# Buttons
Source: https://docs.chatling.ai/ai-agent/actions/buttons



Displays a set of buttons in the chat, such as URL buttons to open a webpage or text buttons to send preset replies that keep the flow moving.

## Configuration

### `Action Name`

A short, specific identifier that tells the Agent what this action does (e.g. best\_sellers\_buttons, support\_button).

### `When to Use`

A detailed description of what the action does and when it must be used.

When applicable, you can specify one or more of the following:

* **Positive cues/phrases**: Example utterances and keywords that signal this action (include a few variations).
* **Preconditions**: What must be true before running.
* **Do not use when**: Explicit exclusions to avoid false triggers.

<img alt="When to use option" />

### `Frequency`

Specify how often the Agent can invoke this action to avoid overusing it, e.g `Once per chat` or `Whenever applicable`.

<img alt="Frequency option" />

### `Buttons`

Add the buttons that you want to display in the chat. Buttons can be of two types:

* **URL button**: Opens a webpage when clicked.
* **Text button**: Sends a message to the AI agent when clicked. If a `Message` is provided, it will be sent as the message. Otherwise, the button label will be used.

To reorder the buttons, click the drag handle next to a button and move it up or down.

<img alt="Buttons option" />


# Cal.com Booking Widget
Source: https://docs.chatling.ai/ai-agent/actions/cal-booking



The Cal.com Booking Widget action embeds your Cal.com scheduler directly inside the chat, so users can view real-time availability and book without leaving the conversation.

<img alt="Cal.com Booking Widget action" />

## Configuration

### `Action Name`

A short, specific identifier that tells the Agent what this action does (e.g. best\_sellers\_buttons, support\_button).

### `When to Use`

A detailed description of what the action does and when it must be used.

When applicable, you can specify one or more of the following:

* **Positive cues/phrases**: Example utterances and keywords that signal this action (include a few variations).
* **Preconditions**: What must be true before running.
* **Do not use when**: Explicit exclusions to avoid false triggers.

<img alt="When to use option" />

### `Frequency`

Specify how often the Agent can invoke this action to avoid overusing it, e.g `Once per chat` or `Whenever applicable`.

<img alt="Frequency option" />

### `Widget`

Configure the widget's settings and appearance.

* **Event link**: The link to the Cal.com event page, such as `https://cal.com/rick/get-rick-rolled`.
* **Layout**: The layout of calendar, such as `Month`, `Week`, or `Column`.
* **Hide event type details**: Whether to hide the details of the event.
* **Pre-fill information**: The information to pre-fill in the booking form, such as `Name`, `Email`, and `Phone`.

### `Save Booking Information`

Save the data from the booking in variables to re-use later in the chat, if applicable.


# Google Sheets
Source: https://docs.chatling.ai/ai-agent/actions/google-sheets

Find, add, and update spreadsheet rows with your AI Agent.

The Google Sheets integration lets your AI Agent read and manage rows in a spreadsheet during a conversation.

## Available actions

* **Find Rows**: Find matching rows and return selected columns.
* **Append Row**: Add a new row.
* **Update Row**: Find one row and update selected columns.

## Set up an action

1. Open your AI Agent and go to **Actions**.
2. Click **New** and choose a Google Sheets action.
3. Connect the Google account that can access the spreadsheet.
4. Choose a spreadsheet and worksheet, then select the header row.
5. Enter an **Action name**, explain **When to use** it, and choose its frequency.
6. Configure the columns used by the action.
7. Create the action, then enable it from the Actions page.

The connection can access spreadsheets selected through the Google file picker.

## Find Rows

Choose the columns the Agent can search and return. Search values can be:

* **Dynamic**: Collected from the conversation at runtime.
* **Preconfigured**: Fixed values or variables defined while setting up the action.

You can also choose whether rows must match all or any filters, use exact or partial text matching, and set a maximum number of results.

## Add or change rows

* **Append Row** maps values to the columns of a new row.
* **Update Row** finds one row, then maps new values to selected columns.

Values can be fixed or inserted from variables populated by input parameters.


# HTTP Request
Source: https://docs.chatling.ai/ai-agent/actions/http-request



The HTTP Request action allows the AI Agent to connect to external APIs and services during the chat and perform an action.

The Agent can collect the needed inputs from the user, pull values from chat history, or use saved contact data—then send the request and use the result to respond or take the next step.

## Configuration

### `Action Name`

A short, specific identifier that tells the Agent what this action does (e.g. check\_order\_status, create\_support\_ticket).

### `When to Use`

A detailed description of what the action does and when it must be used.

When applicable, you can specify one or more of the following:

* **Positive cues/phrases**: Example utterances and keywords that signal this action (include a few variations).
* **Preconditions**: What must be true before running.
* **Do not use when**: Explicit exclusions to avoid false triggers.

### `Frequency`

Specify how often the Agent can invoke this action to avoid overusing it, e.g `Once per chat` or `Whenever applicable`.

### `Input parameters`

Define the parameters the Agent must gather before sending the request. The Agent can capture these from user input, existing chat context, or saved contact data.

For each parameter, you can specify the following:

* **Name**: The name of the parameter. Must start with a letter and contain only letters, numbers, and underscores.
* **Description** (optional): A description of the parameter to indicate what it is and if applicable, the formatting rules and min/max length.
* **Save to variable** (optional): The variable where the data can be saved. Applicable when you want to use the data in the HTTP request's parameters, such as URL, body, headers, etc.

### `Request`

Configure how the HTTP call is made.

* **Method**: GET, POST, PUT, PATCH, DELETE
* **URL**: Enter the request URL, such as an API endpoint.
* **Query Params** (optional): Key-value pairs appended to the URL.
* **Body** (optional): The request payload which can be passed as form data, form URL encoded, or raw JSON.
* **Headers** (optional): Data to be sent as the headers of the request, such as Content-Type and Authorization.

### `Test Request`

Run a live test with sample input values to confirm that it's working.

The request must succeed before the action can be created. A request is considered successful if it returns a 2xx status code and a valid JSON response.


# HubSpot
Source: https://docs.chatling.ai/ai-agent/actions/hubspot

Find, create, and update HubSpot CRM records with your AI Agent.

The HubSpot integration lets your AI Agent work with contacts, companies, and tickets during a conversation.

## Available actions

* **Create Contact, Company, or Ticket**: Create a record using values from the conversation, variables, or fixed values.

## Set up an action

1. Open your AI Agent and go to **Actions**.
2. Click **New** and choose a HubSpot action.
3. Connect your HubSpot account, or select an existing connection.
4. Enter an **Action name**, explain **When to use** it, and choose its frequency.
5. Configure the HubSpot properties used by the action.
6. Create the action, then enable it from the Actions page.


# AI Actions
Source: https://docs.chatling.ai/ai-agent/actions/introduction



Actions unlock the true power of AI Agents. Instead of only generating replies, the agent can actively carry out tasks during a conversation. This might involve saving details of potential leads, interacting with external systems to fetch or store data, creating support tickets, and more.

By using actions, you give your agent the power to handle practical steps on its own. This transforms the chatbot experience from a simple Q\&A into an interactive assistant that can streamline processes, save time, and improve outcomes for both your team and your users.

## Available Actions

* **[Lead Form](/ai-agent/actions/lead-form)**: displays a form to collect the user's details and save them as a contact.
* **[Buttons](/ai-agent/actions/buttons)**: displays a set of buttons in the chat, such as URL buttons to open a webpage or text buttons to send preset replies that keep the flow moving.
* **[HTTP Request](/ai-agent/actions/http-request)**: sends a request to an external API to fetch or store data, or perform an action. This allows you to connect your agent to external tools and services.
* **[Cal.com Booking Widget](/ai-agent/actions/cal-booking)**: Lets users book appointments directly within the chat.
* **[Send Email](/ai-agent/actions/send-email)**: sends a custom email to any recipient.
* **[Google Sheets](/ai-agent/actions/google-sheets)**: finds, adds, updates, clears, or deletes spreadsheet rows.
* **[HubSpot](/ai-agent/actions/hubspot)**: finds, creates, or updates contacts, companies, and tickets.
* **[Zendesk](/ai-agent/actions/zendesk)**: creates support tickets and users.

## How to create an action

1. Go to your AI agent's dashboard.
2. Click on the `Actions` menu from the sidebar.
3. Click the `New` button.
4. Select the action you want to create.
5. Configure the action according to your needs.
6. Click the `Create action` button.

## Tutorials

1. [Fetch and Email Order Confirmation](/ai-agent/actions/tutorials/fetch-and-email-order-confirmation)


# Lead Form
Source: https://docs.chatling.ai/ai-agent/actions/lead-form



Collect qualified leads right inside the conversation. The Lead Form action lets your AI Agent present a form in chat, collect user's information, and save them as a contact.

Any contacts saved by the AI agent will be displayed in the `Contacts` page in your dashboard.

<img alt="Lead form in chat widget" />

## Configuration

Below are the configuration options for the Lead Form action:

### `Mandatory`

Determines whether the form submission is mandatory. When enabled, the user will be required to submit the form before they can continue.

If the option is disabled, an "X" button will be displayed in the form to allow the user to dismiss the form.

<img alt="Lead form dismiss button" />

### `Fields`

Add and configure the fields you want to include in the form. You can add multiple fields and specify whether they must be required.

<img alt="Add and configure fields" />

To reorder, grab the drag handle on the left of a field and move it up or down.

<img alt="Reorder field" />

### `When to Use`

A detailed description of when the AI agent should use this action.

<img alt="When to Use option" />

### `Customize Text`

You can customize the text to be displayed for the submit button and success message.

The success message is the message that is displayed after the form is submitted. It is optional and can be disabled.


# Send Email
Source: https://docs.chatling.ai/ai-agent/actions/send-email



The Send Email action allows the AI Agent to send emails to one or more recipients. You can use it to send notifications, follow ups, order confirmations, transactional emails and other types of emails.

<img alt="Send Email action preview" />

## Configuration

### `Action Name`

A short, specific identifier that tells the Agent what this action does (e.g. best\_sellers\_buttons, support\_button).

### `When to Use`

A detailed description of what the action does and when it must be used.

When applicable, you can specify one or more of the following:

* **Positive cues/phrases**: Example utterances and keywords that signal this action (include a few variations).
* **Preconditions**: What must be true before running.
* **Do not use when**: Explicit exclusions to avoid false triggers.

<img alt="When to use option" />

### `Frequency`

Specify how often the Agent can invoke this action to avoid overusing it, e.g `Once per chat` or `Whenever applicable`.

<img alt="Frequency option" />

### `Input parameters`

Define the parameters the Agent must gather before sending the request. The Agent can capture these from user input, existing chat context, or saved contact data.

For each parameter, you can specify the following:

* **Name**: The name of the parameter. Must start with a letter and contain only letters, numbers, and underscores.
* **Description** (optional): A description of the parameter to indicate what it is and if applicable, the formatting rules and min/max length.
* **Save to variable** (optional): The variable where the data can be saved. Useful when you want to use the data in the email setup, such as the recipient's email address.

### `Email Setup`

Configure the email setup.

* **Sender Name**: The name of the sender.
* **To**: The email addresses of the recipients (max 5).
* **Reply-to**: The email addresses to reply to (max 5).
* **CC**: The email addresses of the recipients who will receive a copy of the email (max 5).
* **Subject**: The subject of the email.
* **Message**: The content of the email.


# 1. Fetch and Email Order Confirmation
Source: https://docs.chatling.ai/ai-agent/actions/tutorials/fetch-and-email-order-confirmation



In this tutorial, you'll build a simple but real-world flow that (1) fetches order data from an API via the [HTTP Request action](/ai-agent/actions/http-request), and (2) sends an email confirmation to the user with the [Send Email action](/ai-agent/actions/send-email).

By the end, your agent will automatically collect the user's email and order number, call your API to verify and fetch the order, and deliver a personalized confirmation email.

<img alt="Send Email action preview" />

## Setup Guide

1. Open your agent dashboard and go to Actions.

2. Click the `New` button and choose `HTTP Request`.

3. Set up the action as follows:

**Action name**: get\_order

**When to use**: When user asks to get an email of their order confirmation, first use this action to fetch the order before using email\_order\_confirmation.

**Frequency**: Whenever applicable

**Input parameters**: Add the parameters that are required to fetch the user's order. In this case, we will add the following parameters:

* `email`: The email address of the order. Save it to a variable, such as "email".
* `order_number`: The user's order number. Save it to a variable, such as "order\_number".

<img alt="input parameters" />

**Request**: Configure the request by defining the API URL, method, payload, and headers that will be used to fetch the user's order.

For this tutorial, we'll use a dummy API that returns an order. However, in a real app, you'd point the HTTP Request to your own or third-party API, include auth (e.g., Bearer token), and the relevant payload such as the user's email and order number.

<img alt="HTTP Request configuration" />

4. Click the `Test Request` button to verify that the request runs successfully and that the agent receives a valid JSON response.

<img alt="test http request" />

5. Click `Create action` to save the action.
6. Go back to the `Actions` page.
7. Click the `New` button and choose `Send Email`.
8. Set up the action as follows:

**Action name**: email\_order\_confirmation

**When to use**: Use this action to send the order confirmation to the user. First use the get\_order action to get the user's order, then use this action to email the order confirmation to the user.

**Frequency**: Whenever applicable

**Input parameters**: We'll add the following parameters that are required to send the email:

* `email`:
  * Description: The email address where the order confirmation should be sent.
  * Save to variable: email
* `order_number`:
  * Description: The order number of the user's order.
  * Save to variable: order\_number
* `order_details`:
  * Description: The details of the order that you retrieve from the get\_order action. Format it as HTML with bullet points.
  * Save to variable: order\_details

<img alt="input parameters" />

**Email Setup**: configure the email as follows:

* Sender name: A name of your choice, for example `Apple`
* To: Type in `{{email}}` and press Enter to use the email address of the user.
* Subject: `Order confirmation for #{{order_number}}`
* Message:

```
Hi there!

As requested, here is your confirmation for order #​{{order_number}}​:

​{{order_details}}​
```

<img alt="email setup" />

9. Click the `Create action` button to save the action.

## Test the actions

Now that you've set up the actions, it's time to test them.

From the `Actions` page, enable both the actions.

Go to the `Playground` page to start a chat with your agent. Ask the agent to email your order confirmation. It should fetch the order details from the API and email the order confirmation to the email address you specify.

Here's an example of how the agent would respond:

<img alt="Send Email action preview" />


# Zendesk
Source: https://docs.chatling.ai/ai-agent/actions/zendesk

Create Zendesk tickets and users with your AI Agent.

The Zendesk integration lets your AI Agent create support tickets and customer records directly from a conversation.

## Available actions

* **Create Ticket**: Send an issue or request to your support team.
* **Create User**: Add a customer as a Zendesk user.

## Set up an action

1. Open your AI Agent and go to **Actions**.
2. Click **New** and choose a Zendesk action.
3. Enter your Zendesk subdomain and connect your account, or select an existing connection.
4. Enter an **Action name**, explain **When to use** it, and choose its frequency.
5. Add any input parameters the Agent should collect.
6. Configure the ticket or user fields.
7. Create the action, then enable it from the Actions page.


# AI settings
Source: https://docs.chatling.ai/ai-agent/ai-settings



To configure the agent's AI settings, click the `Settings` button in the sidebar and select `AI`.

<img alt="Agent AI settings" />

## Available settings

### AI Model

The AI model that the agent will use to think, plan, and generate answers to the user queries.

Every model has different capabilities and costs. We recommend testing with different models in the [Playground](/ai-agent/playground) to see which one works best for your agent.

### Temperature

Controls randomness/creativity in the Agent's writing and decision-making.

Lower = more deterministic; Higher = more varied.

* **0.0-0.3 (Precise)**: Best for support, policy-bound replies, data extraction, or when strict adherence to facts and formats is required.

* **0.4-0.6 (Balanced)**: Good general setting for helpful responses with light creativity.

* **0.7-1.0 (Creative)**: Use for brainstorming, marketing copy, or when variety is desirable. Expect less consistency.

**Tips**

* If your Agent must follow exact steps (e.g., collecting parameters for an HTTP Request), keep temperature low.
* Raise temperature only where tone/creativity matters and accuracy isn't compromised.

### Instructions

Define the Agent's role, goals, guardrails, and style (often called the "system prompt").

Here's some of the things you can include in the instructions:

* **Role & purpose**: What the Agent is for and what success looks like.
* **Scope & boundaries**: What it should/shouldn't answer.
* **Tone & language**: Brand voice, formality level, and multilingual behavior (auto-detect language; reply in user's language).
* **Compliance & safety**: Any legal disclaimers, restricted topics, PII handling, and masking sensitive values.
* **Formatting**: Preferred reply structure (short summaries, bullet points, tables).


# File attachments
Source: https://docs.chatling.ai/ai-agent/file-attachments

Let your AI Agent analyze files sent by users.

AI Agents can inspect supported file attachments sent through the web widget,
WhatsApp, Instagram, and other supported channels. The agent analyzes the
attachment together with the user's message, allowing it to answer questions
about screenshots, product photos, receipts, and other visual content. It can
also refer back to previously sent images when users ask follow-up questions.

## Enable file attachments

1. Open your AI Agent.
2. Go to `Settings` → `AI`.
3. Enable `Attachments`.
4. Choose the maximum number of attachments allowed per message.
5. Enable the type of attachments allowed, such as images.
6. Select an AI model that supports file input, then save.

<Note>Currently, only images are supported as file attachments.</Note>

## AI credit usage

For image attachments, each successfully processed image consumes AI credits based on the model's usage.

For example, if the user sends 2 images and the AI model costs 3 credits per message, the total cost will be 6 credits (2 images \* 3 credits per image).

Failed, rejected or unprocessed attachments are not billed.


# Getting started with AI Agents
Source: https://docs.chatling.ai/ai-agent/getting-started

Learn how to create your first AI agent in Chatling

What we'll be covering:

1. [Create an AI Agent](#1-create-an-ai-agent)
2. [Configure the AI settings](#2-configure-the-ai-settings)
3. [Populate the knowledge base](#3-populate-the-knowledge-base)
4. [Create AI actions](#4-create-ai-actions)
5. [Test your Agent](#5-test-your-agent)
6. [Deploy](#6-deploy-your-agent)

## 1. Create an AI Agent

1. Go to your account and open the "My agents" page. Click the `+ Create` or `New` button.

<img />

2. Select `AI Agent` as the type.

<img />

3. Enter a name for your Agent and click `Create agent`.

<img />

## 2. Configure the AI settings

Once your Agent is created, it's time to configure it's AI settings.

1. From your agent's dashboard, click `Settings` in the sidebar.

<img />

2. Select the `AI` menu.

<img />

3. Here you can configure the AI settings, such as:

* **AI Model**: The AI model that the Agent will use to generate responses.
* **Temperature**: Controls randomness of the agent's responses. A lower temperature will make the outputs more focused and deterministic, whereas a higher temperature will make the responses diverse and creative.
* **Instructions**: Define the agent's role, goals, guardrails, and style (often called the "system prompt"). There are templates available to help you get started. Click the `Browse templates` button to see the available templates.

<img />

## 3. Populate the knowledge base

The Knowledge Base is where you upload information the Agent uses to generate responses to user queries. You can upload information about your business, products, services, policies, and more.

You can add several types of data to the knowledge base, such as websites, documents, texts, and FAQs. You can also connect your Zendesk or Zoho account to import articles from your help center.

When a user asks a question, the Agent queries the knowledge base for relevant information and generates a response based on the data it finds.

<img />

To add data to the knowledge base, click the `+ Add data source` button, then select the type of data you want to add.

<img />

## 4. Create AI actions

Actions unlock the true power of AI Agents. Instead of only generating replies, the Agent can actively carry out tasks during a conversation.

This might involve saving details of potential leads, displaying booking widgets, interacting with external systems to fetch or store data, creating support tickets, and more.

1. Click the `Actions` menu from the sidebar.
2. Click `Create action`.
3. Select the type of action you want to create.
4. Configure the action according to your needs.
5. Click the `Create` button to save the action.

To learn more about actions, check out the [Actions](/ai-agent/actions/introduction) documentation.

## 5. Test your Agent

You can test your AI Agent in the Playground. It is your sandbox to experiment with your Agent in real time.

To open the Playground, click `Playground` from the sidebar menu.

You can tweak core settings—like AI model, enabled actions, temperature, and instructions—then chat with the Agent to see exactly how those changes affect behavior.

<img alt="Open Playground" />

You can also run side-by-side comparisons of up to 5 instances of your Agent, each with different settings, to quickly identify the configuration that performs best.

<img alt="AI Agent Playground" />

## 6. Deploy your Agent

Once you've built your AI Agent, it's time to deploy it to your website, WhatsApp, or other channels.

Click `Deploy` from the sidebar menu. Select the channel you want to deploy your Agent to and follow the on-screen instructions.

<img alt="Deploy AI Agent" />


# AI Agent
Source: https://docs.chatling.ai/ai-agent/introduction



AI Agents are intelligent, configurable assistants that can understand user intent, take actions, and deliver outcomes—not just answers.

An Agent combines your instructions, knowledge, and integrations to hold natural conversations, collect the right data, and execute tasks like creating tickets, checking order status, or showing buttons for next steps.

You can train AI Agents on your own data, such as your company website, documents, policies, and more, to deliver accurate and relevant responses to your users.

## Typical use cases

* **Customer support**: Answer FAQs, verify orders, troubleshoot issues, create/route tickets, and surface KB answers with links.
* **Sales & lead gen**: Qualify prospects, save leads, book appointments and demos, and push them into your CRM.
* **Account tasks**: Update profiles, check balances/usage, manage subscriptions, and more (with your APIs).

## Key features

* **Train on your data**: Ingest your website, docs, FAQs, policies, or third-party knowledge bases (Zoho, Zendesk) to train the AI Agent.
* **AI Actions**: Actively carries out tasks during a conversation, such as collecting user's details, displaying buttons, interacting with external APIs and services, and more.
* **No-code builder**: Create and manage Agents without technical expertise.
* **Simple installation**: Drop the widget on any site (WordPress, Squarespace, Shopify, etc.) with a single line of widget code.
* **Lead capture & CRM sync**: Collect contacts or push to your CRM via Zapier.
* **Multilingual AI**: Auto-detect and reply in the user's language.
* **Playground**: Safely test, iterate, and roll out changes.
* **Analytics & monitoring**: Track conversations, leads, top pages, and fine-tune answers.
* **Security & compliance**: GDPR-ready; encryption in transit and at rest.
* **AI model choice**: Use OpenAI, Anthropic, Gemini, and more.

## How does it differ from AI Chatbots?

Chatbots rely on prebuilt flows whereas AI Agents plan steps dynamically based on context and your rules—no rigid flow design required. They can decide on the tasks to carry out while conversing with users.


# Playground
Source: https://docs.chatling.ai/ai-agent/playground



The Playground is your sandbox to experiment with your AI agent in real time. You can tweak core settings—like AI model, enabled actions, temperature, and instructions—then chat with the agent to see exactly how those changes affect behavior.

You can also run side-by-side comparisons of up to 5 instances of your agent, each with different settings, to quickly identify the configuration that performs best.

<img alt="AI Agent Playground" />

## How to compare multiple variations of your agent?

To test with different variations of your agent, click the `Compare` button in the top right corner of the playground. A new instance of your agent will be created with default settings.

<img alt="Compare different variations of your agent" />

You can then tweak the settings of the new instance and chat with it to see how it performs.

<img alt="Compare multiple variations of your agent" />

All inputs to agents are synced between the instances, so you can see how the agent behaves with different settings. If you want to disable this, you can toggle the `Sync` button above one of the agents.

<img alt="Sync agents" />

To remove an agent, click the `X` button above it.

<img alt="Remove an agent instance" />


# Adding Quick Replies to AI Agents
Source: https://docs.chatling.ai/ai-agent/quick-replies



Quick replies are buttons displayed above the input field that allow users to ask common questions without typing.

<img alt="Quick Replies demo" />

<Note>This guide is for adding quick replies to AI Agents. For AI Chatbots, refer to [this guide](/chatbot/builder/block-options/quick-replies)</Note>

## How to add quick replies to your AI Agent

1. Go to the `Deploy` page of your AI agent.

<img alt="Open Deploy page" />

2. Under the `Website Widget` option, click the settings icon to open the widget settings.

<img alt="Website widget settings button" />

3. Click `Texts` from the sidebar and go to the `Quick Replies` section.

<img alt="Quick replies configuration" />

4. Click the `Add` button to add a new quick reply. Each quick reply will have a label and a message. The label will be displayed on the button and the message will be sent when the user clicks on the button.

<Note>Label is optional, but recommended to keep the button short and descriptive.</Note>

<img alt="Add and configure a quick reply" />

5. You can also add translations for the quick replies, which will be displayed automatically based on the user's language.

6. The `Auto-hide quick replies` option allows you to automatically hide the quick replies after a certain number of messages are sent by the user. This is useful to prevent the quick replies from being displayed at all times.

<img alt="Auto-hide settings for quick replies" />

7. Once you are done, click the `Save` button to save the changes.


# AI credits
Source: https://docs.chatling.ai/ai/ai-credits

Understanding AI credits and how they are consumed

AI credits are used to manage and track AI usage. These credits are consumed each time a chatbot or AI agent generates an AI response.

The number of credits consumed per response varies based on the AI model you use. Below's a breakdown of credit usage by model.

<Note>
  For chatbots, credits are not consumed for normal messages sent and received by users. It is only used when the chatbot uses AI to generate responses (such as when you use the [AI block](/chatbot/builder/blocks/ai/ai-response)).
</Note>

## Credits usage by AI model

* Claude Opus 5: 25
* Claude Opus 4.8: 14
* Claude Opus 4.6: 8
* Claude Sonnet 5: 12
* Claude Sonnet 4.6: 4
* Claude Sonnet 4.5: 3
* Claude Haiku 4.5: 1
* Claude Opus 4: 15
* Gemini 3.6 Flash: 4
* Gemini 3.5 Flash: 4
* Gemini 3.1 Pro: 3
* Gemini 3.1 Flash Lite: 1
* Gemini 3 Flash: 1
* Gemini 2.5 Pro: 1.5
* Gemini 2.5 Flash: 0.5
* GPT-5.6 Sol: 25
* GPT-5.6 Terra: 10
* GPT-5.6 Luna: 5
* GPT-5.5: 14
* GPT-5.4: 4
* GPT-5.2: 6
* GPT-5.1: 5
* GPT-4.1: 2.5
* GPT-4.1 Mini: 2
* GPT-4.1 Nano: 1
* GPT-4o: 5
* GPT-4o mini: 1
* o3 Mini: 2
* o4 Mini: 3.5
* Mistral Small 4: 0.5
* Mistral Medium 3.1: 1
* Mistral Large 3: 1
* DeepSeek v3.2: 0.5
* xAI Grok 4.2: 3
* xAI Grok 4.1: 0.5

## How to check your AIs usage

1. Log in to your account.
2. Click the `Billing & usage` menu in the sidebar.
3. Click the `Usage` tab.
4. The usage will be displayed under the `Monthly usage` section.

<img alt="AI credits usage page" />


# Fix incorrect AI answers
Source: https://docs.chatling.ai/ai/fix-incorrect-answers

Learn how to fix incorrect AI responses using the fine-tuning feature in Chatling.

Although the AI is trained on the data you add to the knowledge base, it may not always get the answer right, such as when it's asked a question that is not in the knowledge base or when it hallucinates.

To fix this, you can use the fine-tuning feature on Chatling's conversations page. This feature is designed to help improve the chatbot's performance by refining incorrect responses.

When you're viewing a conversation, you'll see a "Fine-tune this answer" button below every AI response. This feature allows you to fix incorrect AI responses so that it will learn to answer correctly in the future.

## How to use the fine-tuning feature

1. From the chatbot dashboard, click on the "Conversations" menu.

<img alt="Open conversations page from chatbot dashboard" />

2. Find and open a conversation where the AI has responded incorrectly.

3. Click the `Fine-tune this answer` button below the AI response you want to fix.

<img alt="Click the fine-tune answer button" />

4. A dialog will appear where you can edit the AI's answer or replace it with a correct one.

<img alt="Click finetune button" />

5. Once done, click the `Finetune` button. The new answer will be added to the FAQ sources in the knowledge base and will be queued for processing.

Now, when the AI is asked a similar question, it will respond with the answer you provided.


# Supported AI models
Source: https://docs.chatling.ai/ai/supported-ai-models

A list of supported AI models in Chatling.

