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This page provides a comprehensive guide on how to obtain and manage your ChatbotKit API keys, including steps for account creation, key types, best practices, and troubleshooting tips for effective integration into your applications.

Comprehensive guide to authenticating with the ChatBotKit API using secret keys, JWT tokens, and user impersonation for secure programmatic access.

Blueprint resources represent the collection of related components (bots, datasets, skillsets, integrations, etc.) that are organized within a blueprint, providing a comprehensive view of all assets in a specific configuration.

Blueprints are organizational containers that group related resources like bots, datasets, skillsets, and integrations into reusable templates, enabling efficient management and sharing of complex conversational AI configurations.

Bot memories store information learned from conversations, enabling bots to recall past interactions and maintain context across sessions for more intelligent and personalized responses.

Bot ratings enable you to record feedback and performance metrics for conversational AI agents, providing a structured way to track quality, measure user satisfaction, and identify areas for improvement over time.

Bot sessions provide secure, time-limited authentication tokens for conversational interactions, enabling users to engage with bots through applications, websites, and third-party platforms without exposing full API credentials.

Bots are intelligent conversational agents that can interact with users, answer questions, and perform tasks using AI models and connected resources like datasets and skillsets.

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This page provides comprehensive documentation for the ChatbotKit CLI, including installation instructions, environment setup, command references for bot and dataset management, integration commands, configuration files, common usage examples, error handling, and best practices.

Contacts represent end-users or customers who interact with your chatbots, enabling conversation tracking, contact management, and personalized user experiences.

Conversation feedback allows users to provide ratings and evaluations of AI responses through upvotes and downvotes, helping improve bot performance and gather user sentiment data.

Managing conversation workflows including stateless and stateful interaction patterns for different use cases and integration scenarios.

Messages are individual units of communication within a conversation, representing either user inputs or AI responses, and can be created, retrieved, updated, or deleted to manage conversation content.

Conversations are interactive sessions where messages are exchanged between users and AI bots, enabling rich dialogue experiences with context awareness, memory, and intelligent responses.

Learn how to use files as data sources for your datasets.

Dataset records are individual entries within a dataset that contain specific pieces of information used to provide context and knowledge to the agent.

Datasets can be searched to find relevant records based on a search query.

Datasets are structured collections of data that serve as knowledge bases for various applications, enabling efficient storage, retrieval, and management of information.

Comprehensive guide to managing files in the platform, including uploading, retrieving, updating, and deleting file resources.

Instruction types define how user input is interpreted and transformed into executable actions within the ChatBotKit platform, enabling flexible and powerful agent behaviors through different instruction patterns.

Comprehensive guide to understanding language model configuration in the ChatBotKit platform

Memories are persistent data storage units that enable applications to store and retrieve information associated with bots and contacts, providing context and historical data for intelligent interactions.

Metadata provides a flexible way to attach custom information to platform resources, enabling integrations, tracking, and custom workflows without modifying core data structures.

This page provides detailed documentation for the Chatbotkit Next.js SDK, outlining its key features, installation instructions, server-side integration, best practices, TypeScript support, and examples for implementing AI-powered chat capabilities in Next.js applications.

This page provides a comprehensive guide to the Chatbotkit Node.js SDK, detailing key features, installation instructions, authentication methods, and best practices for building AI-powered chatbots. It covers bot management, dataset handling, conversation management, and usage monitoring, along with error handling strategies and references for further resources.

Partner tokens are API authentication tokens created for partner users (sub-accounts), enabling secure programmatic access to the ChatBotKit platform on behalf of specific customer accounts within a partner's white-label solution.

Partner users are sub-accounts that can be created and managed by partner accounts, enabling white-label SaaS solutions where each customer operates in an isolated environment with custom configurations and restrictions.

This page provides an overview of primers for developers new to ChatBotKit and conversational AI software, including detailed examples, projects, and applications. It serves as a comprehensive resource for understanding and implementing conversational AI solutions.

The React SDK documentation provides comprehensive guidance on utilizing the Chatbotkit React SDK, including installation instructions, detailed explanations of components and hooks, and practical examples for building responsive chat interfaces.

Secrets are secure credential storage for API keys, OAuth tokens, and other sensitive authentication data used by agents and integrations within the platform.

Abilities are the individual actions that skillsets can perform, defined through natural language instructions and executable code blocks.

Skillsets are collections of abilities that define what actions your AI agents can perform, from fetching web data to sending emails and generating content.

This API specification provides a detailed overview of the CBK API, including endpoints, authentication methods, request and response formats, and error handling. It serves as a guide for developers to build and manage AI agents effectively.

Learn how to use streaming responses with the ChatBotKit API to efficiently handle large datasets, long-running operations, and real-time updates by controlling the Accept header in your requests.

Tasks are scheduled or on-demand actions that your agents can perform automatically, enabling workflow automation and periodic operations.