use anyhow::{anyhow, Result};
use std::{collections::HashMap, sync::Arc, time::Duration};
use tokio::sync::Mutex as TokioMutex;
use tracing::{debug, error, info, warn};
use super::{
anthropic_provider::AnthropicProvider,
cache::{CacheConfig, ResponseCache},
circuit_breaker::CircuitBreaker,
config::LLMConfig,
cross_modal_reasoning::{
CrossModalConfig, CrossModalInput, CrossModalReasoning, CrossModalResponse,
},
federated_learning::{FederatedCoordinator, FederatedLearningConfig},
fine_tuning::{FineTuningConfig, FineTuningEngine},
health_checker::{HealthCheckConfig, HealthChecker},
local_provider::LocalModelProvider,
neural_architecture_search::{ArchitectureSearch, ArchitectureSearchConfig},
performance_optimization::{
BenchmarkConfig, BenchmarkResult, OptimizationRecommendation, PerformanceConfig,
PerformanceOptimizer, PerformanceReport,
},
providers::LLMProvider,
real_time_adaptation::{AdaptationConfig, InteractionData, RealTimeAdaptation},
token_budget::{BudgetConfig, TokenBudget},
types::{LLMRequest, LLMResponse},
};
use super::manager_types::{
BackupReport, CapabilityStatus, ComprehensiveStats, DetailedMetrics, LockedSession,
RateLimiter, RestoreReport, Session, SessionStats, UsageStats, UsageTracker,
};
#[cfg(feature = "openai")]
use super::openai_provider::OpenAIProvider;
pub struct LLMManager {
pub(crate) config: LLMConfig,
pub(crate) providers: HashMap<String, Box<dyn LLMProvider + Send + Sync>>,
pub(crate) circuit_breakers: HashMap<String, Arc<CircuitBreaker>>,
pub(crate) usage_tracker: TokioMutex<UsageTracker>,
pub(crate) response_cache: Arc<ResponseCache>,
pub(crate) health_checker: Arc<HealthChecker>,
pub(crate) token_budget: Arc<TokenBudget>,
}
impl LLMManager {
pub fn new(config: LLMConfig) -> Result<Self> {
let response_cache = Arc::new(ResponseCache::new(CacheConfig::default()));
let health_checker = Arc::new(HealthChecker::new(HealthCheckConfig::default()));
let token_budget = Arc::new(TokenBudget::new(BudgetConfig::default()));
let mut manager = Self {
providers: HashMap::new(),
circuit_breakers: HashMap::new(),
usage_tracker: TokioMutex::new(UsageTracker::new()),
response_cache,
health_checker,
token_budget,
config,
};
manager.initialize_providers()?;
manager.initialize_circuit_breakers();
manager.initialize_health_monitoring();
Ok(manager)
}
fn initialize_health_monitoring(&self) {
for provider_name in self.providers.keys() {
let health_checker = Arc::clone(&self.health_checker);
let provider_id = provider_name.clone();
tokio::spawn(async move {
health_checker.register_provider(provider_id).await;
});
}
}
fn initialize_providers(&mut self) -> Result<()> {
if let Some(config) = self.config.providers.get("openai") {
if config.enabled {
#[cfg(feature = "openai")]
{
let provider = Box::new(OpenAIProvider::new(config.clone())?);
self.providers.insert("openai".to_string(), provider);
}
#[cfg(not(feature = "openai"))]
{
warn!(
"OpenAI provider is configured and enabled but the `openai` \
feature is not compiled in; skipping registration. Rebuild \
oxirs-chat with `--features openai` to enable it."