Chatling supports the following LLMs:

* GPT-5.6 (Sol, Terra, Luna)
* GPT-5.5
* GPT-5.4
* GPT-5.2
* GPT-5.1
* GPT-4.1
* GPT-4.1 Mini
* GPT-4.1 Nano
* GPT-4o
* GPT-4o Mini
* o4 Mini
* o3 Mini
* Claude Opus 5
* Claude Opus 4.8
* Claude Opus 4.6
* Claude Opus 4
* Claude Sonnet 5
* Claude Sonnet 4.6
* Claude Sonnet 4
* Gemini 3.6 Flash
* Gemini 3.5 Flash
* Gemini 3.1 Pro
* Gemini 3.1 Flash Lite
* Gemini 3 Flash
* Gemini 2.5 Pro
* Gemini 2.5 Flash
* Mistral Small 4
* Mistral Medium 3.1
* Mistral Large 3
* DeepSeek v3.2
* xAI Grok 4.2
* xAI Grok 4.1

To request a new AI model, please [contact us](mailto:support@chatling.ai).


# Chat with Knowledge Base AI
Source: https://docs.chatling.ai/api-reference/v2/ai-kb/chat

POST /chatbots/{chatbotId}/ai/kb/chat
Chat with the AI using the knowledge base as the response source.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Body

<ParamField type="string">
  The message to send to the AI.
</ParamField>

<ParamField type="integer">
  The ID of the AI model to use for the response. To get a list of available AI models, use the [List AI models](./list-ai-models) endpoint.
</ParamField>

<ParamField type="string">
  The ID of the conversation. This allows the AI to remember the context of the conversation.

  If left blank, a new conversation will be created.
</ParamField>

<ParamField type="string">
  The ID of the contact to associate with the conversation.
</ParamField>

<ParamField type="integer">
  The ID of the language to use for the AI response. To get a list of available languages, use the [List languages](./list-ai-languages) endpoint.
</ParamField>

<ParamField type="float">
  The temperature to be used by the AI. The temperature controls the randomness of the response. A lower temperature value, such as 0, will make the outputs more focused and deterministic, whereas a higher temperature, such as 1, will make the responses more diverse and unpredictable.
</ParamField>

<ParamField type="array">
  List of [instructions](/chatbot/ai/instructions) to tailor the AI's response. It can be used to provide additional context to the AI, such as the desired tone or style of the response.

  Must be an array of strings.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="conversation_id" type="string">
      The unique identifier of the conversation.
    </ResponseField>

    <ResponseField name="response" type="string">
      The response from the AI.
    </ResponseField>

    <ResponseField name="sources" type="array">
      <Expandable title="properties">
        <ResponseField name="type" type="string">
          The type of the source, such as `webpage` or `document`.
        </ResponseField>

        <ResponseField name="title" type="string">
          The title of the source.
        </ResponseField>

        <ResponseField name="url" type="string">
          The URL of the source if it's a webpage.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "conversation_id": "3154224116",
          "response": "We offer a variety of AI models to power your chatbot. Here are the models available:\n\n- **GPT-4o**\n- **GPT-4 Turbo**\n- **GPT-3.5 Turbo**\n- **Claude 3.5 Sonnet**\n- **Claude 3 Opus**\n- **Claude 3 Sonnet**\n- **Claude 3 Haiku**\n\nThese models ensure that you can select the best fit for your specific needs and use cases.",
          "sources": [
              {
                  "type": "webpage",
                  "title": "Supported AI Models - Chatling Documentation",
                  "url": "https://docs.chatling.ai/ai/supported-ai-models"
              },
              {
                  "type": "webpage",
                  "title": "Pricing | Chatling",
                  "url": "https://chatling.ai/pricing"
              },
          ]
      }
  }
  ```
</ResponseExample>


# List AI languages
Source: https://docs.chatling.ai/api-reference/v2/ai-kb/list-ai-languages

GET /chatbots/{chatbotId}/ai/kb/languages
Get a list of all the supported AI languages.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="languages" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="integer">
          The unique identifier of the language.
        </ResponseField>

        <ResponseField name="name" type="string">
          The name of the language.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 6,
              "per_page": 15
          },
          "languages": [
              {
                  "id": 1,
                  "name": "Auto"
              },
              {
                  "id": 2,
                  "name": "English"
              },
              {
                  "id": 3,
                  "name": "Albanian"
              },
              {
                  "id": 4,
                  "name": "Arabic"
              },
              {
                  "id": 5,
                  "name": "Armenian"
              },
              {
                  "id": 7,
                  "name": "Azerbaijani"
              },
              {
                  "id": 9,
                  "name": "Basque"
              },
              {
                  "id": 10,
                  "name": "Belarusian"
              },
              {
                  "id": 11,
                  "name": "Bengali"
              },
              {
                  "id": 12,
                  "name": "Bhojpuri"
              },
              {
                  "id": 13,
                  "name": "Bosnian"
              },
              {
                  "id": 15,
                  "name": "Bulgarian"
              },
              {
                  "id": 17,
                  "name": "Catalan"
              },
              {
                  "id": 19,
                  "name": "Chinese (Simplified)"
              },
              {
                  "id": 20,
                  "name": "Croatian"
              }
          ]
      }
  }
  ```
</ResponseExample>


# List AI models
Source: https://docs.chatling.ai/api-reference/v2/ai-kb/list-ai-models

GET /chatbots/{chatbotId}/ai/kb/models
Get a list of all the supported AI models.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="models" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="integer">
          The unique identifier of the AI model.
        </ResponseField>

        <ResponseField name="name" type="string">
          The name of the model.
        </ResponseField>

        <ResponseField name="credits" type="array">
          The number of AI credits consumed for each response generated by the model.
        </ResponseField>

        <ResponseField name="temperature" type="object">
          The minimum and maximum temperature values for the model.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 1,
              "per_page": 15
          },
          "models": [
              {
                  "id": 1,
                  "name": "GPT-3.5 Turbo",
                  "credits": 1,
                  "temperature": {
                      "min": 0,
                      "max": 1
                  }
              },
              {
                  "id": 2,
                  "name": "GPT-4",
                  "credits": 10,
                  "temperature": {
                      "min": 0,
                      "max": 1
                  }
              },
              {
                  "id": 3,
                  "name": "Claude 3 Opus",
                  "credits": 18,
                  "temperature": {
                      "min": 0,
                      "max": 1
                  }
              },
              {
                  "id": 4,
                  "name": "Claude 3 Sonnet",
                  "credits": 4,
                  "temperature": {
                      "min": 0,
                      "max": 1
                  }
              },
              {
                  "id": 5,
                  "name": "Claude 3 Haiku",
                  "credits": 1,
                  "temperature": {
                      "min": 0,
                      "max": 1
                  }
              },
              {
                  "id": 6,
                  "name": "GPT-4o",
                  "credits": 5,
                  "temperature": {
                      "min": 0,
                      "max": 1
                  }
              },
              {
                  "id": 7,
                  "name": "Claude 3.5 Sonnet",
                  "credits": 4,
                  "temperature": {
                      "min": 0,
                      "max": 1
                  }
              },
          ]
      }
  }
  ```
</ResponseExample>


# Create chatbot
Source: https://docs.chatling.ai/api-reference/v2/chatbots/create-chatbot

POST /chatbots
Create a new chatbot using a template or from scratch.

## Request parameters

### Body

<ParamField type="string">
  The chatbot name.
</ParamField>

<ParamField type="integer">
  The ID of the chatbot template to use. You can get the list of available templates using the [List chatbot templates](./list-chatbot-templates) endpoint.

  Leave blank to create a chatbot from scratch.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="id" type="integer">
      The unique identifier of the chatbot.
    </ResponseField>

    <ResponseField name="name" type="string">
      The name of the chatbot.
    </ResponseField>

    <ResponseField name="version" type="string">
      The version of the chatbot.
    </ResponseField>

    <ResponseField name="visibility" type="string">
      The visibility of the chatbot.
    </ResponseField>

    <ResponseField name="created_at" type="string">
      The date and time when the chatbot was created.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
          "id": "9761342719",
          "name": "My chatbot",
          "version": "2.0",
          "visibility": "public",
          "created_at": "2024-06-17T12:00:00+00:00"
      }
  }
  ```
</ResponseExample>


# Duplicate chatbot
Source: https://docs.chatling.ai/api-reference/v2/chatbots/duplicate-chatbot

POST /chatbots/{chatbotId}/duplicate

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="chatbot_id" type="string">
      The unique identifier of the duplicated chatbot.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
          "chatbot_id": "5285975738"
      }
  }
  ```
</ResponseExample>


# List chatbot templates
Source: https://docs.chatling.ai/api-reference/v2/chatbots/list-chatbot-templates

GET /chatbot-templates
Get a list of all the available chatbot templates. Can be used to create a new chatbot.

## Request parameters

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="templates" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="integer">
          The unique identifier of the template.
        </ResponseField>

        <ResponseField name="name" type="string">
          The name of the template.
        </ResponseField>

        <ResponseField name="description" type="string">
          The description of the template.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 1,
              "per_page": 25
          },
          "templates": [
              {
                  "id": 1,
                  "name": "AI Chatbot",
                  "description": "Uses AI to automatically respond to customers by leveraging your data, such as your website content, documents, and more."
              },
              {
                  "id": 2,
                  "name": "Basic Lead Generation",
                  "description": "Engage with prospective leads and capture their contact information."
              }
          ]
      }
  }
  ```
</ResponseExample>


# List chatbots
Source: https://docs.chatling.ai/api-reference/v2/chatbots/list-chatbots

GET /chatbots
Get a list of all the chatbots in the project.

## Request parameters

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="chatbots" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="string">
          The unique identifier of the chatbot.
        </ResponseField>

        <ResponseField name="name" type="string">
          The name of the chatbot.
        </ResponseField>

        <ResponseField name="version" type="string">
          The version of the chatbot.
        </ResponseField>

        <ResponseField name="visibility" type="string">
          The visibility of the chatbot. Can be `public` or `private`.
        </ResponseField>

        <ResponseField name="created_at" type="string">
          The date the chatbot was created.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 1,
              "per_page": 25
          },
          "chatbots": [
              {
                  "id": "8917794239",
                  "name": "My first chatbot",
                  "version": "2.0",
                  "visibility": "public",
                  "created_at": "2024-06-05T12:13:35:00+00:00"
              }
          ]
      }
  }
  ```
</ResponseExample>


# Retrieve chatbot
Source: https://docs.chatling.ai/api-reference/v2/chatbots/retrieve-chatbot

GET /chatbots/{chatbotId}
Retrieve a chatbot by its ID.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="id" type="integer">
      The unique identifier of the chatbot.
    </ResponseField>

    <ResponseField name="name" type="string">
      The name of the chatbot.
    </ResponseField>

    <ResponseField name="version" type="string">
      The version of the chatbot.
    </ResponseField>

    <ResponseField name="visibility" type="string">
      The visibility of the chatbot.
    </ResponseField>

    <ResponseField name="created_at" type="string">
      The date and time when the chatbot was created.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
          "id": "9761342719",
          "name": "My chatbot",
          "version": "2.0",
          "visibility": "public",
          "created_at": "2024-06-17T12:00:00+00:00"
      }
  }
  ```
</ResponseExample>


# Update chatbot settings
Source: https://docs.chatling.ai/api-reference/v2/chatbots/update-chatbot-settings

PATCH /chatbots/{chatbotId}
Update the settings of a chatbot.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Body

<ParamField type="string">
  The chatbot name.
</ParamField>

<ParamField type="string">
  The visibility of the chatbot. Possible values are `public` and `private`.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="id" type="integer">
      The unique identifier of the chatbot.
    </ResponseField>

    <ResponseField name="name" type="string">
      The name of the chatbot.
    </ResponseField>

    <ResponseField name="version" type="string">
      The version of the chatbot.
    </ResponseField>

    <ResponseField name="visibility" type="string">
      The visibility of the chatbot.
    </ResponseField>

    <ResponseField name="created_at" type="string">
      The date and time when the chatbot was created.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
          "id": "9761342719",
          "name": "My chatbot",
          "version": "2.0",
          "visibility": "public",
          "created_at": "2024-06-17T12:00:00+00:00"
      }
  }
  ```
</ResponseExample>


# Create contact
Source: https://docs.chatling.ai/api-reference/v2/contacts/create-contact

POST /chatbots/{chatbotId}/contacts
Create a new contact for the chatbot.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Body

<ParamField type="object">
  At least one of the following properties is required.

  <Expandable title="properties">
    <ParamField type="string" placeholder="John" />

    <ParamField type="string" placeholder="Doe" />

    <ParamField type="string" placeholder="john.doe@example.com" />

    <ParamField type="string" placeholder="1234567890" />

    <ParamField type="string" placeholder="Software Engineer" />

    <ParamField type="string" placeholder="Acme Inc" />

    <ParamField type="string" placeholder="https://acme.com" />

    <ParamField type="string" placeholder="Technology" />

    <ParamField type="string" placeholder="123 Main St" />

    <ParamField type="string" placeholder="New York" />

    <ParamField type="string" placeholder="NY" />

    <ParamField type="string" placeholder="10001" />

    <ParamField type="string" placeholder="USA" />
  </Expandable>
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="id" type="string">
      The unique identifier of the contact.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "id": "qtr89df0-112d-d197-b541-3f8674663246"
      }
  }
  ```
</ResponseExample>


# Delete contact
Source: https://docs.chatling.ai/api-reference/v2/contacts/delete-contact

DELETE /chatbots/{chatbotId}/contacts/{contactId}
Delete a contact by its ID.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The contact ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success"
  }
  ```
</ResponseExample>


# List contacts
Source: https://docs.chatling.ai/api-reference/v2/contacts/list-contacts

GET /chatbots/{chatbotId}/contacts
Get a list of all the contacts and leads saved by the chatbot.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

<ParamField type="string">
  The sort order. Possible values:

  * `date_desc`: Sort by date in descending order.
  * `date_asc`: Sort by date in ascending order.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="contacts" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="string">
          The unique identifier of the contact.
        </ResponseField>

        <ResponseField name="name" type="string">
          The name of the contact.
        </ResponseField>

        <ResponseField name="email" type="string">
          The email address of the contact.
        </ResponseField>

        <ResponseField name="job_title" type="string">
          The job title of the contact.
        </ResponseField>

        <ResponseField name="phone" type="string">
          The phone number of the contact.
        </ResponseField>

        <ResponseField name="website" type="string">
          The website URL of the contact.
        </ResponseField>

        <ResponseField name="company" type="string">
          The company name of the contact.
        </ResponseField>

        <ResponseField name="created_at" type="string">
          The date and time when the contact was created.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 1,
              "per_page": 25
          },
          "contacts": [
              {
                  "id": "qtr89df0-112d-d197-b541-3f8674663246",
                  "name": "Mark Zuckerberg",
                  "email": "mark@meta.com",
                  "job_title": "CEO",
                  "phone": "555-555-5555",
                  "website": "https://meta.com",
                  "company": "Meta Inc.",
                  "created_at": "2024-06-08T13:38:33+00:00"
              }
          ]
      }
  }
  ```
</ResponseExample>


# Retrieve contact
Source: https://docs.chatling.ai/api-reference/v2/contacts/retrieve-contact

GET /chatbots/{chatbotId}/contacts/{contactId}
Retrieve a contact by its ID.

## Request parameters

### Path

<ParamField type="string">
  The contact ID.
</ParamField>

<ParamField type="string">
  The chatbot ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="id" type="integer">
      The unique identifier of the contact.
    </ResponseField>

    <ResponseField name="name" type="string">
      The name of the contact.
    </ResponseField>

    <ResponseField name="email" type="string">
      The email address of the contact.
    </ResponseField>

    <ResponseField name="job_title" type="string">
      The job title of the contact.
    </ResponseField>

    <ResponseField name="phone" type="string">
      The phone number of the contact.
    </ResponseField>

    <ResponseField name="website" type="string">
      The website URL of the contact.
    </ResponseField>

    <ResponseField name="company" type="string">
      The company name of the contact.
    </ResponseField>

    <ResponseField name="created_at" type="string">
      The date and time when the contact was created.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
          "id": "qtr89df0-112d-d197-b541-3f8674663246",
          "name": "Mark Zuckerberg",
          "email": "mark@meta.com",
          "job_title": "CEO",
          "phone": "555-555-5555",
          "website": "https://meta.com",
          "company": "Meta Inc.",
          "created_at": "2024-06-08T13:38:33+00:00"
      }
  }
  ```
</ResponseExample>


# Delete conversation
Source: https://docs.chatling.ai/api-reference/v2/conversations/delete-conversation

DELETE /chatbots/{chatbotId}/conversations/{conversationId}
Delete a conversation.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The conversation ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success"
  }
  ```
</ResponseExample>


# List conversation messages
Source: https://docs.chatling.ai/api-reference/v2/conversations/list-conversation-messages

GET /chatbots/{chatbotId}/conversations/{conversationId}/messages
Get a list of all the messages for a conversation

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The conversation ID.
</ParamField>

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

<ParamField type="string">
  The sort order. Possible values:

  * `date_desc`: Sort by date in descending order.
  * `date_asc`: Sort by date in ascending order.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="messages" type="array">
      <Expandable title="properties">
        <ResponseField name="text" type="string">
          The text content of the message.
        </ResponseField>

        <ResponseField name="role" type="string">
          The role of the sender of the message (bot, user, or system).
        </ResponseField>

        <ResponseField name="is_ai_kb_response" type="boolean">
          Whether the message is AI generated and uses the knowledge base.
        </ResponseField>

        <ResponseField name="data" type="object">
          The data of the message. Varies depending on the message type.
        </ResponseField>

        <ResponseField name="created_at" type="string">
          The date and time when the message was created.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 1,
              "per_page": 15
          },
          "messages": [
              {
                  "text": "System variables are predefined variables that contain system information or can be used to perform specific actions. These variables are automatically created by the Builder.",
                  "role": "bot",
                  "is_ai_kb_response": true,
                  "data": {
                      "helpful_value": null,
                      "sources": [
                          {
                              "type": "webpage",
                              "title": "Types of variables - Chatling Documentation",
                              "url": "https://docs.chatling.ai/builder/variables/variable-types"
                          },
                          {
                              "type": "webpage",
                              "title": "Sidebar - Chatling Documentation",
                              "url": "https://docs.chatling.ai/builder/sidebar"
                          },
                          {
                              "type": "webpage",
                              "title": "What are variables? - Chatling Documentation",
                              "url": "https://docs.chatling.ai/builder/variables/what-are-variables"
                          }
                      ]
                  },
                  "created_at": "2024-06-17T16:09:52+00:00"
              },
              {
                  "text": "What are system variables",
                  "role": "user",
                  "created_at": "2024-06-17T16:09:45+00:00"
              },
              {
                  "text": "**Hello! How can I assist you today?**\n\nIf you have any questions related to our chatbot or services, please feel free to ask. I'm here to help!",
                  "role": "bot",
                  "is_ai_kb_response": true,
                  "data": {
                      "helpful_value": null,
                      "sources": []
                  },
                  "created_at": "2024-06-14T15:45:39+00:00"
              },
              {
                  "text": "Hello!",
                  "role": "user",
                  "created_at": "2024-06-14T15:45:34+00:00"
              }
          ]
      }
  }
  ```
</ResponseExample>


# List conversations
Source: https://docs.chatling.ai/api-reference/v2/conversations/list-conversations

GET /chatbots/{chatbotId}/conversations
Get a list of all the chatbot's conversations with users.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Query

<ParamField type="string">
  The pagination cursor returned in `pages.next_cursor` from the previous response. Omit this parameter to retrieve the first page. Keep the same `sort` value when requesting subsequent pages.
</ParamField>

<ParamField type="string">
  The sort order. Possible values:

  * `date_desc`: Sort by date in descending order.
  * `date_asc`: Sort by date in ascending order.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="per_page" type="integer">
          The maximum number of conversations returned per request.
        </ResponseField>

        <ResponseField name="has_more_pages" type="boolean">
          Whether more conversations are available.
        </ResponseField>

        <ResponseField name="next_cursor" type="string">
          The cursor to pass to the next request. This is `null` when there are no more conversations.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="conversations" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="string">
          The unique identifier of the conversation.
        </ResponseField>

        <ResponseField name="contact_id" type="string">
          The unique identifier of the contact associated with the conversation.
        </ResponseField>

        <ResponseField name="archived" type="boolean">
          Whether the conversation is archived (by the admin).
        </ResponseField>

        <ResponseField name="important" type="boolean">
          Whether the conversation is marked as important.
        </ResponseField>

        <ResponseField name="created_at" type="string">
          The date and time when the conversation was created.
        </ResponseField>

        <ResponseField name="messages" type="array">
          Recent 20 messages in the conversation.

          <Expandable title="properties">
            <ResponseField name="id" type="string">
              The unique identifier of the message.
            </ResponseField>

            <ResponseField name="text" type="string">
              The text content of the message.
            </ResponseField>

            <ResponseField name="role" type="string">
              The role of the sender of the message (bot, user, or system).
            </ResponseField>

            <ResponseField name="is_ai_kb_response" type="boolean">
              Whether the message is generated by the AI using the knowledge base.
            </ResponseField>

            <ResponseField name="data" type="object">
              The data of the message. Varies depending on the message type.

              <Expandable title="properties">
                <ResponseField name="helpful_value" type="string">
                  (AI response) Whether the AI's response was marked as helpful by the user. Possible values are `1` for helpful, `0` for not helpful, and `null` for not rated.
                </ResponseField>

                <ResponseField name="sources" type="string">
                  (AI response) The sources used by the AI to generate the response.
                </ResponseField>
              </Expandable>
            </ResponseField>

            <ResponseField name="created_at" type="string">
              The date and time when the message was created.
            </ResponseField>
          </Expandable>
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "per_page": 5,
              "has_more_pages": true,
              "next_cursor": "eyJjcmVhdGVkX2F0IjoiMjAyNC0wNi0xNFQxNTo0NTozNC4wMDAwMDBaIiwiaWQiOjg5Nzc2MTc5NTMsIl9wb2ludHNUb05leHRJdGVtcyI6dHJ1ZX0"
          },
          "conversations": [
              {
                  "id": "8977617953",
                  "contact_id": "qtr89df0-112d-d197-b541-3f8674663246",
                  "archived": 0,
                  "important": 1,
                  "created_at": "2024-06-14T15:45:34+00:00",
                  "messages": [
                      {
                          "text": "System variables are predefined variables that contain system information or can be used to perform specific actions. These variables are automatically created by the Builder.",
                          "role": "bot",
                          "is_ai_kb_response": true,
                          "data": {
                              "helpful_value": null,
                              "sources": [
                                  {
                                      "type": "webpage",
                                      "title": "Types of variables - Chatling Documentation",
                                      "url": "https://docs.chatling.ai/builder/variables/variable-types"
                                  },
                                  {
                                      "type": "webpage",
                                      "title": "Sidebar - Chatling Documentation",
                                      "url": "https://docs.chatling.ai/builder/sidebar"
                                  },
                                  {
                                      "type": "webpage",
                                      "title": "What are variables? - Chatling Documentation",
                                      "url": "https://docs.chatling.ai/builder/variables/what-are-variables"
                                  }
                              ]
                          },
                          "created_at": "2024-06-17T16:09:52+00:00"
                      },
                      {
                          "text": "What are system variables",
                          "role": "user",
                          "created_at": "2024-06-17T16:09:45+00:00"
                      },
                      {
                          "text": "**Hello! How can I assist you today?**\n\nIf you have any questions related to our chatbot or services, please feel free to ask. I'm here to help!",
                          "role": "bot",
                          "is_ai_kb_response": true,
                          "data": {
                              "helpful_value": null,
                              "sources": []
                          },
                          "created_at": "2024-06-14T15:45:39+00:00"
                      },
                      {
                          "text": "Hello!",
                          "role": "user",
                          "created_at": "2024-06-14T15:45:34+00:00"
                      }
                  ]
              }
          ]
      }
  }
  ```
</ResponseExample>


# Rate AI answer
Source: https://docs.chatling.ai/api-reference/v2/conversations/rate-ai-answer

PATCH /chatbots/{chatbotId}/conversations/{conversationId}/messages/{messageId}/rate-ai-answer

Use this endpoint to rate an AI answer as helpful or not helpful. You can only rate AI answers generated using the Knowledge Base.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The conversation ID.
</ParamField>

<ParamField type="string">
  The message ID.
</ParamField>

### Body

<ParamField type="string">
  * `0`: Remove rating
  * `1`: Helpful
  * `-1`: Not helpful
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": null
  }
  ```
</ResponseExample>


# Retrieve conversation
Source: https://docs.chatling.ai/api-reference/v2/conversations/retrieve-conversation

GET /chatbots/{chatbotId}/conversations/{conversationId}
Retrieve a conversation by its ID.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The conversation ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="id" type="string">
      The unique identifier of the conversation.
    </ResponseField>

    <ResponseField name="contact_id" type="string">
      The unique identifier of the contact associated with the conversation.
    </ResponseField>

    <ResponseField name="archived" type="boolean">
      Whether the conversation is archived (by the admin).
    </ResponseField>

    <ResponseField name="important" type="boolean">
      Whether the conversation is marked as important.
    </ResponseField>

    <ResponseField name="created_at" type="string">
      The date and time when the conversation was created.
    </ResponseField>

    <ResponseField name="messages" type="array">
      List of the most recent 20 messages in the conversation.

      <Expandable title="properties">
        <ResponseField name="id" type="string">
          The unique identifier of the message.
        </ResponseField>

        <ResponseField name="text" type="string">
          The text content of the message.
        </ResponseField>

        <ResponseField name="role" type="string">
          The role of the sender of the message (bot, user, or system).
        </ResponseField>

        <ResponseField name="is_ai_kb_response" type="boolean">
          Whether the message is generated by the AI using the knowledge base.
        </ResponseField>

        <ResponseField name="data" type="object">
          The data of the message. Varies depending on the message type.

          <Expandable title="properties">
            <ResponseField name="helpful_value" type="string">
              (AI response) Whether the AI's response was marked as helpful by the user. Possible values are `1` for helpful, `0` for not helpful, and `null` for not rated.
            </ResponseField>

            <ResponseField name="sources" type="string">
              (AI response) The sources used by the AI to generate the response.
            </ResponseField>
          </Expandable>
        </ResponseField>

        <ResponseField name="created_at" type="string">
          The date and time when the message was created.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
              "id": "8977617953",
              "contact_id": "qtr89df0-112d-d197-b541-3f8674663246",
              "archived": 0,
              "important": 1,
              "created_at": "2024-06-14T15:45:34+00:00",
              "messages": [
                  {
                      "text": "System variables are predefined variables that contain system information or can be used to perform specific actions. These variables are automatically created by the Builder.",
                      "role": "bot",
                      "is_ai_kb_response": true,
                      "data": {
                          "helpful_value": null,
                          "sources": [
                              {
                                  "type": "webpage",
                                  "title": "Types of variables - Chatling Documentation",
                                  "url": "https://docs.chatling.ai/builder/variables/variable-types"
                              },
                              {
                                  "type": "webpage",
                                  "title": "Sidebar - Chatling Documentation",
                                  "url": "https://docs.chatling.ai/builder/sidebar"
                              },
                              {
                                  "type": "webpage",
                                  "title": "What are variables? - Chatling Documentation",
                                  "url": "https://docs.chatling.ai/builder/variables/what-are-variables"
                              }
                          ]
                      },
                      "created_at": "2024-06-17T16:09:52+00:00"
                  },
                  {
                      "text": "What are system variables",
                      "role": "user",
                      "created_at": "2024-06-17T16:09:45+00:00"
                  },
                  {
                      "text": "**Hello! How can I assist you today?**\n\nIf you have any questions related to our chatbot or services, please feel free to ask. I'm here to help!",
                      "role": "bot",
                      "is_ai_kb_response": true,
                      "data": {
                          "helpful_value": null,
                          "sources": []
                      },
                      "created_at": "2024-06-14T15:45:39+00:00"
                  },
                  {
                      "text": "Hello!",
                      "role": "user",
                      "created_at": "2024-06-14T15:45:34+00:00"
                  }
              ]
          }
  }
  ```
</ResponseExample>


# Update conversation
Source: https://docs.chatling.ai/api-reference/v2/conversations/update-conversation

PATCH /chatbots/{chatbotId}/conversations/{conversationId}
Update a conversation's properties.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The conversation ID.
</ParamField>

### Body

At least one of the following properties is required.

