aprender-serve 0.64.0

Pure Rust ML inference engine built from scratch - model serving for GGUF and safetensors
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/// PARITY-050f: Summary and next steps
#[test]
fn test_parity050f_summary() {
    println!("PARITY-050f: Batch Inference Analysis Summary");
    println!("=============================================");
    println!();
    println!("  FINDINGS:");
    println!("  ---------");
    println!("  1. Extensive batch infrastructure already exists in realizar");
    println!("  2. ContinuousBatchScheduler (PARITY-028) provides dynamic batching");
    println!("  3. GPU FFN wins at batch >= 30 (PARITY-046)");
    println!("  4. Memory allows batch=16+ on RTX 4090 (24GB VRAM)");
    println!("  5. HTTP integration is low complexity (existing components)");
    println!();
    println!("  M4 PARITY PATH:");
    println!("  ---------------");
    println!("  Current: 64 tok/s (single-token ceiling)");
    println!("  Target: 192 tok/s (Ollama * 0.8)");
    println!("  Method: Enable batch inference in HTTP API");
    println!("  Batch size needed: >= 16");
    println!();
    println!("  NEXT STEPS:");
    println!("  -----------");
    println!("  PARITY-051: Wire ContinuousBatchScheduler to /v1/completions");
    println!("  PARITY-052: Add request queuing with batch window");
    println!("  PARITY-053: Benchmark batch throughput");
    println!("  PARITY-054: Achieve M4 parity validation");
    println!();
    println!("  CONCLUSION:");
    println!("  -----------");
    println!("  M4 parity is achievable without new GPU optimizations.");
    println!("  The path is wiring existing batch infrastructure to HTTP serving.");
    println!("  Single-token optimization has reached its ceiling at 64 tok/s.");
    println!("  Batch inference is the ONLY path to 3x improvement needed for M4.");

    // Test passes as documentation
    assert!(true, "PARITY-050f: Summary documented");
}

// ==================== PARITY-051: Batch Scheduler API Integration ====================
//
// OBJECTIVE: Wire ContinuousBatchScheduler to /v1/completions endpoint
//
// ARCHITECTURE:
//   - Add ContinuousBatchScheduler to AppState
//   - Use tokio::sync::mpsc for request queuing
//   - Background task processes batches with configurable window
//   - Responses returned via oneshot channels
//
// IMPLEMENTATION PATH:
//   1. Add batch_scheduler to AppState (Option<Arc<ContinuousBatchScheduler>>)
//   2. Add request_tx channel for queueing (tokio::sync::mpsc::Sender)
//   3. Spawn background batch processor task
//   4. Modify completions handler to use batch path when available
//
// BATCH WINDOW STRATEGY:
//   - Wait up to 10ms to accumulate requests
//   - Process immediately if batch hits target size (16+)
//   - Fallback to single-request if batch disabled
// ================================================================================

/// PARITY-051a: Document AppState changes for batch integration
#[test]
fn test_parity051a_appstate_batch_integration() {
    // Document the AppState changes needed for batch scheduler integration

    struct AppStateChange {
        field: &'static str,
        field_type: &'static str,
        purpose: &'static str,
        complexity: &'static str,
    }

    let changes = [
        AppStateChange {
            field: "batch_scheduler",
            field_type: "Option<Arc<ContinuousBatchScheduler>>",
            purpose: "Scheduler instance for continuous batching",
            complexity: "Low - add field and initialization",
        },
        AppStateChange {
            field: "batch_request_tx",
            field_type: "Option<tokio::sync::mpsc::Sender<BatchRequest>>",
            purpose: "Channel to queue incoming requests",
            complexity: "Low - standard tokio channel",
        },
        AppStateChange {
            field: "batch_config",
            field_type: "BatchConfig { window_ms: u64, min_batch: usize }",
            purpose: "Configuration for batch window and minimum batch size",
            complexity: "Low - simple config struct",
        },
    ];

    println!("PARITY-051a: AppState Batch Integration Changes");
    println!("================================================");
    println!();

    for change in &changes {
        println!("  Field: {}", change.field);
        println!("    Type: {}", change.field_type);
        println!("    Purpose: {}", change.purpose);
        println!("    Complexity: {}", change.complexity);
        println!();
    }

    println!("  EXISTING INFRASTRUCTURE:");
    println!("    - ContinuousBatchScheduler already in gguf.rs (PARITY-028)");
    println!("    - OwnedQuantizedModelCachedSync for cached inference");
    println!("    - DispatchMetrics for CPU/GPU tracking");
    println!();
    println!("  CONCLUSION: 3 new fields needed in AppState");

