symbi-runtime 1.19.0

Agent Runtime System for the Symbi platform
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//! Coordinator session and shared state.
//!
//! Each WebSocket connection gets its own [`CoordinatorSession`] which holds
//! the persistent [`Conversation`] state and drives the [`ReasoningLoopRunner`]
//! for each user message. [`CoordinatorState`] is shared across connections
//! and holds the inference provider, policy gate, and runtime provider.

#[cfg(feature = "http-api")]
use std::sync::Arc;

#[cfg(feature = "http-api")]
use tokio::sync::mpsc;

#[cfg(feature = "http-api")]
use uuid::Uuid;

#[cfg(feature = "http-api")]
use crate::reasoning::circuit_breaker::CircuitBreakerRegistry;
#[cfg(feature = "http-api")]
use crate::reasoning::context_manager::DefaultContextManager;
#[cfg(feature = "http-api")]
use crate::reasoning::conversation::{Conversation, ConversationMessage};
#[cfg(feature = "http-api")]
use crate::reasoning::inference::{InferenceProvider, ToolDefinition};
#[cfg(feature = "http-api")]
use crate::reasoning::loop_types::{
    BufferedJournal, JournalEntry, LoopConfig, LoopEvent, TerminationReason,
};
#[cfg(feature = "http-api")]
use crate::reasoning::policy_bridge::ReasoningPolicyGate;
#[cfg(feature = "http-api")]
use crate::reasoning::reasoning_loop::ReasoningLoopRunner;
#[cfg(feature = "http-api")]
use crate::types::AgentId;

#[cfg(feature = "http-api")]
use super::coordinator_executor::CoordinatorExecutor;
#[cfg(feature = "http-api")]
use super::streaming_journal::StreamingJournal;
#[cfg(feature = "http-api")]
use super::traits::RuntimeApiProvider;
#[cfg(feature = "http-api")]
use super::ws_types::ServerMessage;

/// System prompt for the coordinator agent.
#[cfg(feature = "http-api")]
const COORDINATOR_SYSTEM_PROMPT: &str = "\
You are the Symbiont Coordinator, a meta-agent for the Symbiont runtime.
You help operators monitor, inspect, and manage the agent fleet.
Be concise and factual. Format data clearly.
Every action you propose is policy-evaluated before it runs.
Your own actions are journaled to the operator's session; a delegated agent's \
internal steps are policy-evaluated but are not journaled to the operator.";

/// Shared state across all coordinator WebSocket connections.
#[cfg(feature = "http-api")]
pub struct CoordinatorState {
    pub provider: Arc<dyn InferenceProvider>,
    pub policy_gate: Arc<dyn ReasoningPolicyGate>,
    pub runtime_provider: Arc<dyn RuntimeApiProvider>,
    pub tool_definitions: Vec<ToolDefinition>,
    pub loop_config: LoopConfig,
    /// Live RAG retrieval bridge, or `None` when RAG is not configured/available.
    pub knowledge_bridge: Option<Arc<crate::reasoning::knowledge_bridge::KnowledgeBridge>>,
    /// Stable namespace used for all coordinator knowledge store/recall calls.
    /// Generated once per process so knowledge persists across turns and
    /// sessions (single-runtime deployment). Must stay stable across the
    /// process lifetime; if per-agent search filtering is added later, this
    /// id is what identifies the coordinator's own knowledge namespace.
    pub knowledge_agent_id: AgentId,
    /// In-process agent-to-agent delegation handle, or `None` when no `./agents`
    /// registry was configured. Built once at construction via `with_delegation`.
    pub delegation: Option<Arc<dyn crate::reasoning::delegation::DelegationExecutor>>,
}