);
}
}
}
if let Some(config) = self.config.providers.get("anthropic") {
if config.enabled {
let provider = Box::new(AnthropicProvider::new(config.clone())?);
self.providers.insert("anthropic".to_string(), provider);
}
}
if let Some(config) = self.config.providers.get("local") {
if config.enabled {
let provider = Box::new(LocalModelProvider::new(config.clone())?);
self.providers.insert("local".to_string(), provider);
}
}
Ok(())
}
fn initialize_circuit_breakers(&mut self) {
for provider_name in self.config.providers.keys() {
let circuit_breaker =
Arc::new(CircuitBreaker::new(self.config.circuit_breaker.clone()));
self.circuit_breakers
.insert(provider_name.clone(), circuit_breaker);
}
}
pub async fn generate_response(&mut self, request: LLMRequest) -> Result<LLMResponse> {
let start_time = std::time::Instant::now();
if let Some(cached_response) = self.response_cache.get(&request).await {
debug!("Cache hit for request");
return Ok(cached_response);
}
let user_id = "default_user".to_string();
let estimated_tokens =
self.estimate_input_tokens(&request) + request.max_tokens.unwrap_or(1000);
if let Err(e) = self
.token_budget
.check_budget(&user_id, estimated_tokens as u64)
.await
{
warn!("Token budget exceeded: {}", e);
return Err(e);
}
let provider_chain = self.get_provider_fallback_chain().await;
if provider_chain.is_empty() {
return Err(anyhow!("No providers available"));
}
let mut last_error: Option<anyhow::Error> = None;
for (provider_name, model_name) in provider_chain {
info!(
"Attempting provider: {} with model: {}",
provider_name, model_name
);
if let Some(circuit_breaker) = self.circuit_breakers.get(&provider_name) {
if !circuit_breaker.can_execute().await {
warn!("Circuit breaker is open for provider: {}", provider_name);
continue;
}
}
if !self
.health_checker
.is_provider_healthy(&provider_name)
.await
{
warn!("Provider {} is unhealthy, skipping", provider_name);
continue;
}
match self
.try_provider(&provider_name, &model_name, &request)
.await
{
Ok(response) => {
let elapsed = start_time.elapsed();
self.record_success(&provider_name, elapsed).await;
self.response_cache
.put(&request, response.clone(), provider_name.clone())
.await;
self.token_budget
.record_usage(&user_id, response.usage.total_tokens as u64)
.await?;
{
let mut tracker = self.usage_tracker.lock().await;
tracker.track_usage(
&provider_name,
response.usage.total_tokens,
response.usage.cost,
);
}
info!(
"Successfully generated response using provider {} in {:?}",
provider_name, elapsed
);
return Ok(response);
}
Err(e) => {
let elapsed = start_time.elapsed();
self.record_failure(&provider_name, elapsed).await;
warn!("Provider {} failed: {}", provider_name, e);
last_error = Some(e);
if elapsed.as_millis() < 500 {
debug!("Fast failover to next provider ({}ms)", elapsed.as_millis());
}
continue;
}
}
}
Err(last_error.unwrap_or_else(|| anyhow!("All providers failed")))
}
async fn try_provider(
&self,
provider_name: &str,
model_name: &str,
request: &LLMRequest,
) -> Result<LLMResponse> {
let provider = self
.providers
.get(provider_name)
.ok_or_else(|| anyhow!("Provider {} not found", provider_name))?;
let response = provider.generate(model_name, request).await?;
Ok(response)
}
async fn get_provider_fallback_chain(&self) -> Vec<(String, String)> {
let mut chain = Vec::new();
let priority_order = ["openai", "anthropic", "local"];
for provider_name in priority_order {
if let Some(provider_config) = self.config.providers.get(provider_name) {
if provider_config.enabled && self.providers.contains_key(provider_name) {
if let Some(model) = provider_config.models.first() {
chain.push((provider_name.to_string(), model.name.clone()));
}
}
}
}
chain
}
async fn record_success(&self, provider_name: &str, latency: Duration) {