    // All changes are low complexity
    let low_count = changes
        .iter()
        .filter(|c| c.complexity.starts_with("Low"))
        .count();
    assert_eq!(low_count, 3, "All changes should be low complexity");
}

/// PARITY-051b: Document async channel architecture
#[test]
fn test_parity051b_async_channel_architecture() {
    // Document the async channel architecture for batch request handling

    struct ChannelDesign {
        channel_type: &'static str,
        direction: &'static str,
        purpose: &'static str,
    }

    let channels = [
        ChannelDesign {
            channel_type: "mpsc::channel<BatchRequest>(1024)",
            direction: "Handler -> BatchProcessor",
            purpose: "Queue incoming requests from HTTP handlers",
        },
        ChannelDesign {
            channel_type: "oneshot::channel<BatchResponse>",
            direction: "BatchProcessor -> Handler",
            purpose: "Return result to waiting HTTP handler",
        },
    ];

    // BatchRequest structure
    struct BatchRequestSpec {
        field: &'static str,
        purpose: &'static str,
    }

    let request_fields = [
        BatchRequestSpec {
            field: "prompt_tokens: Vec<u32>",
            purpose: "Tokenized input prompt",
        },
        BatchRequestSpec {
            field: "max_tokens: usize",
            purpose: "Maximum tokens to generate",
        },
        BatchRequestSpec {
            field: "temperature: f32",
            purpose: "Sampling temperature",
        },
        BatchRequestSpec {
            field: "response_tx: oneshot::Sender<BatchResponse>",
            purpose: "Channel to send result back to handler",
        },
    ];

    println!("PARITY-051b: Async Channel Architecture");
    println!("=======================================");
    println!();
    println!("  CHANNEL DESIGN:");
    for ch in &channels {
        println!("    {} ({})", ch.channel_type, ch.direction);
        println!("      Purpose: {}", ch.purpose);
        println!();
    }

    println!("  BatchRequest STRUCTURE:");
    for field in &request_fields {
        println!("    {}", field.field);
        println!("      {}", field.purpose);
    }
    println!();

    println!("  FLOW:");
    println!("    1. HTTP handler receives /v1/completions request");
    println!("    2. Handler creates oneshot channel for response");
    println!("    3. Handler sends BatchRequest via mpsc channel");
    println!("    4. Handler awaits on oneshot receiver");
    println!("    5. BatchProcessor collects requests in batch window");
    println!("    6. BatchProcessor runs batch inference");
    println!("    7. BatchProcessor sends results via oneshot channels");
    println!("    8. Handler receives result and returns HTTP response");

    // 2 channels needed
    assert_eq!(channels.len(), 2, "Need request and response channels");
}

/// PARITY-051c: Document batch window mechanism
#[test]
fn test_parity051c_batch_window_mechanism() {
    // Document the batch window timing strategy

    struct BatchStrategy {
        condition: &'static str,
        action: &'static str,
        latency_impact: &'static str,
    }

    let strategies = [
        BatchStrategy {
            condition: "Batch size >= 16 (M4 threshold)",
            action: "Process immediately",
            latency_impact: "0ms additional latency",
        },
        BatchStrategy {
            condition: "Window timeout (10ms) reached",
            action: "Process current batch",
            latency_impact: "≤10ms additional latency",
        },
        BatchStrategy {
            condition: "Batch size >= 32 (GPU optimal)",
            action: "Process immediately",
            latency_impact: "0ms additional latency",
        },
        BatchStrategy {
            condition: "Single request + low load",
            action: "Fallback to single-request path",
            latency_impact: "0ms (bypass batching)",
        },
    ];

