# ChatBotKit Documentation Index

Comprehensive guides and tutorials for all levels of chatbot development.

- [Introduction](/docs/introduction.md) - Explore the key concepts of ChatBotKit, a state-of-the-art platform for developing conversational AI systems. Learn about backstories, models, stores, bots, datasets, skillsets, conversations, and integrations. Unleash the full potential of ChatBotKit to design intuitive and impactful chatbots.
- [Skillsets](/docs/skillsets.md) - Overview of how chatbot Skillsets and Skillset instructions work. Learn how to customize your chatbot's abilities and improve its performance.
- [Backstories](/docs/backstories.md) - Learn about the importance of backstories in chatbot development and how they contribute to creating engaging and personalized experiences for users. Discover how multilingual chatbots can benefit from customized backstories and how conversation preempting can set the tone for conversations.
- [Rerankers](/docs/rerankers.md) - Explore the capabilities of the reranking algorithm in ChatBotKit, designed to enhance the accuracy and relevance of AI responses by employing a sophisticated second-level sorting mechanism for retrieved records.
- [Stores](/docs/stores.md) - Learn about ChatBotKit's stores, an abstract storage class for efficient and organized storage and retrieval of data. Choose between Ada Sprout, Lingo Sprout, and Ada Loom depending on your dataset and retrieval needs.
- [Bots](/docs/bots.md) - Discover the essential guide to creating customized bots using ChatBotKit's conversational AI platform. Learn how to design, deploy, and integrate bots tailored for various use cases while ensuring privacy and moderation for safe interactions.
- [Datasets](/docs/datasets.md) - Overview of what datasets are and how they can be used in chatbot conversations. Learn how to add contextual information to your chatbot.
- [Conversations](/docs/conversations.md) - Overview of what conversations are and how they work. Learn how to manage conversations and build your own conversation flow using the ChatBotKit API.
- [Contacts](/docs/contacts.md) - Learn how to create and manage contacts in ChatBotKit, a powerful tool for streamlining communication and data management.
- [Files](/docs/files.md) - Upload and manage files in ChatBotKit to use them across bots, datasets, skillsets, and widgets.
- [Memories](/docs/memories.md) - Learn how to use the Memory System in ChatBotKit to enable AI agents to store, retrieve, and leverage contextual information for personalized conversations.
- [Ratings](/docs/ratings.md) - Collect and analyze user feedback to understand how well your chatbot is performing and identify areas for improvement
- [Spaces](/docs/spaces.md) - ChatBotKit Spaces are shared portal data stores where humans and AI agents can collaborate using portable, transferable project data.
- [Tasks](/docs/tasks.md) - Create automated actions for your contacts that your AI agents can perform on schedule or on-demand
- [Secrets](/docs/secrets.md) - Secrets provides a secure environment for storing sensitive information such as tokens, keys, and credentials used across the ChatBotKit services.
- [Blueprints](/docs/blueprints.md) - Blueprints are reusable AI solutions that group bots, datasets, skillsets, and integrations together. Use the visual Blueprint Designer to build, connect, and manage your AI agent systems.
- [Integrations](/docs/integrations.md) - ChatBotKit offers integrations with Widget, Slack, Discord, WhatsApp, Telegram, Google Chat, Microsoft Teams, Twilio, Messenger, Email, Sitemap, Notion, Trigger, MCP Server, Support, Extract, and Zapier. Deploy and manage chatbots across platforms for an optimized user experience.
- [Portals](/docs/portals.md) - Create focused AI experiences for different teams and audiences using dedicated portal websites with custom apps, access control, and branding
- [Usage](/docs/usage.md) - Learn how ChatBotKit tracks and measures your service usage through metrics like tokens, conversations, and messages. 
- [Analytics](/docs/analytics.md) - Overview of the analytics dashboard and how to interpret your ChatBotKit workspace performance metrics. Learn about contacts, conversations, messages, and user satisfaction tracking.
- [Models](/docs/models.md) - Explore ChatBotKit's diverse range of conversational AI models from multiple providers, with details on token costs and custom model settings.
- [Widget](/docs/widget.md) - Learn how to integrate ChatBotKit's widget onto your website to enhance user experience. Easily customize the widget to fit your needs with various options.
- [Slack](/docs/slack.md) - Learn how to integrate ChatBotKit with Slack and deploy chatbots on the platform. This guide provides step-by-step instructions, including how to interact with your ChatBotKit Slack bot, advanced setup details, troubleshooting tips, and more.