if let Some(circuit_breaker) = self.circuit_breakers.get(provider_name) {
circuit_breaker.record_result(true, latency).await;
}
let provider_id = provider_name.to_string();
if let Err(e) = self
.health_checker
.record_call(&provider_id, true, latency)
.await
{
error!("Failed to record success for {}: {}", provider_name, e);
}
}
async fn record_failure(&self, provider_name: &str, latency: Duration) {
if let Some(circuit_breaker) = self.circuit_breakers.get(provider_name) {
circuit_breaker.record_result(false, latency).await;
}
let provider_id = provider_name.to_string();
if let Err(e) = self
.health_checker
.record_call(&provider_id, false, latency)
.await
{
error!("Failed to record failure for {}: {}", provider_name, e);
}
}
pub fn estimate_input_tokens(&self, request: &LLMRequest) -> usize {
let total_content: String = request
.messages
.iter()
.map(|m| m.content.as_str())
.chain(request.system_prompt.as_deref())
.collect::<Vec<_>>()
.join(" ");
total_content.len() / 4
}
pub async fn get_circuit_breaker_stats(&self) -> HashMap<String, super::CircuitBreakerStats> {
let mut stats = HashMap::new();
for (provider_name, circuit_breaker) in &self.circuit_breakers {
let provider_stats = circuit_breaker.get_stats().await;
stats.insert(provider_name.clone(), provider_stats);
}
stats
}
pub async fn reset_circuit_breaker(&self, provider_name: &str) -> Result<()> {
if let Some(circuit_breaker) = self.circuit_breakers.get(provider_name) {
circuit_breaker.reset().await?;
Ok(())
} else {
Err(anyhow!(
"Circuit breaker not found for provider: {}",
provider_name
))
}
}
pub async fn get_usage_stats(&self) -> UsageStats {
let tracker = self.usage_tracker.lock().await;
UsageStats {
total_requests: tracker.total_requests,
total_tokens: tracker.total_tokens,
total_cost: tracker.total_cost,
}
}
}
pub struct EnhancedLLMManager {
pub(crate) inner: LLMManager,
pub(crate) rate_limiter: RateLimiter,
pub(crate) sessions: Arc<TokioMutex<HashMap<String, LockedSession>>>,
pub(crate) fine_tuning_engine: Option<Arc<FineTuningEngine>>,
pub(crate) architecture_search: Option<Arc<ArchitectureSearch>>,
pub(crate) federated_coordinator: Option<Arc<FederatedCoordinator>>,
pub(crate) real_time_adaptation: Option<Arc<RealTimeAdaptation>>,
pub(crate) cross_modal_reasoning: Option<Arc<CrossModalReasoning>>,
pub(crate) performance_optimizer: Option<Arc<PerformanceOptimizer>>,
}
impl EnhancedLLMManager {
pub fn new(config: LLMConfig) -> Result<Self> {
let rate_limiter = RateLimiter::new(&config.rate_limits);
let inner = LLMManager::new(config)?;
let sessions = Arc::new(TokioMutex::new(HashMap::new()));
Ok(Self {
inner,
rate_limiter,
sessions,
fine_tuning_engine: None,
architecture_search: None,
federated_coordinator: None,
real_time_adaptation: None,
cross_modal_reasoning: None,
performance_optimizer: None,
})
}
pub fn with_fine_tuning(mut self, config: super::fine_tuning::EngineConfig) -> Self {
self.fine_tuning_engine = Some(Arc::new(FineTuningEngine::new(config)));
self
}
pub fn with_architecture_search(mut self) -> Self {
self.architecture_search = Some(Arc::new(ArchitectureSearch::new()));
self
}
pub fn with_federated_learning(mut self, config: FederatedLearningConfig) -> Self {
self.federated_coordinator = Some(Arc::new(FederatedCoordinator::new(config)));
self
}
pub fn with_real_time_adaptation(mut self, config: AdaptationConfig) -> Self {
self.real_time_adaptation = Some(Arc::new(RealTimeAdaptation::new(config)));
self
}
pub fn with_cross_modal_reasoning(mut self, config: CrossModalConfig) -> Self {
if let Ok(placeholder_manager) = LLMManager::new(LLMConfig::default()) {
let inner_manager = Arc::new(tokio::sync::RwLock::new(placeholder_manager));
self.cross_modal_reasoning =
