lists sessions from the last 24 hours, summarises them with AI, and emails the highlights to your team.

## Error Handling
The Hedy piece provides descriptive errors for common issues such as:
- Invalid API keys or failed authentication.
- Webhook limits being reached (Hedy allows 10 concurrent webhooks per workspace).
- Invalid webhook URLs (public HTTPS endpoints are required for production).

## Support
- Hedy API documentation: https://api.hedy.bot/docs
- Hedy support: support@hedy.bot
- ActivePieces community: https://www.activepieces.com/discord
npm package: @neurarank/node-huggingface
Description: Interact with Hugging Face Hub: run inference, create models/spaces/datasets, and upload/download files.
Latest version: 0.1.0

# Hugging Face Node

Interact with Hugging Face Hub: run inference, create models/spaces/datasets, and upload/download files.

## Features

### Inference
- **Run Inference**: Execute inference on any Hugging Face model
  - Supports multiple task types (text generation, classification, QA, etc.)
  - Auto-detect task type or specify manually
  - Custom parameters support
  - Wait for model loading option

### Repository Management
- **Create Model**: Create new model repositories
- **Create Space**: Create new Spaces with different SDKs (Gradio, Streamlit, Docker, Static)
- **Create Dataset**: Create new dataset repositories

### File Operations
- **Upload Model**: Upload files to model repositories
- **Upload Dataset**: Upload files to dataset repositories
- **Download Model**: Download files from model repositories
- **Download Dataset**: Download files from dataset repositories

## Authentication

All actions require a Hugging Face access token:
1. Visit [Hugging Face Settings](https://huggingface.co/settings/tokens)
2. Create a new token with appropriate permissions:
   - **Read token**: For inference and downloads
   - **Write token**: For creating repositories and uploading files

## Usage Examples

### Run Text Generation Inference

```json
{
  "model": "gpt2",
  "task": "text-generation",
  "inputs": "The future of AI is",
  "parameters": {
    "max_length": 50,
    "temperature": 0.7
  }
}
```

### Run Classification

```json
{
  "model": "distilbert-base-uncased-finetuned-sst-2-english",
  "task": "text-classification",
  "inputs": "I love this product!"
}
```

### Create Model Repository

```json
{
  "modelId": "username/my-model",
  "private": false
}
```

### Upload Model File

```json
{
  "modelId": "username/my-model",
  "filePath": "/path/to/model.bin",
  "pathInRepo": "pytorch_model.bin",
  "commitMessage": "Upload model weights"
}
```

## API References

- [Hugging Face Inference API](https://huggingface.co/docs/api-inference)
- [Hugging Face Hub API](https://huggingface.co/docs/hub/api)
- [Hugging Face Documentation](https://huggingface.co/docs)

## Notes

- For large file uploads/downloads, consider using the official `huggingface_hub` Python library
- Some operations may require write permissions on your token
- Model inference may take time on first request (cold start)
npm package: @neurarank/node-ibm-cognose
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.0.2

# pieces-ibm-cognose

This library was generated with [Nx](https://nx.dev).

## Running lint

Run `nx lint pieces-ibm-cognose` to execute the lint via [ESLint](https://eslint.org/).
npm package: @neurarank/node-instasent
Description: ## Description Instasent piece for ActivePieces. Enables integration with Instasent's Ingest API for managing contacts and tracking events in your data source. This API allows organizations to consolidate customer data and track interactions, enabling adv
Latest version: 0.0.7

# Instasent

## Description
Instasent piece for ActivePieces. Enables integration with Instasent's Ingest API for managing contacts and tracking events in your data source. This API allows organizations to consolidate customer data and track interactions, enabling advanced audience segmentation and personalized marketing.

### Key Features
- **Contact Management**: Create, update, and delete contacts in your audience
- **Event Tracking**: Record customer interactions and behaviors
- **Data Consolidation**: Unify customer data from various sources
- **Automatic Attribution**: Track which marketing campaigns lead to specific events

## Authentication
This piece requires:
- **Project ID**: Your Instasent project identifier
- **Datasource ID**: Your data source identifier within the project
- **API Key**: Bearer token for authentication (specific to the data source)

To generate your authentication data go to your project and add an ActivePieces data source, if it's not available you can create an Instasent API data source instead.

## Actions

### 1. Add or Update Contact
Add new contacts or update existing ones in your data source. Supports various contact attributes:
- Basic info (name, email, phone)
- Demographics (country, language, gender)
- Marketing preferences
- Custom attributes

### 2. Delete Contact
Remove a contact from your data source. Contacts will be permanently destroyed and removed from your audience.

