pandrs/ml/serving/
mod.rs

1//! Model Serving and Deployment Module
2//!
3//! This module provides comprehensive model serving and deployment capabilities including
4//! model serialization, REST API serving, model registry, versioning, and deployment
5//! configuration management.
6
7pub mod deployment;
8pub mod endpoints;
9pub mod monitoring;
10pub mod registry;
11pub mod serialization;
12pub mod server;
13
14use crate::core::error::{Error, Result};
15use crate::dataframe::DataFrame;
16use serde::{Deserialize, Serialize};
17use std::collections::HashMap;
18use std::path::Path;
19
20/// Model metadata for serving
21#[derive(Debug, Clone, Serialize, Deserialize)]
22pub struct ModelMetadata {
23    /// Model name
24    pub name: String,
25    /// Model version
26    pub version: String,
27    /// Model type (e.g., "linear_regression", "random_forest", "automl")
28    pub model_type: String,
29    /// Feature names expected by the model
30    pub feature_names: Vec<String>,
31    /// Target column name (for supervised models)
32    pub target_name: Option<String>,
33    /// Model description
34    pub description: String,
35    /// Creation timestamp
36    pub created_at: chrono::DateTime<chrono::Utc>,
37    /// Last updated timestamp
38    pub updated_at: chrono::DateTime<chrono::Utc>,
39    /// Model performance metrics
40    pub metrics: HashMap<String, f64>,
41    /// Additional metadata
42    pub metadata: HashMap<String, String>,
43}
44
45/// Prediction request
46#[derive(Debug, Clone, Serialize, Deserialize)]
47pub struct PredictionRequest {
48    /// Input data for prediction
49    pub data: HashMap<String, serde_json::Value>,
50    /// Optional model version (defaults to latest)
51    pub model_version: Option<String>,
52    /// Optional prediction options
53    pub options: Option<PredictionOptions>,
54}
55
56/// Prediction options
57#[derive(Debug, Clone, Serialize, Deserialize)]
58pub struct PredictionOptions {
59    /// Return prediction probabilities (for classification)
60    pub include_probabilities: Option<bool>,
61    /// Return feature importance scores
62    pub include_feature_importance: Option<bool>,
63    /// Return confidence intervals
64    pub include_confidence_intervals: Option<bool>,
65    /// Custom prediction threshold (for binary classification)
66    pub threshold: Option<f64>,
67}
68
69/// Prediction response
70#[derive(Debug, Clone, Serialize, Deserialize)]
71pub struct PredictionResponse {
72    /// Prediction result
73    pub prediction: serde_json::Value,
74    /// Prediction probabilities (if requested)
75    pub probabilities: Option<HashMap<String, f64>>,
76    /// Feature importance scores (if requested)
77    pub feature_importance: Option<HashMap<String, f64>>,
78    /// Confidence intervals (if requested)
79    pub confidence_intervals: Option<ConfidenceInterval>,
80    /// Model metadata used for prediction
81    pub model_metadata: ModelMetadata,
82    /// Prediction timestamp
83    pub timestamp: chrono::DateTime<chrono::Utc>,
84    /// Processing time in milliseconds
85    pub processing_time_ms: u64,
86}
87
88/// Confidence interval
89#[derive(Debug, Clone, Serialize, Deserialize)]
90pub struct ConfidenceInterval {
91    /// Lower bound
92    pub lower: f64,
93    /// Upper bound
94    pub upper: f64,
95    /// Confidence level (e.g., 0.95 for 95%)
96    pub confidence_level: f64,
97}
98
99/// Batch prediction request
100#[derive(Debug, Clone, Serialize, Deserialize)]
101pub struct BatchPredictionRequest {
102    /// Batch input data
103    pub data: Vec<HashMap<String, serde_json::Value>>,
104    /// Optional model version (defaults to latest)
105    pub model_version: Option<String>,
106    /// Optional prediction options
107    pub options: Option<PredictionOptions>,
108}
109
110/// Batch prediction response
111#[derive(Debug, Clone, Serialize, Deserialize)]
112pub struct BatchPredictionResponse {
113    /// Batch prediction results
114    pub predictions: Vec<PredictionResponse>,
115    /// Batch processing summary
116    pub summary: BatchProcessingSummary,
117}
118
119/// Batch processing summary
120#[derive(Debug, Clone, Serialize, Deserialize)]
121pub struct BatchProcessingSummary {
122    /// Total number of predictions
123    pub total_predictions: usize,
124    /// Number of successful predictions
125    pub successful_predictions: usize,
126    /// Number of failed predictions
127    pub failed_predictions: usize,
128    /// Total processing time in milliseconds
129    pub total_processing_time_ms: u64,
130    /// Average processing time per prediction in milliseconds
131    pub avg_processing_time_ms: f64,
132}
133
134/// Model deployment configuration
135#[derive(Debug, Clone, Serialize, Deserialize)]
136pub struct DeploymentConfig {
137    /// Model name
138    pub model_name: String,
139    /// Model version
140    pub model_version: String,
141    /// Deployment environment (e.g., "development", "staging", "production")
142    pub environment: String,
143    /// Resource allocation
144    pub resources: ResourceConfig,
145    /// Scaling configuration
146    pub scaling: ScalingConfig,