#[cfg(feature = "http-api")]
impl CoordinatorState {
    /// Create a new coordinator state with default loop config.
    pub fn new(
        provider: Arc<dyn InferenceProvider>,
        policy_gate: Arc<dyn ReasoningPolicyGate>,
        runtime_provider: Arc<dyn RuntimeApiProvider>,
    ) -> Self {
        let tool_definitions = CoordinatorExecutor::tool_definitions(&[]);
        Self {
            provider,
            policy_gate,
            runtime_provider,
            tool_definitions,
            loop_config: LoopConfig {
                max_iterations: 10,
                max_total_tokens: 50_000,
                timeout: std::time::Duration::from_secs(120),
                ..Default::default()
            },
            knowledge_bridge: None,
            knowledge_agent_id: AgentId::new(),
            delegation: None,
        }
    }

    /// Build and attach the live RAG knowledge bridge when RAG is usable
    /// (the `vector-lancedb` feature is built AND an embedding provider is
    /// configured). Otherwise leaves `knowledge_bridge` as `None` after logging
    /// the reason. Async because building the context manager opens the vector
    /// store.
    pub async fn with_rag(mut self, agent_id: &str) -> Self {
        self.knowledge_bridge = build_knowledge_bridge(agent_id).await;
        self
    }

    /// Build the in-process delegation handle from a name→system-prompt registry
    /// (scanned from `./agents`). Sub-loops reuse the coordinator's deps + a
    /// fresh BufferedJournal (delegate internals are not streamed to the client).
    /// No registry entries → still constructs a handle whose every lookup misses
    /// with an honest error; pass an empty map to disable.
    pub fn with_delegation(mut self, registry: std::collections::HashMap<String, String>) -> Self {
        use crate::reasoning::delegation_executor::SubLoopDelegationExecutor;

        // The model picks delegation targets from the tool description, so the
        // advertised names must be exactly the registry keys that resolve.
        let mut names: Vec<String> = registry.keys().cloned().collect();
        names.sort();
        self.tool_definitions = CoordinatorExecutor::tool_definitions(&names);

        let executor: Arc<dyn crate::reasoning::executor::ActionExecutor> =
            Arc::new(CoordinatorExecutor::new(self.runtime_provider.clone()));
        let delegation = SubLoopDelegationExecutor::new(
            self.provider.clone(),
            executor,
            self.policy_gate.clone(),
            Arc::new(DefaultContextManager::default()),
            Arc::new(CircuitBreakerRegistry::default()),
            Arc::new(BufferedJournal::new(500)),
            registry,
            3,
        );
        self.delegation = Some(delegation);
        self
    }
}

/// Construct a live `KnowledgeBridge` over a real `StandardContextManager`
/// backed by LanceDB, or return `None` (with a loud log) when RAG cannot run.
#[cfg(all(feature = "http-api", feature = "vector-lancedb"))]
async fn build_knowledge_bridge(
    agent_id: &str,
) -> Option<Arc<crate::reasoning::knowledge_bridge::KnowledgeBridge>> {
    use crate::context::embedding::EmbeddingConfig;
    use crate::context::manager::{ContextManagerConfig, StandardContextManager};
    use crate::context::vector_db_factory::VectorBackendConfig;
    use crate::context::vector_db_lance::LanceDbConfig;
    use crate::reasoning::knowledge_bridge::{KnowledgeBridge, KnowledgeConfig};

    let Some(embed_cfg) = EmbeddingConfig::from_env() else {
        tracing::warn!(
            "RAG retrieval disabled: no embedding provider configured (set EMBEDDING_* or \
             OPENAI_API_KEY). Chat will run without knowledge retrieval."
        );
        return None;
    };

    let cfg = ContextManagerConfig {
        enable_vector_db: true,
        vector_backend: Some(VectorBackendConfig::LanceDb(LanceDbConfig {
            vector_dimension: embed_cfg.dimension,
            ..Default::default()
        })),
        ..Default::default()
    };

    match StandardContextManager::new(cfg, agent_id).await {
        Ok(scm) => {
            tracing::info!(
                "RAG knowledge bridge constructed (vector-lancedb + embedding provider); \
                 retrieval will be inactive if the vector backend failed to initialize \
                 (see warnings above)"
            );
            Some(Arc::new(KnowledgeBridge::new(
                Arc::new(scm),
                KnowledgeConfig::default(),
            )))
        }
        Err(e) => {
            tracing::warn!("RAG retrieval disabled: failed to build context manager: {e}");
            None
        }
    }
}