### 3. Add Event
Record contact events such as:
- E-commerce actions (orders, checkouts)
- User behaviour (views, form submissions...)
- Appointments or reservations
- Payments and refunds
- Metrics
- Custom events

Events support attribution parameters to track which marketing campaigns led to specific actions.

## Links
- [Instasent Website](https://instasent.com)
- [Ingest API Docs](https://app.swaggerhub.com/apis-docs/Instasent/instasent-ingest_api/)
- [Instasent APIs](https://docs.instasent.com)

## Support
For support or questions about the API, contact:
- Email: dev@instasent.com
- Website: https://instasent.com
- Customer support: https://help.instasent.com
npm package: @neurarank/node-kizeo-forms
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.3.17

# pieces-kizeo-forms

This library was generated with [Nx](https://nx.dev).

## Running lint

Run `nx lint pieces-kizeo-forms` to execute the lint via [ESLint](https://eslint.org/).
npm package: @neurarank/node-mautic
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.4.12

# pieces-mautic

This library was generated with [Nx](https://nx.dev).

## Running lint

Run `nx lint pieces-mautic` to execute the lint via [ESLint](https://eslint.org/).

## For Testing

Create a Sandbox account by following instructions [here](https://www.mautic.org/demo)

# List of API Used

## Contact API

### [Contact Creation API](https://developer.mautic.org/#create-contact)

### [Contact Search API](https://developer.mautic.org/#list-contacts)

### [Contact Update API](https://developer.mautic.org/#edit-contact)

## Company API

### [Company Creation API](https://developer.mautic.org/#create-companyhttps://developer.mautic.org/#create-company)

### [Company Search API](https://developer.mautic.org/#list-contact-companies)

### [Company Update API](https://developer.mautic.org/#edit-company)

## Metadata API

### [List Fields](https://developer.mautic.org/#list-contact-fields)
npm package: @neurarank/node-multi-language-code
Description: Execute code in multiple programming languages using Node.js subprocess.
Latest version: 0.0.1

# Multi-Language Code Node

Execute code in multiple programming languages using Node.js subprocess.

## Supported Languages

- **PHP**: Execute PHP scripts
- **Python**: Execute Python 3 scripts
- **Golang**: Execute Go programs
- **Ruby**: Execute Ruby scripts
- **Ruby on Rails**: Execute Rails code (requires Rails environment)

## Features

- Execute code in multiple programming languages
- Pass inputs as key-value pairs accessible in code
- Configurable timeout for execution
- Automatic cleanup of temporary files
- Error handling and output capture

## Usage

1. Select the programming language from the dropdown
2. Write your code in the code editor
3. Add inputs as key-value pairs (optional)
4. Set timeout if needed (default: 30 seconds)
5. Execute and get the result

## Code Structure

### Accessing Inputs

In your code, you can access inputs using the `inputs` variable:

**Python:**
```python
result = inputs.get('key', 'default_value')
```

**PHP:**
```php
$value = $inputs['key'] ?? 'default_value';
```

**Golang:**
```go
value := inputs["key"].(string)
```

**Ruby:**
```ruby
value = inputs['key'] || 'default_value'
```

### Return Values

Your code should set a `result` variable that will be returned as JSON:

**Python:**
```python
result = {"message": "Hello", "value": 42}
```

**PHP:**
```php
$result = ["message" => "Hello", "value" => 42];
```

**Golang:**
```go
result := map[string]interface{}{
    "message": "Hello",
    "value": 42,
}
```

**Ruby:**
```ruby
result = { "message" => "Hello", "value" => 42 }
```

## Requirements

The following runtime environments must be installed on the server:

- PHP (for PHP execution)
- Python 3 (for Python execution)
- Go (for Golang execution)
- Ruby (for Ruby and Rails execution)
- Rails (optional, for Rails execution)

## Security Notes

- Code execution happens in isolated temporary directories
- Timeout limits prevent infinite loops
- All temporary files are automatically cleaned up after execution
npm package: @neurarank/node-mycase-piece
Description: This piece provides integration with MyCase API using OAuth 2.0 authentication.
Latest version: 0.0.2

# MyCase Piece

This piece provides integration with MyCase API using OAuth 2.0 authentication.

