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content/3.flow-controls/3.list-iterator.md

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+---
+title: List iterator (Loop)
+---
+# List Iterator / Loop
+
+## Introduction
+
+The List Iterator is a powerful flow control tool in Locale that allows users to execute a sub-workflow for each item in a list. This feature is particularly useful when you need to perform repetitive actions on a collection of data, enabling more dynamic and flexible workflow designs.
+
+## Overview
+
+Located under the Flow Controls section in Locale, the List Iterator provides a way to loop through arrays or lists of data. For each item in the list, it executes a defined sub-workflow, passing the current item's data into that sub-flow.
+
+## Key Features
+
+- Iterate over arrays or lists of data
+- Execute a custom sub-workflow for each item
+- Pass individual item data to the sub-workflow
+- Flexible integration with other Locale actions and apps
+
+## How to Use the List Iterator
+
+### Step 1: Add the List Iterator to Your Workflow
+
+1. In your Locale workflow, locate the Flow Controls section.
+2. Drag and drop the List Iterator action into your workflow where you want the iteration to occur.
+
+### Step 2: Configure the List Iterator
+
+1. Click on the List Iterator node to open its configuration panel.
+2. Specify the data source for your list. This could be:
+   - A data variable from a previous node (e.g., `{{ previousNode.data.items }}`)
+   - The result of a database query or API call
+
+### Step 3: Define the Sub-Workflow
+
+1. Connect the output handle of the List Iterator to the first action of your sub-workflow.
+2. Add and configure the actions you want to perform for each item in the list.
+3. Use the `{{ item }}` variable to access the current item's data within the sub-workflow.
+
+## Example Use Case
+
+Let's say you have a list of customer emails and you want to send a personalized message to each one:
+
+1. Use a database query or API call to fetch the list of customer emails.
+2. Add the List Iterator and configure it to use the fetched list.
+3. In the sub-workflow:
+   - Add an "Send Email" action.
+   - Configure the email with:
+     - To: `{{ tool.data.email }}`
+     - Subject: "Special offer for {{ tool.data.name }}"
+     - Body: "Hello {{ tool.data.name }}, we have a special offer for you..."
+4. The List Iterator will execute this sub-workflow for each customer in the list.
+
+## Best Practices
+
+1. **Data Preparation**: Ensure your list data is properly formatted before using the List Iterator.
+2. **Error Handling**: Consider adding error handling within your sub-workflow to manage potential issues with individual items.
+3. **Performance**: Be mindful of the size of your list. For very large lists, consider implementing pagination or batching strategies.
+4. **Testing**: Thoroughly test your workflow with different list sizes and data types to ensure it behaves as expected.
+
+## Limitations
+
+- The List Iterator processes items sequentially. For parallel processing of large datasets, you may need to explore other solutions.
+- The performance of the List Iterator depends on the complexity of the sub-workflow and the size of the list.
+
+---
+
+The List Iterator is a versatile tool in Locale that enables users to create more dynamic and data-driven workflows. By allowing the execution of sub-workflows for each item in a list, it opens up possibilities for batch processing, personalized actions, and complex data manipulations within your automation processes.

content/4.apps/2.AI.md

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 ---
-navigation: false
+title: AI Actions
 ---
-# AI
+# AI Actions
+
+## Introduction
+
+AI Actions in Locale.ai enable users to leverage Large Language Models (LLMs) within their workflows, enhancing automation capabilities with artificial intelligence. These actions allow for sophisticated text generation, classification, and data extraction tasks, making workflows more intelligent and adaptive.
+
+## Available LLM Models
+
+Locale currently offers users a choice between two powerful LLM models:
+
+1. Claude Sonnet
+2. Chat GPT
+
+Users can select their preferred model when configuring AI actions in their workflows.
+
+## Types of AI Actions
+
+Locale provides three distinct AI actions that users can incorporate into their workflows:
+
+### 1. AI Text Generator
+
+The AI Text Generator action allows users to create dynamic, context-aware text based on a given prompt.
+
+#### How it works:
+- Users provide a prompt for the AI to generate text.
+- Data variables can be included within the prompt to offer additional context.
+- The AI generates text based on the prompt and any provided context.
+
+#### Example Use Case:
+Generating personalized email responses based on customer inquiries.
+
+```
+Prompt: Write a friendly response to a customer inquiry about {{product_name}}. 
+The customer's name is {{customer_name}} and their question was: "{{customer_question}}".
+```
+
+### 2. AI Classifier
+
+The AI Classifier action categorizes input text into predefined classes based on a given prompt and classification parameters.
+
+#### How it works:
+- Users provide a prompt with context for classification.
+- Classification parameters are defined by the user, each with a unique key and description.
+- The AI classifies the input into one of the given parameters.
+
+#### Example Use Case:
+Categorizing customer feedback into sentiment categories.
+
+```
+Prompt: Classify the following customer feedback into one of the provided categories.
+
+Feedback: {{customer_feedback}}
+
+Classification Parameters:
+- positive: The feedback expresses satisfaction or approval.
+- neutral: The feedback is neither clearly positive nor negative.
+- negative: The feedback expresses dissatisfaction or criticism.
+```
+
+### 3. AI Data Extractor
+
+The AI Data Extractor action extracts specific information from given text based on user-defined parameters.
+
+#### How it works:
+- Users provide a prompt with context for data extraction.
+- Extraction parameters are defined by the user, each with a unique key and description.
+- The AI extracts the requested information based on the provided parameters.
+
+#### Example Use Case:
+Extracting key details from customer support call transcripts.
+
+```
+Prompt: Extract the following information from this customer support call transcript:
+
+Transcript: {{call_transcript}}
+
+Extraction Parameters:
+- customer_name: The name of the customer
+- product_mentioned: Any product names mentioned in the call
+- main_issue: The primary problem or concern raised by the customer
+- resolution_status: Whether the issue was resolved (resolved/unresolved)
+```
+
+## Configuring AI Actions in Workflows
+
+To use AI actions in your Locale workflows:
+
+1. Add the desired AI action node to your workflow.
+2. Choose between Claude Sonnet or Chat GPT as the LLM model.
+3. Configure the action-specific settings (prompt, classification parameters, or extraction parameters).
+4. Use data variables to incorporate dynamic content from previous nodes in the workflow.
+
+## Best Practices
+
+- Provide clear and specific prompts to get the most accurate results.
+- Use data variables to make your AI actions dynamic and context-aware.
+- Test your AI actions with various inputs to ensure they perform as expected across different scenarios.
+- For classification and data extraction, provide detailed descriptions for each parameter to guide the AI's decision-making process.
+
+---
+
+AI Actions in Locale bring the power of advanced language models to your workflows, enabling more intelligent automation, personalized content generation, and sophisticated data processing. By leveraging these AI capabilities, users can create more efficient, adaptive, and powerful workflows that can handle complex tasks with ease.