<ParamField type="boolean">
  Whether to archive the conversation.
</ParamField>

<ParamField type="boolean">
  Whether to mark the conversation as important.
</ParamField>

<ParamField type="string">
  The ID of the contact to associate with the conversation.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="id" type="string">
      The unique identifier of the conversation.
    </ResponseField>

    <ResponseField name="contact_id" type="string">
      The unique identifier of the contact associated with the conversation.
    </ResponseField>

    <ResponseField name="archived" type="boolean">
      Whether the conversation is archived (by the admin).
    </ResponseField>

    <ResponseField name="important" type="boolean">
      Whether the conversation is marked as important.
    </ResponseField>

    <ResponseField name="created_at" type="string">
      The date and time when the conversation was created.
    </ResponseField>

    <ResponseField name="messages" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="string">
          The unique identifier of the message.
        </ResponseField>

        <ResponseField name="text" type="string">
          The text content of the message.
        </ResponseField>

        <ResponseField name="role" type="string">
          The role of the sender of the message (bot, user, or system).
        </ResponseField>

        <ResponseField name="is_ai_kb_response" type="boolean">
          Whether the message is generated by the AI using the knowledge base.
        </ResponseField>

        <ResponseField name="data" type="object">
          The data of the message. Varies depending on the message type.

          <Expandable title="properties">
            <ResponseField name="helpful_value" type="string">
              (AI response) Whether the AI's response was marked as helpful by the user. Possible values are `1` for helpful, `0` for not helpful, and `null` for not rated.
            </ResponseField>

            <ResponseField name="sources" type="string">
              (AI response) The sources used by the AI to generate the response.
            </ResponseField>
          </Expandable>
        </ResponseField>

        <ResponseField name="created_at" type="string">
          The date and time when the message was created.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json theme={null}
  {
      "status": "success",
      "data": {
              "id": "8977617953",
              "contact_id": "qtr89df0-112d-d197-b541-3f8674663246",
              "archived": 0,
              "important": 1,
              "created_at": "2024-06-14T15:45:34+00:00",
              "messages": [
                  {
                      "text": "System variables are predefined variables that contain system information or can be used to perform specific actions. These variables are automatically created by the Builder.",
                      "role": "bot",
                      "is_ai_kb_response": true,
                      "data": {
                          "helpful_value": null,
                          "sources": [
                              {
                                  "type": "webpage",
                                  "title": "Types of variables - Chatling Documentation",
                                  "url": "https://docs.chatling.ai/builder/variables/variable-types"
                              },
                              {
                                  "type": "webpage",
                                  "title": "Sidebar - Chatling Documentation",
                                  "url": "https://docs.chatling.ai/builder/sidebar"
                              },
                              {
                                  "type": "webpage",
                                  "title": "What are variables? - Chatling Documentation",
                                  "url": "https://docs.chatling.ai/builder/variables/what-are-variables"
                              }
                          ]
                      },
                      "created_at": "2024-06-17T16:09:52+00:00"
                  },
                  {
                      "text": "What are system variables",
                      "role": "user",
                      "created_at": "2024-06-17T16:09:45+00:00"
                  },
                  {
                      "text": "**Hello! How can I assist you today?**\n\nIf you have any questions related to our chatbot or services, please feel free to ask. I'm here to help!",
                      "role": "bot",
                      "is_ai_kb_response": true,
                      "data": {
                          "helpful_value": null,
                          "sources": []
                      },
                      "created_at": "2024-06-14T15:45:39+00:00"
                  },
                  {
                      "text": "Hello!",
                      "role": "user",
                      "created_at": "2024-06-14T15:45:34+00:00"
                  }
              ]
          }
  }
  ```
</ResponseExample>


# API Introduction
Source: https://docs.chatling.ai/api-reference/v2/intro

The Chatling API allows you to manage your chatbots programmatically.

Integrate Chatling into your application or interact with your chatbots programmatically using our API.

This documentation guides you through creating your API key, authenticating requests, and sending requests to the API.

## Generate your API key

To send requests to the API, you must include your API key. Here's how to create it:

1. Go to your Chatling account and open the Project Settings.
2. Click the API Keys tab.
3. Press the `New API key` button.
4. Enter a name for the key and press `Generate key`.
5. Copy the newly created key. For security purposes, the API key will be displayed once only. Note it down and store it in a secure place.

If you forget your API key, you must delete it and generate a new one.

## Authentication

Your API key acts as the Bearer token and must be supplied in the `Authorization` header of every request.

<Accordion title="Example">
  ```
  Authorization: Bearer <API_KEY>
  ```
</Accordion>

## Retrieving the chatbot ID

Some endpoints require that you pass a chatbot ID as the path parameter. Here's a couple of ways to retrieve it:

* **Recommended method**: Using the `List chatbots` endpoint, you can fetch all the chatbots along with their IDs.
* Open the chatbot's settings in your account and you will find its ID listed there.


# Add FAQ
Source: https://docs.chatling.ai/api-reference/v2/knowledge-base/add-faq

POST /chatbots/{chatbotId}/knowledge-base/data-sources/faqs
Add new FAQ data sources to the knowledge base.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Body

<ParamField type="array">
  Array of FAQs to add to the knowledge base.

  <Expandable title="properties">
    <ParamField type="string">
      The question of the FAQ.
    </ParamField>

    <ParamField type="string">
      The answer of the FAQ.
    </ParamField>
  </Expandable>
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="faqs_added" type="integer">
      The number of FAQs that were added successfully.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "faqs_added": 45
      }
  }
  ```
</ResponseExample>


# Add link
Source: https://docs.chatling.ai/api-reference/v2/knowledge-base/add-link

POST /chatbots/{chatbotId}/knowledge-base/data-sources/links
Add new link data sources to the knowledge base.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Body

<ParamField type="string[]">
  Array of webpage links to add to the knowledge base.
</ParamField>

<ParamField type="string[]">
  Exclude sections of webpages based on their HTML class names.
</ParamField>

<ParamField type="string[]">
  Exclude sections of webpages based on their HTML IDs.
</ParamField>

<ParamField type="boolean">
  Exclude `header` tags.
</ParamField>

<ParamField type="boolean">
  Exclude `footer` tags.
</ParamField>

<ParamField type="boolean">
  Exclude `nav` tags.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="links_added" type="integer">
      The number of links that were added successfully.
    </ResponseField>

    <ResponseField name="duplicate_links_removed" type="array">
      An array of duplicate links that were removed.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "links_added": 105,
          "duplicate_links_removed": []
      }
  }
  ```
</ResponseExample>


# Add text
Source: https://docs.chatling.ai/api-reference/v2/knowledge-base/add-text

POST /chatbots/{chatbotId}/knowledge-base/data-sources/texts
Add new text data sources to the knowledge base.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Body

<ParamField type="string[]">
  Array of texts to add to the knowledge base.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="texts_added" type="integer">
      The number of texts that were added successfully.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "texts_added": 45
      }
  }
  ```
</ResponseExample>


# Delete data source
Source: https://docs.chatling.ai/api-reference/v2/knowledge-base/delete-source

Delete /chatbots/{chatbotId}/knowledge-base/data-sources/{dataSourceId}
Delete a data source from the knowledge base.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The data source ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success"
  }
  ```
</ResponseExample>


# List data sources
Source: https://docs.chatling.ai/api-reference/v2/knowledge-base/list-data-sources

GET /chatbots/{chatbotId}/knowledge-base/data-sources
Get a list of the data sources added to the knowledge base.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

<ParamField type="string">
  The sort order. Possible values:

  * `date_desc`: Sort by date in descending order.
  * `date_asc`: Sort by date in ascending order.
</ParamField>

<ParamField type="string">
  Filter by the type of the data source. Possible values are `link`, `text`, `faq`, `document`, and `zoho`.

  Leave blank to get all types of data sources.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="sources" type="array">
      <Expandable title="properties">
        <ResponseField name="id" type="string">
          The unique identifier of the data source.
        </ResponseField>

        <ResponseField name="type" type="string">
          The type of the data source.
        </ResponseField>

        <ResponseField name="status" type="string">
          The processing status of the data source. Possible values are `pending`, `processing`, `processed`, `error`.
        </ResponseField>

        <ResponseField name="characters" type="integer">
          The number of characters used by the data source.
        </ResponseField>

        <ResponseField name="resync_queued" type="boolean">
          Whether the data source is queued for resync.
        </ResponseField>

        <ResponseField name="data" type="object">
          Additional data based on the type of the data source.
        </ResponseField>

        <ResponseField name="created_at" type="string">
          The date and time when the data source was created.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 3,
              "per_page": 25
          },
          "sources": [
              {
                  "id": "321e979b-a174-89fc-25de-f0b31dbd659f",
                  "type": "link",
                  "status": "processed",
                  "characters": 6232,
                  "resync_queued": false,
                  "data": {
                      "url": "https://chatling.ai",
                      "page_title": "No-Code AI Chatbot for Your Website | Chatling"
                  },
                  "created_at": "2024-06-15T12:23:41"
              },
          ]
      }
  }
  ```
</ResponseExample>


# Resync data source
Source: https://docs.chatling.ai/api-reference/v2/knowledge-base/resync-source

POST /chatbots/{chatbotId}/knowledge-base/data-sources/{dataSourceId}/resync
Resync a data source.

**The following limitations apply:**

* You can have up to 50 data sources queued for resync. If you exceed this limit, you will receive an error and must wait until some of the queued resyncs are complete.
* You can only resync data sources that are in the `processed` state.

## Request parameters

### Path

<ParamField type="string">
  The chatbot ID.
</ParamField>

<ParamField type="string">
  The data source ID.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success"
  }
  ```
</ResponseExample>


# List members
Source: https://docs.chatling.ai/api-reference/v2/members/list-members

GET /members
Get a list of all the members in the project.

## Request parameters

### Query

<ParamField type="integer">
  The page number for pagination.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="pages" type="object">
      <Expandable title="properties">
        <ResponseField name="current_page" type="integer">
          The current page number.
        </ResponseField>

        <ResponseField name="last_page" type="integer">
          The last page number.
        </ResponseField>

        <ResponseField name="per_page" type="integer">
          The number of items per page.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="members" type="array">
      <Expandable title="properties">
        <ResponseField name="email" type="string">
          The email address of the member.
        </ResponseField>

        <ResponseField name="status" type="string">
          The status of the member (`Active` or `Pending`).
        </ResponseField>

        <ResponseField name="roles" type="array">
          The roles of the member in the project.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "pages": {
              "current_page": 1,
              "last_page": 1,
              "per_page": 15
          },
          "members": [
              {
                  "email": "elon@tesla.com",
                  "status": "Active",
                  "roles": [
                      "Owner"
                  ]
              },
              {
                  "email": "mark@meta.com",
                  "status": "Active",
                  "roles": [
                      "Admin"
                  ]
              },
              {
                  "email": "sundar@google.com",
                  "status": "Pending",
                  "roles": [
                      "Editor",
                      "Billing"
                  ]
              }
          ]
      }
  }
  ```
</ResponseExample>


# List settings
Source: https://docs.chatling.ai/api-reference/v2/project/list-settings

GET /project/settings
Retrieve the settings of the project.

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="project_id" type="string">
      The unique identifier of the project.
    </ResponseField>

    <ResponseField name="name" type="string">
      The name of the project.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "project_id": "8917794239",
          "name": "My first project"
      }
  }
  ```
</ResponseExample>


# Update settings
Source: https://docs.chatling.ai/api-reference/v2/project/update-settings

PATCH /project/settings
Update the project settings.

## Request parameters

### Body

<ParamField type="string">
  The project name.
</ParamField>

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="project_id" type="string">
      The unique identifier of the project.
    </ResponseField>

    <ResponseField name="name" type="string">
      The name of the project.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "project_id": "8917794239",
          "name": "My project"
      }
  }
  ```
</ResponseExample>


# Rate limiting
Source: https://docs.chatling.ai/api-reference/v2/rate-limiting

Our API has rate limits to prevent abuse and ensure fair usage.

We enforce rate limits to balance the load on our servers and provide a fair environment for all developers to interact with the Chatling API.

Therefore, the number of requests you send to the API will be measured and throttled if you surpass the allowed rate limit.

## Rate limit

The default rate limit is **300 API calls per minute** for each API key. We may adjust these limits in the future.

When you exceed the rate limit, you will receive a 429 status code with the following response:

```json theme={null}
{
    "status": "error",
    "message": "Too many requests"
}
```

## When does the rate limit reset?

The rate limit lasts 1 minute, and the number of requests you've sent within that window will reset at the next minute.


# AI Credits
Source: https://docs.chatling.ai/api-reference/v2/usage/ai-credits

GET /usage/ai-credits
Get the AI credits usage for the project.

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="used" type="integer">
      The number of AI credits used.
    </ResponseField>

    <ResponseField name="max" type="integer">
      The maximum number of AI credits allowed for the project.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "used": 55,
          "max": 3000
      }
  }
  ```
</ResponseExample>


# Chatbots
Source: https://docs.chatling.ai/api-reference/v2/usage/chatbots

GET /usage/chatbots
Get the chatbots usage for the project.

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="used" type="integer">
      The number of chatbots created.
    </ResponseField>

    <ResponseField name="max" type="integer">
      The maximum number of chatbots allowed for the project.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "used": 2,
          "max": 5
      }
  }
  ```
</ResponseExample>


# Email Credits
Source: https://docs.chatling.ai/api-reference/v2/usage/email-credits

GET /usage/email-credits
Get the email credits usage for the project.

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="used" type="integer">
      The number of email credits used.
    </ResponseField>

    <ResponseField name="max" type="integer">
      The maximum number of email credits allowed for the project.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "used": 125,
          "max": 1500
      }
  }
  ```
</ResponseExample>


# Knowledge Base
Source: https://docs.chatling.ai/api-reference/v2/usage/knowledge-base

GET /usage/knowledge-base
Get the knowledge base usage for the project.

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="used" type="integer">
      Total number of characters used in the knowledge base.
    </ResponseField>

    <ResponseField name="max" type="integer">
      The maximum number of characters allowed for the project.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "used": 1500000,
          "max": 20000000
      }
  }
  ```
</ResponseExample>


# User Seats
Source: https://docs.chatling.ai/api-reference/v2/usage/user-seats

GET /usage/user-seats
Get the user seats usage for the project.

## Response

<ResponseField name="status" type="string">
  The status of the request. Will be `success` if the request was successful, otherwise `error`.
</ResponseField>

<ResponseField name="data" type="object">
  <Expandable title="properties">
    <ResponseField name="used" type="integer">
      The number of seats used.
    </ResponseField>

    <ResponseField name="max" type="integer">
      The maximum number of seats allowed for the project.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
      "status": "success",
      "data": {
          "used": 3,
          "max": 10
      }
  }
  ```
</ResponseExample>


# Instructions
Source: https://docs.chatling.ai/chatbot/ai/instructions

A guide on what AI Instructions are and how to use them.

Instructions are a way to provide guidance to the AI on how to respond.

You can use instructions to tailor the AI's responses to your specific needs, such as providing more detailed responses, using a specific tone, have a specific personality, or avoiding certain topics.

Here are a few examples:

* Your name is "Joanne" and you are our customer support assistant. When referring to yourself, do not mention anything about being an AI assistant or AI model. Instead, refer to yourself as "Joanne".
* Keep your answers short and to the point, and do not provide unnecessary information.
* Use a friendly and casual tone when responding to users.
* You must act as a professional customer support agent. NEVER break character.
* When responding in English, use American English spelling and grammar.
* Promote special offers or promotions when appropriate. For example, if a customer asks about a product, you can mention that we have a store-wide promotion of 50% off.
* Limit your answers to a maximum of 5 sentences.
* You are a lead generation assistant for a Digital Marketing agency and you are communicating with a prospective customer.
* Do not discuss politics, religion, or any other sensitive topics.

## How to add instructions

The method for adding instructions depends on the [Response Source](/chatbot/builder/blocks/ai/ai-response#what-is-the-response-source) that you've set for the [AI Response](/chatbot/builder/blocks/ai/ai-response) block.

### Response Source: Knowledge Base

If you are using the Knowledge Base as the response source, you can add instructions using the [AI Configuration menu](/chatbot/builder/sidebar#ai-configuration) in the Builder's sidebar.

1. Click on the AI Configuration menu in the sidebar.

<img alt="Open AI Configuration menu from sidebar" />

2. Go to `Instructions`.

<img alt="Open Instructions page from AI Configuration sidebar menu" />

3. Click the `Add instruction` button and enter your instruction.

<img alt="Add new instruction in AI Configuration sidebar menu" />

4. To add more instructions, click the `New` button to create a new instruction.

### Response Source: AI Model

If you are using the AI Model as the response source, you can add instructions directly from the [AI Response block](/chatbot/builder/blocks/ai/ai-response).

1. Click the AI Response block on the canvas to open the block editor.
2. Under the `Instructions` section, you can add all your instructions. You can add multiple instructions in the same field, separated by a new line.

<img alt="Add instructions for AI Model response source" />


# Setting the AI model
Source: https://docs.chatling.ai/chatbot/ai/set-ai-model

Learn how to set the LLM model used by the AI.

There are various [AI models](/ai/supported-ai-models) available in Chatling that you can use to generate responses for your chatbot.

We recommend testing with different models to see which one works best for your chatbot and provides the most accurate responses. Each model uses a different amount of credits per response.

## How to set the AI model?

The method for choosing the AI model depends on the [Response Source](/chatbot/builder/blocks/ai/ai-response#what-is-the-response-source) that you've set for the [AI Response](/chatbot/builder/blocks/ai/ai-response) block.

Below are the instructions based on the response source you've selected.

### 1. Response Source: Knowledge Base

If you are using the Knowledge Base as the response source, you can set the AI model using the [AI Configuration menu](/chatbot/builder/sidebar#ai-configuration) in the Builder's sidebar.

1. Click on the AI Configuration menu in the sidebar.

<img alt="Open AI Configuration menu from sidebar" />

2. Go to `Settings`.

<img alt="Open Settings page from AI Configuration sidebar menu" />

3. Select the AI model you want to use from the dropdown list.

<img alt="Select AI model in AI Configuration settings sidebar menu" />

Once you've selected the AI model, all AI Response blocks that use the Knowledge Base as the response source will use this model to generate responses.

#### Setting the model on a per-block basis

If you want to set the AI model on a per-block basis, you can do so by opening the AI Response block's editor and settings the `Model` option. This will override the default model set in the AI Configuration settings.

<img alt="Override AI model setting in AI Response block" />

### 2. Response Source: AI Model

If you are using the "AI Model" as the response source, you can set the AI model from the block's editor using the `Model` option.

<img alt="Set model in AI Model response block" />


# Block Editor
Source: https://docs.chatling.ai/chatbot/builder/block-editor

Learn how to edit blocks in the Builder.

The Block Editor is where you can configure the settings of a block in the Builder.

The editor appears when you click a block that you've added to the canvas. Every block has its own unique settings that you can configure.

<img alt="Opening the block editor" />


# Adding Quick Replies to AI Chatbots
Source: https://docs.chatling.ai/chatbot/builder/block-options/quick-replies



Quick replies are messages that will help users respond quickly without having to type out a full response. They are displayed as buttons above the input field and users can click on them to send a message.

<img alt="Quick Replies demo" />

<Note>This guide is for adding quick replies to AI Chatbots. For AI Agents, refer to [this guide](/ai-agent/quick-replies)</Note>

## Supported blocks

Quick replies are available for the following Capture Response blocks:

* Text
* Number
* Email
* URL

## Setting up Quick Replies

Here's how to add quick replies to a supported block:

* Open the block editor for a block that supports quick replies.
* Under the "Quick Replies" section, click `Add` to add a new quick reply.

<img alt="Add a quick reply" />

* Enter the label for the quick reply. This is the text that will be displayed on the button.
* Enter the message that will be sent when the user clicks on the quick reply button.

For example if the label is "Pricing" and the message is "Tell me about your pricing", the user will see a button with the text "Pricing" and when they click on it, the message "Tell me about your pricing" will be sent.


# Voice Input
Source: https://docs.chatling.ai/chatbot/builder/block-options/voice-input

Allow users to speak to your chatbot using Voice Input.

Voice Input is a speech-to-text feature that allows users to record voice messages and transcribes them into text. Rather than typing their message, users can speak to your chatbot and it will automatically be converted to text.

<img alt="Voice Input demo" />

## Supported blocks

Currently, Voice Input is available for the Text input block only.

## How to enable Voice Input

Open the block editor for a Text input block and toggle on the "Voice Input" option.

<img alt="Enable Voice Input" />

The chatbot will then display a microphone icon when the block is displayed. Users can click on the microphone icon to record a voice message.

<img alt="Chatbot Voice Input" />

## What happens when I run out of Speech to Text credits?

When you're out of credits, the voice recording icon will be removed and users will not be able to access the feature. You can upgrade your plan to increase the credits limit or wait until the next billing cycle for the credits to reset.


# Create Contact Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/action/create-contact

Learn about the Create Contact block and how to set it up in the Builder.

The `Create Contact` block can be used to save a user's information as a contact. All saved contacts are displayed on the `Contacts` page in your dashboard.

When a contact is created, it is associated with the user and the information persists across multiple chat sessions. The information can be used to personalize the conversation, skip repetitive questions, and tailor the flow accordingly.

The block consists of the following components:

* **Contact details**: Define which fields you want to collect and save—such as first name, email, etc. These can be mapped from variables captured in the conversation flow (e.g. from a form or user input).
* **Deduplication**: Allows you to define how Chatling handles duplicate contacts during the creation process.


# Delete Contact Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/action/delete-contact

Learn about the Delete Contact block and how to set it up in the Builder.

The `Delete Contact` block can be used to delete a contact and dissociate it from the user.

The block consists of the following components:

* **Search**: Specify the field and value to use to look up the contact. You can enter a variable to search dynamically.


# Get Contact Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/action/get-contact

Learn about the Get Contact block and how to set it up in the Builder.

The `Get Contact` block can be used to retrieve a contact's information.

The block consists of the following components:

* **Search**: Specify the field and value to use to look up the contact. You can enter a variable to search dynamically.
* **Contact details**: Define the properties to retrieve and the variables to store the values in.


# HTTP Request Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/action/http-request

Learn about the HTTP Request block and how to set it up in the Builder.

The HTTP Request block is used to send HTTP requests to external APIs and services. You can use it to fetch data, send data, or perform other actions by interacting with APIs.

The block consists of the following components:

* **Request method**: The HTTP method to use for the request, such as GET, POST, PUT, PATCH, and DELETE.
* **URL**: The URL of the API endpoint to send the request to.
* **Request options**: You can configure additional options for the request, such as headers, query parameters, and request body.
* **Capture Response**: You can capture the responses from the API and store them a variable. The response must be in JSON format.

## Method and URL

In order to send a request, you must provide the endpoint URL and select the appropriate request method. The following request methods are supported:

* **GET**: Retrieve data from the server.
* **POST**: Send data to the server.
* **PUT**: Update data on the server.
* **PATCH**: Partially update data on the server.
* **DELETE**: Delete data from the server.

As an example, an endpoint URL might look like this:

`https://openlibrary.org/works/OL45804W.json`

## Request Options

When sending requests to external APIs, you may need to provide additional options such as headers, query parameters, and request body. Here are the available options:

* **Headers**: You can set headers for the request, such as Content-Type, Authorization, and Accept.
* **Query Params**: The URL query parameters to include for the request.
* **Request Body**: The request payload which can be passed as form data, form URL encoded, or raw JSON.

### How to use variables in JSON payload

To use variables in the request payload, you must enclose the variable's name in double curly braces within quotes. Here's an example:

```json theme={null}
{
    "name": "{{contact_name}}",
    "age": 21,
    "email": "{{contact_email}}"
}
```

Some points to note:

* Make sure that the variables exist and that their name is correct. Otherwise, they will not be replaced with the actual value.
* If you change a variable's name, you must also update the JSON payload to reflect the change.
* Variables must be enclosed in double curly braces as shown in the example above.

## Capture Response

Responses from the API can be captured and stored in one or more variables. In order for this to work, the response from the endpoint must be in JSON format.

Click the `Add` button to add a new row for capturing a value. You must specify the key and the variable where the value will be stored.

The naming convention for the key is as follows:

* **Top level data**: use the key, such as name or age.
* **Nested data**: use dot notation, such as user.name or profile.address.city.
* **Array data**: use the index, such as users\[0].name or countries\[1].cities\[0].population.

Let's take a look at an example. Below is a sample JSON response from an API endpoint:

```json theme={null}
{
    "title": "Fantastic Mr Fox",
    "permalink": "/works/OL45804W",
    "authors": [
    {
        "author": {
            "name": "Roald Dahl"
        },
    }
    ],
    "description": "The main character of Fantastic Mr. Fox is an extremely clever anthropomorphized fox named Mr. Fox. He lives with his wife and four little foxes. In order to feed his family, he steals food from the cruel, brutish farmers named Boggis, Bunce, and Bean every night.\r\n\r\nFinally tired of being constantly outwitted by Mr. Fox, the farmers attempt to capture and kill him. The foxes escape in time by burrowing deep into the ground. The farmers decide to wait outside the hole for the foxes to emerge. Unable to leave the hole and steal food, Mr. Fox and his family begin to starve. Mr. Fox devises a plan to steal food from the farmers by tunneling into the ground and borrowing into the farmer's houses.\r\n\r\nAided by a friendly Badger, the animals bring the stolen food back and Mrs. Fox prepares a great celebratory banquet attended by the other starving animals and their families. Mr. Fox invites all the animals to live with him underground and says that he will provide food for them daily thanks to his underground passages. All the animals live happily and safely, while the farmers remain waiting outside in vain for Mr. Fox to show up.",
    "meta": {
        "published_at": "1970-06-01"
    },
}
```

To capture the title, date of publication, and author name from the response, you would use the following keys:

* **Title**: `title`
* **Published date**: `meta.published_at`
* **Author Name**: `authors[0].author.name`

<img alt="HTTP Request capture response example" />


# Send Email Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/action/send-email

Learn about the Send Email block and how to set it up in the Builder.

The Send Email block is used to send emails to one or more recipients. You can use it to send notifications, follow ups, transactional emails and other types of emails.

The block consists of the following components:

* **From**: The email address from which the email will be sent.
* **From name**: The name of the sender. For example, you can use your company name.
* **Reply to**: The email address to which the recipient can reply. For example, if you want to receive replies to your email address, you can set it here. Whenever the recipient replies to the email, it will be sent to your inbox.
* **To**: The email addresses of the recipients. You can add one or more email addresses.
* **CC**: The email addresses of the recipients who will receive a copy of the email. You can add one or more email addresses.
* **Subject**: The subject of the email.
* **Message**: The content of the email. You can use variables to personalize the email content.


# Set Variable
Source: https://docs.chatling.ai/chatbot/builder/blocks/action/set-variable

Learn about the Set Variable block and how to set it up in the Builder.

The Set Variable block is used to set the value of one or more variables. With it, you can modify variable values dynamically at any point in the flow.

## How to configure

1. Click on the Set Variable block in the canvas to open its settings.
2. Select the variable you want to modify.
3. Select the type of the modification:
   * **Value**: Set the variable to a specific value. You can also insert variables to make the value dynamic.
   * **Add/Subtract/Multiply/Divide**: Perform a mathematical operation on the variable. You can add, subtract, multiply, or divide the variable by a specific value. The value must be a number.
4. Enter the value.

<img alt="Configure Set Variable block" />

## Multiple variables

You can set multiple variables at once by clicking on the **Add variable** button. This will add a new row where you can select another variable and set its value.

<img alt="Add additional variable" />

## Example

Let's say you're building a lead generation chatbot for a real estate brokerage. You want to prompt the AI to ask the customer three questions about their requirements and forward the answers to the team. You can do this by using a counter variable that increments each time the user answers a question.

Below is a sample flow that demonstrates how to use the Set Variable block.

<img alt="Real estate sample chatbot flow using Set Variable block" />

We're using a variable called `counter` to keep track of the number of questions that have been asked. This variable is incremented by 1 each time the user answers a question.

Then, we're using the Condition block to check if the counter is greater or equal to 3. If it is, a message is displayed to inform the user that their inquiry has been forwarded to the team. Else, the AI asks the next question.


# Update Contact Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/action/update-contact

Learn about the Update Contact block and how to set it up in the Builder.

The `Update Contact` block can be used to update an existing contact.

The block consists of the following components:

* **Search**: Specify the field and value to use to look up the contact. You can enter a variable to search dynamically.
* **Contact details**: Define the properties you want to update.


# AI Response Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/ai/ai-response

Learn about the AI Response block and how to set it up in the Builder.

The AI Response block is used for generating responses to user input using AI. It can provide answers based on the information you have added to the [Knowledge Base](/knowledge-base/overview) or from the AI's pretrained data.

The AI uses natural language processing (NLP) to understand the user's input and generate relevant responses.

## What is the "Response Source"?

The Response Source determines where the AI will look for answers to user queries. You can choose from the following options:

* **Knowledge Base**: The AI will search the data you've uploaded to the Knowledge Base for the relevant information and return the corresponding answer.
* **AI Model**: The AI will use its pretrained data to generate a response based on the user's query. This is ideal for a general-purpose AI that can answer a wide range of questions without limiting its responses to the data in the knowledge base.

## Configurations for Knowledge Base Response Source

<img alt="AI block knowledge base settings" />

When you select the "Knowledge Base" as the Response Source, you can configure the following settings:

* **Question**: The user's input or query that the AI will process to generate a response. You can use variables to make the question dynamic. For example, you can capture the user's input using a Text input block and store it in a variable called `user_input`. Then, you can use this variable in the "Question" field to make the AI response dynamic.
* **Store response in variable**: You can store the AI response in a variable to use it in other blocks.
* **Stream**: When enabled, the AI response will be streamed to the user in real-time as it is generated. This provides a more interactive experience for the user.
  * When Stream is enabled, some features that require post-processing, such as "Not Found path" will be disabled.
* **Not Found path**: The path to follow if the AI does not find a relevant answer in the Knowledge Base.
* **Model**: The AI model to use for generating responses.
* **Language**: The language in which the AI will respond to the user. If you set it to "Auto," the AI will detect the language of the user's input and respond in the same language.
  * If you want the AI to respond in a certain dialect or accent, you can specify it in Instructions section of the [AI Configuration](/chatbot/builder/sidebar#ai-configuration).
* **Temperature**: The randomness of the AI's responses. A higher temperature value will result in more diverse and creative responses, while a lower value will produce more accurate responses.

### What does "Use global AI settings" mean?

When you set an option, such as the AI model, language, or temperature to "Use global AI settings", the AI will use the settings defined in the [AI Configuration](/chatbot/builder/sidebar#ai-configuration) menu in the [sidebar](/chatbot/builder/sidebar). This allows you to define global settings that will be applied to all AI blocks in your bot.

## Configurations for AI Model Response Source

When you set the Response Source to "AI Model", you can configure the following settings:

* **Prompt**: The message or query that the AI will use to generate a response. You can use variables to make the prompt dynamic.
* **Store response in variable**: You can store the AI response in a variable to use it in other blocks.
* **Instructions**: Additional instructions for the AI to follow when generating a response. For example, you can specify its personality, tone, or style, or provide specific context for the response.
* **Model**: The AI model to use for generating responses.
* **Max Length**: Maximum number of tokens to generate, shared between the prompt and the response. One token is roughly 4 characters.
* **Temperature**: Randomness of the AI's responses. A higher temperature value will result in more diverse and creative responses, while a lower value will produce more focused and deterministic responses.
* **Top P**: Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered.
* **Frequency Penalty**: How much to penalize new tokens based on their existing frequency in the text so far. Decreases the model's likelihood to repeat the same line verbatim.
* **Presence Penalty**: How much to penalize new tokens based on whether they appear in the text so far. Increases the model's likelihood to talk about new topics.

## How to set up the AI block to respond from the knowledge base?

Here's a high level overview of how the AI generates responses using the knowledge base:

* The user inputs a question or query, which is saved in a variable of your choice.
* The stored input is passed to the AI which uses natural language processing (NLP) to understand the user's query and the context of the conversation.
* The AI searches the knowledge base for relevant information.
* The AI generates the response and displays it to the user.

To set up the AI block, follow these steps:

1. Add a Text input block to the canvas. We'll use this block to capture the user's input and store it in a variable so it can be passed to the AI block.

<img alt="Adding text input block to the builder" />

2. Click on the Text block to open the editor. In the `Store answer in variable` field, enter a variable where the user's input will be stored. In this example, we'll create and use a variable called `user_query`.

<img alt="Storing user input in a variable" />

3. Next, drag and drop the AI Response block onto the canvas.

<img alt="Setting up AI block for knowledge base response" />

4. Connect the Text input block to the AI block by dragging the connector from the Text block to the AI block.

<img alt="Connecting text input to AI block" />

5. Click the AI Response block to open the editor. In the `Question` field, enter the variable where the user's input is stored. In step 2, we used the `user_query` variable, so we'll enter `{user_query}` in the Question field.

<img alt="Setting up AI block for knowledge base response" />

6. Set up the global AI settings by going to the `AI Configuration` in the sidebar. You can define settings such as the AI model, instructions, language, and business name.

7. Lastly, set up the block connections accordingly. For example, a setup like below will allow the user to continually ask questions and receive responses from the AI.

<img alt="Setting up AI block for knowledge base response" />


# Language
Source: https://docs.chatling.ai/chatbot/builder/blocks/condition/language

Learn how to use the Language condition block in Chatling

The Language condition block is used to define flows based on the user's browser language. This can be useful for creating multilingual bots that respond in the user's preferred language.

Let's say you want to create a bot that supports English, Spanish, and French languages. You can use the Language condition block to define different responses or actions based on the user's preferred language setting in their browser.

Below is an example of such a flow. The Else path is a fallback for users whose language is not supported by the bot. In this case, it falls back to the English language.

<img alt="Language conditional flow" />


# Overview
Source: https://docs.chatling.ai/chatbot/builder/blocks/condition/overview

Learn about the condition blocks and how to use them

Condition blocks are used to create conditional logic in your bot. You can use it to check if a certain condition is met and then perform different actions based on the result.

Similar to an "if-else" statement in programming, condition blocks evaluate a condition and executes different paths based on whether the condition is true or false.

<img alt="Condition block" />

## Types of condition blocks

There are two types of condition blocks available in Chatling:

* [**Variable**](./variable): Compares a variable with a value or another variable.
* **Language**: Checks if the user's language matches a specific language. Useful for creating multilingual bots.

## How do condition blocks work?

Condition blocks consist of two main parts:

* **Conditions**: The conditions that the block will evaluate. You can use variables, languages, comparison operators, and logical operators to create complex conditions.
* **Paths**: The paths that the block will follow based on the result of the conditions. Every condition you add will have a corresponding path that the block will follow if the condition is true.

<img alt="Condition block components" />

Here's an example of how a condition block works:

1. The block evaluates conditions in the order they are added.
2. If a condition is true, the block follows the path associated with that condition.
3. If none of the conditions are true, the block follows the "Else" path.

## The Else condition

The `Else` condition is executed if none of the other conditions are met. You can use it to define a fallback path that the block will follow if none of the other conditions are true.

## Comparison operators

Conditions support a variety of comparison operators that you can use to compare values. Here are some of the operators you can use:

* **Equals**: Checks if the variable is equal to the value.
* **Not equals**: Checks if the variable is not equal to the value.
* **Contains**: Checks if the variable contains the value.
* **Not contains**: Checks if the variable does not contain the value.
* **Greater than or equals**: Checks if the variable is greater than or equal to the value.
* **Less than**: Checks if the variable is less than the value.
* **Less than or equals**: Checks if the variable is less than or equal to the value.
* **Starts with**: Checks if the variable starts with the value.
* **Ends with**: Checks if the variable ends with the value.
* **Is empty**: Checks if the variable is empty.
* **Is not empty**: Checks if the variable is not empty.

## Group and child conditions

Conditions are grouped together to create complex logic using logical operators like "AND" and "OR". Every group contains one or more conditions that are evaluated together.

<img alt="Group and child conditions" />

Conditions within a group are evaluated together to determine if the group is true or false. You can use logical operators such as "AND" and "OR" to combine conditions within a group.

For example, you can create a group with two conditions and set it to "AND" to require both conditions to be true for the group to be true. On the other hand, you can set it to "OR" to require only one of the conditions to be true for the group to be true.

By default, condition blocks have one group with one condition. To add additional groups, click the `Add group condition` button.

## Logical operators

Logical operators are used to combine conditions within a group. You can choose from the following logical operators:

* **AND**: Requires all conditions in the group to be true for the group to be true.
* **OR**: Requires at least one condition in the group to be true for the group to be true.

<Accordion title="Example">
  - Group 1:
    * Condition 1: Variable A equals 5
    * Condition 2: Variable B equals 10
    * Logical operator: AND

  - Group 2:
    * Condition 1: Variable C contains "hello"
    * Condition 2: Variable D contains "world"
    * Logical operator: OR

  In this example, Group 1 will be true only if Variable A equals 5 and Variable B equals 10. Group 2 will be true if either Variable C contains "hello" or Variable D contains "world".
</Accordion>


# Variable
Source: https://docs.chatling.ai/chatbot/builder/blocks/condition/variable

Learn how to use the Variable condition block in Chatling

The Variable condition block is used to compare a variable with a value or another variable. You can use it to create conditional logic in your bot based on user inputs, stored values, or system variables.

## Components of a variable condition

<img alt="Components of a variable condition" />

* **Label**: A descriptive label for the condition, which will be displayed in the block on the canvas. This is optional and can be skipped.
* **Variable**: The variable or value that the block will evaluate. The variable can be a user input, a stored value, or a system variable.
* **Comparison operator**: The operator that the block will use to compare the variable with the value you specify. You can choose from a list of comparison operators, such as "equals," "greater than," "contains," etc.
* **Value**: The value that the block will compare with the variable. This can be a static value or a variable for dynamic comparisons.

## Examples

### 1. Real estate bot

In a real estate bot, you can use conditions to check if the user is looking to buy or rent a property and display properties accordingly.

You can create two conditions:

* Condition 1: User input contains "buy"
* Condition 2: User input contains "rent"

Here's how to set it up in the editor:

<img alt="Real estate conditions setup example" />

Once you have set up the conditions, you can define the paths for each condition. Here's an example:

<img alt="Real estate conditions example" />

Based on the above, here's how the bot will respond:

* If the user input contains "buy," the bot will respond with `Great! Let me show you our available properties for sale`.
* If the user input contains "rent," the bot will respond with `Sure! We've got amazing properties for rent. Here's the list`.
* Else if none of the conditions are met, the bot will respond with `I'm sorry, I didn't understand. Please respond by typing "Buy" or "Rent"`.

### 2. Filtering job application candidates

Let's say a candidate is applying for a job through the bot and you want to qualify them based on the following criteria:

* Location: New York
* Willing to relocate: Yes
* Years of experience: 3 or more

You can set up the following conditions:

<img alt="Job application conditions setup" />

Once you have set up the conditions, you can define the paths for each condition. Here's an example:

<img alt="Job application condition block" />

Based on the above, here's how the bot will respond:

* If the candidate is from New York, willing to relocate, and has 3 or more years of experience, the bot will respond with `Congratulations! You've been shortlisted for the next round of interviews`.
* Otherwise, the bot will respond with `Sorry, you are not qualified for this job opening. We'll keep your application on file for future opportunities`.


# Create Company
Source: https://docs.chatling.ai/chatbot/builder/blocks/hubspot/create-company

Create companies in HubSpot from your chatbot.

Easily create new companies in HubSpot through your chatbot to streamline lead capture and keep your CRM up to date automatically.

## Configuration

1. Click the `Connect account` button under the Account field to connect your HubSpot account to Chatling or select an existing connection.
2. Under the `Company details` section, add the properties you want to set for the company. You can enter variables in certain fields for dynamic values.
3. To store the company's ID when the company is created, select a variable for the `Company ID` field under the `Save response` section.


# Create Contact
Source: https://docs.chatling.ai/chatbot/builder/blocks/hubspot/create-contact

Create contacts in HubSpot from your chatbot.

Create contacts in HubSpot from your chatbot. This is useful for capturing leads and enriching your CRM data.

## Configuration

1. Click the `Connect account` button under the Account field to connect your HubSpot account to Chatling or select an existing connection.
2. Under the `Contact details` section, add the properties you want to set for the contact.
3. To store the contact's ID when the contact is created, select a variable for the `Contact ID` field under the `Save response` section.


# Create Ticket
Source: https://docs.chatling.ai/chatbot/builder/blocks/hubspot/create-ticket

Create tickets in HubSpot from your chatbot.

Create tickets in HubSpot from your chatbot. This is useful for forwarding user queries to your support team or creating tickets for issues that require further investigation.

## Configuration

1. Click the `Connect account` button under the Account field to connect your HubSpot account to Chatling or select an existing connection.
2. Select the `Pipeline` where the ticket should be created.
3. Enter the ticket's details, such as the subject, status, and description. You can enter variables in all fields to make the ticket dynamic.
4. To store the ticket's ID when the ticket is created, select a variable for the `Ticket ID` field under the `Save response` section.


# HubSpot Integration
Source: https://docs.chatling.ai/chatbot/builder/blocks/hubspot/overview

Integrate with HubSpot and manage your contacts, companies, and tickets directly from your chatbot.

The HubSpot integration enables you to connect your Chatling chatbot to your HubSpot account, allowing you to automate and manage key CRM workflows directly within conversations.

With this integration, your chatbot can:

* Create support tickets
* Create, update, and retrieve contacts
* Create and update companies

This allows your team to capture leads, resolve issues, and enrich CRM data without leaving the chat interface.

<CardGroup>
  <Card title="Create Ticket" icon="ticket" href="/chatbot/builder/blocks/hubspot/create-ticket" />

  <Card title="Create Contact" icon="user" href="/chatbot/builder/blocks/hubspot/create-contact" />

  <Card title="Update Contact" icon="user" href="/chatbot/builder/blocks/hubspot/update-contact" />

  <Card title="Retrieve Contact" icon="user" href="/chatbot/builder/blocks/hubspot/retrieve-contact" />

  <Card title="Create Company" icon="building" href="/chatbot/builder/blocks/hubspot/create-company" />

  <Card title="Update Company" icon="building" href="/chatbot/builder/blocks/hubspot/update-company" />
</CardGroup>


# Retrieve Contact
Source: https://docs.chatling.ai/chatbot/builder/blocks/hubspot/retrieve-contact

Retrieve contacts from HubSpot to use in your chatbot.

With this block, you can retrieve contacts from HubSpot and use them in your chatbot.

## Configuration

1. Click the `Connect account` button under the Account field to connect your HubSpot account to Chatling or select an existing connection.
2. The `Search method` determines how the contact is found in HubSpot. You can either search by the contact's ID or email address. You can enter variables to make the search dynamic.
3. Add the contact's properties you want to retrieve and select a variable for each property.


# Update Company
Source: https://docs.chatling.ai/chatbot/builder/blocks/hubspot/update-company

Update companies in HubSpot from your chatbot.

Easily update companies in HubSpot through your chatbot to keep your CRM up to date automatically.

## Configuration

1. Click the `Connect account` button under the Account field to connect your HubSpot account to Chatling or select an existing connection.
2. The `Search method` determines how the contact is found in HubSpot. Currently, only searching by company ID is supported.
3. Add the properties you want to update for the company. You can enter variables in certain fields for dynamic values.


# Update Contact
Source: https://docs.chatling.ai/chatbot/builder/blocks/hubspot/update-contact

Update contacts in HubSpot from your chatbot.

With this block, you can update contacts in HubSpot from your chatbot, for example to enrich your CRM data.

## Configuration

1. Click the `Connect account` button under the Account field to connect your HubSpot account to Chatling or select an existing connection.
2. The `Search method` determines how the contact is found in HubSpot. You can either search by the contact's ID or email address.
3. Add the properties you want to update for the contact. You can enter variables in certain fields to make the contact dynamic.


# Buttons Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/buttons

Learn about the Buttons input block and how to set it up in the Builder.

The Buttons block is used to display a set of buttons that users can click to trigger actions or provide responses. You can use this block to present multiple options to users and guide them through the conversation flow.

<img alt="Buttons block preview" />

Every button in the block has a connector that allows you to link it to other blocks.

# Configuration

Buttons have the following configuration options:

* **Label**: The text that appears on the button.
* **Store selected button in variable**: The variable where the selected button's value will be stored. For example, if the user selects the "Yes" button, you can store the value "Yes" in a variable for later use.

<img alt="Input buttons block editor" />

## Connecting buttons

Buttons must be connected to other blocks so that the chatbot can respond to the user's selection.

To connect a button, click the connector next to it and drag it to the group you want to connect it to.

In the example below, when the user clicks the "Software Development" button, the chatbot will display the "Sure thing! Our team can help..." message and continues the flow from there.

<img alt="Connect buttons" />


# Date/Time Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/date

Learn about the Date/Time input block and how to set it up in the Builder.

The Date/Time block is used to collect the date and time from users. You can use this block to ask users for dates, times, or date-time combinations.

## Configuration

The Date/Time block has the following configuration options:

* **Store answer in variable**: The variable where the user's input will be stored.
* **Input required**: Whether the user's input is mandatory. If disabled, a Skip button will appear, allowing users to skip the input.
* **Format**: The type of input the block will accept. You can choose from the following:
  * Date
  * Time
  * Date & Time
* **Min**: The minimum value the user can input.
* **Max**: The maximum value the user can input.

<img alt="Input date/time block editor" />


# Email Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/email

Learn about the Email input block and how to set it up in the Builder.

The Email block is used to capture a valid email address from the user. You can use this block to collect email addresses of users for various purposes, such as saving them as leads, sending newsletters, or providing account-related information.

## Configuration

<img alt="Input email block editor" />

The Email block has the following configuration options:

* **Store email in variable**: The variable where the user's email address will be stored.
* **Input required**: Determine whether the user must provide an email address to proceed. If this option is disabled, a Skip button will appear, allowing users to skip the input.
* **Disallowed domains**: Specify a list of email domains that are not allowed. Users will not be able to enter email addresses associated with these domains.
* **[Quick replies](/chatbot/builder/block-options/quick-replies)**


# Form Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/form

Learn about the Form input block and how to set it up in the Builder.

The Form block is used to collect multiple pieces of information from users in a structured way. You can use this block to create forms for lead generation, user feedback, surveys, and more.

You can add multiple fields to the form and configure each field to collect different types of information, such as text, email, phone number, and more.

<img alt="Form block preview" />

## Configuration

The Form block has the following configuration options:

* **Fields**: Add and configure the fields you want to include in the form.
  * **Label**: The label of the field to indicate what information is being collected.
  * **Type**: Type of the field, such as Text, Email, Number, etc. This prevents users from entering invalid data.
  * **Store user input in variable**: The variable where the user's response to the field will be stored.

<img alt="Form block editor" />


# Number Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/number

Learn about the Number input block and how to set it up in the Builder.

The Number block is used to collect numerical input from users. You can use this block to ask users for numbers, such as quantities, prices, or percentages.

## Configuration

The Number block has the following configuration options:

* **Store answer in variable**: The variable where the user's input will be stored.
* **Input required**: Whether the user's input is mandatory. If disabled, a Skip button will appear, allowing users to skip the input.
* **Date type**: The type of number the block will accept. You can choose from the following options:
  * \*\*Number (Integer/Decimal): Accepts any number, including whole numbers and decimals.
  * **Integer**: Accepts only whole numbers.
* **Min**: The minimum value the user can input.
* **Max**: The maximum value the user can input.
* **[Quick replies](/chatbot/builder/block-options/quick-replies)**

<img alt="Input number block editor" />


# Phone Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/phone

Learn about the Phone input block and how to set it up in the Builder.

The Phone block is used to collect phone numbers from users.

At the moment, the Phone block is not fully developed and doesn't have the ability to validate phone numbers or provide option for users to select their country code. We are working on improving this block and will update this documentation once the changes are live.


# Text Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/text

Learn about the Text input block and how to set it up in the Builder.

The Text block is used to capture user input in the form of text. You can use this block to prompt users for answers and collect the necessary information.

## Configuration

<img alt="Input text block editor" />

You can configure the following settings for the Text block:

* **Store answer in variable**: Choose a variable to store the user's response. You can use the stored data in other blocks to personalize the conversation.
* **Input required**: Determine whether the user must provide an answer to proceed. If this option is disabled, a Skip button will appear, allowing users to skip the input.
* **[Voice Input](/chatbot/builder/block-options/voice-input)**: Toggle on the Voice Input option to allow users to send messages using voice.
* **Min. characters**: The minimum number of characters the user must enter.
* **Max. characters**: The maximum number of characters the user can enter.
* **[Quick replies](/chatbot/builder/block-options/quick-replies)**


# URL Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/inputs/url

Learn about the URL input block and how to set it up in the Builder.

The URL block is used to collect URLs from users. It validates the user's input to ensure that it is a valid URL.

You can use this block to ask users for website URLs, social media profiles, or any other web addresses.

## Configuration

The URL block has the following configuration options:

* **Store answer in variable**: The variable where the user's input will be stored.
* **Input required**: Whether the user's input is mandatory. If disabled, a Skip button will appear, allowing users to skip the input.
* **[Quick replies](/chatbot/builder/block-options/quick-replies)**

<img alt="Input URL block editor" />


# Blocks
Source: https://docs.chatling.ai/chatbot/builder/blocks/overview

Blocks are the core components of every chatbot. Learn how to use them to build your chatbot's conversational flow.

With Blocks, you can build the conversational flow of your chatbot. They define the sequence in which the chatbot interacts with users and responds to their queries.

You can add blocks to the canvas and connect them to create a flow. Each block performs a specific action, such as sending a message, capturing user input, or integrating with external services.

<img alt="Blocks menu" />

## Types of blocks

Here are the different categories of blocks that are available:

* **Send message**: Display messages to the user.
* **Capture response**: Capture answers from the user, such as text, email, form submission, and more.
* **AI**: Use AI to generate responses to user's questions.
* **Condition**: Add conditions and logic to your flow.
* **Action**: Perform actions such as sending emails, setting variables, and more.
* **Trigger**: Trigger events automatically based on user's actions.
* **Zendesk**: Connect your chatbot to Zendesk to create tickets.
* **Cal.com**: Integration for Cal.com to book events and appointments.

## Groups

Blocks can be grouped together for better organization and for creating connections between them. A group is created when you drop a block onto an empty area of the canvas. You can then drag other blocks into the group to organize them.

<img alt="Group blocks" />


# Audio Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/send/audio

Learn about the Audio block and how to set it up in the builder

The Audio block allows you to play an audio file to the user in the conversation. It can be used for various purposes, such as playing a welcome message, providing information, or playing music.

## Adding an audio file

To add an audio file, you can either upload an audio file directly or provide a link to a file hosted online. The supported audio formats are `MP3`, `WAV`, and `OGG`.

<img alt="Audio block editor" />

You can enable the `Autoplay` option to automatically play the audio file when the block is displayed to the user.


# Carousel Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/send/carousel

Learn about the Carousel block and how to set it up in the builder

The Carousel block allows you to display a carousel of cards to the user. Each card can contain an image, title, description, and buttons.

Carousels are a great way to showcase multiple products, services, or information in a visually appealing format.

<img />

## Adding a carousel

To add a carousel, you can create multiple cards within the block editor. For each card, you can set an image, title, description, and buttons.

You can add as many cards as you like to the carousel. Users can swipe through the cards to view the content.

<img alt="Carousel block editor" />


# Image Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/send/image

Learn about the Image block and how to set it up in the builder

You can use the Image block to display an image to the user. It can be used for various purposes, such as showing product images, providing visual instructions, or adding visual elements to your chatbot conversation.

## Adding an image

You can upload an image or insert its URL. The support image formats are `JPG/JPEG`, `PNG`, `WEBP`, and `GIF`.

<img alt="Image block editor" />


# Text Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/send/text

Learn about the Text block and how to set it up in the builder

The Text block is used to display a text message to the user. You can use it to provide information, ask questions, or guide the user through the conversation.

## Adding text

Once you add a Text block to the canvas, click on it to open the block editor. You can then enter your message in the text editor and apply formatting using the toolbar.

<img alt="Output text block editor" />

## Inserting variables

You can insert variables into your text message to make it more dynamic and personalized.

To insert a variable, type `{` and a list of available variables will appear. Select the variable you want to insert and it will be added to the text message.

<img alt="Insert variable" />

For example, if you have captured the user's name earlier in the conversation and stored it in a variable called `contact_name`, you can insert it into the text message by typing `{contact_name}`. When the message is sent to the user, the variable will be replaced with the user's name.

<img alt="output user's name within the text" />


# URL Button Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/send/url-button

Learn about the URL Button block and how to set it up in the builder

The URL Button block displays buttons that redirect users to other pages.

<img />

## Adding URL buttons

1. Drag and drop the URL Button block on the canvas.

<img />

2. Click on the block to edit it.
3. Click `Add button` button to add a new button.

<img />

4. Enter the button label and URL. The label is the text that will be displayed on the button.

<img />

5. To add more buttons, click the `+` icon.

<img />


# Video Block
Source: https://docs.chatling.ai/chatbot/builder/blocks/send/video

Learn about the Video block and how to set it up in the builder

The Video block allows you to display a video to the user in the conversation. You can add a video from YouTube, Vimeo, or any other video hosting platform, or you can paste the direct link to a video file.

For video platforms that support embedding, Chatling will automatically embed the video in the conversation. Here's an example:

<img />

## Adding a video

Adding a video is simple. Just paste the URL to the video in the block editor and the chatbot will automatically embed it in the conversation.

<img />


# Triggers
Source: https://docs.chatling.ai/chatbot/builder/blocks/trigger/overview

Learn about triggers in Chatling and how to use them effectively in your chatbot flows.

Triggers are events that automatically start a specific flow in your chatbot based on user behavior. They enable you to create more dynamic and responsive chatbot experiences.

## Types of Triggers

The following triggers are currently available:

1. Returning Visitor: This trigger is activated when a visitor returns to your website after a period of time.
2. Specific Webpage Opened: This trigger is activated when a visitor opens a specific page on your website.
3. Intent: Triggered when there's a matching intent in the user's message.

## How Triggers Work

Triggers are automatically invoked when their conditions are met. When a trigger is activated, the chatbot will follow the conversation flow connected to that trigger in the builder.
For example, if you have a "Returning User" trigger set up, and a user comes back to your website after being away for a certain period, the chatbot will automatically start the conversation flow linked to this trigger.

## How to Use Triggers

To use triggers in your chatbot:

1. Open your chatbot builder.
2. From the Blocks page in the sidebar, look for the "Triggers" section.
3. Drag and drop the desired trigger onto your canvas.
4. Connect the trigger to the subsequent blocks in your conversation flow.
5. Configure the trigger settings if necessary (e.g. specifying the trigger frequency).


# Create Ticket
Source: https://docs.chatling.ai/chatbot/builder/blocks/zendesk/create-ticket

Learn how to create tickets in Zendesk from your chatbot.

Create tickets in Zendesk directly from your chatbot using this block. This is useful for forwarding user queries to your support team or creating tickets for issues that require further investigation.

## Configuration

* **Account**: The Zendesk account to create the ticket in.
* **Subject**: The subject of the ticket.
* **Priority**: The priority of the ticket, such as Low, Normal, High, or Urgent.
* **Requester name**: The name of the user who should be associated with the ticket. Normally, this should be the customer's name.
* **Requester email**: The email address of the user who should be associated with the ticket. Normally, this should be the customer's email address.
* **Description**: The description of the ticket.


# Canvas
Source: https://docs.chatling.ai/chatbot/builder/canvas

Learn about the canvas and how to navigate and interact with it.

![Builder interface](https://chatling-assets.b-cdn.net/canvas.png)

The canvas is where you design the conversational flow of your chatbot. You can add [blocks](/chatbot/builder/blocks/overview), connect them, and define the logic for how the chatbot responds to user inputs.

To move around the canvas, click and drag an empty area. To zoom in or out, use your mouse scroll wheel or the zoom controls in top toolbar.

All chatbots contain a default `Start` block, which is the entry point of the conversation. From there, you can add blocks to create the flow.


# Chatbot Builder
Source: https://docs.chatling.ai/chatbot/builder/introduction

Learn about the Builder and how to create conversational flows for your chatbot.

Chatling's Builder is a visual interface that allows you to create and manage conversational flows for your chatbot. It's where you define how the chatbot interacts with users and responds to their queries.

## Builder Interface

![Builder interface](https://chatling-assets.b-cdn.net/chatling-builder-interface.jpg)

The Builder consists of the following components:

* **[Canvas](/chatbot/builder/canvas)**: The main area where you add and connect blocks to build the conversational flow.
* **[Sidebar](/chatbot/builder/sidebar)**: Contains menus for adding blocks, managing variables, and configuring the AI and general settings.
* **Toolbar**: Appears at the top and contains controls for zooming in/out, saving, preview, and publishing the chatbot.

<iframe title="YouTube video player" />

In the next sections, we'll explore each component of the Builder in detail and learn how to create conversational flows for your chatbot.


# Publish your chatbot
Source: https://docs.chatling.ai/chatbot/builder/publish-your-chatbot

Learn how to publish your chatbot and make it live.

Once you've built your chatbot and tested it thoroughly, you can publish it to make it live.

By publishing, any changes you've made to the chatbot will become available to users where the chatbot is embedded.

To publish your chatbot, click the `Publish` button in the top right corner of the Builder.

![Publish your chatbot](https://chatling-assets.b-cdn.net/publish-your-chatbot.jpeg)


# Save your work
Source: https://docs.chatling.ai/chatbot/builder/save-your-work

Learn how to save your changes in the Builder.

Any changes you make to your chatbot's flow in the [Builder](/chatbot/builder/introduction) is saved automatically. You can also save it manually by clicking the `Save` button in the top right side of the screen.

<img alt="Save your work in the Builder" />

When you save your changes, it will be saved as a draft and will not be published. This allows you to work on the chatbot and test it without affecting the live version.


# Sidebar
Source: https://docs.chatling.ai/chatbot/builder/sidebar

Learn about the Sidebar and its functionalities in the Builder.

<img />

The sidebar contains four menus:

* Blocks
* Variables
* AI Configuration
* Settings

## Sidebar Menus

### Blocks

The Blocks menu contains all the blocks you can add to your flow. [Blocks](/chatbot/builder/blocks/overview) build up the conversational flow of your chatbot.

You can drag and drop blocks onto the canvas to add them to your flow.

![Adding blocks](https://chatling-assets.b-cdn.net/Drag%20blocks.gif)

Here are the different categories of blocks that are available:

* **Send message**: Display a message to the user.
* **Capture response**: Capture answers from the user, such as text, email, form submission, and more.
* **AI**: Use AI to generate responses to user's questions.
* **Logic**: Add conditions and logic to your flow.
* **Integration**: Connect your chatbot to external services.

### Variables

Variables are placeholders that store information during the conversation. You can use variables to store user inputs, API responses, and more. These variables can be used to personalize the conversation and make it more dynamic.

<img />

There are two types of variables:

* **System variables**: These are predefined variables that store system information or can be used to perform a specific action. For example, the `contact_email` variable can be used to store the user's email address and save them as a lead.

  If you click on a system variable, you can view its purpose.

  There are also additional system variables that aren't imported by default. To view and import them, click the `Import system variables` button.

* **Custom variables**: These are variables you create to store information specific to your chatbot. For example, you can create a custom variable to store the user's question and use it in the `AI Response` block to generate a response from the AI.

### AI Configuration

The AI Configuration menu allows you to configure the default AI settings for your chatbot. These settings are used when the chatbot generates AI responses using the Knowledge Base.

<img />

You can configure the following settings:

* **Instructions**: Provide instructions to the AI to tailor its responses. For example, you can instruct the AI to provide more detailed responses or to use a specific tone. You can click the `View examples` button to see examples of instructions you can provide.
* **Settings**:
  * **Business, product, or brand name**: This will be used by the AI to generate more relevant responses and avoids answering off-topics questions that aren't related to your business, product, or brand, such as questions related to your competitors, weather, etc.
  * **AI Model**: The AI model to use for generating responses. Every model uses a different amount of credits per response. We recommend testing with different models to see which one works best for your chatbot.
  * **Language**: The language in which the AI should generate responses. If you set it to Auto, the AI will detect the language of the user's question and generate a response in the same language.
  * **Temperature**: Controls the randomness of the responses. A higher temperature will generate more creative responses, while a lower temperature will generate more accurate responses.

### Settings

The Settings menu allows you to configure the chatbot's general settings. Here's what you can configure:

* **Message Delay**: The time delay in seconds between chatbot's messages.


# Test your chatbot
Source: https://docs.chatling.ai/chatbot/builder/test-your-chatbot

Learn how to test your chatbot to see how it works.

While you're building the chatbot, you can test it to see how it works. This allows you to identify any issues and make improvements before publishing it.

Click the `Preview bot` button in the top right corner of the Builder to launch the chatbot for testing.

![Testing your chatbot](https://chatling-assets.b-cdn.net/testing-your-chatbot.jpg)


# Available system variables
Source: https://docs.chatling.ai/chatbot/builder/variables/available-system-variables

List of all the system variables available and what they do.

Here are all the system variables that are available. If a variable is not present in your chatbot, you must [import it](/chatbot/builder/variables/import-system-variables).

`chat_id`

The unique identifier of the chat.

`user_id`

The unique identifier of the user.

`conversation_content`

The chat transcript (recent 25 messages).

`current_date`

The current date in UTC.

`current_time`

The current time in UTC.

`locale`

The user's browser locale, such as en-US, en-CA, fr-FR, pt-BR, etc.

`page_title`

The title of the page the user is currently on.

`page_url`

The URL of the page the user is currently on.

`timestamp`

The UNIX timestamp, which is the number of seconds since January 1, 1970 UTC.

`current_time`

The current time in UTC.

`current_date`

The current date in UTC.


# How to create variables
Source: https://docs.chatling.ai/chatbot/builder/variables/how-to-create-variables

Learn how to create variables in the Builder

Variables can be created from the [sidebar](/chatbot/builder/sidebar) in the Builder. Here's how:

1. Click on the `Variables` menu in the sidebar.
2. Select `+ New`.

<img alt="Create variable from sidebar" />

3. Enter a name for the variable and click `Create`. The name must be alphanumeric and can include underscores, such as `first_name`, `firstName`, or `First Name`.

<img alt="Define name for new variable" />

Note that variable names are case-sensitive. For example, `first name` and `First Name` are considered different variables.


# How to use variables
Source: https://docs.chatling.ai/chatbot/builder/variables/how-to-use-variables

A guide on how to use Variables in your chatbot

Variables can be used for capturing information, displaying dynamic content, and processing data in your chatbot.

## How to store data in variables

You can store data in variables using the `Store answer in variable` or a similar option that's available for certain blocks in the builder. This option appears in the [block editor](/chatbot/builder/block-editor).

Let's take the [Text input block](/chatbot/builder/blocks/inputs/text) as an example. This block allows users to enter text. To store the user's response in a variable, click the dropdown below the `Store answer in variable` option and select a variable.

<img alt="Store answer in variable option in Text Input block" />

## How to display variables in messages

You can display variables in messages using the `{variableName}` syntax. The variable name should be enclosed in curly braces.

As an example, let's you have a variable called `first_name` and you want to greet the user by their name. Here's how to do it:

1. Add a [Text output block](/chatbot/builder/blocks/send/text) to your chatbot.
2. Click the block to open the editor.
3. Type `Hello, {first_name}!` in the message field.

<img alt="Display variable in message in Text Output block" />

4. When the chatbot displays this block, it will replace `{first_name}` with the value stored by the variable.

<img alt="Display variable in message" />

Note that the values stored are on a per-conversation basis. This means that the value of a variable is unique to each conversation and is not shared across different conversations.


# Import system variables
Source: https://docs.chatling.ai/chatbot/builder/variables/import-system-variables

Learn how to import system variables that aren't available by default in your chatbot.

Not all system variables are available by default when you create a chatbot. If you require additional system variables that aren't available, you can import them from the `Variables` menu in the builder's [sidebar](/chatbot/builder/sidebar).

## How to import additional system variables

1. Go to the `Builder` in your chatbot.
2. Click the `Variables` menu in the sidebar.

<img alt="Open variables menu" />

3. Click `Import system variables`.

<img alt="Import system variables button" />

4. A list is displayed with all the additional system variables that you can import. Select the ones you want to import.

<img alt="Import system variables" />

5. Click the `Import` button.

<img alt="Import system variables" />

6. The selected system variables are now available to use in your chatbot.


# Types of variables
Source: https://docs.chatling.ai/chatbot/builder/variables/variable-types

There are two types of variables: System Variable and Custom Variable. Learn how to use them in your chatbot.

Variables in the Builder are of two types:

* System Variable
* Custom Variable

## System Variable

<img alt="System variables" />

System variables are predefined variables that contain system information or which can be used to perform specific actions. These variables are automatically created by the Builder.

To learn what a specific system variable does, you can open it from the Variables menu in the [sidebar](/chatbot/builder/sidebar) and read its description.

There are also additional system variables that aren't imported by default. To view and import them, go to the Variables menu from the [Sidebar](/chatbot/builder/sidebar) and click the `Import system variables` button.

<img alt="Import system variables" />

## Custom Variable

These are variables that you create to store information specific to your chatbot.

For example, you can create a custom variable to store the user's query and pass it to the AI for generating a response from the knowledge base.


# What are variables?
Source: https://docs.chatling.ai/chatbot/builder/variables/what-are-variables

Learn about Variables, the different types, and how to use them

<img alt="Variables sidebar menu" />

Variables are placeholders that store information during the conversation. You can use variables to store user inputs, API responses, and more. These variables can be used to personalize the conversation and make it more dynamic.

For example, you can store the user's name in a variable and use it to greet the user. This way, you can make the conversation more engaging and interactive.

In the next section, you will learn about the different types of variables and how to use them in your chatbot.


# Save contacts from chatbot conversations
Source: https://docs.chatling.ai/chatbot/contacts/create



You can collect user information at any point in your chatbot flow and save it as a contact using the [Create Contact](/chatbot/builder/blocks/action/create-contact) block. The contact is automatically associated with the user and retained across future chat sessions.

The example below shows a flow that collects the user's name, email, and phone number using a form. Once submitted, it is used to create a new contact.

<img />

All contacts created by the chatbot are displayed in the `Contacts` page in your dashboard.


# Identify users across multiple chats
Source: https://docs.chatling.ai/chatbot/contacts/identify-users



