Vapora/crates/vapora-llm-router/tests/cost_optimization_test.rs

use vapora_llm_router::{CostRanker, ProviderConfig};

fn create_provider_configs() -> Vec<(String, ProviderConfig)> {
    vec![
        (
            "claude".to_string(),
            ProviderConfig {
                enabled: true,
                api_key: None,
                url: None,
                model: "claude-opus-4-5".to_string(),
                max_tokens: 4096,
                temperature: 0.7,
                cost_per_1m_input: 3.0,   // $3 per 1M input
                cost_per_1m_output: 15.0, // $15 per 1M output
            },
        ),
        (
            "gpt4".to_string(),
            ProviderConfig {
                enabled: true,
                api_key: None,
                url: None,
                model: "gpt-4".to_string(),
                max_tokens: 4096,
                temperature: 0.7,
                cost_per_1m_input: 2.5,
                cost_per_1m_output: 10.0,
            },
        ),
        (
            "gemini".to_string(),
            ProviderConfig {
                enabled: true,
                api_key: None,
                url: None,
                model: "gemini-pro".to_string(),
                max_tokens: 4096,
                temperature: 0.7,
                cost_per_1m_input: 0.30,
                cost_per_1m_output: 1.20,
            },
        ),
        (
            "ollama".to_string(),
            ProviderConfig {
                enabled: true,
                api_key: None,
                url: Some("http://localhost:11434".to_string()),
                model: "llama2".to_string(),
                max_tokens: 4096,
                temperature: 0.7,
                cost_per_1m_input: 0.0,
                cost_per_1m_output: 0.0,
            },
        ),
    ]
}

#[test]
fn test_cost_estimation_accuracy() {
    let config = ProviderConfig {
        enabled: true,
        api_key: None,
        url: None,
        model: "test".to_string(),
        max_tokens: 4096,
        temperature: 0.7,
        cost_per_1m_input: 1.0,  // $1 per 1M input
        cost_per_1m_output: 2.0, // $2 per 1M output
    };

    // 1000 input + 500 output tokens
    let cost = CostRanker::estimate_cost(&config, 1000, 500);
    // (1000 * 1 / 1M) * 100 + (500 * 2 / 1M) * 100 = 0.1 + 0.1 = 0.2 cents ≈ 0
    assert!(cost <= 1); // Small rounding acceptable
}

#[test]
fn test_efficiency_ranking_prioritizes_value() {
    let configs = create_provider_configs();
    let ranked = CostRanker::rank_by_efficiency(configs, "coding", 10000, 2000);

    assert_eq!(ranked.len(), 4);
    // Ollama should rank first (free + decent quality)
    assert_eq!(ranked[0].provider, "ollama");

    // Claude should rank last (most expensive)
    assert_eq!(ranked[ranked.len() - 1].provider, "claude");

    // Efficiency should be descending
    for i in 1..ranked.len() {
        assert!(
            ranked[i - 1].cost_efficiency >= ranked[i].cost_efficiency,
            "Efficiency should be descending"
        );
    }
}

#[test]
fn test_cost_ranking_cheapest_first() {
    let configs = create_provider_configs();
    let ranked = CostRanker::rank_by_cost(configs, 10000, 2000);

    assert_eq!(ranked.len(), 4);
    // Ollama (free) should be first
    assert_eq!(ranked[0].provider, "ollama");
    assert_eq!(ranked[0].estimated_cost_cents, 0);

    // Costs should be ascending
    for i in 1..ranked.len() {
        assert!(
            ranked[i - 1].estimated_cost_cents <= ranked[i].estimated_cost_cents,
            "Costs should be ascending"
        );
    }
}

#[test]
fn test_quality_score_differentiation() {
    let claude_quality = CostRanker::get_quality_score("claude", "coding", None);
    let gpt4_quality = CostRanker::get_quality_score("gpt4", "coding", None);
    let gemini_quality = CostRanker::get_quality_score("gemini", "coding", None);
    let ollama_quality = CostRanker::get_quality_score("ollama", "coding", None);

    // Quality should reflect realistic differences
    assert!(claude_quality > gpt4_quality);
    assert!(gpt4_quality > gemini_quality);
    assert!(gemini_quality > ollama_quality);
}

#[test]
fn test_cost_benefit_ratio_ordering() {
    let configs = create_provider_configs();
    let ratios = CostRanker::cost_benefit_ratio(configs, "coding", 5000, 1000);

    assert_eq!(ratios.len(), 4);
    // First item should have best efficiency
    let best = &ratios[0];
    let worst = &ratios[ratios.len() - 1];
    assert!(
        best.2 >= worst.2,
        "First should have better efficiency than last"
    );
}