/// Without the `vector-lancedb` feature there is no real vector backend, so RAG
/// stays off honestly.
#[cfg(all(feature = "http-api", not(feature = "vector-lancedb")))]
async fn build_knowledge_bridge(
    _agent_id: &str,
) -> Option<Arc<crate::reasoning::knowledge_bridge::KnowledgeBridge>> {
    tracing::warn!(
        "RAG retrieval disabled: built without the 'vector-lancedb' feature. \
         Rebuild with --features vector-lancedb to enable knowledge retrieval."
    );
    None
}

/// Per-connection session that holds conversation state.
#[cfg(feature = "http-api")]
pub struct CoordinatorSession {
    state: Arc<CoordinatorState>,
    conversation: Conversation,
    ws_tx: mpsc::Sender<ServerMessage>,
    session_id: String,
}

#[cfg(feature = "http-api")]
impl CoordinatorSession {
    /// Create a new session for a WebSocket connection.
    pub fn new(state: Arc<CoordinatorState>, ws_tx: mpsc::Sender<ServerMessage>) -> Self {
        Self {
            state,
            conversation: Conversation::with_system(COORDINATOR_SYSTEM_PROMPT),
            ws_tx,
            session_id: Uuid::new_v4().to_string(),
        }
    }

    /// Handle a chat message from the user.
    ///
    /// Runs the reasoning loop and streams events to the WebSocket client.
    pub async fn handle_chat(&mut self, content: String) {
        let request_id = Uuid::new_v4().to_string();

        // Push user message into conversation
        self.conversation.push(ConversationMessage::user(&content));

        // Set up streaming journal
        let inner_journal = Arc::new(BufferedJournal::new(500));
        let (journal_tx, mut journal_rx) = mpsc::channel::<JournalEntry>(64);
        let streaming_journal = Arc::new(StreamingJournal::new(inner_journal, journal_tx));

        // Build executor
        let executor = Arc::new(CoordinatorExecutor::new(
            self.state.runtime_provider.clone(),
        ));

        // Build loop config with tool definitions
        let mut config = self.state.loop_config.clone();
        config.tool_definitions = self.state.tool_definitions.clone();

        // Build the runner
        let runner = ReasoningLoopRunner {
            provider: self.state.provider.clone(),
            policy_gate: self.state.policy_gate.clone(),
            executor,
            context_manager: Arc::new(DefaultContextManager::default()),
            circuit_breakers: Arc::new(CircuitBreakerRegistry::default()),
            journal: streaming_journal,
            knowledge_bridge: self.state.knowledge_bridge.clone(),
            delegation: self.state.delegation.clone(),
        };

        // Spawn the journal→WebSocket bridge task
        let ws_tx = self.ws_tx.clone();
        let bridge_request_id = request_id.clone();
        let bridge_handle = tokio::spawn(async move {
            while let Some(entry) = journal_rx.recv().await {
                let msg = match &entry.event {
                    LoopEvent::ReasoningComplete { actions, .. } => {
                        // Report tool call starts
                        for action in actions {
                            if let crate::reasoning::loop_types::ProposedAction::ToolCall {
                                call_id,
                                name,
                                arguments,
                            } = action
                            {
                                if let Err(e) = ws_tx
                                    .send(ServerMessage::ToolCallStarted {
                                        request_id: bridge_request_id.clone(),
                                        call_id: call_id.clone(),
                                        tool_name: name.clone(),
                                        arguments: arguments.clone(),
                                    })
                                    .await
                                {
                                    tracing::debug!(
                                        request_id = %bridge_request_id,
                                        call_id = %call_id,
                                        error = %e,
                                        "WS tool_call_started send failed — client likely disconnected"
                                    );
                                }
                            }
                        }
                        None
                    }
                    LoopEvent::PolicyEvaluated {
                        action_count,
                        denied_count,
                        ..
                    } => {
                        if *denied_count > 0 {
                            Some(ServerMessage::PolicyDecision {
                                request_id: bridge_request_id.clone(),
                                action: format!("{} actions", action_count),
                                decision: "partial_deny".into(),
                                reason: format!("{} denied", denied_count),
                            })
                        } else {
                            Some(ServerMessage::PolicyDecision {
                                request_id: bridge_request_id.clone(),
                                action: format!("{} actions", action_count),
                                decision: "allow".into(),
                                reason: "All actions approved".into(),
                            })
                        }
                    }
                    LoopEvent::ObservationsCollected { .. } => {
                        // Tool results are embedded in the final response
                        None
                    }
                    _ => None,
                };