When you save a contact, it's associated with the user and persists across multiple chat sessions. This information can be used to personalize the conversation, skip repetitive questions, and tailor the flow accordingly.

## How it works

The [Get Contact](/chatbot/builder/blocks/action/get-contact) block can be used to fetch the contact information associated with the current user.

The example below shows a flow that identifies the user and takes different actions based on whether their contact details exist.

<img />

Here's how the above flow works:

1. When the chat starts, the `Get Contact` block is executed to check if a contact exists for the current user.
   <Note>We're using the `user_id` variable to search for the associated contact. This is a system variable that contains the user's unique ID. If this variable doesn't exist in your builder, you can [import it from the Variables menu](/chatbot/builder/variables/import-system-variables).</Note>
2. If a contact is found, the information is stored in variables. For example, we're storing the contact's first name and email in the `first_name` and `email` variables.
3. Next, the [Variable condition block](/chatbot/builder/blocks/condition/variable) is used to check if the `email` and `first_name` variables are not empty.
   * If they're not empty, it means the user is a returning user. In this case, we skip the form and greet the user by name.
   * If they're empty, it means the user is new. In this case, we show the form to collect the user's name and email.


# Overview
Source: https://docs.chatling.ai/chatbot/contacts/overview

Learn how to leverage the Contacts feature to capture leads and manage your customer data.

Chatling makes it easy to capture and manage leads directly through chatbot conversations. All saved contacts are displayed in the `Contacts` page in your dashboard.

With the Contacts feature, you can automatically collect and store user information during chat interactions—turning conversations into valuable customer records.

## What you can do

* Automatically create contact records using chatbot flows
* Capture key details like name, email, phone number, company, and more
* Customize how and when contact info is collected using the [Create Contact](/chatbot/builder/blocks/action/create-contact) block
* View, manage, and export saved contacts from the Contacts page
* Sync contact data with your CRM or other tools via exports, Zapier, or our API


# Getting started with AI Chatbots
Source: https://docs.chatling.ai/chatbot/getting-started

Learn how to create your first AI chatbot in Chatling

What we'll be covering:

1. [Create a chatbot](#1-create-a-chatbot)
2. [Building your chatbot](#2-building-your-chatbot)
3. [Populating the knowledge base](#3-populate-the-ai-knowledge-base)
4. [Customize and deploy your chatbot](#4-customize-and-deploy-your-chatbot)

## 1. Create a chatbot

After you sign up and verify your email, the first step is to create your chatbot.

1. From the dashboard, click on the `Create chatbot` button.

<img />

2. You can choose to create a chatbot from scratch or use a template. Templates help you get started quickly with pre-built flows.

<img />

3. Give your chatbot a name and click `Create chatbot`.

<img />

Congrats! You've created your first chatbot. Now you can start building it based on your requirements.

## 2. Building your chatbot

For your chatbot to be functional, you need to build its conversational flow. This can be done using the Builder.

From your chatbot's dashboard, click on the `Builder` menu to open it.

![Open the builder](https://chatling-assets.b-cdn.net/builder-menu.jpg)

The [Builder](/chatbot/builder/introduction) is where you can create and manage your chatbot's flow. It's a visual interface that allows you to add and connect blocks to create a conversational flow.

All chatbots contain a default `Start` block, which is the entry point of the conversation.

![Builder canvas](https://chatling-assets.b-cdn.net/canvas.png)

### Sidebar

On the left sidebar, you'll find the following menus:

* **[Blocks](/chatbot/builder/blocks/overview)**: Contains all the blocks you can add to your flow. Blocks build up the conversational flow of your chatbot.
  You can drag and drop blocks from this menu to the canvas to add them to your flow.
  ![Adding blocks](https://chatling-assets.b-cdn.net/Drag%20blocks.gif)
* **Variables**: These are like containers that store information during the conversation. You can use variables to personalize the conversation and make it more dynamic.

<img />

* **AI Configuration**: Configure the default AI settings for your chatbot. These settings are used when the chatbot generates AI responses using the Knowledge Base.
* **Settings**: Configure the general settings for your chatbot.

### Connecting blocks

Once you add blocks to the [canvas](/chatbot/builder/canvas), you must connect them to create a flow that guides users through the conversation. Failure to do so will result in the chat ending prematurely.

![Connect blocks](https://chatling-assets.b-cdn.net/connect-blocks-1.gif)

### Configuring blocks

Each block has its own configuration settings that you can customize. To configure a block, click it and its settings will appear on the right side of the screen.

![Configure block](https://chatling-assets.b-cdn.net/block-configuration.jpg)

### Testing your chatbot

While you're building the chatbot, you can test it to see how it works. This allows you to identify any issues and make improvements before publishing it.

Click the `Preview bot` button in the top right corner of the screen to launch the chatbot for testing.

![Testing your chatbot](https://chatling-assets.b-cdn.net/testing-your-chatbot.jpg)

Your work is saved automatically as you build your chatbot. You can also save it manually by clicking the `Save` button in the top right side of the screen.

### Saving your work

Your work is saved automatically as you build your chatbot. You can also save it manually by clicking the `Save` button in the top right side of the screen.

Any changes you make to the chatbot are saved as drafts until you publish them. This allows you to work on the chatbot and test it without affecting the live version.

### Publish your chatbot

Once you've built and tested your chatbot, you can publish it to make it live. Click the `Publish` button in the top right corner of the screen to publish your chatbot.

<img alt="Publish your chatbot" />

## 3. Populate the AI knowledge base

The Knowledge Base is where you upload information that the AI uses to generate responses to user queries.  It uses this information to provide accurate and relevant responses to users.

<img alt="Knowledge base" />

You can add websites, documents, texts, FAQs, and many more data sources to the knowledge base. When a user asks a question, the AI searches the knowledge base for relevant information and generates a response based on the data it finds.

Therefore, if your chatbot contains an AI Response block and it's "Response Source" is set to "Knowledge Base", you need to populate the Knowledge Base with information that the AI can use to generate responses.

## 4. Customize and deploy your chatbot

Once you've built your chatbot, it's time to customize the widget and deploy it to your website. Here's how you can do it:

1. First, make sure that you've published your chatbot. You can publish it from the Builder page.

<img alt="Publish your chatbot" />

2. Go back to the dashboard and click the `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the chatbot widget code.
7. Paste the code into the `head` or `body` section of your website's HTML.

* If you selected the `Inline` mode, you must paste the code where you want the chatbot to appear on your website.

That's it! Your chatbot is now live on your website, ready to engage with your visitors.


# Intents
Source: https://docs.chatling.ai/chatbot/intents/introduction

Learn about intents and how they work in Chatling

<img alt="Intents page" />

## What are Intents?

Intents identify what users are trying to accomplish and capture the meaning behind their messages, regardless of how they phrase them.

For example, when users ask "Where's my order?" or "Track package", they share the same underlying goal - to locate their order.

Intents can be used to define how your chatbot should respond when it recognizes these user goals. Each intent can be linked to specific conversation flows, data collection requirements, and response templates, enabling the chatbot to take appropriate action.

## How Intents Work

Intents are defined in the `Intents` section of your chatbot's builder. Each intent consists of:

* **Name**: A clear, descriptive identifier (e.g., "Order Tracking", "Submit ticket").
* **Description**: Explains the user's goal or purpose this intent represents.
* **Sample phrases**: Collection of sample messages that would trigger this intent. This helps the chatbot understand the intent and accurately match it to user messages.


# Manage intents
Source: https://docs.chatling.ai/chatbot/intents/manage

A guide on how to create and manage your chatbot's intents

## Accessing the Intent page

The Intents page is located inside your chatbot's builder. To access it:

1. Open the Builder.
2. Click on the `Intents` button in the top left.

<img alt="Accessing the Intents page" />

## Creating an intent

1. Open the Intents page.
2. Click the `New` button.

<img alt="Creating an intent" />

3. Enter the details for the intent.

* **Name**: A clear, descriptive identifier (e.g., "Order Tracking", "Submit ticket").
* **Description**: Explains the user's goal or purpose this intent represents.
* **Sample phrases**: Examples of user messages that should trigger this intent. This helps the chatbot understand and match the intent.

<img alt="Enter intent details" />

4. Click the `Create intent` button.

## Editing an intent

1. Open the Intents page to view all the existing intents.
2. Find and click on the intent you want to edit.
3. Make changes to the intent's details, such as name, description, and sample phrases.

<img alt="Edit intent details" />

4. Click the `Save` button to save your changes.

## Deleting intents

1. Open the Intents page to view all the existing intents.
2. Click the checkbox next to one or more intents you want to delete.

<img alt="Select intents in bulk" />

3. Click the `Delete` button in the top left.

<img alt="Delete intents" />


# Using intents
Source: https://docs.chatling.ai/chatbot/intents/using-intents

Learn how to use intents to create more complex chatbot flows

To make your intents work, there are two essential steps:

1. Enable intent matching in blocks to tell the chatbot which intents to look for in user messages.
2. Define the flow of the chatbot when an intent is matched.

## 1. Intent matching

Currently, intent matching can be enabled in [Text input blocks](/chatbot/builder/blocks/inputs/text).

When users send messages using the Text block, you can configure whether these messages should be checked against one or more defined intents. This allows you to control when intent matching occurs and trigger appropriate flows based on the matches.

### Enabling intent matching

1. Open the editor for a text block.
2. Next to the `Match intent` option, click the `+` button.

<img alt="Match intent option" />

3. Select the intents you want user messages to be checked against.

<img alt="Select intents for intent matcher" />

When a user sends a message, the chatbot will check if the message matches any of the selected intents and trigger the appropriate flow. If there are no matches, the flow will continue normally.

## 2. Defining intent flows

There are two ways to define the actions for an intent:

1. Intent trigger block (global)
2. Local trigger

### Intent trigger block

Intent triggers are flows that will be executed when an intent is matched. These triggers are global, meaning that they will be executed by any block that matches the intent. This is useful if you want to create a standard response for an intent that can be used in multiple places in your chatbot.

For example, if you create an Intent trigger for `Order Tracking`:

* Any block that matches this intent will start this flow.
* The same flow runs whether matched in a welcome message or support conversation.
* Flow can include actions like fetching order status, asking for order number, etc.

This provides a consistent response when users ask about order tracking anywhere in your chatbot.

**To add the trigger:**

1. Open `Blocks` from the sidebar.

<img alt="Open Blocks menu" />

2. Under the `Triggers` section, drag and drop the `Intent` block onto the canvas.

<img alt="Drag and drop Intent trigger" />

3. Click on the block to open the editor.

4. Select an intent this trigger belongs to.

<img alt="Select intent for trigger" />

5. Define the flow to run when the intent is triggered.

<img alt="Define flow for intent trigger" />

### Local trigger

Sometimes you want different flows for the same intent depending on where in the conversation it was matched. This is where local triggers come in.

* Open the block where you want to enable local trigger for an intent.
* Find the intent under the `Match intent` option and click the `Local trigger` icon as shown below. For example, we will enable local trigger for the `Order status` intent.

<img alt="Enable local trigger for intent" />

* Define the specific flow for this intent. For example, we will ask the user for their order number before fetching the order status. As such, whenever the input in this block matches the `Order status` intent, the flow defined here will be executed instead of the global trigger.

<img alt="Define flow for local trigger" />

Note that the local trigger takes precedence over the global trigger when enabled.

### Using both triggers

You can have both global and local triggers for intents:

* Use global triggers for standard responses
* Override with local triggers where context-specific flows are needed

This flexibility allows you to:

* Maintain consistent base responses
* Customize flows for specific conversation stages
* Create more dynamic user experiences

## What happens when no intents match?

If no intent is matched, the chatbot will continue with the flow as normal.


# AI Chatbot
Source: https://docs.chatling.ai/chatbot/introduction



AI Chatbots are flow-based assistants you design with Chatling's visual, drag-and-drop builder. They follow the exact steps you define—messages, questions, buttons, conditions, and AI answers—to deliver predictable, on-brand conversations for support, sales, and guided self-service.

Unlike [AI Agents](/ai-agent/introduction) (which plan actions autonomously), Chatbots run the flow you create, making them ideal where compliance, consistency, and tight control matter.

Chatbots also come with built-in AI capabilities, which means you can use AI to generate responses to user's questions.

<img alt="Chatbot visual builder" />

## Key features

* **Visual builder**: Create conversational flows with a drag-and-drop interface.
* **Capture leads**: Collect name, email, phone, and custom fields; store values as variables and send to your CRM via Zapier or API calls to an external service.
* **Route with conditions**: Branch by user choices, variable values, device/page, or language.
* **Show buttons & media**: Present quick replies, links, and images to streamline choices.
* **Answer from your content**: Optionally insert an AI step that responds from your knowledge base (site, docs, FAQs, Zoho/Zendesk, etc.).
* **Escalate when needed**: Create tickets in email, Zendesk, HubSpot, or Zoho when human intervention is required.
* **Multilingual AI**: Auto-detect and reply in the user's language.
* **Analytics & monitoring**: Track conversations, leads, top pages, and fine-tune answers.
* **Security & compliance**: GDPR-ready; encryption in transit and at rest.
* **AI model choice**: Use OpenAI, Anthropic, Gemini, and more.


# How to delete your account
Source: https://docs.chatling.ai/faq/delete-account

Learn how to permanently delete your Chatling account and data.

You can permanently delete your Chatling account from your account settings.

**Account deletion is permanent** and cannot be reversed. All projects you own—including their AI agents, chatbots, and associated data—will be permanently deleted.

Any active subscriptions on projects you own will be automatically canceled and will not renew. However, we recommend canceling them manually from the Billing page before deleting your account.

## Delete your account

1. Click your profile picture in the bottom of the sidebar menu and select `Account settings`.

<img alt="Toggle user menu" />

2. Select the `Delete account` tab.

<img alt="Click delete account tab" />

3. Click `Delete account permanently`.

<img alt="Click delete account permanently" />

4. Enter the confirmation phrase and your current password.

<img alt="Delete account permanently confirmation" />

Your access ends immediately. Projects you own, their chatbots, and associated data are permanently deleted. Active subscriptions are canceled and will not renew.


# How to hide the chatbot on specific pages
Source: https://docs.chatling.ai/faq/hide-chatbot-on-specific-pages

Learn how to set the visibility of your chatbot on specific pages.

Sometimes you may want to hide your chatbot on specific pages of your website. This could be for various reasons, such as maintaining a distraction-free environment on certain pages, or to comply with specific page requirements. Chatling provides a simple way to control the visibility of your chatbot by allowing you to specify URLs where the chatbot widget should not appear.

## How to hide the chatbot on specific pages

1. From the chatbot dashboard, go to `Settings`.

<img alt="Open chatbot settings" />

2. Click the `Visibility` tab.
3. In the `Hide chatbot on specific pages` section, type the URL of the page where you want to hide the chatbot and press the Enter key.
4. Repeat the previous step for each page where you want to hide the chatbot.
5. Click `Save` to apply the changes.

You can also enter wildcard URLs to hide the chatbot on multiple pages. For example, if you want to hide the chatbot on the blog, you can enter `https://example.com/blog/*` to hide it from all pages in the blog.


# How to reset the chat on page load
Source: https://docs.chatling.ai/faq/reset-chat-on-page-load



By default, chat history is retained when users navigate away from the chatbot and return to it, refresh the page, or go to a different page. This means that when users return to the chatbot, they can see their existing chat and continue from where they left off.

If you want to disable this so that the chat is reset on page load, you can do so by following these steps:

1. From your chatbot dashboard, go to `Builder`.

<img alt="Open builder from sidebar" />

2. Click the settings icon in the sidebar.

<img alt="Open builder settings from sidebar" />

3. Enable the the `Reset chat on page load` option.

<img alt="Toggle reset chat on page load" />


# What happens when AI credits are exhausted?
Source: https://docs.chatling.ai/faq/what-happens-when-ai-credits-exhausted



When your AI credits are exhausted, users can still interact with the chatbot and send messages, but an error will be displayed saying "Insufficient AI credits".

When the usage exceeds the limit, you must top up your AI credits by purchasing the **Extra AI Credits** add-on from Billing & Usage > Add-ons page. Alternatively, you can upgrade your plan to get more credits.

You can enable the **AI Credit Usage** notification in your account to be alerted when your usage reaches a threshold such as 50%, 75%, 90% or 100%.


# Custom domain
Source: https://docs.chatling.ai/general-settings/custom-domain

Learn how to add a custom domain to your chatbot.

You can use a custom subdomain for the chatbot widget and sharing link rather than the default one used by Chatling. This allows you to whitelabel your chatbots to maintain your brand identity or make them look like your team developed them.

## How to set a custom domain

1. Open the chatbot you want to set a custom subdomain for.
2. From the menu, click on `Settings` under the `Chatbot` section.

<img alt="Open chatbot settings" />

3. Go to the `Custom Domain` tab.

<img alt="Open custom domain settings" />

4. Enter the custom domain you want to use for the chatbot, such as `sample.domain.com`, and click the `Save` button.

<img alt="Enter custom domain" />

5. Add the DNS records displayed on the page to your domain provider to activate the custom domain.

<img alt="DNS configuration" />

6. Once you add the DNS records, it may take up to 24 hours for the changes to propagate. You can click the `Verify` button to check if the records are active.

7. Once completed and the status is `Active`, the chatbot widget and sharing link will use the custom domain.


# How to delete a chatbot
Source: https://docs.chatling.ai/general-settings/delete

Learn how to remove a chatbot permanently from your account.

If you no longer need a chatbot, you can delete it from the dashboard.

Deleting a chatbot will permanently remove it from your account, and you won't be able to recover it. All data associated with the chatbot, including contacts, conversations, and knowledge base will be removed permanently.

## How to delete a chatbot

1. Open the chatbot you want to delete.
2. From the menu, click on `Settings` under the `Chatbot` section.

<img alt="Open chatbot settings" />

3. Go to the `Delete` tab.

<img alt="Click delete tab in chatbot settings" />

4. Click the `Delete` button.

<img alt="Click delete button" />

5. Confirm the deletion by typing `delete permanently` in the text box and click \`Delete\`\`

<img alt="Confirm delete chatbot" />


# How to duplicate a chatbot or agent
Source: https://docs.chatling.ai/general-settings/duplicate

Learn how to duplicate a chatbot/agent to create a copy of it.

You can duplicate chatbots or agents and create copies of them to use as templates or to make changes without affecting the original bot. This can be useful if you want to experiment with different configurations or create a backup of your bot.

By duplicating a chatbot or agent, all its settings, appearance, and builder configurations will be copied to the new chatbot. You can then make changes to the duplicated chatbot without affecting the original one.

## Duplicating a chatbot

1. Go to your project's dashboard where you can view all your chatbots and agents.

<img alt="Chatbots list" />

2. Click on the ellipsis `...` icon next to the chatbot or agent you want to duplicate.

<img alt="Chatbot more actions menu" />

3. Select the `Duplicate` option from the dropdown menu.

<img alt="Duplicate chatbot" />


# Limits
Source: https://docs.chatling.ai/general-settings/limits

Set per-Agent limits to control how much they consume from your project's quotas.

The `Limits` tab lets you cap how much an individual AI agent can consume from your project-wide quotas. This is useful when you want to:

* Prevent a single AI Agent from depleting all of your project's AI credits.
* Allocate budgets across multiple AI Agents under the same project.
* Stay in control of costs when sharing AI Agents with sub-customers, clients, or teammates.

## Available limits

### AI credit limit

Cap how many [AI credits](/ai/ai-credits) a single Agent can use per month. Once the cap is reached, that Agent will stop responding until either:

* The next monthly billing cycle starts and the counter resets, or
* You raise (or disable) the limit.

The limit is **per AI Agent**, not per end-user. It applies on top of your project-level AI credit quota — your project's pool is checked first, and only after that does the per-Agent cap apply.

1. Open your AI Agent's dashboard.
2. Go to settings.

<img alt="Open chatbot settings" />

3. Click the `Limits` tab.
4. Enable the `AI credit limit` toggle.
5. Enter the number of credits this Agent is allowed to use per month.
6. Click `Save`.


# Rate limit
Source: https://docs.chatling.ai/general-settings/rate-limit

Learn how to set a rate limit for your chatbot to prevent it from being spammed.

Rate limiting allows you to limit the number of messages a user can send to your chatbot in a given period of time. This helps prevent end-users from spamming your chatbot and depleting your account credits.

<Note>Rate limiting is only available for web widgets and not for other integrations, such as Instagram, WhatsApp, API, etc.</Note>

## How to set a rate limit

1. Open your chatbot's dashboard.
2. Go to chatbot settings.

<img alt="Open chatbot settings" />

3. Click the `Security` tab.
4. Under the `Rate limiting` section, add a rate limit, e.g. 10 messages per minute. You can add multiple rate limits for different periods of time, such as per minute, per hour, or per day.
   <Note>The rate limit is applied to individual users. For example, if you set a rate limit of 10 messages per minute, each user can send up to 10 messages per minute.</Note>
5. You can also add a custom error message to be displayed when the rate limit is exceeded. If left blank, a default error message will be displayed.
   <Note>The default error message is automatically translated into the language of your chatbot widget. If you override it with a custom message, it won't be translated.</Note>
6. Click `Save`.

Once you've set the rate limits, your chatbot will prevent end-users from sending more messages than the rate limit in a given period of time. If the rate limit is exceeded, an error message will be displayed.


# Share
Source: https://docs.chatling.ai/general-settings/sharing

A guide on how to share your chatbot or agent with others.

You can generate a unique link for your chatbot or agent, and share it with others for testing, collaboration, or other purposes. Here's how to do it:

1. From the dashboard, click `Share`.

<img alt="Click share sidebar menu" />

2. Click `Generate Link`.

<img alt="Click create share link" />

3. To password protect the link, enable `Require password` and type in a password.

<img alt="Require password" />

4. Copy the link and share it with others.


# Connect Instagram
Source: https://docs.chatling.ai/instagram/create-ai-agent

Learn how to create an Instagram AI agent in Chatling.

The steps below will guide you through the process of creating and connecting Instagram to your **AI Agent** in Chatling.

## Requirements

To use the Instagram integration, you will need:

* An Instagram Business or Creator account
* Permission to connect your account to Chatling

## How to integrate Instagram with Chatling

1. Login to your [Chatling account](https://app.chatling.ai).
2. From the `My agents` page, click the `+ Create` button.

<img />

3. Choose `AI Agent` as the type.

<img />

4. Enter a name for your Agent and click the `Create agent` button.

<img />

5. From your Agent's dashboard, click the `Deploy` button in the sidebar.

<img alt="Deploy" />

6. Click the `Setup` button under the `Instagram` option.

<img alt="Setup Instagram for AI Agent" />

7. A popup will appear to guide you through the process of connecting your Instagram account to Chatling. Click the `Sign in with Instagram` button to continue.

<img />

8. The Instagram authentication window will open. Sign in to your account and click the `Continue` button.

<img />

9. Instagram will display the permissions required by Chatling. Enable all the permissions and click the `Allow` button.

<Note>We only request the necessary permissions to allow Chatling to automate your DMs.</Note>

<img />

10. Instagram will process the authentication and once completed, the dialog will close. Go back to Chatling and a message will be displayed that your authentication is being processed.

    If successful, you should see a message similar to below. Click the `Close` button to finish the setup process.

<img />

The Instagram deployment is now complete and Chatling will send and receive messages from your audience on Instagram.


# Monitor Instagram conversations
Source: https://docs.chatling.ai/instagram/monitor-conversations

Learn how to monitor conversations between your AI agent and Instagram users in Chatling.

Once your Instagram account is connected, you can monitor all conversations between your AI agent and Instagram users directly from the Chatling dashboard.

## How to view conversations

1. Open the AI Agent in Chatling.
2. Click the `Conversations` menu in the sidebar.
3. Here you can view all conversations between your AI agent and Instagram users.

Inside the conversation view, you can:

* Read the full message history between the Instagram user and your AI agent
* See incoming and outgoing messages in chronological order
* Identify the user who started the conversation
* Monitor how your AI agent responded to user questions
* Fine-tune the AI agent's answer to improve future responses

This helps you review how your AI agent is interacting with customers and identify areas for improvement.


# Instagram Integration
Source: https://docs.chatling.ai/instagram/overview

Learn how to connect integrate your Instagram account with Chatling.

The Instagram integration allows you to connect your Instagram account to Chatling so your AI agent can automatically respond to messages from users on Instagram. This enables businesses to provide instant support, capture leads, and answer common questions directly within Instagram Direct Messages (DMs).

By connecting Instagram to Chatling, incoming messages from Instagram conversations are routed to your AI agent, which can generate responses based on the knowledge and behavior you've configured in your agent. This helps you automate customer interactions while maintaining fast response times.

<Note>This integration is currently available for AI Agents only.</Note>

<CardGroup>
  <Card title="Create AI Agent for Instagram" icon="plus" href="/instagram/create-ai-agent" />

  <Card title="Monitor conversations" icon="chat" href="/instagram/monitor-conversations" />
</CardGroup>


# Introduction
Source: https://docs.chatling.ai/introduction



Welcome to the Chatling documentation. This is your end-to-end guide to the platform that explains core concepts, walks you through setup and deployment, and helps you get the most out of the platform.

## What is Chatling?

Chatling is a no-code platform that lets you build conversational AI agents in minutes, trained on custom data, such as business websites, company policies, knowledge bases and documents.

Deploy your agents seamlessly on your website and other channels to automate customer support, capture and qualify leads, and deliver accurate answers.

## Products

There are two types of products available in the Chatling platform.

### 1. AI Agents

Outcome-driven assistants that understand intent and act autonomously. Agents follow your instructions, use your knowledge, and invoke custom actions to fetch/store/update data and complete tasks—no flow building required.

### 2. AI Chatbots

Flow-based bots you design with a visual builder. Define steps, branches, and messages to create predictable, guided experiences (menus, FAQs, forms) with optional AI answers—ideal where tight control and consistency matter.

## Difference between AI Agents and AI Chatbots

The main difference between AI agents and chatbots is how they handle conversations and tasks.

### Chatbots

Chatbots operate using prebuilt flows—structured, step-by-step conversation paths that you design ahead of time in the visual builder.

When a user interacts with a chatbot, it follows a predetermined script: if the user says X, the bot responds with Y, then moves to the next predefined step. This flow-based approach makes chatbots ideal for repetitive, predictable scenarios like FAQ responses, appointment booking, or lead qualification where you know exactly what questions to ask and in what order.

The trade-off is that chatbots struggle with unexpected inputs or complex conversations that deviate from the designed flow.

### AI Agents

AI Agents work fundamentally differently—they don't follow rigid flows. Instead, they plan and execute actions dynamically based on the conversation context, the instructions you provide, and the tools/actions you've configured.

When a user makes a request, an AI Agent interprets the intent, determines what needs to be done, and decides which sequence of actions to take in real-time.

For example, if a user asks to "check my order and update the shipping address," an AI Agent can autonomously decide to first query the order database, then update the address in your CRM, without you having to map out this specific flow in advance. This makes AI Agents significantly more flexible and capable of handling complex, multi-step interactions that would be impractical to predefine.

A major advantage of AI Agents is their multi-channel capability. You can connect multiple platforms—such as Web, WhatsApp, and Instagram—to a single agent. This allows you to maintain one unified system that handles conversations consistently across all channels, rather than building and maintaining separate chatbots for each platform. Updates to the agent's knowledge, instructions, or capabilities instantly apply everywhere.

## Documentation

To get started, explore the documentation for the product you're interested in.

<CardGroup>
  <Card title="AI Agents" icon="sparkles" href="/ai-agent/introduction" />

  <Card title="AI Chatbots" icon="message-bot" href="/chatbot/introduction" />
</CardGroup>


# Add data source
Source: https://docs.chatling.ai/knowledge-base/add-data-source

A guide on adding data sources to the Knowledge Base.

<img alt="Add data sources to the Knowledge Base" />

## How to add data to the knowledge base

To add data to the Knowledge Base, follow these steps:

1. From the dashboard, go to `Knowledge Base`.

<img />

2. Click on the `Add new` or `New Data Source` button.

<img />

3. Select the type of data source you want to add.

<img />

4. Follow the on-screen instructions to add the data source to the knowledge base.

Once added, it will take a few minutes for the data to be processed. The status of the data source will be displayed in the Knowledge Base page and will change to "Processed" once the AI has extracted the information.

<img />


# Auto-sync data sources
Source: https://docs.chatling.ai/knowledge-base/auto-sync-data-sources

Learn how to auto-sync data sources in the Knowledge Base.

Auto-syncing allows you to automatically sync your knowledge base sources at specified intervals, such as daily, weekly, or monthly, to fetch the latest data. This ensures that your knowledge base is always up to date with the latest information.

## How to enable auto-syncing

1. Go to the `Knowledge Base` page.
2. From the `Auto-sync` column, you can select an interval for each data source.

<img />

3. Click on the auto-sync value for a specific source and choose an interval.

<img />

4. If you want to enable auto-syncing for multiple sources, you can select the sources and click the `Change auto-sync frequency` button to update all selected sources at once.

<img />


# Types of data sources
Source: https://docs.chatling.ai/knowledge-base/data-source-types

Learn about the different types of data sources you can add to the Knowledge Base.

Data sources are the sources of information you can add to the Knowledge Base. Together, they provide information the AI needs to respond accurately to user queries.

You can add the following types of data sources to the Knowledge Base:

* **Website**: When you add a website, our crawler will visit and extract all the pages from the website. You can then select the pages you want to add to the Knowledge Base.
  * The website crawler can extract up to 1,000 pages from a website. If your site contains more pages, you must use the Sitemap data source.
* **Sitemap**: Add a sitemap URL to fetch all the pages of your website. The sitemap is suitable when your website has more than 1,000 pages. Once the sitemap is fetched, you can select the pages to add to the Knowledge Base.
* **URL List**: Add a list of URLs to the Knowledge Base. This is useful when you want to add specific links instead of an entire website.
* **Document**: Upload documents such as PDF, DOCX, and TXT. The AI will extract the text from the document and use it to generate responses.
* **Text**: You can add text directly to the Knowledge Base. This is useful when you want to add custom information that isn't available on your website or documents.
* **FAQs**: You can add a list of questions and answers that users frequently ask. This is useful when the information is not available through other data sources. You can also use it for fine-tuning the AI responses, such as when it responds incorrectly to certain questions.
* **Zoho**: Import all or select articles from your Zoho account into the Chatling knowledge base.
* **Zendesk**: Import all or select articles from your Zendesk account into the Chatling knowledge base.
* **Notion**: Import all or select pages from your Notion account into the Chatling knowledge base.


# Delete data sources
Source: https://docs.chatling.ai/knowledge-base/delete-data-sources

Learn how to delete data sources in the Knowledge Base.

If you no longer need a data source or want to prevent the AI from using it, you can delete it from the Knowledge Base. The information associated with the deleted data source will be purged permanently and cannot be recovered.

## How to delete a data source

1. Go to the `Knowledge Base`.
2. Next to every data source is a delete icon, as shown below. Click on the icon to delete the data source.

<img alt="Delete data sources in the Knowledge Base" />

## How to delete data sources in bulk

To delete multiple data sources at once, click on the checkbox next to the data sources you want to delete. Then, click the `Bulk action` dropdown and select `Delete`.

<img alt="Delete data sources in bulk in the Knowledge Base" />


# Exclude webpage sections
Source: https://docs.chatling.ai/knowledge-base/exclude-webpage-sections

Learn how to exclude certain sections of a webpage when adding a data source.

Websites often contain a lot of information that may not be relevant to the AI. When you add webpages to the knowledge base, you can exclude certain sections of the page from being crawled and indexed by the AI.

This can be useful for removing irrelevant information as well as preventing unnecessary characters from being counted towards your plan's limit.

## How to exclude sections of a webpage

1. Go to the `Knowledge Base`.
2. Click the `New Data Source` or `Add new` button.

<img />

3. Select `Website`, `Sitemap`, or `URL list` as the data source type.
4. Click the `Advanced Settings` button.

<img />

5. You can exclude sections by entering the HTML classes or IDs of the elements you want to exclude. You must press Enter after each class or ID to add it to the list.

You can also select the HTML tags you want to remove, such as `header` or `footer`.

<img />

You can now go ahead with entering the website, sitemap, or list of URLs that you want to add to the knowledge base. The crawler will exclude the sections you specified.


# Overview
Source: https://docs.chatling.ai/knowledge-base/overview

Learn about the Knowledge Base and how it works.

<img />

The Knowledge Base is where you upload information that the AI uses to generate responses to user queries. You can add [data sources](/knowledge-base/data-source-types) such as websites, webpages, documents, texts, and FAQs to the knowledge base.

When a user asks a question, the AI searches the Knowledge Base for all relevant information and returns the best answer based on the data it finds.

If your chatbot contains an AI Response block and it's "Response Source" is set to "Knowledge Base", it's essential to populate the knowledge base with information that the AI can use to generate responses.


# Re-sync data sources
Source: https://docs.chatling.ai/knowledge-base/re-sync-data-sources

Learn how to re-sync data sources in the Knowledge Base.

If you've made changes to your Link data sources (websites/webpages) or want to update the information in the Knowledge Base, you can re-sync the data sources to fetch the latest data. This process will re-fetch the data from the source and update the information in the Knowledge Base.

## Supported data sources

Re-syncing is available for Links data sources only, which include websites and webpages. Other data sources like Documents, Text, and FAQs do not require re-syncing as they are static and do not change unless you manually update them.

## How to re-sync a data source

To re-sync data sources in the Knowledge Base, follow these steps:

* Go to the `Knowledge Base`.
* Click on the `Link` tab to view all the links you have added.
* Next to every link is a re-sync icon, as shown below. Click on the icon to queue the link for re-syncing.

<img alt="Re-sync data sources in the Knowledge Base" />

## Re-sync data sources in bulk

To re-sync multiple data sources at once, click on the checkbox next to the links you want to re-sync. Then, click on the `Bulk action` dropdown and select `Re-sync links`.

<img alt="Re-sync multiple data sources in the Knowledge Base" />


# Routing
Source: https://docs.chatling.ai/live-chat/agent-routing

Route handed-off conversations to a team queue or automatically assign an agent using ordered routing rules.

Agent routing determines who receives a conversation when a human handoff occurs. You can leave the conversation unassigned in a team queue or automatically assign an agent using round-robin routing.

Routing is configured separately for each **Human Handoff** action or block. This lets you use different routing rules for different handoff scenarios.

<Note>Availability of this feature depends on your plan.</Note>

## Before you begin

Before configuring routing:

* Set up human handoff for your [AI Agent](/live-chat/human-handoff/ai-agent) or [Chatbot](/live-chat/human-handoff/chatbot).
* If you want to route to a team, create the team and add its members under **Settings > Teams**. See [Teams](/live-chat/teams).
* Make sure the agents you want to include have access to the chatbot or AI Agent's conversations.

## Open the routing settings

### AI Agent

1. Open your AI Agent.
2. Go to **Actions**.
3. Find the **Human Handoff** action and click `Edit Action`.
4. Scroll to the **Agent routing** section.

### Chatbot

1. Open your Chatbot.
2. Go to **Builder**.
3. Select the **Human Handoff** block you want to configure.
4. Find the **Agent routing** section in the block editor.

## Create a routing rule

1. Click `Add rule`.
2. Choose whether **all** or **any** of the rule's conditions must match.
3. Add the conditions that identify the conversations you want to route.
4. Choose what should happen when the rule matches.
5. Save the Human Handoff action, or save and publish your Chatbot flow.

Rules are evaluated from top to bottom. The first enabled rule that matches is applied, and the remaining rules are skipped.

<Tip>Place your most specific rules first and your broadest fallback rule last.</Tip>

## Conditions

Conditions let you route conversations using information available at the time of handoff:

* **Channel**: Route based on where the conversation started, such as Web, WhatsApp, API, Instagram, Messenger, or Telegram.
* **Language**: Route based on the user's detected language.
* **Priority**: Route using the conversation's assigned priority.
* **Sentiment**: Route using the user's detected sentiment.
* **Captured variable**: Route using information gathered during the conversation, such as a department, product, region, or customer type.

Use **Is** or **Is not** to compare one value. Use **Is one of** or **Is not one of** to select multiple accepted values.

For captured variables, enter the variable name and choose the appropriate comparison. Variable names must match the information configured for the handoff.

### Match all or any conditions

* **All conditions match**: Every condition in the rule must match.
* **Any condition matches**: At least one condition in the rule must match.

A rule with no conditions always matches. Use it as the final rule when you want a default routing destination.

## Routing actions

### Leave in team queue

Select **Leave in team queue**, then choose a team.

The conversation is assigned to the team but remains unassigned to an individual agent. Any eligible member of that team can pick it up from the Conversations page.

Use this option when your team manages a shared queue and agents choose conversations themselves.

### Round-robin auto-assign

Round-robin routing automatically assigns each matching conversation to the next eligible agent in rotation.

Choose one of the following agent pools:

* **All agents with access**: Rotate between all eligible agents who can access the chatbot or AI Agent's conversations.
* **Selected team**: Rotate between eligible members of a specific team. The conversation is assigned to both the team and the selected agent.
* **Custom agent pool**: Rotate between only the agents you select.

Each chatbot and routing target maintains its own rotation. After the final eligible agent receives a conversation, the next assignment starts again from the beginning.

<Note>Round-robin routing currently does not consider agent online status, capacity, or current workload.</Note>

## Reorder, disable, or remove rules

* Drag rules to change their evaluation order.
* Use the toggle on a rule to temporarily disable it without deleting its configuration.
* Click the delete icon to remove a rule.

Routing runs when at least one rule is enabled.

## What happens when routing cannot assign a conversation

The conversation remains in the unassigned queue when:

* No enabled rule matches.
* A selected team is unavailable.
* A round-robin pool has no eligible agents.
* Routing is unavailable on the current plan.

The human handoff still succeeds, so an agent can assign or pick up the conversation manually.

## Example setup

You could create the following ordered rules:

1. If the captured variable `department` is `billing`, leave the conversation in the **Billing** team queue.
2. If priority is `urgent` or `high`, round-robin between the **Escalations** team.
3. If there are no conditions, round-robin between all agents with access.

The third rule acts as the default because a rule without conditions always matches.

## Next steps

<CardGroup>
  <Card title="Teams" icon="users" href="/live-chat/teams">
    Create teams and manage their members.
  </Card>

  <Card title="Managing Conversations" icon="comments" href="/live-chat/managing-conversations">
    Learn how agents pick up and manage handed-off conversations.
  </Card>

  <Card title="Notifications" icon="bell" href="/live-chat/notifications">
    Configure notifications for agent and team assignments.
  </Card>
</CardGroup>


# Availability
Source: https://docs.chatling.ai/live-chat/availability

Configure office hours and reply time for your live chat team.

The Availability settings let you define when your team is available for live chat and set response time expectations for your users. These settings are found under **Settings > Live Chat** in your AI Agent or Chatbot dashboard.

<img alt="Live chat availability settings page" />

## 1. Office hours

Office hours define when your team is available to handle live chat conversations. When users start a live chat outside of these hours, they can be informed when you'll be back.

### Setting up office hours

1. Go to your AI Agent or Chatbot dashboard.
2. Navigate to **Settings > Live Chat**.
3. Under **Office hours**, configure your schedule:
   * Select the **days** from the dropdown (e.g. Weekdays, Weekends, or individual days).
   * Set the **start** and **end** times.
4. Click **Save**.

### Day options

The following day options are available:

| Option             | Days                                                              |
| ------------------ | ----------------------------------------------------------------- |
| Every day          | Monday – Sunday                                                   |
| Weekdays (Mon-Fri) | Monday – Friday                                                   |
| Weekends (Sat-Sun) | Saturday – Sunday                                                 |
| Individual days    | Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, or Sunday |

### Multiple schedules

You can add multiple schedules to cover different time ranges. For example, you might set:

* **Weekdays (Mon-Fri)**: 09:00 – 17:00
* **Saturday**: 10:00 – 14:00

To add another schedule, click **+ New**. To remove a schedule, click the delete icon next to it.

<Note>The schedule is based on your timezone configured in **General settings**.</Note>

## 2. Reply time

Reply time is displayed to customers during office hours to set expectations for how quickly they can expect a response.

### Setting reply time

1. Under **Reply time**, select an option from the dropdown.

* None: No reply time shown.
* In a few minutes
* In a few hours
* In a day
* As soon as possible
* Custom time: Specify a custom time (e.g. "Under 15 minutes").

2. Click **Save**.

## Customer availability after leaving

For AI Agent web widgets, **Web Widget > Email reply notifications** can collect a customer's email during live chat. When a human agent replies after the customer leaves the website, the customer receives the latest conversation transcript by email.

This uses recent widget heartbeats to determine whether the customer is still online. Presence is temporary and is not stored as a status on the conversation.

See [Notifications](/live-chat/notifications#customer-reply-notifications) for configuration details.


# Canned Responses
Source: https://docs.chatling.ai/live-chat/canned-responses

Save replies you send often and insert them into the composer with a click or a shortcode.

Canned responses are saved reply templates you can drop into the live chat composer to avoid retyping the same message every time, such as greetings, account-info requests, troubleshooting steps, closing remarks, etc.

Each response has a **title**, a **message** (rich text), and an optional **shortcode** for keyboard insertion.

<img alt="Manage canned responses" />

## Managing canned responses

1. To manage canned responses, go to **Settings > Canned Responses**.

2. Click the `+` button next to the search bar to add a new canned response.

<img alt="Add new canned response button" />

3. Provide a title, a message, and (optionally) a shortcode.

<img alt="New canned response form" />

### Shortcodes

A shortcode is a short keyword (e.g. `greet`, `refund-policy`, `out-of-office`) you assign to a canned response so you can insert it quickly.

**To use:** in the composer, type a backtick followed by the shortcode e.g. `` `greet ``. A floating menu shows matching responses as you type. Press <kbd>Enter</kbd> to insert the highlighted one, or click it. <kbd>Esc</kbd> dismisses the menu.

### Variables (AI Agent only)

In the message editor, type `{{` to insert a variable. Variables resolve at insert-time against the current conversation - `{{contact_fname}}`, `{{contact_email}}`, etc. — and fall back to an empty string if the value is unknown.

Variables are **not** available on standard chatbots; the editor shows them as plain text on those.

## Inserting a canned response

Three ways from the composer:

1. **Picker**: click the bookmark icon in the reply composer. You can search for a canned response by title or shortcode, and select it to insert it into the composer.
2. **Shortcode**: type a backtick followed by your shortcode (e.g. `` `greet ``). A floating menu shows matches; press <kbd>Enter</kbd> or <kbd>Tab</kbd> to insert the highlighted one.
3. **Slash command**: type `/`, choose **Canned response** to open the canned response picker.


# Copilot
Source: https://docs.chatling.ai/live-chat/copilot

Your AI teammate inside every conversation

Copilot is an AI assistant built into the conversation view. It helps agents reply faster by drafting responses, summarizing long threads, reading customer intent and sentiment, and answering questions using your knowledge base.

Copilot is private to the agent - customers never see your Copilot chat, and nothing is sent to the customer until you choose to use a draft.

<img alt="Copilot chat preview" />

<Note>
  Copilot usage consumes AI credits. Each message costs 3 credits and is consumed from your account's AI credit pool.
</Note>

## Opening Copilot

In any conversation, open the right panel and select the **Copilot** tab, or press <kbd>⌘</kbd> + <kbd>J</kbd> (<kbd>Ctrl</kbd> + <kbd>J</kbd> on Windows) to toggle it.

<img alt="How to open Copilot chat" />

## Asking Copilot

Type a question in the composer at the bottom of the panel and press <kbd>Enter</kbd>. You can ask questions like:

* Draft a reply to the customer
* Summarize the conversation
* What is the customer's sentiment?

Copilot reads the recent messages in the current conversation for context and searches your knowledge base when needed. Answers are **grounded in your knowledge base**, so they're based on your content rather than guessed.

When Copilot uses your knowledge base, the relevant sources appear below its answer. Click a source to open it in a new tab.

## Drafting and using replies

When you ask Copilot to draft a reply to the customer, it searches your knowledge base for relevant information and automatically writes a reply for you.

Once the reply is drafted, it appears in a **Suggested reply** card. You can use it by clicking the **Use draft** button, which inserts the text straight into the live-chat composer, where you can edit it before sending.

### Refining a draft

You can also use the three-dots menu on a draft card to refine it without retyping your request.

<img alt="Copilot draft refine menu" />

The following actions are available:

| Action          | What it does                                                                       |
| --------------- | ---------------------------------------------------------------------------------- |
| **Adjust tone** | Rewrites in a chosen tone: Professional, Friendly, Empathetic, Casual, or Concise. |
| **Expand**      | Adds more detail.                                                                  |
| **Shorten**     | Makes it more concise.                                                             |
| **Rephrase**    | Rewrites while keeping the meaning.                                                |

Each refinement produces a new draft so you can compare and pick the best version.