content/4.apps/7.fireflies.md

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+---
+title: Fireflies.ai
+---
+# Fireflies.ai Integration in Locale
+
+## Introduction
+
+Fireflies.ai is a powerful call recording and transcription tool that automatically joins online meetings and calls to record and transcribe conversations. The integration of Fireflies.ai with Locale allows users to automate workflows based on completed calls, leveraging the rich data captured during meetings.
+
+## Integration
+
+To use Fireflies.ai in your Locale workflows, you'll need to set up the integration by following these steps:
+
+### Obtaining the API Key
+
+1. Log in to your account at [app.fireflies.ai](https://app.fireflies.ai)
+2. Navigate to the Integrations section
+3. Click on Fireflies API
+4. Copy and store your API key securely
+
+### Connecting Fireflies.ai to Locale
+
+1. In Locale, navigate to the Integrations section
+2. Find and select Fireflies.ai from the list of available integrations
+3. Enter the API key you obtained from Fireflies.ai when prompted
+4. Complete any additional authentication steps if required
+
+Once connected, you'll be able to use Fireflies.ai triggers and actions in your Locale workflows.
+
+## Triggers
+
+### New Call Completed
+
+The "New Call Completed" trigger initiates workflows automatically when a call is finished in Fireflies.ai.
+
+#### Trigger Data
+When a call is completed, the trigger provides essential information about the call, including:
+
+- Participants
+- Date and Time
+- Host
+- Summary
+- Transcript
+
+This data can be used in subsequent steps of your workflow to automate tasks, generate reports, or trigger follow-up actions.
+
+## Actions
+
+### Fetch Call Transcripts
+
+The "Fetch Call Transcripts" action enables users to retrieve specific call transcripts and details by providing the call ID.
+
+## Using Fireflies.ai in Your Workflows
+
+### Creating a Workflow with the "New Call Completed" Trigger
+
+1. Start a new workflow in Locale.
+2. Select "Fireflies.ai" as the trigger app.
+3. Choose "New Call Completed" as the trigger event.
+4. Configure any additional settings if required.
+
+#### Example Workflow
+
+1. Trigger: New call completed in Fireflies.ai
+2. Action: Send a summary email to all participants
+3. Action: Create a task in your project management tool for any action items identified
+
+### Using the "Fetch Call Transcripts" Action
+
+1. Add the Fireflies.ai app to your workflow.
+2. Select the "Fetch Call Transcripts" action.
+3. Configure the action by providing the call ID. This can be a static value or a dynamic value from a previous step in your workflow.
+
+#### Example Workflow
+
+1. Trigger: New task created in project management tool
+2. Action: Fetch call transcript from Fireflies.ai using the call ID stored in the task description
+3. Action: Analyze the transcript using AI to extract key points
+4. Action: Update the task with the extracted information
+
+## Best Practices
+
+1. Use data variables to dynamically insert call information into your workflow actions.
+2. Combine the Fireflies.ai integration with AI actions in Locale to analyze call transcripts and extract valuable insights.
+3. Set up automated follow-up tasks or reminders based on the content of your calls.
+4. Create different workflows for different types of calls (e.g., sales calls, team meetings, customer support) to automate specific processes for each.
+
+--- 
+
+The Fireflies.ai integration in Locale provides a powerful way to automate workflows based on your calls and meetings. By leveraging the "New Call Completed" trigger and the "Fetch Call Transcripts" action, you can create sophisticated automations that save time, improve follow-up processes, and extract valuable insights from your conversations. Remember to keep your API key secure and never share it publicly.