- [Discord](/docs/discord.md) - Learn how to easily integrate ChatBotKit with Discord and access a wide range of conversational AI functionalities directly within the popular messaging and collaboration platform for gamers and communities. Follow our step-by-step guide to get started.
- [WhatsApp](/docs/whatsapp.md) - Learn how to easily integrate your chatbot with WhatsApp using ChatBotKit. Our step-by-step guide will show you how to set up your integration and connect with your audience on WhatsApp.
- [Messenger](/docs/messenger.md) - Integrate ChatBotKit with your Facebook Messenger to deploy powerful conversational AI and engage effectively with your Messenger audience.
- [Telegram](/docs/telegram.md) - Integrate ChatBotKit with your Telegram bot to create powerful conversational AI chatbots. Engage effectively with your Telegram audience. Follow the steps to set up your bot on Telegram and integrate it with ChatBotKit.
- [Email](/docs/email.md) - ChatBotKit's Email Integration allows users to set up a dedicated email inbox for their AI chatbot, enhancing its capabilities to manage queries and support tickets.
- [Trigger](/docs/trigger.md) - Learn how to use ChatBotKit Trigger Integration to seamlessly send events and information to your bots, enabling powerful workflows and enhanced performance. 
- [Twilio](/docs/twilio.md) - Connect your ChatBotKit bot to Twilio for SMS messaging and phone-call voice agents
- [Google Chat](/docs/google-chat.md) - Connect your ChatBotKit bot to Google Chat spaces and direct messages
- [Microsoft Teams](/docs/microsoft-teams.md) - Connect your ChatBotKit bot to Microsoft Teams channels, group chats, and direct messages via the Azure Bot Framework
- [MCP Server](/docs/mcp-server.md) - Expose your ChatBotKit skillsets as MCP tools for AI applications like Claude Desktop, VSCode, and GitHub Copilot
- [Sitemap](/docs/sitemap.md) - Learn how to import a website's information into your dataset with ChatBotKit's Sitemap feature. Automatically summarise long pages using AI, and access important information easily from your chatbot.
- [Notion](/docs/notion.md) - Learn how to integrate ChatBotKit with Notion and deploy chatbots on the platform. This guide provides instructions set up and interact with your Notion bot.
- [Support](/docs/support.md) - Learn how to integrate your AI chatbot with support systems such as Zendesk, Intercom, and email groups using ChatBotKit. Automatically extract customer details and provide real-time assistance to customers.
- [Extract](/docs/extract.md) - Learn how to use the Data Extraction integration in ChatBotKit to extract contextually relevant information from conversations. This integration facilitates efficient data usage in customer support, transcriptions, and data analytics, empowering AI chatbots to autonomously interact with users and enrich conversation metadata.
- [Zapier](/docs/zapier.md) - The ChatBotKit Zapier integration, which allows you to automate processes and improve efficiency by connecting ChatBotKit with other applications. Learn about the key benefits, getting started, and available actions to streamline your workflows and enhance your interactions with customers.
- [Webhooks](/docs/webhooks.md) - Learn how to set up and use webhooks within ChatBotKit to automate workflows and integrate different services. This section covers step-by-step setup, event selection, and validating incoming webhook requests using the X-Hub-Signature header.
- [Primers](/docs/primers.md) - Overview of the ChatBotKit Primers. Learn how to create conversational AI chatbots using ChatBotKit API and SDKs.
- [API](/docs/api.md) - The ChatBotKit API is a powerful tool for developers looking to integrate conversational AI functionality into their applications. This documentation provides a comprehensive guide to understanding and utilizing the various endpoints and features offered by the API.
- [Node SDK](/docs/node-sdk.md) - ChatBotKit Node SDK allows developers to build conversational AI interfaces and chatbots. Read on to learn how to install and use the SDK, along with its authentication, pagination, and error handling features.
- [Go SDK](/docs/go-sdk.md) - ChatBotKit Go SDK allows developers to build conversational AI interfaces and chatbots using Go. Learn how to install and use the SDK, along with its authentication, streaming, and agent execution features.
- [Terraform Provider](/docs/terraform-provider.md) - ChatBotKit Terraform Provider allows you to manage your AI chatbot infrastructure as code. Learn how to install, configure, and use the provider to deploy bots, datasets, skillsets, and integrations.