## Features

### Authentication
- **OAuth 2.0**: Uses Authorization Code grant flow with refresh tokens
- **Automatic Token Management**: Handles access token and refresh token lifecycle
- **Secure**: Follows MyCase's recommended authentication practices

### Actions
- **Get Firm Information**: Retrieve information about the authenticated firm
- **List Contacts**: Retrieve and search contacts with pagination support

## Authentication Setup

### Prerequisites
1. **MyCase Account**: You need an active MyCase account
2. **Client Credentials**: Contact MyCase support to obtain:
   - Client ID
   - Client Secret
   - Redirect URI (must be pre-registered with MyCase)

### OAuth 2.0 Flow
1. **Authorization**: Users are redirected to MyCase authorization server
2. **Code Exchange**: Authorization code is exchanged for access token
3. **API Access**: Access token is used for authenticated API requests
4. **Token Refresh**: Refresh tokens are used to obtain new access tokens

### Configuration
- **Authorization URL**: `https://auth.mycase.com/login_sessions/new`
- **Token URL**: `https://auth.mycase.com/tokens`
- **Token Lifetime**: 24 hours (access token), 2 weeks (refresh token)
- **Rate Limits**: 25 requests per second per client

## API Integration

### Base URL
All API requests are made to: `https://api.mycase.com/v1`

### Authentication Header
```
Authorization: Bearer <access_token>
```

### Error Handling
- **401 Unauthorized**: Access token expired (automatic refresh handled)
- **Rate Limiting**: 25 requests per second limit enforced
- **Scope Validation**: Ensures required permissions for API endpoints

## Building

Run `nx build pieces-mycase-piece` to build the library.
npm package: @neurarank/node-placid
Description: Placid is a creative automation engine that generates dynamic images, PDFs, and videos from templates and data. This integration empowers AI agents and workflows to produce and retrieve media assets automatically.
Latest version: 0.0.9

# Placid

Placid is a creative automation engine that generates dynamic images, PDFs, and videos from templates and data. This integration empowers AI agents and workflows to produce and retrieve media assets automatically.

## Features

### Actions
- **Create Image**: Generate a dynamic image from a specified template using input data
- **Create PDF**: Generate a PDF document from a specified template
- **Create Video**: Produce a video based on a template
- **Convert File to URL**: Convert uploaded file(s) into media URL(s) consumable by Placid templates
- **Get Image**: Retrieve a generated image by its ID (especially after processing delay)
- **Get PDF**: Retrieve the generated PDF by its ID
- **Get Video**: Retrieve the generated video by its ID

## Authentication

This piece requires a Placid API token. You can obtain your API token by:

1. Logging in to [placid.app](https://placid.app/login)
2. Going to your Projects overview
3. Selecting your desired project
4. Clicking "API Tokens" in the left menu

## Logo Requirements

This piece requires a logo to be uploaded to the Activepieces CDN at:
`https://cdn.activepieces.com/pieces/placid.png`

### Logo Files Included:
- `placid-logo.png` - Downloaded from Placid's official site

### For Maintainers:
Please upload the logo file to the CDN during the merge process.

## Documentation

- [Placid API Documentation](https://placid.app/docs/2.0/rest/)
- [Placid Templates](https://placid.app/templates)
npm package: @neurarank/node-seven
Description: <img src="https://www.seven.io/wp-content/uploads/Logo.svg" width="250" />
Latest version: 0.0.9

<img src="https://www.seven.io/wp-content/uploads/Logo.svg" width="250" />

Official seven piece for [Activepieces](https://www.activepieces.com/)

## Installation
### Dashboard
Settings -> My Pieces -> Install Piece -> type in `seven`

### Package Manager
`npm i @seven.io/activepieces`

## Actions
- Send SMS
- Text-To-Speech Call
- Lookup
- Send RCS

## Triggers
- Inbound SMS

## Support

Need help? Feel free to [contact us](https://www.seven.io/en/company/contact/).

[![MIT](https://img.shields.io/badge/License-MIT-teal.svg)](LICENSE)
npm package: @neurarank/node-stable-diffusion-webui
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.0.10

# pieces-stable-diffusion-webui

This library was generated with [Nx](https://nx.dev).

Integration with [Stable Diffusion web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui)

## Building

Run `nx build pieces-stable-diffusion-webui` to build the library.
npm package: @neurarank/node-talkable
Description: ======================
Latest version: 0.1.9

# Talkable piece

======================

Talkable’s marketing technology empowers e-commerce brands to acquire & retain high-value customers through referral & loyalty marketing programs. As a single-source solution for your referral marketing and loyalty marketing needs, brands are able to create seamless user experiences designed to increase brand engagement and build brand affinity.

