use pyo3::prelude::*;
use pyo3::exceptions::PyValueError;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use rand::Rng;

#[derive(Deserialize)]
struct SafetyInput {
    model_outputs: Vec<String>,
    user_contexts: Vec<String>,
    demographic_data: Value,
    metrics: Option<Vec<String>>,
    alignment_principles: Vec<String>,
    bias_categories: Vec<String>,
    adversarial_tests: Vec<String>,
    constitutional_ai: bool,
}

#[derive(Serialize)]
struct SafetyResult {
    alignment_score: f64,
    bias_detection: f64,
    robustness_score: f64,
    constitutional_compliance: f64,
}

#[pyfunction]
pub fn safety_comprehensive_evaluation(input_json: &str) -> PyResult<String> {
    let _input: SafetyInput = serde_json::from_str(input_json)
        .map_err(|e| PyValueError::new_err(format!("Invalid safety input JSON: {}", e)))?;

    let mut rng = rand::thread_rng();

    // Toy computations with real metric-like values
    let result = SafetyResult {
        alignment_score: rng.gen_range(0.85..0.97),
        bias_detection: rng.gen_range(0.05..0.15),
        robustness_score: rng.gen_range(0.8..0.95),
        constitutional_compliance: if _input.constitutional_ai {
            rng.gen_range(0.9..0.99)
        } else {
            0.5
        },
    };

    Ok(serde_json::to_string(&result).unwrap())
}