- [Widget SDK](/docs/widget-sdk.md) - The Widget SDK allows developers to easily initialize and configure ChatBotKit AI Widgets. This guide provides detailed instructions for embedding, utilizing the global object, and managing widget properties and events.
- [Tokens](/docs/tokens.md) - Create and manage API tokens to authenticate programmatic access to your ChatBotKit account
- [Policies](/docs/policies.md) - Automatically manage conversation lifecycles with retention policies that set expiration dates for idle conversations. Learn how to create and configure policies through the dashboard interface.
- [Moderation](/docs/moderation.md) - Learn about the content moderation features provided by ChatBotKit to ensure the safety and integrity of bot-user interactions. Enable content scanning and automatic refusal to protect against harmful and inappropriate content.
- [Privacy](/docs/privacy.md) - The following document outlines the privacy features of ChatBotKit. Learn about ChatBotKit’s encryption, anonymity and entity handling.
- [Security](/docs/security.md) - Explore various aspects of security, including compliance, encryption, privacy, and more. Discover how ChatBotKit ensures the security of your data and protects your privacy. Learn about security testing, compliance protocols, privacy features, encryption standards, monitoring systems, incident response, authentication and authorization, data residency, data retention, and continuous improvement.
- [Events](/docs/events.md) - Overview of ChatBotKit's event monitoring capabilities for tracking platform activities and analyzing usage patterns.
- [Audit](/docs/audit.md) - Overview of ChatBotKit's audit trail capabilities for tracking changes and maintaining compliance records.
- [Blueprint Embed Preview](/docs/blueprint-embed-preview.md) - Embed a live, read-only blueprint canvas diagram into any webpage or application using a simple iframe.
- [Playgrounds](/docs/playgrounds.md) - Overview of ChatBotKit Playgrounds. Learn how to use Playgrounds to experiment, debug, and prototype conversational AI workflows.
- [Apps](/docs/apps.md) - Discover the ChatBotKit Apps ecosystem featuring Chat, Connect, Inbox, Usage, Task, and Trace applications designed to enhance conversational AI capabilities.
- [Partner](/docs/partner.md) - Learn about the Partner API offered by ChatBotKit, a powerful tool for developing Software as a Service (SaaS) solutions. Discover how the Partner API simplifies SaaS development by providing unique sub-accounts with customizable configurations and restrictions.
- [Teams](/docs/teams.md) - Learn how to create and manage teams in ChatBotKit for basic collaboration and organization.
- [Glossary](/docs/glossary.md) - This glossary provides definitions for key terms related to conversational AI, including conversational AI, AI bots, chatbots, RAG, AI, machine learning, deep learning, GPT, LLM, transformer models, intent recognition, entity recognition, dialogue management, and sentiment analysis and more.
- [Billing](/docs/billing.md) - Explore ChatBotKit's billing system, designed for transparency and predictability. Understand credit tokens, subscription plans, and how to optimize your costs while using AI models effectively. Tailored solutions available for enterprises seeking unlimited agreements.
- [Deployments](/docs/deployments.md) - Discover flexible deployment options with ChatBotKit, offering cloud and on-premises solutions tailored for your organization's needs. This guide covers architecture, security, and implementation processes to ensure effective conversational AI integration.
- [Partnership](/docs/partnership.md) - Discover Chatbotkit's flexible partnership program for resellers, featuring both direct and white-label options. Benefit from tailored onboarding, adaptable contract terms, and comprehensive technical support to enhance your business model.
- [GitHub Actions](/docs/github-actions.md) - Learn how to run ChatBotKit AI agents inside GitHub Actions workflows using the official chatbotkit/github-actions integration.
- [API V1 Spec](/docs/api/v1/spec.md) - The API V1 Spec provides a comprehensive guide to the RESTful API provided by our service. It includes all available endpoints, the expected input and output parameters for each endpoint, and detailed examples of how to use the API.
- [llms.txt](/llms.txt) - The llms.txt file for ChatBotKit provides a standardized way for websites to communicate their support for various language models (LLMs) to web crawlers and other automated systems. By including this file, ChatBotKit can inform these systems about the LLMs it supports, enabling better integration and interaction with AI-driven services.
- [Context7 LLM Docs](https://context7.com/llmstxt/chatbotkit_llms_txt) - The ChatBotKit Context7 LLM Docs provide quick access to LLMs, coding assistants and AI tools that can be integrated with ChatBotKit. This resource offers detailed information on how to leverage these LLMs to enhance chatbot capabilities, improve user interactions, and streamline development processes.