## Website

[https://www.talkable.com/](https://www.talkable.com/)

## API documentation

[https://docs.talkable.com/api_v2.html](https://docs.talkable.com/api_v2.html)

## Actions:

- Find coupon
- Get Loyalty actions
- Create Event
- Create batch of events
- Create Purchase
- Create batch of purchases
- Refund origin
- Find Person
- Update Person data
- Anonymize Person (GDPR)
- Unsubscribe Person

---

This library was generated with [Nx](https://nx.dev).

## Building

Run `nx build pieces-talkable` to build the library.
npm package: @neurarank/node-tavily
Description: ## Description Tavily is an AI-powered search engine designed for accurate and real-time information retrieval. This piece enables integration with Tavily's API to perform searches and extract information.
Latest version: 0.0.7

# Tavily

## Description
Tavily is an AI-powered search engine designed for accurate and real-time information retrieval. This piece enables integration with Tavily's API to perform searches and extract information.

## Actions
1. **Search**: Perform a search query using Tavily's AI search engine
   - Supports both basic and advanced search depths
   - Optional AI-generated answer
   - Configurable result limits
   - Raw content inclusion option

2. **Extract**: Extract structured data from a webpage using Tavily's extraction API
   - Clean and formatted content extraction
   - Supports various content types
   - Removes ads and irrelevant content

## Authentication
This piece requires an API key from Tavily. To obtain your API key:
1. Visit https://tavily.com/ and sign up for an account
2. Navigate to your dashboard
3. Copy your API key from the dashboard

## Requirements
- Tavily API Key
npm package: @neurarank/node-vimeo
Description: ## How to create an API app 1. Log into your Vimeo account at https://developer.vimeo.com 2. Select **Create an app** in the upper right-hand corner, or visit: https://developer.vimeo.com/apps/new 3. Enter a name and description for your app 4. Select Cre
Latest version: 0.0.2

# pieces-vimeo

## How to create an API app
1. Log into your Vimeo account at https://developer.vimeo.com
2. Select **Create an app** in the upper right-hand corner, or visit: https://developer.vimeo.com/apps/new
3. Enter a name and description for your app
4. Select Create app

### Generate personal access token
1. After creating the app, navigate to https://developer.vimeo.com/apps
2. Select your app
3. Scroll and find **Authentication** -> **Generate an access token**
4. Select **Authenticated (you)**
5. Select this scope:
 - Private
 - Delete
 - Upload (you need to request for upload access)
 - Video Files
6. Click the **Generate** button
7. Copy the created token

### To request API upload access:
1. Visit the My Apps page
2. Select the name of your app
3. On your app's information page, under the Permissions section, select the **Request Upload Access** link and fill the required information.
4. Or you can also submit a [support ticket](https://vimeo.com/help/contact) requesting Vimeo API upload access
npm package: @neurarank/node-zoho-crm
Description: This library was generated with [Nx](https://nx.dev).
Latest version: 0.1.15

# pieces-zoho-crm

This library was generated with [Nx](https://nx.dev).

## Running lint

Run `nx lint pieces-zoho-crm` to execute the lint via [ESLint](https://eslint.org/).
npm package: @neuravision/ng-construct
Description: Angular components for the Construct Design System
Latest version: 0.5.1

# Angular

This project was generated using [Angular CLI](https://github.com/angular/angular-cli) version 21.1.0.

## Code scaffolding

Angular CLI includes powerful code scaffolding tools. To generate a new component, run:

```bash
ng generate component component-name
```

For a complete list of available schematics (such as `components`, `directives`, or `pipes`), run:

```bash
ng generate --help
```

## Building

To build the library, run:

```bash
ng build angular
```

This command will compile your project, and the build artifacts will be placed in the `dist/` directory.

### Publishing the Library

Once the project is built, you can publish your library by following these steps:

1. Navigate to the `dist` directory:
   ```bash
   cd dist/angular
   ```

2. Run the `npm publish` command to publish your library to the npm registry:
   ```bash
   npm publish
   ```

## Running unit tests

To execute unit tests with the [Karma](https://karma-runner.github.io) test runner, use the following command:

```bash
ng test
```

## Running end-to-end tests

For end-to-end (e2e) testing, run:

```bash
ng e2e
```

Angular CLI does not come with an end-to-end testing framework by default. You can choose one that suits your needs.

## Additional Resources

For more information on using the Angular CLI, including detailed command references, visit the [Angular CLI Overview and Command Reference](https://angular.dev/tools/cli) page.