    println!("PARITY-051c: Batch Window Mechanism");
    println!("===================================");
    println!();
    println!("  BATCH WINDOW CONFIGURATION:");
    println!("    window_ms: 10 (maximum wait time)");
    println!("    min_batch: 4 (minimum batch for GPU benefit)");
    println!("    optimal_batch: 16 (M4 parity threshold)");
    println!("    max_batch: 32 (GPU optimal from PARITY-046)");
    println!();

    println!("  STRATEGIES:");
    for s in &strategies {
        println!("    Condition: {}", s.condition);
        println!("      Action: {}", s.action);
        println!("      Latency: {}", s.latency_impact);
        println!();
    }

    println!("  LATENCY vs THROUGHPUT TRADEOFF:");
    println!("    - Small batch (1-4): Low latency, low throughput");
    println!("    - Medium batch (8-16): Medium latency, M4 throughput");
    println!("    - Large batch (32+): Higher latency, maximum throughput");
    println!();
    println!("  ADAPTIVE BEHAVIOR:");
    println!("    Under high load: Batches fill quickly, minimal wait");
    println!("    Under low load: Single-request fallback, no added latency");

    // Verify strategies cover key scenarios
    assert!(
        strategies.iter().any(|s| s.condition.contains("16")),
        "M4 threshold should be documented"
    );
}

/// PARITY-051d: Document background batch processor task
#[test]
fn test_parity051d_batch_processor_task() {
    // Document the background task that processes batches

    println!("PARITY-051d: Background Batch Processor Task");
    println!("============================================");
    println!();
    println!("  TASK STRUCTURE (pseudo-code):");
    println!("  ```rust");
    println!("  async fn batch_processor(");
    println!("      mut rx: mpsc::Receiver<BatchRequest>,");
    println!("      scheduler: Arc<ContinuousBatchScheduler>,");
    println!("      model: Arc<OwnedQuantizedModelCachedSync>,");
    println!("      config: BatchConfig,");
    println!("  ) {{");
    println!("      let mut batch: Vec<BatchRequest> = Vec::new();");
    println!("      let mut window_start = Instant::now();");
    println!("      ");
    println!("      loop {{");
    println!("          // Collect requests until batch ready or timeout");
    println!(
        "          match timeout(Duration::from_millis(config.window_ms), rx.recv()).await {{"
    );
    println!("              Ok(Some(req)) => batch.push(req),");
    println!("              Ok(None) => break, // Channel closed");
    println!("              Err(_) => {{ }} // Timeout, process batch");
    println!("          }}");
    println!("          ");
    println!("          // Process batch when ready");
    println!("          let should_process = batch.len() >= config.optimal_batch");
    println!("              || window_start.elapsed() >= Duration::from_millis(config.window_ms);");
    println!("          ");
    println!("          if should_process && !batch.is_empty() {{");
    println!("              process_batch(&scheduler, &model, &mut batch).await;");
    println!("              window_start = Instant::now();");
    println!("          }}");
    println!("      }}");
    println!("  }}");
    println!("  ```");
    println!();
    println!("  PROCESS_BATCH STEPS:");
    println!("    1. Submit all requests to ContinuousBatchScheduler");
    println!("    2. Call model.forward_batch_with_gpu_ffn() for batch inference");
    println!("    3. Poll scheduler for completed results");
    println!("    4. Send results via oneshot channels to waiting handlers");
    println!("    5. Clear batch, reset window timer");
    println!();
    println!("  CONCURRENCY:");
    println!("    - Single batch processor task (serialized batches)");
    println!("    - Multiple HTTP handlers can queue concurrently");
    println!("    - Scheduler handles slot management thread-safely");

    // Test passes as documentation
    assert!(true, "PARITY-051d: Batch processor documented");
}

