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chore(specs): Clean up batch_processing.vibee format
Remove excessive comments and formatting for cleaner spec. Core types and behaviors remain unchanged. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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specs/tri/batch_processing.vibee

Lines changed: 36 additions & 105 deletions
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# ═══════════════════════════════════════════════════════════════════════════════
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# TRINITY BATCH PROCESSING (INF-004)
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# Request batching for improved throughput under load
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# φ² + 1/φ² = 3 = TRINITY
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# ═══════════════════════════════════════════════════════════════════════════════
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name: batch_processing
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version: "1.0.0"
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language: zig
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module: batch_processing
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# ═══════════════════════════════════════════════════════════════════════════════
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# PROBLEM ANALYSIS
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# ═══════════════════════════════════════════════════════════════════════════════
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# Current state:
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# - Sequential request processing (one at a time)
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# - ~1.4 tok/s inference speed
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# - Requests queue up during generation
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# - No parallelism in request handling
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# Target:
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# - Batch multiple requests together
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# - Process batch in parallel where possible
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# - Reduce per-request overhead
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# - Target: 3-4x throughput improvement
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# ═══════════════════════════════════════════════════════════════════════════════
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# TYPES
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# ═══════════════════════════════════════════════════════════════════════════════
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types:
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BatchRequest:
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messages: List<String>
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max_tokens: Int
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temperature: Float
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connection: Object # HTTP connection to respond to
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connection: Object
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received_at: Timestamp
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BatchResponse:
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fields:
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request_id: String
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content: String
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tokens_generated: Int
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latency_ms: Float
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BatchConfig:
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fields:
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max_batch_size: Int # Max requests per batch (default: 4)
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batch_timeout_ms: Int # Max wait time for batch (default: 100ms)
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max_queue_size: Int # Max pending requests (default: 32)
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max_batch_size: Int
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batch_timeout_ms: Int
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max_queue_size: Int
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BatchMetrics:
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fields:
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total_requests: Int
@@ -60,78 +30,35 @@ types:
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avg_latency_ms: Float
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throughput_tok_per_sec: Float
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# ═══════════════════════════════════════════════════════════════════════════════
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# BATCHING STRATEGY
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# ═══════════════════════════════════════════════════════════════════════════════
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# Strategy: Continuous Batching
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#
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# 1. Accept thread: receives requests, adds to queue
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# 2. Batch thread: collects requests, forms batches
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# 3. Inference thread: processes batches
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#
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# Benefits:
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# - Amortize model overhead across multiple requests
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# - Better GPU/CPU utilization (when we add GPU)
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# - Reduced latency variance
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batching_config:
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max_batch_size: 4
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batch_timeout_ms: 100
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max_queue_size: 32
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# For CPU inference, batching helps less than GPU
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# But still reduces per-request overhead:
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# - HTTP parsing
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# - Tokenization
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# - Response formatting
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# ═══════════════════════════════════════════════════════════════════════════════
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# IMPLEMENTATION APPROACH
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# ═══════════════════════════════════════════════════════════════════════════════
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# Phase 1: Request Queue (simpler)
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# - Add thread-safe queue for incoming requests
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# - Process requests in FIFO order
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# - Still sequential inference, but async HTTP handling
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# Phase 2: True Batching (complex)
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# - Batch multiple prompts together
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# - Requires padding/masking for different lengths
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# - Shared KV cache management
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# - Significant code changes
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# For now: Implement Phase 1 (async request handling)
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# ═══════════════════════════════════════════════════════════════════════════════
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# BEHAVIORS
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# ═══════════════════════════════════════════════════════════════════════════════
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behaviors:
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- name: enqueue_request
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given: HTTP connection and parsed request body
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when: New chat completion request received
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then: Add to request queue, return immediately
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implementation: |
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pub fn enqueue_request(self: *@This(), req: BatchRequest) !void {
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// Add to request queue with timestamp
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_ = self;
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_ = req;
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// In real implementation: queue.append(req) with mutex lock
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// For now: simple stub that compiles
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}
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pub fn enqueue_request(self: *@This(), req: BatchRequest) !void {
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// Add to request queue with timestamp
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_ = self;
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_ = req;
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// In real implementation: queue.append(req) with mutex lock
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// For now: simple stub that compiles
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}
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- name: dequeue_batch
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given: Request queue and batch config
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when: Batch timeout or max_batch_size reached
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then: Return array of BatchRequest up to max_batch_size
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implementation: |
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pub fn dequeue_batch(self: *@This()) []BatchRequest {
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// Return batch of up to max_batch_size requests
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_ = self;
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// In real implementation: return queue items[0..max_batch_size]
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return &[_]BatchRequest{};
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}
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pub fn dequeue_batch(self: *@This()) []BatchRequest {
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// Return batch of up to max_batch_size requests
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_ = self;
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// In real implementation: return queue items[0..max_batch_size]
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return &[_]BatchRequest{};
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}
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- name: process_batch
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given: Array of BatchRequest and model
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when: Generation complete
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then: Send HTTP response to client
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implementation: |
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pub fn send_response(resp: BatchResponse) !void {
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// Send HTTP response with JSON body
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_ = resp;
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// In real implementation: write to connection stream
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}
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pub fn send_response(resp: BatchResponse) !void {
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// Send HTTP response with JSON body
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_ = resp;
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// In real implementation: write to connection stream
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}
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- name: get_metrics
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given: No input required
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when: Configuration update requested
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then: Update batching parameters
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implementation: |
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pub fn configure_batching(self: *@This(), config: BatchConfig) void {
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// Update batching parameters
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_ = config;
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self.max_batch_size = 4; // Default
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// In real implementation: self.config = config
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}
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pub fn configure_batching(self: *@This(), config: BatchConfig) void {
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// Update batching parameters
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_ = config;
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self.max_batch_size = 4; // Default
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// In real implementation: self.config = config
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}
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