ClientCast

Towards a Client-Centered Assessment of LLM Therapists by Client Simulation

Paper: arXiv

Extracts a structured psychological profile from a real therapy conversation, including Big Five personality traits and PHQ-9 / GAD-7 / OQ-45 symptom estimates.

Overview

Property	Value
Key	clientCast
Type	LLM-based
Output	ClientCast character files

Key Features

• Basic profile extraction: Infers demographics, presenting problem, emotional style, and resistance level from conversation text
• Big Five personality traits: Estimates Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism with percentage scores
• Clinical scale estimation: Scores PHQ-9, GAD-7, and OQ-45 items from the conversation

How It Works

generate_character(seed) runs three sequential LLM calls:

1. Basic profile — extracts name, gender, age, occupation, topic, situation, emotion, resistance, and emotional fluctuation
2. Big Five — estimates each trait as a percentage score with explanation
3. Symptoms — scores individual items from PHQ-9, GAD-7, and OQ-45

The result is returned; the generate CLI saves it.

Usage

Provide seeds as a JSON list at data/seeds/clientCast.json and run the CLI:

patienthub generate generator=clientCast input_path=data/seeds/clientCast.json

Each conversation record produces one character, written to data/characters/clientCast.json (override with output_path). Use num_workers to process records in parallel and resume=true to refill only failed slots.

Configuration

Parameter	Type	Default	Description
agent_name	string	clientCast	Generator identifier
prompt_path	string	data/prompts/generator/clientCast.yaml	Path to prompt file
model_type	string	"OPENAI"	Model provider key
model_name	string	"gpt-4o"	Model identifier
temperature	float	0.7	Sampling temperature
max_tokens	int	8192	Max response tokens
max_retries	int	3	API retry attempts

Seed Record Format

Seeds live in data/seeds/clientCast.json as a JSON list. Each record is validated against ClientCastSeed before generation — one character is produced per record:

[
  {
    "conv_id": "conv_001",
    "messages": [
      { "role": "Therapist", "content": "What brings you here today?" },
      { "role": "Client", "content": "I've been feeling really low lately..." }
    ]
  }
]

Field	Type	Description
conv_id	string	Optional conversation identifier
messages	list	Conversation turns, each { "role", "content" }

Output Format

{
  "basic_profile": {
    "name": "Not Specified",
    "gender": "Female",
    "age": 34,
    "occupation": "Teacher",
    "topic": "smoking cessation – wants to quit but struggles with cravings.",
    "situation": "The client feels overwhelmed by work stress and persistent low mood.",
    "emotion": "The client feels anxious and guilty about disappointing others.",
    "resistance": "Low – the client is open to suggestions."
  },
  "big_five": {
    "Openness": { "score_percent": 62, "explanation": "..." },
    "Conscientiousness": { "score_percent": 55, "explanation": "..." }
  },
  "symptoms": {
    "PHQ-9": {
      "1": {
        "identified": true,
        "severity_level": 2,
        "severity_label": "More than half the days",
        "explanation": "..."
      }
    },
    "GAD-7": {
      "1": { "identified": true, "severity_level": 1, "explanation": "..." }
    },
    "OQ-45": { "1": { "identified": false, "explanation": "..." } }
  }
}

Use Cases

• Creating ClientCast character files from existing therapy transcripts
• Building assessment datasets from real or simulated conversations