147    /// Health check configuration
148    pub health_check: HealthCheckConfig,
149    /// Monitoring configuration
150    pub monitoring: MonitoringConfig,
151}
152
153/// Resource allocation configuration
154#[derive(Debug, Clone, Serialize, Deserialize)]
155pub struct ResourceConfig {
156    /// CPU cores
157    pub cpu_cores: f64,
158    /// Memory in MB
159    pub memory_mb: u64,
160    /// GPU allocation (if available)
161    pub gpu_memory_mb: Option<u64>,
162    /// Maximum concurrent requests
163    pub max_concurrent_requests: usize,
164}
165
166/// Scaling configuration
167#[derive(Debug, Clone, Serialize, Deserialize)]
168pub struct ScalingConfig {
169    /// Minimum number of instances
170    pub min_instances: usize,
171    /// Maximum number of instances
172    pub max_instances: usize,
173    /// Target CPU utilization for auto-scaling
174    pub target_cpu_utilization: f64,
175    /// Target memory utilization for auto-scaling
176    pub target_memory_utilization: f64,
177    /// Scale up threshold
178    pub scale_up_threshold: f64,
179    /// Scale down threshold
180    pub scale_down_threshold: f64,
181}
182
183/// Health check configuration
184#[derive(Debug, Clone, Serialize, Deserialize)]
185pub struct HealthCheckConfig {
186    /// Health check endpoint path
187    pub path: String,
188    /// Health check interval in seconds
189    pub interval_seconds: u64,
190    /// Health check timeout in seconds
191    pub timeout_seconds: u64,
192    /// Number of consecutive failures before marking unhealthy
193    pub failure_threshold: usize,
194    /// Number of consecutive successes before marking healthy
195    pub success_threshold: usize,
196}
197
198/// Monitoring configuration
199#[derive(Debug, Clone, Serialize, Deserialize)]
200pub struct MonitoringConfig {
201    /// Enable metrics collection
202    pub enable_metrics: bool,
203    /// Enable request logging
204    pub enable_logging: bool,
205    /// Enable distributed tracing
206    pub enable_tracing: bool,
207    /// Metrics export interval in seconds
208    pub metrics_interval_seconds: u64,
209    /// Log level
210    pub log_level: String,
211}
212
213/// Model serving interface trait
214pub trait ModelServing {
215    /// Make a single prediction
216    fn predict(&self, request: &PredictionRequest) -> Result<PredictionResponse>;
217
218    /// Make batch predictions
219    fn predict_batch(&self, request: &BatchPredictionRequest) -> Result<BatchPredictionResponse>;
220
221    /// Get model metadata
222    fn get_metadata(&self) -> &ModelMetadata;
223
224    /// Health check
225    fn health_check(&self) -> Result<HealthStatus>;
226
227    /// Get model information
228    fn info(&self) -> ModelInfo;
229}
230
231/// Health status
232#[derive(Debug, Clone, Serialize, Deserialize)]
233pub struct HealthStatus {
234    /// Overall health status
235    pub status: String,
236    /// Detailed status information
237    pub details: HashMap<String, String>,
238    /// Last health check timestamp
239    pub timestamp: chrono::DateTime<chrono::Utc>,
240}
241
242/// Model information
243#[derive(Debug, Clone, Serialize, Deserialize)]
244pub struct ModelInfo {
245    /// Model metadata
246    pub metadata: ModelMetadata,
247    /// Model statistics
248    pub statistics: ModelStatistics,
249    /// Model configuration
250    pub configuration: HashMap<String, serde_json::Value>,
251}
252
253/// Model statistics
254#[derive(Debug, Clone, Serialize, Deserialize)]
255pub struct ModelStatistics {
256    /// Total number of predictions made
257    pub total_predictions: u64,
258    /// Average prediction time in milliseconds
259    pub avg_prediction_time_ms: f64,
260    /// Error rate (0.0 to 1.0)
261    pub error_rate: f64,
262    /// Throughput (predictions per second)
263    pub throughput_per_second: f64,
264    /// Last prediction timestamp
265    pub last_prediction_at: Option<chrono::DateTime<chrono::Utc>>,
266}
267
268/// Model serving factory
269pub struct ModelServingFactory;
270
271impl ModelServingFactory {
272    /// Create a new model serving instance from a file
273    pub fn from_file<P: AsRef<Path>>(path: P) -> Result<Box<dyn ModelServing>> {
274        let model_path = path.as_ref();
275
276        // Check file extension to determine serialization format
277        match model_path.extension().and_then(|ext| ext.to_str()) {
278            Some("json") => {
279                let serializer = serialization::JsonModelSerializer;
280                serializer.load(model_path)
281            }
282            Some("yaml") | Some("yml") => {
283                let serializer = serialization::YamlModelSerializer;
284                serializer.load(model_path)
285            }
286            Some("toml") => {
287                let serializer = serialization::TomlModelSerializer;
288                serializer.load(model_path)
289            }
290            Some("bin") | Some("pandrs") => {
291                let serializer = serialization::BinaryModelSerializer;
292                serializer.load(model_path)
293            }
294            _ => Err(Error::InvalidInput(format!(
