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feat(agent): dialogue state and referential resolution (Slice 6) - #273
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Phase 4.6 Slice 6. Session-scoped working memory for short follow-ups. Domain types: - DialogueState: focus_entities, comparison_set, slots, tool_subjects - FocusEntity: kind + name (city, service, environment, etc.) - DialogueSlot: named key-value pairs (location, timezone) Service: - DialogueStateStore: in-memory HashMap with TTL expiry (30min) - update_state_from_turn(): deterministic entity/slot extraction from user message + tool output + assistant response - Detects: services (.service), cities (weather triggers + "and" split for comparisons), environments (staging/prod/dev) Integration: - handle_inbound_message.rs: updates state after each turn - InboundMessagePorts: carries optional DialogueStateStore - ChannelRuntimeContext: creates store at init This fixes "and the second one?" / "restart it" / "which city?" class of failures where the agent should resolve from session context, not long-term memory. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
Phase 4.6 Slice 6. Session-scoped working memory for short follow-ups.
DialogueState: focus_entities, comparison_set, slots, tool_subjectsDialogueStateStore: in-memory with 30min TTLFixes "and the second one?", "restart it", "which city?" failures.
Test plan
cargo clippy -p synapse_domain --lib -- -D warnings— cleancargo test -p synapse_domain --lib— 480 passed (+8 new)cargo check --features channel-matrix— zero new errors🤖 Generated with Claude Code