<img alt="Shorten Copilot draft example" />

## Settings

Click the settings icon at the top of the Copilot panel to open the **Copilot settings**. You can configure the following:

* **Tone** - controls how Copilot phrases drafted replies. This setting is yours only and doesn't affect your teammates.

<img alt="Open Copilot settings" />

## Managing the thread

The three-dots menu at the top of the Copilot panel allows you to manage the thread.

* **Restart Copilot chat** - clears the current Copilot thread and starts fresh.
* **Manage knowledge** - opens your knowledge base in a new tab so you can fix or add content.

<img alt="View more actions in Copilot chat" />


# Set up handoff for AI Agent
Source: https://docs.chatling.ai/live-chat/human-handoff/ai-agent

Learn how to configure human handoff for your AI Agent.

The Human Handoff action allows your AI Agent to automatically transfer a conversation to a human team member when certain conditions are met.

This action is created by default for every AI Agent, but is **disabled** by default. You just need to enable it and configure when it should be triggered.

<Tip>This guide is for setting up handoff for an AI Agent. For Chatbot, see [Set up handoff for Chatbot](/live-chat/human-handoff/chatbot).</Tip>

## Configuration

To configure human handoff for your AI Agent, follow these steps:

1. Go to your AI Agent's dashboard.
2. Click on **Actions** from the sidebar.

<img alt="Open Actions page for your AI Agent" />

3. Find the **Human Handoff** action.
4. Click `Edit Action`.

<img alt="Edit Human Handoff action for your AI Agent" />

5. Configure the following settings:

### `Enabled`

Toggle this to enable or disable automatic handoff. When disabled, the AI Agent will not hand off conversations to human agents automatically.

### `When to Use`

Describe when the AI Agent should hand off the conversation to a human agent. This is the core of your handoff configuration. The AI uses this description to determine when to trigger the handoff.

<img alt="Configure when to trigger handoff for your AI Agent" />

You can specify:

* **Trigger conditions**: When the handoff should occur (e.g. "when the user asks to speak with a human", "when the user has a billing issue").
* **Pre-handoff behavior**: How the AI should handle the conversation before handing off (e.g. "try to resolve the issue first, then hand off if unsuccessful").
* **Topics for escalation**: Specific topics or keywords that should always trigger a handoff.
* **Handoff message**: Describe how the AI should inform the user when initiating the handoff (e.g. notify the user that they are being transferred to a team member). Avoid providing exact phrases, as the AI will adapt the message to match the user's language.

<Tip>Be as specific as possible. The more detailed your instructions, the better the AI will be at determining when to hand off. Include example phrases and scenarios if applicable.</Tip>

### `Auto-assign priority`

When enabled, the AI will automatically assign a priority level to the conversation when handing it off. This helps your team triage and address the most urgent conversations first.

The priority is determined by the AI based on the context and urgency of the conversation.

<img alt="Auto-assign priority for your AI Agent" />

### `Agent routing`

Create ordered rules that route handed-off conversations to a team queue or automatically assign an agent using round-robin routing.

See [Agent routing](/live-chat/agent-routing) for setup instructions and routing options.

### `Information to Gather`

Define parameters the AI Agent must collect from the user before initiating the handoff. The Agent will automatically gather these from the conversation context or ask the user directly.

This is useful for ensuring your team has the necessary information when they pick up the conversation, such as the user's name, email, order number, or a description of their issue.

<img alt="Configure information to gather for your AI Agent" />

## What happens after handoff

Once the AI Agent triggers the handoff:

1. The conversation is flagged as **Needs agent intervention** in the [Conversations](/live-chat/managing-conversations) page.

<img alt="Indicator in the conversation thread that the conversation needs agent intervention" />

2. An [AI summary](/live-chat/managing-conversations#ai-summary) of the conversation is generated for the agent.

<img alt="AI summary for the agent after handoff" />

3. If [notifications](/live-chat/notifications) are enabled, your team will be notified.
4. A team member can then pick up the conversation and reply directly.

## Next steps

<CardGroup>
  <Card title="Agent routing" icon="route" href="/live-chat/agent-routing">
    Route handoffs to a team queue or automatically assign an agent.
  </Card>

  <Card title="Availability" icon="clock" href="/live-chat/availability">
    Set office hours and reply time for your team.
  </Card>

  <Card title="Notifications" icon="bell" href="/live-chat/notifications">
    Configure notifications for your team.
  </Card>

  <Card title="Managing Conversations" icon="comments" href="/live-chat/managing-conversations">
    Learn how to manage handed-off conversations.
  </Card>
</CardGroup>


# Set up handoff for Chatbot
Source: https://docs.chatling.ai/live-chat/human-handoff/chatbot

Learn how to configure human handoff for your AI Chatbot using the Builder.

With the AI Chatbot, you have full control over how and when conversations are handed off to a human agent. Using the Builder, you can design a flow that determines the exact conditions for triggering a handoff.

The two key components are:

* **Human Handoff block** — An action block that transfers the conversation to a human agent when reached in the flow.
* **Intent trigger** — Detects when a user's message matches a specific intent (e.g. requesting human support) and routes the conversation to the handoff block.

<Tip>This guide is for setting up handoff for a Chatbot. For AI Agent, see [Set up handoff for AI Agent](/live-chat/human-handoff/ai-agent).</Tip>

<Note>If you're unfamiliar with the Builder, refer to the [Builder introduction](/chatbot/builder/introduction) first. For intents, see [Introduction to Intents](/chatbot/intents/introduction).</Note>

## Set up automatic handoff

This guide walks you through setting up an automatic handoff that triggers when the AI detects the user wants to speak with a human agent.

### Step 1: Create a handoff intent

First, create an intent that defines when the conversation should be handed off.

1. Go to your chatbot's dashboard and open the **Builder** page from the sidebar.

<img alt="Accessing the Builder page" />

2. Click on the `Intents` button in the top left.

<img alt="Accessing the Intents page" />

3. Click the `Templates` button in the top right.
4. Select the **Human agent / Live support** template. This creates a pre-configured intent with common phrases like "live agent" and "speak with human".

You can customize the intent's description and phrases to match your use case. For more details on managing intents, see [Manage Intents](/chatbot/intents/manage).

<img alt="Configure Human agent / Live support intent template" />

5. Click the `Create intent` button.

<Tip>The template includes common handoff phrases, but you should add any phrases specific to your business or industry to improve detection accuracy.</Tip>

### Step 2: Add an Intent trigger block

Next, add an Intent trigger block to the canvas so the chatbot knows what to do when the handoff intent is detected.

1. Open **Blocks** from the sidebar.
2. Under the **Triggers** section, drag and drop the **Intent** block onto the canvas.

<img alt="Add Intent trigger block" />

4. Click on the intent block to open its editor.
5. Select the **Human agent / Live support** intent from the dropdown.

<img alt="Configure Intent trigger block" />

### Step 3: Add a Human Handoff block

Now add the block that will actually transfer the conversation to a human agent.

1. Open **Blocks** from the sidebar.
2. Under the **Actions** section, drag and drop the **Human Handoff** block onto the canvas.

<img alt="Add Human Handoff block" />

3. Click the block to open its editor and configure the following settings:

* **Auto-assign priority**: Automatically assign a priority level to the conversation.
* **Handoff confirmation message**: Automatically generate and display a confirmation message to the user when the handoff is initiated.
* **Agent routing**: Route the handoff to a team queue or automatically assign an agent. See [Agent routing](/live-chat/agent-routing).

### Step 4: Connect the blocks

Connect the Intent trigger to the Human Handoff block so the handoff is executed when the intent is detected.

1. Drag a connection from the Intent trigger block to the Human Handoff block.

<img alt="Connect Intent trigger to Human Handoff block" />

### Step 5: Enable intent matching on input blocks

Finally, tell the chatbot to check for the handoff intent when users send messages.

1. Open the input block where users enter their queries (e.g. a **Capture Text** block).

<img alt="Open Capture Text block" />

2. Under the **Match intent** section, click the **+** icon.
3. Select the **Human agent / Live support** intent.

<img alt="Select human handoff intent" />

Now, whenever a user sends a message through that input block, the chatbot will check if it matches the handoff intent. If it does, the Intent trigger fires and the Human Handoff block is executed, transferring the conversation to your team.

<Info>If no intent matches, the chatbot continues with its normal flow.</Info>

### Complete flow

Your finished flow should look something like this:

<img alt="Complete flow showing Intent trigger → Human Handoff block" />

## Alternative: Manual placement

You don't have to use intents for handoff. You can place the Human Handoff block anywhere in your chatbot flow and connect it directly to other blocks.

For example, you could:

* Connect it after a **Buttons** block where one option is "Talk to a human".
* Place it at the end of a troubleshooting flow as a fallback when the chatbot can't resolve the issue.
* Trigger it from a **Condition** block based on a variable value.

This gives you full flexibility to design the exact handoff experience you want.

## What happens after handoff

Once the handoff is triggered:

1. The conversation is flagged as **Needs agent intervention** in the [Conversations](/live-chat/managing-conversations) page.

<img alt="Indicator in the conversation thread that the conversation needs agent intervention" />

2. An [AI summary](/live-chat/managing-conversations#ai-summary) of the conversation is generated for the agent.

<img alt="AI summary for the agent after handoff" />

3. If [notifications](/live-chat/notifications) are enabled, your team will be notified.
4. A team member can then pick up the conversation and reply directly.

## Next steps

<CardGroup>
  <Card title="Agent routing" icon="route" href="/live-chat/agent-routing">
    Route handoffs to a team queue or automatically assign an agent.
  </Card>

  <Card title="Availability" icon="clock" href="/live-chat/availability">
    Set office hours and reply time for your team.
  </Card>

  <Card title="Notifications" icon="bell" href="/live-chat/notifications">
    Configure notifications for your team.
  </Card>

  <Card title="Managing Conversations" icon="comments" href="/live-chat/managing-conversations">
    Learn how to manage handed-off conversations.
  </Card>
</CardGroup>


# Managing conversations
Source: https://docs.chatling.ai/live-chat/managing-conversations

Learn how to view conversations, reply to users, add notes, and use AI summaries.

The Conversations page in your AI Agent or Chatbot dashboard lists all conversations that users have had with your AI. Admins and agents can review conversations, monitor activity, and track performance from here.

When a conversation is handed off from the AI to a human agent, it also appears here, flagged for attention so your team can pick it up, reply to the user, review the AI summary, add internal notes, and manage priority.

<img alt="Conversations page" />

## 1. Viewing conversations

To view conversations, open the **Conversations** page from the menu in your AI Agent or Chatbot dashboard.

You'll see a list of all conversations, with the most recent at the top.

Click on any conversation to open it. The conversation thread shows the full message history between the user and the AI, as well as any agent replies and internal notes.

## 2. Finding conversations that need attention

Conversations that have been handed off are flagged with a **Needs agent intervention** indicator, making them easy to spot in your conversation list.

<img alt="Indicator in the conversation thread that the conversation needs agent intervention" />

### Filtering conversations

Use the filter drawer to quickly find the conversations you need. The following filters are available:

<img alt="Open conversation page filters" />

## 3. Replying to a conversation

To take over a conversation and reply to the user:

1. Open the Conversations page.
2. Select a conversation from the list.
3. Press **R** or click the **Reply** button at the bottom of the conversation thread.
4. Type your message in the composer and click **Send**.

<img alt="Reply composer at bottom of conversation" />

Your message is sent directly to the user in real time.

<Tip>You can jump into any conversation and reply at any time — the conversation doesn't need to have been formally handed off. This is useful for proactively assisting users when needed.</Tip>

## 4. AI summary

When a conversation is handed off to a human agent, the AI automatically generates a summary of the conversation. This summary is displayed in the conversation view, giving you full context before you respond.

<img alt="AI summary for the agent after handoff" />

The summary includes key points from the conversation, such as:

* What the user asked about
* What the AI tried or recommended
* Why the conversation was handed off
* Priority level
* User sentiment (e.g Neutral, Positive, Negative)

This helps agents get up to speed quickly without having to read through the entire conversation history.

## 5. Internal notes

Notes allow team members to leave internal comments within a conversation that are only visible to your team.

To add a note:

1. Open a conversation.
2. Click the **Add note** button (or press **N**).
3. Type your note and press **Send**.

Notes are useful for:

* Leaving context for the next agent who picks up the conversation.
* Documenting actions taken or follow-ups needed.
* Communicating with team members about a specific conversation.

## 6. Assigning conversations

You can assign a conversation to a specific team member from the **Chat Information** panel in the sidebar.

1. Open a conversation.
2. In the sidebar, find the **Assigned agent** field under **Chat Information**.
3. Select a team member from the dropdown.

<img alt="Assign conversation to an agent" />

When a conversation is assigned, that team member will receive a notification (if [notifications](/live-chat/notifications) are enabled).

## 7. Priority

Each conversation can have a priority level to help your team triage effectively. Priority can be set in two ways:

* **Automatically** — If [auto-assign priority](/live-chat/human-handoff/ai-agent#auto-assign-priority) is enabled, the AI assigns a priority level when handing off the conversation based on the context and urgency.
* **Manually** — Any team member can change the priority from the **Chat Information** panel in the sidebar.

To change priority manually:

1. Open a conversation.
2. In the sidebar, find the **Priority** field under **Chat Information**.
3. Select a priority level from the dropdown.

<img alt="Change conversation priority" />


# Notifications
Source: https://docs.chatling.ai/live-chat/notifications

Configure notification for live chat events

Configure notifications for your team and customers during live chat conversations. Personal notifications alert team members about conversations that need attention, while email reply notifications let customers receive human agent replies after leaving your website.

## Personal notifications

Personal notifications are sent to members of your support team when specific live chat events occur.

<img alt="Personal live chat notification settings" />

### Available notifications

| Notification                                         | Description                                                                                     |
| ---------------------------------------------------- | ----------------------------------------------------------------------------------------------- |
| A new conversation is waiting for agent intervention | Sent when a conversation is handed off from the AI and is waiting for a human agent to respond. |
| A conversation is assigned to me                     | Sent when a conversation is assigned to you by another team member.                             |
| A conversation is assigned to my team                | Sent when a conversation is assigned to a team you belong.                                      |

### How to configure

1. Go to your AI Agent or Chatbot dashboard.
2. Navigate to **Settings > Notifications**.
3. Under **Personal notifications**, check the **Email** checkbox next to the notifications you want to receive.
4. Click **Save**.

<Note>These are per-user settings. Each team member on your project needs to configure their own notification preferences.</Note>

## Email reply notifications

Email reply notifications are sent to customers. Web chats can collect a customer's email address when a conversation is handed off to your team. If a human agent replies after the customer leaves your website, the customer receives an email containing the new replies they missed.

<img alt="Email form to collect customer email address for offline replies" />

Configure this behavior under **[Widget Editor](/web-widget/customize) > Configure > Email reply notifications**:

* **Require email before messaging** requires customers to provide an email address before they can send messages.
* **Show email reminder** displays a reminder above the message box when email collection is optional and a customer skips the email form.

<Note>Set your business name in **Settings > General** so it is displayed in the email notification, such as in the subject line and sender name. If no business name is set, the email uses a generic subject, which is not recommended.</Note>


# Live Chat & Human Handoff
Source: https://docs.chatling.ai/live-chat/overview

Learn how to use the Live Chat & Human Handoff feature in Chatling.

Live Chat & Human Handoff allows you to seamlessly transition conversations from your AI agent or chatbot to a human team member when needed.

Instead of your AI trying to handle every situation, you can define exactly when and how a conversation should be handed off, ensuring your users always get the right level of support.

Your team can also jump in and take over any conversation at any time directly from the [Conversations](/live-chat/managing-conversations) page.

## How it works

1. A user starts a conversation with your AI agent or chatbot.
2. Based on your configuration, the AI determines when to hand off the conversation to a human agent, either automatically or through a specific flow you've defined.
3. The conversation is flagged as `Needs agent intervention` in the Conversations page.
4. An [AI-generated summary](/live-chat/managing-conversations#ai-summary) of the conversation is displayed so the agent has full context before responding.
5. A team member picks up the conversation and replies directly from the Conversations page.

## Key features

* **Automatic handoff**: Configure when the AI should hand off to a human.
* **Office hours & reply time**: Define when your team is available and set response time expectations for your users.
* **AI summary**: When a conversation is handed off, the AI generates a summary so agents can quickly get up to speed.
* **Auto-assign priority**: The AI can automatically assign a priority level to handed-off conversations.
* **Agent routing**: Route handed-off conversations to a team queue or automatically assign an agent.
* **Internal notes**: Team members can leave notes within a conversation for other agents to see.
* **Email notifications**: Get notified when conversations need attention.

## Setup

The setup process differs depending on whether you're using an AI Agent or an AI Chatbot.

<CardGroup>
  <Card title="Set up for AI Agent" icon="sparkles" href="/live-chat/human-handoff/ai-agent">
    Configure human handoff through the AI Agent's Actions.
  </Card>

  <Card title="Set up for Chatbot" icon="shapes" href="/live-chat/human-handoff/chatbot">
    Configure human handoff using the Builder's Human Handoff block and Intents.
  </Card>
</CardGroup>

## Learn more

<CardGroup>
  <Card title="Availability" icon="clock" href="/live-chat/availability">
    Set office hours and reply time expectations.
  </Card>

  <Card title="Managing Conversations" icon="comments" href="/live-chat/managing-conversations">
    Take over chats, view AI summaries, add notes, and manage priority.
  </Card>

  <Card title="Notifications" icon="bell" href="/live-chat/notifications">
    Configure email notifications for handoff events.
  </Card>

  <Card title="Teams" icon="users" href="/live-chat/teams">
    Manage your team members and their availability.
  </Card>

  <Card title="Agent routing" icon="route" href="/live-chat/agent-routing">
    Route handoffs to team queues or automatically assign agents.
  </Card>

  <Card title="Copilot" icon="robot" href="/live-chat/copilot">
    Use the Copilot to help you with your conversations.
  </Card>

  <Card title="Canned Responses" icon="file-text" href="/live-chat/canned-responses">
    Use canned responses to help you with your conversations.
  </Card>
</CardGroup>


# Teams
Source: https://docs.chatling.ai/live-chat/teams

Group agents into teams to organize the inbox, assign conversations, and target notifications.

Teams let you group the agents working on a chatbot or AI Agent into smaller units (Sales, Support, Billing, etc.) and use them throughout the live chat experience.

A conversation can have a team assigned **independently** of the agent assigned to it. The agent is the individual responsible; the team adds organizational context (useful for routing, filtering, and notifications).

## Creating a team

1. Open your chatbot or AI Agent.
2. Navigate to **Settings > Teams**.
3. Click **New team** and fill in:
   * **Name** — required, must be unique within the chatbot.
   * **Description** — optional context for the team.
   * **Color** — picked from a fixed palette; used as a visual badge in the inbox.
   * **Members** — multi-select of project members who have conversation access.
4. Click **Create team**.

## Assigning a conversation to a team

In the conversations inbox, open any conversation. In the right-hand sidebar you'll see a **Team** field. Pick a team from the dropdown to assign it to.

## Filtering by team

To filter conversations by team, open the filter drawer in the conversations inbox and select the team(s) you want to filter by.

## Team-scoped notifications

In **Settings > Notifications > Personal notifications**, you can enable to receive notifications when a conversation is assigned to a team you are a member of.


# Got other questions?
Source: https://docs.chatling.ai/missing-topics



If there are any topics you'd like to see covered in the documentation, please let us know! We're always looking to improve our documentation and make it as helpful as possible for our users.

Please reach out to us at [support@chatling.ai](mailto:support@chatling.ai) with your suggestions and any questions you have.


# Invite Team Members
Source: https://docs.chatling.ai/team-members/invite

Learn about the different roles and permissions that can be assigned to team members in a project.

You can invite team members to your project if you are an Owner or Admin. Here's how:

1. From the Project menu, go to **Members**.

<img alt="Go to Members" />

2. Click the **Invite** button.

<img alt="Click Invite button" />

3. Enter the email address of the member you want to invite and select one or more roles to assign to them.

<img alt="Enter member email and select roles" />

4. Click **Send invite**.

The user will receive an email invitation to join the project. Once they accept the invitation, they will be added to the project with the assigned roles.


# Overview
Source: https://docs.chatling.ai/team-members/overview

A guide on how to manage team members in your project.

As you build chatbots, you may need to collaborate with other team members to create, manage, and maintain them. Chatling allows you to invite team members and collaborate with them on your projects.

Team members can be added to each project and assigned different roles and permissions based on their responsibilities. This allows you to control what they can access and modify within the project.

Every project has an Owner who has full access and cannot be removed from the project.

As an Owner or Admin of a project, you can invite members and manage their roles and permissions. You can assign multiple roles to a team member, and each role has different permissions.


# Remove Team Members
Source: https://docs.chatling.ai/team-members/remove

Learn how to remove team members from your project.

To remove team members from your project:

1. From the Project menu, go to **Members**.

<img alt="Go to Members" />

2. Find the member you want to remove and click the ellipsis icon next to them.

<img alt="Open team member action menu" />

3. Click **Remove member**.

The member will be removed from the project immediately and will no longer have access to it.


# Restrict Access to Specific AI Agents
Source: https://docs.chatling.ai/team-members/restrict-access

Learn how to limit a team member's access to specific AI agents within a project.

By default, team members can access every AI agent in a project. If you need to limit a member to only certain agents, for example, to keep client work separated or to scope a support agent to a specific product, you can restrict their access when inviting them or at any time afterwards.

## How to restrict a member's access

### When inviting a new member

1. From the Project menu, go to **Settings** > **Members** and click **Invite**.
2. Enter the member's email address and select their role(s).
3. In the **Restrict access** section, click the search field and select one or more agents from the dropdown. You can type to filter by name.

<img alt="Agent access restriction" />

4. Click **Send invite**.

The member will only be able to see and interact with the agents you selected once they accept the invite.

### For an existing member

1. From the **Members** page, click the three-dot menu next to a member and choose **Edit role**.
2. In the **Restrict access** section, click the search field and select one or more agents from the dropdown. You can type to filter by name.
3. Click **Update**.

## Removing a restriction

To give a member access to all agents again, go to the member's role editor and remove all AI agents from the **Restrict access** field (leaving it empty). Click **Update** - the member will immediately regain full project access.

## What happens when access is restricted

When you save a restriction (or narrow an existing one), the following cleanup is applied automatically:

* Member is immediately restricted from accessing any agents outside their allowed set.
* The member is unassigned from any open conversations that belong to agents they can no longer access.
* The member is removed from notifications for agents outside their allowed set.
* Any pending scheduled notification emails for restricted agents are cancelled.

## Viewing a member's current restriction

On the **Members** page, restricted members are shown with a badge listing the agents they have access to. Members with full access show no badge.


# Roles & Permissions
Source: https://docs.chatling.ai/team-members/roles

Learn how to invite team members to your project and assign them different roles.

Members can be assigned one or more roles, each having different permissions.

Here are the available roles and their permissions:

1. **Admin**: Full access to all settings and features, including inviting members, creating chatbots and API keys, and managing billing.

<Accordion title="Permissions">
  * Create, update, and delete projects
  * Create, view, test, and delete chatbots
  * View analytics
  * View and update chatbot settings
  * View, update, and publish chatbots in the Builder
  * View, update, and delete conversations
  * View, update, export, and delete leads
  * View and update appearance settings
  * View and update knowledge base
  * View, create, update, and delete members
  * Share chatbots
  * View, create, and delete API keys
  * View and update billing settings
  * View usage
  * View invoices
  * View, download, and delete exports
</Accordion>

2. **Editor**: Can access and modify the builder, knowledge base, and widget appearance. Can also create chatbots and view usage.

<Accordion title="Permissions">
  * Create, view, and test chatbots
  * View and update chatbot settings
  * View, update, and publish chatbots in the Builder
  * View and update appearance settings
  * View and update knowledge base
  * Share chatbots
  * View billing
  * View usage
</Accordion>

3. **Analyst**: Can access chatbot analytics, conversations, and leads.

<Accordion title="Permissions">
  * View chatbots
  * View analytics
  * View, update, and delete conversations
  * View, update, export, and delete leads
  * View, download, and delete exports
  * View billing
  * View usage
</Accordion>

4. **Agent**: Can access and reply to conversations.

<Accordion title="Permissions">
  * View chatbots & agents
  * View, update, export, and delete conversations
  * View analytics
</Accordion>

5. **Billing**: Can update account billing and view usage.

<Accordion title="Permissions">
  * View and update billing settings
  * View usage
  * View invoices
</Accordion>

6. **Viewer**: Can view the builder and test chatbots, but doesn't have the ability to modify.

<Accordion title="Permissions">
  * View and test chatbots
  * View chatbot flow in the Builder
</Accordion>


# Add disclaimer, privacy notice, or custom text to footer
Source: https://docs.chatling.ai/web-widget/add-footer-text

Learn how to display custom text in the chatbot's footer.

<img alt="Custom footer text" />

Often times, you may want to display a text in the chatbot's footer, such as a disclaimer, privacy notice, or any other text. Here's how you can do that.

1. Open the `Deploy` page.

<img alt="Open Deploy page" />

2. Under the `Website Widget` option, click the settings icon to open the widget settings.

<img alt="Website widget settings button" />

3. Click on `Texts` from the sidebar.

<img alt="Open texts settings" />

4. Under the `Footer` section, you can enter the text you want to display.

<img alt="Add footer text" />

5. Click `Save` to apply the changes.


# Configure and customize your web widget
Source: https://docs.chatling.ai/web-widget/customize

A guide on how to configure and customize the appearance of your website widget.

![Widget appearance customization](https://chatling-assets.b-cdn.net/web-widget-editor.jpg)

You can customize the appearance of your website chat widget to match your brand. Many aspects of the widget, such as the colors, icons, and other design elements can be customized to create a widget that fits seamlessly into your website.

## How to customize the widget

1. Go to your chatbot or AI agent's dashboard.
2. Click the `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Under the `Website Widget` option, click the settings icon to open the widget settings.

<img alt="Website widget settings button" />

# Customization options

Here are some of the available customization options:

* **Colors**: Change the primary, secondary, and chat icon colors.
* **Chat Width**: Set the width of the chat window.
* **Position**: Choose the position where the widget should appear on your website, such as bottom right or bottom left.
* **Bot Icon**: Upload a custom image for the icon that appears next to the bot's messages.
* **Chat Icon**: Upload a custom image for the chat icon that users click to open the chatbot.
* **Header Title**: The title that appears at the top of the chat window, such as "Support Chat" or "Virtual Assistant".
* **Interface Language**: The language of the chatbot's interface. Note that this doesn't affect the language used by the AI.
* **Ask user to rate AI response**: Enabling this will display a thumbs up/down icon after the AI response, allowing users to rate it. This feedback can be used to improve the AI's performance.
* **Hide "Powered by Chatling" text**: At the bottom of the chatbot, there's a "Powered by Chatling" text. You can hide it by enabling this option.
* **Hovering Message**: You can display attention-grabbing messages above the chat icon to encourage users to start a conversation.
* **Show Sources for AI Response**: Enable this option to show the sources of the AI responses when it answers from the Knowledge Base. This helps users understand where the information is coming from.
* **Auto-Open Chat**: Automatically open the chat window when the page loads.

Once you've made the changes, click the `Save` button to apply them to your chatbot.


# Display AI sources
Source: https://docs.chatling.ai/web-widget/display-sources

Learn how to enable sources for AI responses.

1. Open the widget settings. To learn how to access it, see [this guide](/web-widget/customize#how-to-customize-the-widget).

2. Go to `Configure`.

<img alt="Configure menu" />

3. Enable the `Show Sources for AI Response` option. You can customize it by selecting the number and type of sources to display.

<img alt="Enable Show Sources for AI Response" />

Here's how it appears in the chatbot:

<img alt="AI response sources" />


# Download transcripts
Source: https://docs.chatling.ai/web-widget/download-chat-transcripts

A guide to enabling chat transcript downloads for end-users.

If you'd like your chatbot users to have the option to download chat transcripts, you can turn on this feature in the chatbot's appearance settings.

## How to allow end-users to download chat transcripts

1. Open your chatbot's dashboard.
2. Go to the [widget settings](/web-widget/customize).
3. Click `Configure` from the sidebar.

<img alt="Open apperance configuration settings" />

4. Enable `Allow users to download chat transcripts`.

<img alt="Enable chat transcript download" />

5. Click `Save`.


# File attachments
Source: https://docs.chatling.ai/web-widget/file-attachments

Allow users and agents to share files in live chat.

You can let end-users send files (images, documents, audio, video) in the
chat widget, and your agents can do the same when replying from the
conversations dashboard. This is useful for support flows that involve
screenshots, receipts, ID checks, voice messages, or any other media.

<Note>
  File attachments are only available during **live chat**. They are not
  available while the AI is handling the conversation.
</Note>

## How to enable file attachments

1. Open your chatbot's dashboard.
2. Go to the [widget settings](/web-widget/customize). To learn how to access it, see [this guide](/web-widget/customize).
3. Click `Configure` from the sidebar.

<img alt="Open appearance configuration settings" />

4. Enable `File attachments`.
5. Choose which file types to allow.
6. Click `Save`.

## Allowed file types

Once attachments are enabled, you can pick which categories of files end-users
are allowed to send:

* **Images** — JPEG, PNG, WebP, GIF, AVIF.
* **Documents** — PDF, Word, Excel, PowerPoint, plain text and CSV.
* **Audio** — MP3, M4A, AAC, WAV, OGG, WebM.
* **Video** — MP4, MOV, WebM, OGG.

Disabling a category hides those file types from the file picker on the
widget. Files that don't match an enabled category are rejected before
they're uploaded.

## Limits

| Limit                       | Value |
| --------------------------- | ----- |
| Max attachments per message | 3     |
| Max image size              | 2 MB  |
| Max document size           | 10 MB |
| Max audio size              | 10 MB |
| Max video size              | 10 MB |

If a user tries to attach more than 3 files in a single message, the
extra files are blocked with an inline error and not uploaded. Files
above the per-type size limit are also rejected up front.

## How users send attachments

When attachments are enabled, end-users see a paperclip icon in the
message input. They can also drag-and-drop files directly onto the chat
window.

Each attached file appears as a chip above the input with a preview (for
images) or filename and size (for documents/audio/video). The user can
optionally type a message to send along with the files, then click send.

Each attachment is delivered as its own message bubble in the
conversation, similar to how WhatsApp or Crisp handles attachments.

## How agents send attachments

From the **Conversations** page in your dashboard, agents can attach files
the same way: paperclip icon in the composer, or drag-and-drop onto the
conversation thread. The same per-message and per-type limits apply.

Attachments sent by agents appear as separate message bubbles in the
end-user's chat.

<Note>
  Agents can also attach files when replying to **WhatsApp** and
  **Instagram** conversations, but the supported file types are restricted
  by Meta's APIs. Instagram only accepts images, audio, and video (no
  documents). WhatsApp accepts all four categories but only specific file
  formats per category. The file picker automatically narrows to what each
  channel supports.
</Note>


# Geo-blocking
Source: https://docs.chatling.ai/web-widget/geoblocking

Learn how to block visitors from specific countries from accessing your chatbot.

If you're receiving a lot of spam from visitors of certain countries or don't want to make your chatbot available in certain countries, you can block those countries using the Geo-blocking feature.

By blocking countries, the widget will be disabled for visitors from those countries.

## How to block countries

1. Open your chatbot's dashboard.
2. Go to Settings.

<img alt="Open chatbot settings" />

3. Click the `Security` tab.
4. Under the `Geo-blocking` section, type and choose the country you want to block.
5. Click `Save`.


# Bubble
Source: https://docs.chatling.ai/web-widget/installation/bubble

Learn how to add Chatling to your Bubble website

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. Go to your Bubble account and open the app/website where you want to add the widget.

<img alt="Bubble dashboard" />

8. On the side, click the gear icon to open Settings.

<img alt="Open Bubble app settings" />

9. Go to `SEO / metatags`.

<img alt="Bubble SEO / metatags" />

10. Under the `SEO settings` section, paste the widget code in the header or body textbox.

<img alt="Add chatbot code to Bubble header or body" />

11. The settings will be saved automatically. Click the Preview icon to confirm that the widget has been added.

* Note that this method only works on paid plans. If you're on a free account, Bubble doesn't load the widget.

<img alt="Bubble chatbot" />


# Custom Website
Source: https://docs.chatling.ai/web-widget/installation/custom-website

Learn how to add Chatling to your website

You can easily add Chatling to your website by pasting the widget code to your website's header or body section.

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. Paste the code into the `head` or `body` section of your website's HTML.

* If you selected the `Inline` mode, you must paste the code where you want the chatbot to appear on your website.


# Google Tag Manager
Source: https://docs.chatling.ai/web-widget/installation/google-tag-manager

Learn how to add Chatling to your website using Google Tag Manager

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. Go to Google Tag Manager and open your website's container.
8. Click on `Add a new tag`.

<img alt="Add new tag" />

9. Enter a name for the tag, such as `Chatling`.

<img alt="Rename tag" />

10. Click on `Tag Configuration`.

<img alt="Open tag configuration" />

11. Select `Custom HTML`.

<img alt="Select custom HTML" />

12. Paste the widget code into the `HTML` field.

<img alt="Paste code in HTML tag" />

13. Click on `Triggering`.

<img alt="Open triggering" />

14. Select `All Pages`.

<img alt="Trigger all pages" />

15. Click `Save`.

<img alt="Save tag" />


# Overview
Source: https://docs.chatling.ai/web-widget/installation/overview

Learn how to add Chatling to your website.

Chatling can be added to any website, whether it's a custom website or a website that's built using a CMS like WordPress, Shopify, or Wix.

Simply copy the widget code from your chatbot's dashboard and add it to your website's header or body section. This will embed the chatbot on your website, allowing visitors to interact with it.

Below are guides on adding Chatling to your custom websites and CMS platforms.

<CardGroup>
  <Card title="Custom Website" icon="globe" href="/web-widget/installation/custom-website" />

  <Card title="WordPress" icon="wordpress" href="/web-widget/installation/wordpress" />

  <Card title="Google Tag Manager" icon="google" href="/web-widget/installation/google-tag-manager" />

  <Card title="Shopify" icon="shopify" href="/web-widget/installation/shopify" />

  <Card title="Wix" icon="wix" href="/web-widget/installation/wix" />

  <Card title="Squarespace" icon="squarespace" href="/web-widget/installation/squarespace" />

  <Card title="Webflow" icon="webflow" href="/web-widget/installation/webflow" />

  <Card title="Bubble" icon="b" href="/web-widget/installation/bubble" />

  <Card title="PrestaShop" icon="p" href="/web-widget/installation/prestashop" />
</CardGroup>


# PrestaShop
Source: https://docs.chatling.ai/web-widget/installation/prestashop

Learn how to add Chatling to your PrestaShop website

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy chatbot widget code" />

7. Download our [PrestaShop module](https://static.chatling.ai/files/chatling-prestashop-v1-0.zip).

8. Extract the zip file and open the `chatling` folder.

<img alt="Extract chatling prestashop module" />

9. Inside the folder, open the `chatling.php` file using a text editor of your choice, such as Notepad on Windows or TextEdit on macOS.

<img alt="Open chatling.php file" />

10. Go to the bottom of the file and find the line that says `Paste code snippet here`.

<img alt="Open chatling.php file" />

Replace it with the code snippet you copied in step #2, as shown below.

<img alt="Replace code snippet" />

11. Save the file and close it.

12. Zip the `chatling` folder. Do not rename the folder to anything else otherwise the module won't work.

<img alt="Zip chatling folder" />

13. Go to your PrestaShop admin panel. From the sidebar menu, click `Module` > `Module Manager`.

<img alt="PrestaShop module manager" />

14. Click the `Upload a module` button in the top right. Browse and select the module's zip file.

<img alt="Upload chatling prestashop module" />

15. Once the module is uploaded, the widget will be live on your website.

<img alt="PrestaShop chatbot live" />


# Shopify
Source: https://docs.chatling.ai/web-widget/installation/shopify

Learn how to add Chatling to your Shopify store

## Method 1: Using theme.liquid

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. Go to your Shopify dashboard and click on `Online Store` from the sidebar.

<img />

8. Edit your theme by clicking the ellipsis icon next to your current theme and choosing `Edit code`.

<img />

9. Find and open the `theme.liquid` file From the sidebar where the list of files is displayed.

<img />

10. Paste the widget code in the `<head>` section. You can paste it anywhere between the opening `<head>` tag and the closing `</head>` tag.

<img />

11. Click the Save button.

The chatbot will be live on your website and should appear across all your store's pages.

<img />

## Method 2: Using Customization

1. Follow steps 1-6 from Method 1 to copy the widget code.

2. From your Shopify dashboard, click on `Online Store` and go to `Themes`.

<img />

3. Click on the `Customize` button next to your current theme.

<img />

4. Under the `Header` section, choose `Add section`. Search for `Custom liquid` and add it.

<img />

5. Open the `Custom liquid` editor and paste your widget code into the `Liquid code` field.

<img />

6. Set the `Top padding` and `Bottom padding` to `0` so the section doesn't create a blank space in your site's header.

<img />

7. Click the `Save` button.

The widget will be live on your website and should appear across all your store's pages.

<img />


# Squarespace
Source: https://docs.chatling.ai/web-widget/installation/squarespace

Learn how to add Chatling to your Squarespace website

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. Sign in to your Squarespace account and open the website where you want to add the widget.

<img />

8. From the sidebar menu, select `Website`.

<img />

9. Scroll to the bottom of the sidebar menu and choose `Website Tools`.

<img />

10. Open `Code Injection`.

* If you're on an older version of Squarespace, such as v7.0, code injection is located in `Settings` > `Developer Tools` > `Code Injection`.

<img />

11. Paste the widget code in the `Header` section, and click `Save`.

<img />

12. The widget is now live on your website, and visitors can interact with it.

<img />


# Webflow
Source: https://docs.chatling.ai/web-widget/installation/webflow

Learn how to add Chatling to your Webflow website

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. Go to your Webflow dashboard and open the website where you want to add the widget.

<img />

8. Click the webflow icon in the top left and select `Site settings`.

<img />

9. Click on `Custom code` from the sidebar.

<img />

10. Paste the widget code in the `Head code` textbox and click `Save`.

<img />

11. Publish the website. The widget will now be appear on your Webflow website.

<img />


# Wix
Source: https://docs.chatling.ai/web-widget/installation/wix

Learn how to add Chatling to your Wix website

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. Go to your Wix dashboard and click `Settings` from the sidebar menu.

<img />

8. Scroll down to the Advanced section and click `Custom code`.

<img />

9. Under the Head section, click `Add Code`.

<img />

10. Paste the widget code into the text box that appears and click `Apply`.

<img />

11. The widget is now live on your Wix website and visitors can interact with it.

<img />


# WordPress
Source: https://docs.chatling.ai/web-widget/installation/wordpress

Learn how to add Chatling to your WordPress website

## Method 1: Install using a plugin

1. Go to your dashboard.
2. Click `Deploy` button in the sidebar menu.

<img alt="Open Deploy page" />

3. Click the `Manage` button under the `Website Widget` option.

<img alt="Manage website widget" />

4. Design the appearance of the widget by clicking the `Open widget settings` button.

<img alt="Open website widget designer" />

5. Select the display mode for your chatbot, such as "Floating Chat", "Inline", or "Fullscreen".

<img alt="Configure website widget display type" />

6. Copy the widget code.

<img alt="Copy widget code" />

7. In your WordPress dashboard, go to `Plugins` > `Add new plugin`.

<img alt="Add new plugin" />

8. Search for the `Insert Headers And Footers` plugin and install the one by WPBrigade.

<img alt="Insert Headers And Footers plugin" />

9. Once installed, activate the plugin.

10. Go to `Settings` > `WP Headers and Footers` from the sidebar.

<img alt="Open WP Headers and Footers settings" />

11. Paste the chatbot widget code in the header section.

<img alt="Add chatbot widget code in the header section" />

12. Click `Save Changes`.

## Method 2: Install using the theme editor

1. Follow steps 1-6 from Method 1 to copy the widget code.

2. Open your WordPress dashboard.

3. From the sidebar menu, select `Appearance` > `Theme File Editor`.

<img alt="Open theme file editor" />

4. Under the `Theme Files` section (right side of the screen), search and open the `header.php` file.

<img alt="Edit theme header" />

5. Paste the widget code before the closing `</head>` tag.

<img alt="Embed code in header" />

6. Click `Update File` to save.


# Set the language of your chatbot widget
Source: https://docs.chatling.ai/web-widget/language

Set the language of your chatbot widget.

The chatbot is available in over 45 languages. You can customize the language of your chatbot to match your audience's preferences. This affects all text elements in the chatbot widget, including placeholders, buttons, and system messages.

By default, the language is set to `Auto`. This means that the chatbot will automatically detect the user's language based on their browser settings.

## Set the language

1. Open the [widget settings](/web-widget/customize). To learn how to access it, see [this guide](/web-widget/customize).

2) Click `Interface` from the sidebar.
3) Use the `Widget language` dropdown to select the language of your chatbot.

Note: If you set the language to `Auto`, the chatbot will automatically detect the user's language based on their browser settings.

<img alt="Set chatbot language" />

4. Click `Save`.


# Operating hours
Source: https://docs.chatling.ai/web-widget/operating-hours

Schedule the chatbot to be visible at certain times.

You can set the operating hours for your chatbot to define when it should be available to users. This is useful if you want to limit the chatbot's availability to certain times of the day or week, e.g during business hours or off-hours.

When outside of the operating hours, your chatbot will be automatically hidden, ensuring it's only live when you want it to be.

## Set operating hours

1. From your chatbot's dashboard, go to the **Settings** page.

<img alt="Open chatbot settings" />

2. Click the `Visibility` tab.

<img alt="Open chatbot visibility settings" />

3. Under the `Operating hours` section, click the `Set operating hours` button.

<img alt="Set chatbot operating hours" />

4. Select the days and times when the chatbot should be visible. **Note that the timezone is UTC.**

To keep the chatbot visible throughout the day, leave the start and end times empty.

<img alt="Define chatbot operating hours" />

5. Click the `Add` button to add the schedule.
6. Click the `Save` button to save the changes.

Once you define the operating hours, the chatbot will be visible during the specified times and hidden outside of these hours.

## Edit existing operating hours

To edit the operating hours, you have to delete one or more schedules that you want to edit and then add the new schedules.


# Remove "Powered by Chatling" branding
Source: https://docs.chatling.ai/web-widget/remove-powered-by-chatling-branding

Learn how to remove the Chatling branding from your chatbot widget.

## Which plans can remove the branding?

The branding can be removed if you're on the **Ultimate** plan or by purchasing the [Remove "Powered by Chatling" branding add-on](https://chatling.com/pricing).

## How to remove the branding

1. Open the [widget settings](/web-widget/customize). To learn how to access it, see [this guide](/web-widget/customize#how-to-customize-the-widget).

2. Go to `Configure`.

<img alt="Configure menu" />

3. Enable the `Hide "Powered by Chatling"` option.

4. Click the `Save` button to apply the changes.


# Satisfaction survey
Source: https://docs.chatling.ai/web-widget/satisfaction-survey

A guide on how to set up and display satisfaction surveys.

You can collect feedback from users at the end of their chat by displaying a satisfaction survey. This can help you gain insights into user satisfaction, identify areas for improvement, and track the overall effectiveness of your chatbot over time.

## How to set up a satisfaction survey

1. From the chatbot dashboard, go to `Settings`.

<img alt="Open chatbot settings" />

2. Click the `Satisfaction Survey` tab.

<img alt="Click satisfaction survey tab in chatbot settings" />

3. Toggle on the `Show survey` option.

<img alt="Enable chatbot satisfaction survey" />

4. Customize the survey by selecting the rating type, questions to display, and more.

<img alt="Customize satisfaction survey" />

5. Click `Save` to apply the changes.

<img alt="Save satisfaction survey settings" />

## View survey responses

You can view survey responses from the `Conversations` page of your chatbot dashboard. If a conversation has a survey response, the result will appear within the conversation thread as well as on the `Details` section in the sidebar.

<img alt="View satisfaction survey responses" />


# Visibility
Source: https://docs.chatling.ai/web-widget/visibility

A guide on configuring your widget's visibility.

Control who can see your Web Widget by setting its visibility to **Public** or **Private**. A public widget is visible to all visitors on any website where it's embedded. A private widget is hidden from all embedded websites and its Sharing feature is disabled.

## How to set the visibility

1. From your dashboard, go to the [widget settings](/web-widget/customize).
2. Go to `Visibility`.
3. Set the status to `Public` or `Private`.
4. Click `Save` to apply the changes.


# Whitelist domains
Source: https://docs.chatling.ai/web-widget/whitelist-domains

Learn how to whitelist domains for your chatbot to prevent it from being added to unauthorized websites.

If you want to prevent your widget from being added to unauthorized websites, you can whitelist domains.

By adding whitelisted domains, the widget will only appear on websites that match the whitelisted domains.

## How to whitelist domains

1. Open your chatbot's dashboard.
2. Go to Settings.

<img alt="Open chatbot settings" />

3. Click the `Security` tab.
4. Under the `Whitelist domains` section, type in a domain you want to whitelist and click the `+ Add` button. You can add multiple domains.
5. Click `Save`.


# Widget SDK
Source: https://docs.chatling.ai/web-widget/widget-sdk



## Configuration

You can configure the widget during launch by setting the `window.chtlConfig` object, as shown below.