295                "Unsupported model file format: {:?}",
296                model_path.extension()
297            ))),
298        }
299    }
300
301    /// Create a new model serving instance from a model registry
302    pub fn from_registry(
303        registry: &dyn registry::ModelRegistry,
304        model_name: &str,
305        version: Option<&str>,
306    ) -> Result<Box<dyn ModelServing>> {
307        let model_version = version.unwrap_or("latest");
308        registry.load_model(model_name, model_version)
309    }
310
311    /// Create a new model serving instance with deployment configuration
312    pub fn with_deployment_config(
313        model: Box<dyn ModelServing>,
314        config: DeploymentConfig,
315    ) -> Result<deployment::DeployedModel> {
316        deployment::DeployedModel::new(model, config)
317    }
318}
319
320/// Model serving server
321pub struct ModelServer {
322    /// Registered models
323    models: HashMap<String, Box<dyn ModelServing>>,
324    /// Server configuration
325    config: ServerConfig,
326    /// Model registry
327    registry: Option<Box<dyn registry::ModelRegistry>>,
328}
329
330/// Server configuration
331#[derive(Debug, Clone, Serialize, Deserialize)]
332pub struct ServerConfig {
333    /// Server host
334    pub host: String,
335    /// Server port
336    pub port: u16,
337    /// Maximum request size in bytes
338    pub max_request_size: usize,
339    /// Request timeout in seconds
340    pub request_timeout_seconds: u64,
341    /// Enable CORS
342    pub enable_cors: bool,
343    /// Enable authentication
344    pub enable_auth: bool,
345    /// API key (if authentication is enabled)
346    pub api_key: Option<String>,
347}
348
349impl Default for ServerConfig {
350    fn default() -> Self {
351        Self {
352            host: "0.0.0.0".to_string(),
353            port: 8080,
354            max_request_size: 10 * 1024 * 1024, // 10MB
355            request_timeout_seconds: 30,
356            enable_cors: true,
357            enable_auth: false,
358            api_key: None,
359        }
360    }
361}
362
363impl ModelServer {
364    /// Create a new model server
365    pub fn new(config: ServerConfig) -> Self {
366        Self {
367            models: HashMap::new(),
368            config,
369            registry: None,
370        }
371    }
372
373    /// Register a model with the server
374    pub fn register_model(&mut self, name: String, model: Box<dyn ModelServing>) -> Result<()> {
375        if self.models.contains_key(&name) {
376            return Err(Error::InvalidOperation(format!(
377                "Model '{}' is already registered",
378                name
379            )));
380        }
381
382        self.models.insert(name, model);
383        Ok(())
384    }
385
386    /// Unregister a model from the server
387    pub fn unregister_model(&mut self, name: &str) -> Result<()> {
388        if self.models.remove(name).is_none() {
389            return Err(Error::KeyNotFound(format!(
390                "Model '{}' is not registered",
391                name
392            )));
393        }
394
395        Ok(())
396    }
397
398    /// Set model registry
399    pub fn set_registry(&mut self, registry: Box<dyn registry::ModelRegistry>) {
400        self.registry = Some(registry);
401    }
402
403    /// Get list of registered models
404    pub fn list_models(&self) -> Vec<String> {
405        self.models.keys().cloned().collect()
406    }
407
408    /// Get model by name
409    pub fn get_model(&self, name: &str) -> Result<&dyn ModelServing> {
410        self.models
411            .get(name)
412            .map(|model| model.as_ref())
413            .ok_or_else(|| Error::KeyNotFound(format!("Model '{}' not found", name)))
414    }
415
416    /// Start the server (placeholder - actual implementation would use a web framework)
417    pub fn start(&self) -> Result<()> {
418        log::info!(
419            "Starting model server on {}:{}",
420            self.config.host,
421            self.config.port
422        );
423
424        // In a real implementation, this would start an HTTP server
425        // using a framework like warp, axum, or actix-web
426        Err(Error::NotImplemented(
427            "HTTP server implementation requires additional dependencies".to_string(),
428        ))
429    }
430}
431
432// Re-export public types
433pub use deployment::{DeployedModel, DeploymentManager, DeploymentMetrics, DeploymentStatus};
434pub use endpoints::{
435    ApiResponse, BatchPredictionEndpoint, HealthEndpoint, ModelInfoEndpoint, PredictionEndpoint,
436};
437pub use monitoring::{
438    AlertConfig, AlertSeverity, ComparisonOperator, MetricsCollector, ModelMonitor,
439    PerformanceMetrics,
440};
441pub use registry::{
442    FileSystemModelRegistry, InMemoryModelRegistry, ModelRegistry, ModelRegistryEntry,
443};
444pub use serialization::{
445    GenericServingModel, ModelSerializer, SerializableModel, SerializationFormat,
446};
447pub use server::{HttpModelServer, HttpResponse, RequestContext, ServerStats};
pandrs/ml/serving/mod.rs

pandrs/ml/serving/
mod.rs
