Function reference

Getting Started

Core classes and basic chatbot setup

ChatBot: Main entry point for building and managing conversational AI chatbots with integrated
ChatBot.model(): Configure the language model to use for generating responses.
ChatBot.preset(): Apply a pre-configured behavior template to instantly specialize the chatbot.
ChatBot.temperature(): Control the randomness and creativity level of chatbot responses.
ChatBot.max_tokens(): Set the maximum number of tokens for chatbot responses.
ChatBot.tools(): Configure tools for this chatbot with unified API for custom and built-in tools.
ChatBot.persona(): Set the persona for the chatbot.
ChatBot.avoid(): Set topics or behaviors to avoid.
ChatBot.verbose(): Enable or disable verbose output.

Prompt Engineering

Advanced prompt building and conversation pathways

PromptBuilder: Builds structured prompts using attention mechanisms and cognitive principles.
PromptBuilder.persona(): Set a behavioral persona to anchor the model’s response style and establish expertise
PromptBuilder.task_context(): Define the primary task context that establishes what needs to be accomplished.
PromptBuilder.focus_on(): Set the primary focus that leverages both front-loading and recency bias for maximum
PromptBuilder.critical_constraint(): Add a critical constraint that will be front-loaded for maximum attention and impact.
PromptBuilder.core_analysis(): Define core analysis requirements as a high-priority, required structured section.
PromptBuilder.structured_section(): Add a structured section with clear hierarchical boundaries and visual organization.
PromptBuilder.constraint(): Add a standard constraint to the prompt that will appear in the additional constraints
PromptBuilder.avoid_topics(): Specify topics or behaviors to avoid through negative constraints that guide AI responses
PromptBuilder.output_format(): Specify output formatting requirements to prevent ambiguous responses and ensure structured
PromptBuilder.example(): Add an input/output example for few-shot learning and response format demonstration.
PromptBuilder.final_emphasis(): Set final emphasis that leverages recency bias to ensure critical instructions receive
PromptBuilder.vocabulary(): Add domain-specific vocabulary definitions to ensure consistent understanding of
PromptBuilder.pathways(): Add conversational pathway guidance to structure and guide conversation flow.
VocabularyTerm: Define domain-specific terminology with multilingual support for consistent AI understanding.
Pathways: Chainable builder for defining structured conversational pathways.
Pathways.state(): Define a state with natural language description as the primary identifier.
Pathways.required(): Specify required information for the current state to be considered complete.
Pathways.optional(): Specify optional information that would be helpful but not required.
Pathways.tools(): Specify tools available for use in the current state.
Pathways.success_condition(): Define what indicates successful completion of the current state.
Pathways.next_state(): Define direct transition to the next state.
Pathways.branch_on(): Define conditional branch to another state based on specific conditions.
Pathways.fallback(): Define fallback transition when normal state progression fails.
ChatBot.prompt_builder(): Create an attention-optimized prompt builder for declarative prompt composition.
ChatBot.structured_prompt(): Configure the chatbot with a structured prompt built from keyword sections.
ChatBot.chain_prompts(): Chain multiple structured prompts in attention-optimized order.
architectural_analysis_prompt(): Create a pre-configured prompt builder for architectural analysis tasks.
code_review_prompt(): Create a pre-configured prompt builder for code review tasks.
debugging_prompt(): Create a pre-configured prompt builder for debugging tasks.

Conversations & Messages

Managing conversations, messages, and context

Conversation: Manages sequences of messages in conversational AI interactions, primarily returned by ChatBot methods.
Conversation.add_message(): Add a new message to the conversation.
Conversation.add_user_message(): Add a user message to the conversation.
Conversation.add_assistant_message(): Add an assistant message to the conversation.
Conversation.add_system_message(): Add a system message to the conversation.
Conversation.clear_messages(): Clear all messages from the conversation.
Conversation.get_messages(): Get all messages, optionally filtered by role.
Conversation.get_last_message(): Get the last message, optionally filtered by role.
Conversation.get_message_count(): Get the total number of messages.
Conversation.get_context_messages(): Get messages within the context window.
Conversation.set_context_window(): Set the maximum context window length.
Conversation.to_dict(): Convert conversation to dictionary format.
Conversation.from_dict(): Create a conversation from dictionary data.
Message: Represents a single message in a conversational AI interaction, discovered through Conversation objects.
Message.to_dict(): Convert message to dictionary format.
Message.from_dict(): Create a message from dictionary data.

File Attachments

Attaching and processing files in conversations

Attachments: File attachment handler for Talk Box conversations.
Attachments.with_prompt(): Add a text prompt to accompany the file attachments.
Attachments.get_metadata(): Get metadata for all processed attachments.
Attachments.summary(): Get a human-readable summary of attached files.
AttachmentMetadata: Metadata for individual file attachments.

Presets & Templates

Behavior templates and preset management

Preset: Defines reusable behavior templates for chatbot personality and capabilities.
PresetManager: Centralized manager for loading, storing, and applying chatbot behavior presets.

Testing & Validation

Tools for testing chatbot behavior and compliance

autotest_avoid_topics(): Comprehensive avoid topics testing with automated violation detection.
TestResults: Enhanced test results container with rich reporting and analysis capabilities.

Supporting Types

Internal types and enums for advanced usage

Priority: Priority levels for prompt components based on attention positioning.
PromptSection: Represents a structured section of an attention-optimized prompt with priority and ordering
BuilderTypes: Predefined builder types for autocomplete and type safety when using prompt builders.