Some(Arc::new(CrossModalReasoning::new(config, inner_manager)));
}
self
}
pub fn with_performance_optimization(mut self, config: PerformanceConfig) -> Self {
self.performance_optimizer = Some(Arc::new(PerformanceOptimizer::new(config)));
self
}
pub async fn generate_response_with_limits(
&mut self,
request: LLMRequest,
) -> Result<LLMResponse> {
self.rate_limiter.check_rate_limit("default").await?;
self.inner.generate_response(request).await
}
pub async fn with_persistence<P: AsRef<std::path::Path>>(
_store: Arc<dyn oxirs_core::Store>,
persistence_path: P,
) -> Result<Self> {
let path = persistence_path.as_ref();
if !path.exists() {
std::fs::create_dir_all(path)
.map_err(|e| anyhow!("Failed to create persistence directory: {}", e))?;
}
let mut config = LLMConfig::default();
config.rate_limits.burst_allowed = true;
let mut manager = Self::new(config)?;
manager.load_persisted_sessions(path).await?;
manager
.setup_session_persistence(path.to_path_buf())
.await?;
info!(
"Enhanced LLM manager initialized with persistence at: {:?}",
path
);
Ok(manager)
}
async fn load_persisted_sessions<P: AsRef<std::path::Path>>(
&mut self,
persistence_path: P,
) -> Result<()> {
let path = persistence_path.as_ref();
let session_files = std::fs::read_dir(path)
.map_err(|e| anyhow!("Failed to read persistence directory: {}", e))?;
let mut loaded_count = 0;
for entry in session_files.flatten() {
let file_path = entry.path();
if file_path.extension().and_then(|s| s.to_str()) == Some("session") {
if let Some(session_id) = file_path.file_stem().and_then(|s| s.to_str()) {
match self
.load_session_from_file(&file_path, session_id.to_string())
.await
{
Ok(_) => {
loaded_count += 1;
debug!("Loaded session: {}", session_id);
}
Err(e) => {
warn!(
"Failed to load session {} from {:?}: {}",
session_id, file_path, e
);
}
}
}
}
}
info!("Loaded {} persisted sessions", loaded_count);
Ok(())
}
async fn load_session_from_file<P: AsRef<std::path::Path>>(
&mut self,
file_path: P,
session_id: String,
) -> Result<()> {
use tokio::fs::File;
use tokio::io::AsyncReadExt;
let mut file = File::open(file_path).await?;
let mut contents = Vec::new();
file.read_to_end(&mut contents).await?;
let session: Session =
oxicode::serde::decode_from_slice(&contents, oxicode::config::standard())
.map_err(|e| anyhow!("Failed to deserialize session: {}", e))?
.0;
let locked_session = Arc::new(TokioMutex::new(session));
let mut sessions = self.sessions.lock().await;
sessions.insert(session_id, locked_session);
Ok(())
}
async fn setup_session_persistence(&self, persistence_path: std::path::PathBuf) -> Result<()> {
let sessions = Arc::clone(&self.sessions);
let path = persistence_path;
tokio::spawn(async move {
let mut interval = tokio::time::interval(Duration::from_secs(300));
loop {
interval.tick().await;
let sessions_guard = sessions.lock().await;
for (session_id, session_arc) in sessions_guard.iter() {
let session_guard = session_arc.lock().await;
let session_file = path.join(format!("{session_id}.session"));
match Self::save_session_to_file(&session_guard, &session_file).await {
Ok(_) => debug!("Saved session: {}", session_id),
Err(e) => error!("Failed to save session {}: {}", session_id, e),
}
}
}
});
Ok(())
}
async fn save_session_to_file<P: AsRef<std::path::Path>>(
session: &Session,
file_path: P,
) -> Result<()> {
use tokio::fs::File;
use tokio::io::AsyncWriteExt;
let serialized = oxicode::serde::encode_to_vec(session, oxicode::config::standard())
.map_err(|e| anyhow!("Failed to serialize session: {}", e))?;
let temp_path = file_path.as_ref().with_extension("session.tmp");
{
let mut file = File::create(&temp_path).await?;
file.write_all(&serialized).await?;
file.sync_all().await?;
}
std::fs::rename(&temp_path, file_path.as_ref())?;