                if let Some(msg) = msg {
                    if let Err(e) = ws_tx.send(msg).await {
                        tracing::debug!(
                            request_id = %bridge_request_id,
                            error = %e,
                            "WS policy/bridge send failed — client likely disconnected"
                        );
                    }
                }
            }
        });

        // Run the reasoning loop. The coordinator uses one stable knowledge
        // namespace (set once at process start) so store/recall persist
        // across turns and sessions in this single-runtime deployment; keep
        // this stable if per-agent search filtering is added later.
        let agent_id = self.state.knowledge_agent_id;
        tracing::info!(
            session_id = %self.session_id,
            request_id = %request_id,
            "Starting coordinator reasoning loop"
        );

        let result = runner
            .run(agent_id, self.conversation.clone(), config)
            .await;

        // Wait for bridge to drain
        drop(runner);
        if let Err(e) = bridge_handle.await {
            tracing::warn!(
                session_id = %self.session_id,
                error = %e,
                "Coordinator journal->WS bridge task joined with error"
            );
        }

        // Send final chat chunk
        if let Err(e) = self
            .ws_tx
            .send(ServerMessage::ChatChunk {
                request_id: request_id.clone(),
                content: result.output.clone(),
                done: true,
            })
            .await
        {
            tracing::debug!(
                request_id = %request_id,
                error = %e,
                "Final WS ChatChunk send failed — client likely disconnected"
            );
        }

        // Check for errors
        if let TerminationReason::Error { ref message } = result.termination_reason {
            if let Err(e) = self
                .ws_tx
                .send(ServerMessage::Error {
                    request_id: Some(request_id),
                    code: "LOOP_ERROR".into(),
                    message: message.clone(),
                })
                .await
            {
                tracing::debug!(
                    error = %e,
                    "WS Error message send failed — client likely disconnected"
                );
            }
        }

        // Push assistant response into conversation for context continuity
        self.conversation
            .push(ConversationMessage::assistant(&result.output));

        tracing::info!(
            session_id = %self.session_id,
            iterations = result.iterations,
            tokens = result.total_usage.total_tokens,
            "Coordinator reasoning loop complete"
        );
    }
}

#[cfg(all(test, feature = "http-api"))]
mod rag_wiring_tests {
    use super::*;

    #[tokio::test]
    #[serial_test::serial(embedding_env)]
    async fn build_knowledge_bridge_returns_none_without_embedding_provider() {
        // Clear every env var that EmbeddingConfig::from_env() reads so
        // from_env() is guaranteed to return None regardless of ambient env.
        for k in [
            "EMBEDDING_API_KEY",
            "OPENAI_API_KEY",
            "EMBEDDING_API_BASE_URL",
            "OPENAI_API_BASE_URL",
            "EMBEDDING_PROVIDER",
            "EMBEDDING_MODEL",
            "VECTOR_DIMENSION",
        ] {
            std::env::remove_var(k);
        }
        let bridge = build_knowledge_bridge("test-agent").await;
        assert!(
            bridge.is_none(),
            "with no embedding provider configured, RAG must stay off (None)"
        );
    }
}