Eliza
ELIZA is a classic pattern-matching conversational agent originally developed at MIT, providing a nostalgic but functional therapist implementation.
Overview
| Property | Value |
|---|---|
| Key | eliza |
| Type | Rule-based |
| Focus | Rogerian Therapy |
Description
ELIZA was one of the first chatbots, created by Joseph Weizenbaum at MIT in the 1960s. This implementation recreates the classic DOCTOR script, which simulates a Rogerian psychotherapist. Despite its simplicity, ELIZA demonstrates how pattern matching can create surprisingly engaging conversations.
Key Features
- Pattern matching - Uses regex patterns to generate contextual responses
- Reflection - Reflects statements back to the client
- Open-ended questions - Asks questions that encourage elaboration
- Unconditional positive regard - Maintains a supportive, non-judgmental tone
Configuration
YAML Configuration
therapist:
key: eliza
Python Usage
from patienthub.therapists import TherapistRegistry
therapist = TherapistRegistry.create("eliza")
Parameters
ELIZA uses a fixed rule-based system and does not require additional configuration parameters.
Use Cases
- Baseline comparisons with LLM-based therapists
- Historical/educational demonstrations
- Low-resource environments where LLM access is unavailable
- Research on human-computer interaction