Ok(())
}
pub async fn get_or_create_session(&self, session_id: String) -> Result<LockedSession> {
let mut sessions = self.sessions.lock().await;
if let Some(session) = sessions.get(&session_id) {
Ok(session.clone())
} else {
let session = Session::new(session_id.clone());
let locked_session = Arc::new(TokioMutex::new(session));
sessions.insert(session_id, locked_session.clone());
Ok(locked_session)
}
}
pub async fn get_session_stats(&self) -> SessionStats {
let sessions = self.sessions.lock().await;
let mut total_duration_secs = 0.0;
let mut valid_sessions = 0;
for session_arc in sessions.values() {
let session = session_arc.lock().await;
let duration = session
.last_activity
.signed_duration_since(chrono::DateTime::<chrono::Utc>::from(session.created_at))
.to_std()
.unwrap_or(Duration::from_secs(0));
total_duration_secs += duration.as_secs_f64();
valid_sessions += 1;
}
let average_session_duration = if valid_sessions > 0 {
total_duration_secs / valid_sessions as f64
} else {
0.0
};
SessionStats {
active_sessions: sessions.len(),
total_sessions: sessions.len(),
average_session_duration,
}
}
pub async fn get_detailed_metrics(&self) -> DetailedMetrics {
let sessions = self.sessions.lock().await;
let mut metrics = DetailedMetrics {
total_sessions: sessions.len(),
active_sessions: sessions.len(),
..Default::default()
};
let mut total_messages = 0;
for session in sessions.values() {
let session_guard = session.lock().await;
total_messages += session_guard.messages.len();
}
metrics.total_messages = total_messages;
metrics
}
pub async fn backup_sessions<P: AsRef<std::path::Path>>(
&self,
backup_path: &P,
) -> Result<BackupReport> {
let sessions = self.sessions.lock().await;
let backup_dir = backup_path.as_ref();
tokio::fs::create_dir_all(backup_dir)
.await
.map_err(|e| anyhow!("Failed to create backup directory: {}", e))?;
let mut successful_backups = 0;
let mut failed_backups = 0;
let mut total_size = 0u64;
for (session_id, session_arc) in sessions.iter() {
match session_arc.try_lock() {
Ok(session) => {
let session_data = serde_json::to_string(&*session).map_err(|e| {
anyhow!("Failed to serialize session {}: {}", session_id, e)
})?;
let session_file = backup_dir.join(format!("{session_id}.json"));
match tokio::fs::write(&session_file, &session_data).await {
Ok(_) => {
successful_backups += 1;
total_size += session_data.len() as u64;
debug!("Successfully backed up session: {}", session_id);
}
Err(e) => {
failed_backups += 1;
warn!("Failed to backup session {}: {}", session_id, e);
}
}
}
Err(_) => {
failed_backups += 1;
warn!("Session {} is locked, skipping backup", session_id);
}
}
}
info!(
"Backup completed: {} successful, {} failed, {} bytes",
successful_backups, failed_backups, total_size
);
Ok(BackupReport {
sessions_backed_up: successful_backups,
backup_size: total_size,
backup_path: backup_dir.to_string_lossy().to_string(),
successful_backups,
failed_backups,
})
}
pub async fn remove_session(&self, session_id: &str) -> Result<()> {
let mut sessions = self.sessions.lock().await;
sessions.remove(session_id);
Ok(())
}
pub async fn restore_sessions<P: AsRef<std::path::Path>>(
&self,
restore_path: &P,
) -> Result<RestoreReport> {
let restore_dir = restore_path.as_ref();
let mut sessions = self.sessions.lock().await;
if !restore_dir.exists() {
return Err(anyhow!(
"Restore directory does not exist: {:?}",
restore_dir
));
}
let mut sessions_restored = 0;
let mut failed_restorations = 0;
let mut total_size = 0u64;
let mut dir_entries = tokio::fs::read_dir(restore_dir)
.await
.map_err(|e| anyhow!("Failed to read restore directory: {}", e))?;
while let Some(entry) = dir_entries
.next_entry()
.await
.map_err(|e| anyhow!("Failed to read directory entry: {}", e))?
