AnnaAgent Generator

Creates character files for the AnnaAgent client, supporting multi-session counseling simulations with dynamic memory and clinical scale tracking.

Overview

Property	Value
Key	annaAgent
Type	LLM-based
Output	AnnaAgent character files

Key Features

• Scale-based profiling: Fills BDI, GHQ, and SASS scales for both previous and current treatment states
• Age-appropriate event triggering: Selects triggering life events from curated adult/teen event databases
• Complaint chain generation: Produces a 3–7 stage cognitive change chain from the triggering event
• Speaking style inference: Extracts the patient's speaking style from prior conversation history
• Status summarization: Analyzes scale changes across sessions to produce a current psychological status summary

How It Works

generate_character() runs the following pipeline:

1. Fill previous-session BDI, GHQ, and SASS scales from the input case report
2. Select a triggering life event (age-matched from adult_events.csv / teen_events.json)
3. Generate a complaint cognitive change chain (3–7 stages)
4. Generate current situation, speaking style, and representative statements
5. Fill current-session BDI, GHQ, and SASS scales
6. Analyze scale changes and summarize the patient's current status
7. Save the resulting character JSON to output_dir

Usage

from patienthub.generators import get_generator

generator = get_generator(agent_name="annaAgent", lang="en")
generator.generate_character()

Configuration

Parameter	Type	Default	Description
prompt_path	string	data/prompts/generator/annaAgent.yaml	Path to prompt file
input_dir	string	data/resources/AnnaAgent	Directory with case.json, event files, etc.
output_dir	string	data/characters/AnnaAgent.json	Path where the generated character is saved
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

Input Data Format

The generator reads from input_dir/case.json:

{
  "profile": {
    "name": "...",
    "age": 30,
    "gender": "Female"
  },
  "report": "...",
  "previous_conversations": [
    {"role": "Therapist", "content": "..."},
    {"role": "Client", "content": "..."}
  ]
}

Output Format

{
  "profile": { "name": "...", "age": 30 },
  "situation": "Second-person description of current situation",
  "statement": ["Representative utterance 1", "Representative utterance 2"],
  "style": ["Speaking style trait 1", "Speaking style trait 2"],
  "complaint_chain": [
    {"stage": 1, "content": "..."},
    {"stage": 2, "content": "..."}
  ],
  "status": "Summary of current psychological status",
  "report": "Previous session psychological report",
  "previous_conversations": [...]
}

Use Cases

• Creating character files for AnnaAgent multi-session simulations
• Building longitudinal therapy research datasets