/// PARITY-051e: Document completions handler modification
#[test]
fn test_parity051e_completions_handler_modification() {
    // Document changes needed to openai_completions_handler

    println!("PARITY-051e: Completions Handler Modification");
    println!("=============================================");
    println!();
    println!("  CURRENT FLOW (single-request):");
    println!("    1. Receive request");
    println!("    2. Tokenize prompt");
    println!("    3. Call model.generate_with_cache()");
    println!("    4. Decode output");
    println!("    5. Return response");
    println!();
    println!("  NEW FLOW (batch-enabled):");
    println!("    1. Receive request");
    println!("    2. Tokenize prompt");
    println!("    3. IF batch_request_tx available:");
    println!("       a. Create oneshot channel");
    println!("       b. Send BatchRequest via mpsc");
    println!("       c. Await oneshot response");
    println!("    4. ELSE:");
    println!("       a. Call model.generate_with_cache() (fallback)");
    println!("    5. Decode output");
    println!("    6. Return response");
    println!();
    println!("  CODE CHANGE LOCATION:");
    println!("    File: src/api.rs");
    println!("    Function: openai_completions_handler (line ~2866)");
    println!("    Change: Add batch path before single-request fallback");
    println!();
    println!("  BACKWARD COMPATIBILITY:");
    println!("    - Batch mode is opt-in via AppState configuration");
    println!("    - Default behavior unchanged (single-request)");
    println!("    - No breaking changes to API contract");

    // Test passes as documentation
    assert!(true, "PARITY-051e: Handler modification documented");
}

/// PARITY-051f: Document performance projections
#[test]
fn test_parity051f_performance_projections() {
    // Document expected performance with batch integration

    struct PerformanceProjection {
        scenario: &'static str,
        batch_size: usize,
        projected_toks: f64,
        latency_p50_ms: f64,
        m4_status: &'static str,
    }

    let projections = [
        PerformanceProjection {
            scenario: "Single request (current)",
            batch_size: 1,
            projected_toks: 64.0,
            latency_p50_ms: 15.6, // 1/64 sec
            m4_status: "❌ 3x below",
        },
        PerformanceProjection {
            scenario: "Low concurrency (4 users)",
            batch_size: 4,
            projected_toks: 100.0,
            latency_p50_ms: 40.0,
            m4_status: "❌ 1.9x below",
        },
        PerformanceProjection {
            scenario: "Medium concurrency (16 users)",
            batch_size: 16,
            projected_toks: 192.0,
            latency_p50_ms: 83.0,
            m4_status: "✅ M4 ACHIEVED",
        },
        PerformanceProjection {
            scenario: "High concurrency (32 users)",
            batch_size: 32,
            projected_toks: 256.0,
            latency_p50_ms: 125.0,
            m4_status: "✅ Beyond M4",
        },
    ];

    println!("PARITY-051f: Performance Projections");
    println!("====================================");
    println!();
    println!(
        "  {:30} | {:>10} | {:>12} | {:>12} | {:>12}",
        "Scenario", "Batch Size", "Throughput", "Latency p50", "M4 Status"
    );
    println!(
        "  {:-<30}-|-{:->10}-|-{:->12}-|-{:->12}-|-{:->12}",
        "", "", "", "", ""
    );

    for p in &projections {
        println!(
            "  {:30} | {:>10} | {:>10.0} tok/s | {:>10.1} ms | {}",
            p.scenario, p.batch_size, p.projected_toks, p.latency_p50_ms, p.m4_status
        );
    }

    println!();
    println!("  KEY INSIGHTS:");
    println!("    - M4 parity achieved at 16 concurrent users");
    println!("    - Latency increases with batch size (expected tradeoff)");
    println!("    - Single-request latency unchanged (fallback path)");
    println!();
    println!("  LOAD TESTING PLAN (PARITY-053):");
    println!("    - Use wrk/ab to generate concurrent requests");
    println!("    - Measure throughput at various concurrency levels");
    println!("    - Verify M4 parity (192 tok/s) at 16+ concurrent requests");

    // M4 achieved at batch=16
    let m4_achieved = projections
        .iter()
        .any(|p| p.batch_size == 16 && p.m4_status.contains("ACHIEVED"));
    assert!(m4_achieved, "M4 should be achieved at batch=16");
}