{
let path = entry.path();
if path.extension().and_then(|s| s.to_str()) == Some("json") {
match self.restore_single_session(&path).await {
Ok((session_id, session_arc)) => {
if let Ok(metadata) = tokio::fs::metadata(&path).await {
total_size += metadata.len();
}
sessions.insert(session_id.clone(), session_arc);
sessions_restored += 1;
info!("Successfully restored session: {}", session_id);
}
Err(e) => {
failed_restorations += 1;
warn!("Failed to restore session from {:?}: {}", path, e);
}
}
}
}
info!(
"Restore completed: {} sessions restored, {} failed, {} bytes processed",
sessions_restored, failed_restorations, total_size
);
Ok(RestoreReport {
sessions_restored,
restore_size: total_size,
restore_path: restore_dir.to_string_lossy().to_string(),
failed_restorations,
})
}
async fn restore_single_session<P: AsRef<std::path::Path>>(
&self,
session_file: P,
) -> Result<(String, LockedSession)> {
let session_data = tokio::fs::read_to_string(&session_file)
.await
.map_err(|e| anyhow!("Failed to read session file: {}", e))?;
let session: Session = serde_json::from_str(&session_data)
.map_err(|e| anyhow!("Failed to deserialize session: {}", e))?;
let session_id = session.id.clone();
let locked_session = Arc::new(TokioMutex::new(session));
Ok((session_id, locked_session))
}
pub async fn cleanup_expired_sessions(&self) -> Result<usize> {
let mut sessions = self.sessions.lock().await;
let now = chrono::Utc::now();
let mut removed_count = 0;
let mut sessions_to_remove = Vec::new();
for (session_id, session_arc) in sessions.iter() {
match session_arc.try_lock() {
Ok(session_guard) => {
let hours_inactive = now
.signed_duration_since(session_guard.last_activity)
.num_hours();
if hours_inactive > 1 {
sessions_to_remove.push(session_id.clone());
debug!(
"Marking session {} for removal (inactive for {} hours)",
session_id, hours_inactive
);
}
}
Err(_) => {
debug!(
"Session {} is locked, skipping expiration check",
session_id
);
}
}
}
for session_id in sessions_to_remove {
if sessions.remove(&session_id).is_some() {
removed_count += 1;
info!("Removed expired session: {}", session_id);
}
}
if removed_count > 0 {
info!(
"Cleanup completed: removed {} expired sessions",
removed_count
);
}
Ok(removed_count)
}
pub async fn get_session(&self, session_id: &str) -> Result<Option<LockedSession>> {
let sessions = self.sessions.lock().await;
Ok(sessions.get(session_id).cloned())
}
pub async fn submit_fine_tuning_job(&self, config: FineTuningConfig) -> Result<String> {
if let Some(engine) = &self.fine_tuning_engine {
engine.submit_job(config).await
} else {
Err(anyhow!("Fine-tuning engine not enabled"))
}
}
pub async fn get_fine_tuning_status(
&self,
job_id: &str,
) -> Result<super::fine_tuning::FineTuningJob> {
if let Some(engine) = &self.fine_tuning_engine {
engine.get_job_status(job_id).await
} else {
Err(anyhow!("Fine-tuning engine not enabled"))
}
}
pub async fn start_architecture_search(
&self,
config: ArchitectureSearchConfig,
) -> Result<String> {
if let Some(search) = &self.architecture_search {
search.start_search(config).await
} else {
Err(anyhow!("Architecture search not enabled"))
}
}
pub async fn get_architecture_search_status(
&self,
search_id: &str,
) -> Result<super::neural_architecture_search::SearchState> {
if let Some(search) = &self.architecture_search {
search.get_search_status(search_id).await
} else {
Err(anyhow!("Architecture search not enabled"))
}
}
pub async fn start_federation_round(&self) -> Result<usize> {
if let Some(coordinator) = &self.federated_coordinator {