```javascript theme={null}
window.chtlConfig = {
    // Configuration options
};
```

Below are the available properties you can set.

### `chatIconVisible`

Whether to display the chat icon (open and close buttons).

* Possible values: `true`, `false`
* Default: `true`

```javascript theme={null}
window.chtlConfig = {
    chatIconVisible: true,
    // ... other config options
};
```

### `displayType`

The type of widget to display.

* Possible values: `floating`, `fullscreen`, `page_inline`
* Default: `floating`

```javascript theme={null}
window.chtlConfig = {
    displayType: 'floating',
    // ... other config options
};
```

### `language`

The language of the widget in ISO 639-1 format. This will override the language set in your chatbot's appearance settings.

* Possible values: `en`, `ar`, `az`, `bg`, `bn`, `bs`, `ca`, `cs`, `da`, `de`, `el`, `en`, `es`, `et`, `fa`, `fi`, `fr`, `he`, `hi`, `hr`, `hu`, `hy`, `id`, `it`, `ja`, `ko`, `lt`, `lv`, `mn`, `ms`, `nl`, `no`, `pl`, `pt`, `pt-br`, `ro`, `ru`, `sk`, `sl`, `sq`, `sr`, `sv`, `th`, `tr`, `uk`, `ur`, `vi`, `zh-cn`, `zh-tw`