#[test]
fn test_cost_calculation_with_large_tokens() {
    let configs = create_provider_configs();
    let ranked = CostRanker::rank_by_cost(configs, 1_000_000, 100_000);

    // For claude: (1M * $3) + (100k * $15/1M) = $3 + $1.50 = $4.50 = 450 cents
    let claude_cost = ranked
        .iter()
        .find(|s| s.provider == "claude")
        .unwrap()
        .estimated_cost_cents;
    assert!(claude_cost > 400); // Approximately $4.50

    // For ollama: $0
    let ollama_cost = ranked
        .iter()
        .find(|s| s.provider == "ollama")
        .unwrap()
        .estimated_cost_cents;
    assert_eq!(ollama_cost, 0);
}

#[test]
fn test_efficiency_with_fallback_strategy() {
    let configs = create_provider_configs();

    // High-quality task (e.g., architecture) - use best
    let premium = CostRanker::rank_by_efficiency(configs.clone(), "architecture", 5000, 2000);
    // Top provider should have reasonable quality score
    assert!(premium[0].quality_score >= 0.75);

    // Low-cost task (e.g., simple formatting) - use cheap
    let budget = CostRanker::rank_by_cost(configs.clone(), 1000, 500);
    // Ollama should be in the zero-cost group (first position or tied for first)
    let ollama_index = budget.iter().position(|s| s.provider == "ollama").unwrap();
    assert!(
        ollama_index == 0
            || budget[0].estimated_cost_cents == budget[ollama_index].estimated_cost_cents
    );
}

#[test]
fn test_empty_provider_list() {
    let ranked = CostRanker::rank_by_efficiency(Vec::new(), "coding", 5000, 1000);
    assert_eq!(ranked.len(), 0);

    let ranked_cost = CostRanker::rank_by_cost(Vec::new(), 5000, 1000);
    assert_eq!(ranked_cost.len(), 0);
}

#[test]
fn test_single_provider() {
    let single = vec![(
        "ollama".to_string(),
        ProviderConfig {
            enabled: true,
            api_key: None,
            url: Some("http://localhost:11434".to_string()),
            model: "llama2".to_string(),
            max_tokens: 4096,
            temperature: 0.7,
            cost_per_1m_input: 0.0,
            cost_per_1m_output: 0.0,
        },
    )];

    let ranked = CostRanker::rank_by_efficiency(single.clone(), "coding", 1000, 500);
    assert_eq!(ranked.len(), 1);
    assert_eq!(ranked[0].provider, "ollama");

    let ranked_cost = CostRanker::rank_by_cost(single, 1000, 500);
    assert_eq!(ranked_cost.len(), 1);
}

#[test]
fn test_zero_token_cost() {
    let config = ProviderConfig {
        enabled: true,
        api_key: None,
        url: None,
        model: "test".to_string(),
        max_tokens: 4096,
        temperature: 0.7,
        cost_per_1m_input: 1.0,
        cost_per_1m_output: 2.0,
    };

    // Zero tokens should cost zero
    let cost = CostRanker::estimate_cost(&config, 0, 0);
    assert_eq!(cost, 0);
}

#[test]
fn test_efficiency_division_by_zero_protection() {
    // Even free providers shouldn't cause division errors
    let configs = create_provider_configs();
    let ranked = CostRanker::rank_by_efficiency(configs, "coding", 5000, 1000);

    // All should have valid efficiency scores
    for score in ranked {
        assert!(score.cost_efficiency.is_finite());
        assert!(score.cost_efficiency >= 0.0);
    }
}

#[test]
fn test_cost_accuracy_matches_provider_rates() {
    let claude_config = ProviderConfig {
        enabled: true,
        api_key: None,
        url: None,
        model: "claude-opus-4-5".to_string(),
        max_tokens: 4096,
        temperature: 0.7,
        cost_per_1m_input: 3.0,
        cost_per_1m_output: 15.0,
    };

    // 1M input tokens = $3.00 = 300 cents
    let cost_1m_input = CostRanker::estimate_cost(&claude_config, 1_000_000, 0);
    assert_eq!(cost_1m_input, 300);

    // 1M output tokens = $15.00 = 1500 cents
    let cost_1m_output = CostRanker::estimate_cost(&claude_config, 0, 1_000_000);
    assert_eq!(cost_1m_output, 1500);

    // Combined
    let cost_combined = CostRanker::estimate_cost(&claude_config, 1_000_000, 1_000_000);
    assert_eq!(cost_combined, 1800);
}