coordinator.start_federation_round().await
} else {
Err(anyhow!("Federated learning not enabled"))
}
}
pub async fn register_federated_node(
&self,
node: super::federated_learning::FederatedNode,
) -> Result<()> {
if let Some(coordinator) = &self.federated_coordinator {
coordinator.register_node(node).await
} else {
Err(anyhow!("Federated learning not enabled"))
}
}
pub async fn process_adaptation_interaction(
&self,
request: &LLMRequest,
response: &LLMResponse,
) -> Result<()> {
if let Some(adaptation) = &self.real_time_adaptation {
let interaction = InteractionData {
interaction_id: format!("interaction_{}", uuid::Uuid::new_v4()),
request: request.clone(),
response: response.clone(),
user_feedback: None,
context_information: super::real_time_adaptation::ContextInformation {
user_profile: super::real_time_adaptation::UserProfile {
user_id: "default_user".to_string(),
expertise_level: super::real_time_adaptation::ExpertiseLevel::Intermediate,
preferences: super::real_time_adaptation::UserPreferences {
response_style:
super::real_time_adaptation::ResponseStyle::Conversational,
detail_level: super::real_time_adaptation::DetailLevel::Medium,
preferred_formats: vec!["text".to_string()],
language_preferences: vec!["en".to_string()],
},
interaction_history: super::real_time_adaptation::InteractionHistory {
total_interactions: 0,
average_satisfaction: 0.8,
common_topics: vec![],
feedback_patterns: HashMap::new(),
},
},
session_context: super::real_time_adaptation::SessionContext {
session_id: "default_session".to_string(),
session_duration: Duration::from_secs(300),
conversation_flow: super::real_time_adaptation::ConversationFlow {
topic_transitions: vec![],
question_types: vec![],
complexity_progression: vec![],
},
current_objectives: vec![],
},
domain_context: super::real_time_adaptation::DomainContext {
primary_domain: "general".to_string(),
secondary_domains: vec![],
domain_expertise_required: 0.5,
domain_specific_patterns: HashMap::new(),
},
temporal_context: super::real_time_adaptation::TemporalContext {
time_of_day: "day".to_string(),
day_of_week: "weekday".to_string(),
seasonal_patterns: vec![],
trending_topics: vec![],
},
},
timestamp: std::time::SystemTime::now(),
};
adaptation.process_interaction(interaction).await
} else {
Ok(())
}
}
pub async fn generate_enhanced_response(&mut self, request: LLMRequest) -> Result<LLMResponse> {
let response = self.generate_response_with_limits(request.clone()).await?;
self.process_adaptation_interaction(&request, &response)
.await?;
Ok(response)
}
pub async fn perform_cross_modal_reasoning(
&self,
input: CrossModalInput,
query: &str,
) -> Result<CrossModalResponse> {
if let Some(reasoning) = &self.cross_modal_reasoning {
reasoning.reason(input, query).await.map_err(|e| anyhow!(e))
} else {
Err(anyhow!("Cross-modal reasoning not enabled"))
}
}
pub async fn get_cross_modal_history(&self) -> Result<Vec<CrossModalResponse>> {
if let Some(reasoning) = &self.cross_modal_reasoning {
Ok(reasoning.get_reasoning_history().await)
} else {
Err(anyhow!("Cross-modal reasoning not enabled"))
}
}
pub async fn clear_cross_modal_history(&self) -> Result<()> {
if let Some(reasoning) = &self.cross_modal_reasoning {
reasoning.clear_history().await;
Ok(())
} else {
Err(anyhow!("Cross-modal reasoning not enabled"))
}
}
pub async fn get_cross_modal_stats(
&self,
) -> Result<super::cross_modal_reasoning::CrossModalStats> {
if let Some(reasoning) = &self.cross_modal_reasoning {
Ok(reasoning.get_stats().await)
} else {
Err(anyhow!("Cross-modal reasoning not enabled"))