```javascript theme={null}
window.chtlConfig = {
    language: 'en',
    // ... other config options
};
```

### `variables`

An object containing variable names and their values to pass to the chatbot during launch. The variables must have been created in your chatbot or AI agent and the names must match exactly.

```javascript theme={null}
window.chtlConfig = {
    variables: {
        "contact_name": "John Doe",
        "contact_email": "john.doe@example.com",
        "age": 25
    },
    // ... other config options
};
```

## Methods

Below are the SDK methods you can call to interact with the widget.

<Note>You must wait for the widget script to load before calling these methods.</Note>

### `open()`

Opens the chatbot, similar to when a user clicks the chat icon.

```javascript theme={null}
window.Chatling.open();
```

### `minimize()`

Minimizes the chatbot, similar to when a user clicks the minimize button in the widget.

```javascript theme={null}
window.Chatling.minimize();
```

### `hideChatIcon()`

Hides the chat icon.

```javascript theme={null}
window.Chatling.hideChatIcon();
```

### `showChatIcon()`

Shows the chat icon.

```javascript theme={null}
window.Chatling.showChatIcon();
```

### `setVariables()`

You can pass custom values to the chatbot at any point after it's loaded.

The method takes an object containing the variable names and values. You must make sure that the variables [have been created](/chatbot/builder/variables/how-to-create-variables) in the builder and that the names match exactly.

<Note>To pass custom data during launch, read [this guide](/web-widget/pass-custom-data#pass-custom-data-during-launch).</Note>

```javascript theme={null}
window.Chatling.setVariables({
    "contact_name": "Rick Astley",
    "contact_email": "rick.astley@example.com",
    "age": 30
}, function(success, errorMessage) {
    if (!success) {
        // handle error
    }
});
```

### `destroy()`

Permanently removes the chatbot from the page.

```javascript theme={null}
window.Chatling.destroy();
```


# Change language
Source: https://docs.chatling.ai/whatsapp/change-language

A guide to change the language of system and error messages in your WhatsApp chatbot.

You can set the language that your chatbot or AI agent will use for system messages, errors, and various other messages.

The steps differ for AI Agents and Chatbots. We've created separate guides for each below.

## How to change the WhatsApp language for a Chatbot

1. From your chatbot's dashboard, click the `Settings` button under the Chatbot menu.

<img />

2. Under the `General` tab, you will see the `Language` setting. Select the language you want to use.

<img />

3. Click `Save` to save the changes.

## How to change the WhatsApp language for an AI Agent

1. From your agent's dashboard, click the `Deploy` button in the sidebar.

<img alt="Deploy" />

2. Click the settings icon for `WhatsApp`.

<img />

3. You will see the `Language` settings. Select the language you want to use.

<img />

4. Click `Save` to save the changes.


# Create a WhatsApp AI Agent
Source: https://docs.chatling.ai/whatsapp/create-ai-agent

Learn how to create a WhatsApp AI agent in Chatling.

The steps below will guide you through the process of creating and connecting your WhatsApp to your **AI Agent** in Chatling.

1. Login to your [Chatling account](https://app.chatling.ai).
2. From the "My agents" page, click the `Create` button.

<img />

3. Choose `AI Agent` as the type.

<Note>To learn the difference between AI Agents and Chatbots, refer to [this page](/introduction#difference-between-ai-agents-and-ai-chatbots).</Note>

<img />

4. Enter a name for your Agent and click the `Create agent` button.

<img />

5. From your Agent's dashboard, click the `Deploy` button in the sidebar.

<img alt="Deploy" />

6. Click the `Setup` button under the `WhatsApp` option.

<img alt="Setup WhatsApp for AI Agent" />

7. A popup will appear to guide you through the process of connecting your WhatsApp Business account to Chatling.

<Warning>
  Before continuing, note that the phone number you connect must not be in use by a WhatsApp account. If it's in use, you must delete the account from WhatsApp before continuing.

  Here's how to delete a WhatsApp account:

  1. Open the WhatsApp app.
  2. Go to `Settings` > `Account` > `Delete my account`.
  3. Type in your phone number for confirmation and tap on `Delete my account`.

  Once deleted, the phone number can be used to create a WhatsApp Business account.
</Warning>

8. Click the `Login with Facebook` button to continue.

<img alt="Click Login with Facebook button" />

9. The Facebook authentication window will open. Sign in to your Facebook account and click the `Continue` button.

<img />

10. Select `Get started`.

<img />

11. Choose or create a new business profile.

<img />

12. Choose or create a new WhatsApp Business account and profile.

<img />

13. If you chose to create a new profile:

* Enter the required information for the profile.
* When prompted to add a phone number, select `Add a new phone number`. Do not select `Get a free WhatsApp number` as it will not work with Chatling.

<img />

14. Facebook will display the permissions required by Chatling. Review and click the `Continue` or `Confirm` button.

<img />

15. Facebook begins verifying the information you provided. Once it's completed successfully, you should see a message similar to below. Click the `Finish` button.

<img />

16. Go back to Chatling and a message will be displayed that your authentication is being processed. If successful, you should see a message similar to below.

<img />

17. Next, you must enter a 6-digit code for two-factor authentication so your phone number can be registered with WhatsApp.

    If the number already has 2FA enabled, enter the same code you had set up.

<img />

18. Once the phone number is registered successfully, you're all set and your WhatsApp Business account is connected to Chatling. Click the `Close` button to finish the setup process.

<Warning>WhatsApp provides 1,000 free conversations per month. If you reach this limit, you must add a payment method in your Facebook Business Manager to continue sending and receiving messages.</Warning>


# Create a WhatsApp AI Chatbot
Source: https://docs.chatling.ai/whatsapp/create-ai-chatbot

Learn how to create a WhatsApp AI chatbot in Chatling.

The steps below will guide you through the process of creating and connecting your WhatsApp to your **AI Chatbot** in Chatling.

1. Login to your [Chatling account](https://app.chatling.ai).
2. From the "My agents" page, click the `Create` button.

<img />

3. Choose `AI Chatbot` as the type.

<Note>To learn the difference between AI Agents and Chatbots, refer to [this page](/introduction#difference-between-ai-agents-and-ai-chatbots).</Note>

<img />

4. Select `WhatsApp` as the platform.

<img />

5. You can choose to create a chatbot from scratch or use a template. Templates help you get started quickly with pre-built flows.

6. Enter a name for your chatbot and click the `Create chatbot` button.

<img />

7. A setup wizard will open to guide you through connecting your WhatsApp Business account.

<Warning>
  Before continuing, note that the phone number you connect must not be in use by a WhatsApp account. If it's in use, you must delete the account from WhatsApp before continuing.

  Here's how to delete a WhatsApp account:

  1. Open the WhatsApp app.
  2. Go to `Settings` > `Account` > `Delete my account`.
  3. Type in your phone number for confirmation and tap on `Delete my account`.

  Once deleted, the phone number can be used to create a WhatsApp Business account.
</Warning>

8. Click the `Login with Facebook` button to continue.

<img alt="Click Login with Facebook button" />

9. The Facebook authentication window will open. Sign in to your Facebook account and click the `Continue` button.

<img />

10. Select `Get started`.

<img />

11. Choose or create a new business profile.

<img />

12. Choose or create a new WhatsApp Business account and profile.

<img />

13. If you chose to create a new profile:

* Enter the required information for the profile.
* When prompted to add a phone number, select `Add a new phone number`. Do not select `Get a free WhatsApp number` as it will not work with Chatling.

<img />

14. Facebook will display the permissions required by Chatling. Review and click the `Continue` or `Confirm` button.

<img />

15. Facebook begins verifying the information you provided. Once it's completed successfully, you should see a message similar to below. Click the `Finish` button.

<img />

16. Go back to Chatling and a message will be displayed that your authentication is being processed. If successful, you should see a message similar to below.

<img />

17. Next, you must enter a 6-digit code for two-factor authentication so your phone number can be registered with WhatsApp.

    If the number already has 2FA enabled, enter the same code you had set up.

<img />

18. Once the phone number is registered successfully, you're all set and your WhatsApp Business account is connected to Chatling. Click the `Open Dashboard` button to continue.

<Warning>WhatsApp provides 1,000 free conversations per month. If you reach this limit, you must add a payment method in your Facebook Business Manager to continue sending and receiving messages.</Warning>

<img />


# Customize profile
Source: https://docs.chatling.ai/whatsapp/customize-profile

Learn how to change your profile picture, name, bio, and more.

You can visit the [WhatsApp Manager](https://business.facebook.com/latest/whatsapp_manager) on Facebook to change your profile picture, display name, and business details such as description, address, email, and website.

## How to customize your WhatsApp Business profile

1. Go to the [WhatsApp Manager](https://business.facebook.com/latest/whatsapp_manager) on Facebook.
2. From the sidebar, click on the `Phone numbers` tab.

<img />

3. Find your phone number from the list and click on the settings icon next to it.

<img />

4. From here, you can update the profile information for your WhatsApp Business account.

<img />


# Disconnect WhatsApp account
Source: https://docs.chatling.ai/whatsapp/disconnect-account

Learn how to disconnect your WhatsApp account in Chatling.

The guide below will walk you through the process of disconnecting your WhatsApp account from your chatbot or AI agent in Chatling.

The steps differ for chatbots and AI agents. We've created separate guides for each below.

<Warning>Disconnecting your WhatsApp account will prevent Chatling from sending and receiving messages from WhatsApp. To restore this functionality, you must reconnect your WhatsApp account.</Warning>

## How to disconnect WhatsApp from your chatbot

1. From your chatbot's dashboard, click the `Settings` button under the Chatbot menu.

<img />

2. Go to the `WhatsApp` tab.

<img />

3. Click the `Disconnect` button.

<img />

## How to disconnect WhatsApp from your AI Agent

1. From your agent's dashboard, click the `Deploy` button in the sidebar.

<img alt="Deploy" />

2. Click the settings icon for `WhatsApp`.

<img />

3. Click the `Disconnect` button.

<img />


# Display name approval
Source: https://docs.chatling.ai/whatsapp/display-name-approval

Learn how to fix issues related to the display name approval for your WhatsApp account.

If you get an error message stating `WhatsApp provided number needs display name approval before messages can be sent`, it means you cannot use the WhatsApp bot until Facebook approves your display name.

This normally happens when you use the free WhatsApp number provided by Facebook when you first connect your WhatsApp account to Chatling.

To fix this issue, you must verify your business in Facebook before they approve your display name.

## How to verify your business in Facebook

1. Go to the [Security Center](https://business.facebook.com/latest/settings/security_center) in your Facebook Business Manager.
2. Under the `Business Verification` section, set the verification use case to `Setting up a WhatsApp Business account`.

<img />

3. Click the `Start verification` button.

<img />

4. Follow the on-screen instructions to verify your business.
5. Once you complete the process, your business will either be verified immediately or placed under review.
6. After your business is verified, Facebook will begin reviewing your display name. To view the status of the review:

* Go to [WhatsApp Manager](https://business.facebook.com/latest/whatsapp_manager/overview).
* Click `Phone numbers` in the left sidebar.
* You will see the status of the review under the display name as shown below.

<img />

7. Once the review is complete, you'll receive an email notification from Facebook and you can begin using your WhatsApp bot to send and receive messages.


# Mute contacts
Source: https://docs.chatling.ai/whatsapp/mute-contacts

Stop the AI agent or chatbot from replying to specific WhatsApp contacts while still allowing human agents to respond.

Muting a WhatsApp contact prevents your chatbot or AI agent from sending **any** automated reply to that number, including AI responses, error messages, and system messages. Incoming messages from muted contacts are still saved and shown in the Conversations dashboard so a human teammate can reply manually.

This is especially useful in the WhatsApp Coexistence setup, where sales reps have ongoing conversations with regular clients, colleagues, or suppliers on the same business number, and you don't want the AI interrupting those threads.

<Info>**Mute vs. Block** — Blocking drops incoming messages entirely (nothing is saved). Muting keeps the conversation visible to your team but silences the AI agent. Use mute when you still want to reply manually; use block when you want to ignore the contact completely.</Info>

## What happens when a contact is muted

* The bot/AI will **not** send any reply, including error or system messages.
* Incoming messages from the contact are still saved and visible in the Conversations page.
* Coexistence echoes (messages your team sends from the WhatsApp Business app) are still saved.
* Human agents can still reply to the contact from the Chatling dashboard.

## How to mute a contact manually (by phone number)

Use this when you want to mute a contact in advance.

1. From your chatbot or AI agent's WhatsApp settings, click the `+` icon next to the `Muted contacts` option.

<img alt="Mute contact manually" />

2. Select the country and enter the phone number.

<img alt="Enter phone number to mute contact" />

3. Optionally add a reason.
4. Click `Mute`.

## How to mute a contact from the Conversations page

This is the fastest way to mute someone you're already chatting with.

1. Open the conversation in the `Conversations` page.
2. Click the `More` (three-dot) menu at the top right of the conversation thread.
3. Click `Mute contact`.

## How to view and manage muted contacts

The `Muted contacts` section in your WhatsApp settings shows every muted number for the current chatbot or AI agent, along with:

* **Phone** — The number in international format
* **Contact** — The contact name (if known from previous chats)
* **Reason** — The note you added when muting
* **Muted by** — The teammate who muted the contact

Click `Unmute` next to any row to remove the mute. Unmuting also removes any auto-generated regional variants for that number.


# WhatsApp Integration
Source: https://docs.chatling.ai/whatsapp/overview

Learn how to connect integrate your WhatsApp account with Chatling.

The WhatsApp integration enables you to deploy AI assistance directly on WhatsApp, allowing you to automate conversations, handle inquiries, and engage with customers on one of the world's most popular messaging platforms.

The integration is available for both AI Agents and AI Chatbots. The steps differ for both and we have created separate guides for each, as listed below.

<Note>To learn the difference between AI Agents and Chatbots, refer to [this page](/introduction#difference-between-ai-agents-and-ai-chatbots).</Note>

<CardGroup>
  <Card title="Create AI Agent for WhatsApp" icon="plus" href="/whatsapp/create-ai-agent" />

  <Card title="Create AI Chatbot for WhatsApp" icon="plus" href="/whatsapp/create-ai-chatbot" />

  <Card title="Display name approval" icon="badge-check" href="/whatsapp/display-name-approval" />

  <Card title="Change language" icon="language" href="/whatsapp/change-language" />

  <Card title="Customize profile" icon="user" href="/whatsapp/customize-profile" />

  <Card title="Disconnect account" icon="plug-circle-xmark" href="/whatsapp/disconnect-account" />

  <Card title="Re-connect account" icon="repeat" href="/whatsapp/reconnect-account" />
</CardGroup>