The old code wrote a JSON object with named section keys, which
serde_json serialized in alphabetical order — putting conversation
before system, making logs misleading. Write a single flat array
in section order instead, matching what the model actually sees.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
compute_run_stats() walks the conversation AST after each agent
completes, counting messages and tool calls by tool name. Stats
are returned from save_agent_log(), stored on UnconsciousAgent,
and displayed in the agent list UI.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Save all context sections (system, identity, journal, conversation)
to per-agent log files for both subconscious and unconscious agents.
Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
Pick the agent that ran longest ago (or never) instead of
scanning alphabetically. Fairness via min_by_key(last_run).
Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
Gate unconscious agents on 60s of no conscious activity using
sleep_until() instead of polling. Remove COOLDOWN constant — once
idle, agents run back-to-back to keep the GPU busy.
Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
The priority field existed in agent definitions and was serialized
into vLLM requests, but was never actually set — every request went
out with no priority, so vLLM treated them equally. This meant
background graph maintenance agents could preempt the main
conversation.
Add priority to AgentState and set it at each call site:
0 = interactive (main conversation)
1 = surface agent (needs to feed memories promptly)
2 = other subconscious agents
10 = unconscious/standalone agents (batch)
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Loading 23K nodes + building graph was blocking consciousness startup.
Now computed on first trigger cycle (runs async from mind loop).
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
- AutoAgent stored on UnconsciousAgent, swapped out for runs, restored
on completion (same pattern as subconscious agents)
- Agent Arc created before spawn and stored on UnconsciousAgent so
the TUI can lock it to read conversation context live
- run_shared() method on AutoAgent for running with a pre-created Agent
- Default tools: memory_tools (not memory_and_journal_tools)
- trigger/spawn_agent made async for Agent::new()
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
- Scan agents directory for all .agent files instead of hardcoded list
- Persist enabled state to ~/.consciousness/agent-enabled.json
- Spacebar on F3 agent list toggles selected agent on/off
- Both subconscious and unconscious agents support toggle
- Disabled agents shown dimmed with "off" indicator
- New agents default to disabled (safe default)
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Graph health stats (alpha, gini, cc, episodic ratio, consolidation
plan) now computed directly by the unconscious module on startup and
every 10 minutes, instead of fetching from the poc-memory daemon.
F4 screen renamed to hippocampus, stripped down to just the health
gauges — daemon task list removed (agents now shown on F3).
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
- AutoAgent.enabled: universal toggle for any auto agent
- Subconscious: should_trigger checks auto.enabled
- Unconscious: simplified from consolidation-plan-driven budgets to
simple loop with cooldown. Static agent list, max 2 concurrent.
- TUI: unconscious agents shown in F3 subconscious screen under
separator, with enabled/running/runs display
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
- push_node: notify before dropping state lock instead of relocking
- Mind::run: single lock for timeout + turn_active + has_input;
single lock for turn_handle + complete_turn
- Agent triggers (subconscious/unconscious) spawned as async tasks
so they don't block the select loop
- has_pending_input() peek for DMN sleep guard — don't sleep when
there's user input waiting
- unconscious: merge collect_results into trigger, single store load
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Unconscious agents (organize, linker, distill, etc.) run independently
of the conversation context. They create fresh Agent instances, select
target nodes via their .agent file queries, and are scheduled by the
consolidation plan which analyzes graph health metrics.
Key differences from subconscious agents:
- No fork — standalone agents with fresh context
- Self-selecting — queries in .agent files pick target nodes
- Budget-driven — consolidation plan allocates runs per type
- Max 2 concurrent, 60s min interval between same-type runs
Wired into Mind event loop alongside subconscious trigger/collect.
TUI display not yet implemented.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