}
}
pub async fn optimize_request(
&self,
request: &LLMRequest,
) -> Result<super::performance_optimization::OptimizedRequest> {
if let Some(optimizer) = &self.performance_optimizer {
optimizer
.optimize_request(request)
.await
.map_err(|e| anyhow!(e))
} else {
Err(anyhow!("Performance optimization not enabled"))
}
}
pub async fn run_benchmark(&self, config: BenchmarkConfig) -> Result<BenchmarkResult> {
if let Some(optimizer) = &self.performance_optimizer {
optimizer
.benchmark_system(config)
.await
.map_err(|e| anyhow!(e))
} else {
Err(anyhow!("Performance optimization not enabled"))
}
}
pub async fn get_optimization_recommendations(
&self,
) -> Result<Vec<OptimizationRecommendation>> {
if let Some(optimizer) = &self.performance_optimizer {
optimizer
.generate_optimization_recommendations()
.await
.map_err(|e| anyhow!(e))
} else {
Err(anyhow!("Performance optimization not enabled"))
}
}
pub async fn get_performance_report(&self) -> Result<PerformanceReport> {
if let Some(optimizer) = &self.performance_optimizer {
optimizer
.get_performance_report()
.await
.map_err(|e| anyhow!(e))
} else {
Err(anyhow!("Performance optimization not enabled"))
}
}
pub async fn get_comprehensive_stats(&self) -> Result<ComprehensiveStats> {
let basic_stats = self.get_session_stats().await;
let fine_tuning_stats = if let Some(engine) = &self.fine_tuning_engine {
Some(engine.get_training_statistics().await?)
} else {
None
};
let federation_stats = if let Some(coordinator) = &self.federated_coordinator {
Some(coordinator.get_federation_statistics().await?)
} else {
None
};
let adaptation_metrics = if let Some(adaptation) = &self.real_time_adaptation {
Some(adaptation.get_adaptation_metrics().await?)
} else {
None
};
let cross_modal_stats = if let Some(reasoning) = &self.cross_modal_reasoning {
Some(reasoning.get_stats().await)
} else {
None
};
let performance_report = if let Some(optimizer) = &self.performance_optimizer {
Some(
optimizer
.get_performance_report()
.await
.unwrap_or_else(|_| PerformanceReport {
current_metrics:
super::performance_optimization::PerformanceMetrics::default(),
benchmark_results: Vec::new(),
recommendations: Vec::new(),
cache_statistics: super::performance_optimization::CacheStatistics {
total_entries: 0,
total_size_bytes: 0,
hit_rate: 0.0,
miss_rate: 1.0,
eviction_count: 0,
average_access_count: 0.0,
average_compression_ratio: 0.0,
},
compression_statistics:
super::performance_optimization::CompressionStatistics {
total_compressed_requests: 0,
average_compression_ratio: 0.0,
total_bytes_saved: 0,
compression_time_average: Duration::from_millis(0),
},
optimization_summary:
super::performance_optimization::OptimizationSummary {
overall_performance_score: 0.0,
target_achievement_rate: 0.0,
bottleneck_analysis: Vec::new(),
improvement_potential: 0.0,
optimization_status:
super::performance_optimization::OptimizationStatus::Critical,
},
generated_at: std::time::SystemTime::now(),
}),
)
} else {
None
};
Ok(ComprehensiveStats {
session_stats: basic_stats,
fine_tuning_stats,
federation_stats,
adaptation_metrics,
cross_modal_stats,
performance_report,
version: "1.3+".to_string(),
capabilities_enabled: CapabilityStatus {
fine_tuning: self.fine_tuning_engine.is_some(),
architecture_search: self.architecture_search.is_some(),
federated_learning: self.federated_coordinator.is_some(),
real_time_adaptation: self.real_time_adaptation.is_some(),
cross_modal_reasoning: self.cross_modal_reasoning.is_some(),
performance_optimization: self.performance_optimizer.is_some(),
},
})
}
}