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name: logic-adapters description: "Configure ChatterBot logic adapters, response selection, comparison methods, custom adapters, MCP tool adapters, and experimental Ollama/OpenAI LLM adapters." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Logic Adapters

Use this sub-skill when a task asks how ChatterBot chooses a response, how to configure built-in logic adapters, how to add a custom adapter, why confidence values behave a certain way, or how experimental Ollama/OpenAI adapters expose deterministic adapters as tools.

Quick route

1. Read references/logic-api.md for verified adapter signatures, parameters, and response-selection surfaces.
2. Read references/workflows.md for concrete BestMatch, default response, math/time/unit conversion, specific response, custom adapter, and LLM-tool recipes.
3. Read references/troubleshooting.md for optional dependencies, missing model, provider/service failures, invalid adapter dicts, and confidence surprises.
4. Run scripts/logic_adapter_demo.py for deterministic math/time/specific/default/unit adapter smoke checks.

Built-in adapters

Adapter	Use for	Notes
BestMatch	find learned responses from storage	default adapter; uses search + response selection
SpecificResponseAdapter	exact or matcher-triggered canned response	requires input_text and output_text
MathematicalEvaluation	natural-language or symbolic math	uses mathparse; also exposes calculate as a tool
TimeLogicAdapter	current time questions	uses spaCy phrase matching; also exposes current time as a tool
UnitConversion	natural-language unit conversion	requires pint; exposes convert_units as a tool
OllamaLogicAdapter	experimental local/remote Ollama responses	requires model, client package, and an Ollama service
OpenAILogicAdapter	experimental OpenAI-compatible responses	requires model, client package, and credentials/base URL

Adapter configuration pattern

Use import paths or config dictionaries:

from chatterbot import ChatBot

bot = ChatBot(
    "Logic Bot",
    logic_adapters=[
        {
            "import_path": "chatterbot.logic.BestMatch",
            "default_response": "I am sorry, but I do not understand.",
            "maximum_similarity_threshold": 0.90,
        },
        {
            "import_path": "chatterbot.logic.SpecificResponseAdapter",
            "input_text": "Help me!",
            "output_text": "Read the support guide.",
        },
    ],
)

If multiple adapters can process a statement, ChatterBot returns the response with the highest confidence, with special handling when multiple adapters agree on the same statement.

Boundaries

• For ChatBot lifecycle, Statement, taggers, and search classes, use core-chatbot.
• For training data that powers BestMatch, use training.
• For SQL/Mongo/Redis storage behavior used by search, use storage-adapters.
• For Django-specific adapter usage, use django-integration.