Files
codex/codex-rs/memories/README.md
jif-oai fa127be25f Stabilize memory Phase 2 input ordering (#19967)
## Why

Phase 2 still needs to choose the most relevant stage-1 memory outputs
by usage and recency, but exposing that ranking as the rendered
`raw_memories.md` order creates unnecessary large diff. Usage-count or
timestamp changes can reshuffle otherwise unchanged memories, making the
workspace diff noisy and giving the consolidation prompt a misleading
recency signal from file position.
This fix will reduce token consumption

## What Changed

- Keep the existing top-N Phase 2 selection ranking by `usage_count`,
`last_usage`, `source_updated_at`, and `thread_id`.
- Return the selected rows in stable ascending `thread_id` order before
syncing Phase 2 filesystem inputs.
- Update the memory README, raw memories header, and consolidation
prompt so they describe the stable order and tell the prompt to use
metadata and workspace diffs instead of file order as the recency
signal.
- Adjust the memory runtime tests to use deterministic thread IDs and
assert the stable return order separately from the ranked selection
semantics.

## Test Coverage

- Existing memory runtime tests in
`codex-rs/state/src/runtime/memories.rs` now cover the stable returned
ordering for Phase 2 inputs.

---------

Co-authored-by: Codex <noreply@openai.com>
2026-04-28 13:32:05 +02:00

7.3 KiB

Memories

This directory owns reusable memory crates and the memory pipeline documentation.

Runtime orchestration for Phase 1 and Phase 2 still lives in codex-core under codex-rs/core/src/memories/.

Crates

  • codex-rs/memories/read (codex-memories-read) owns the read path: memory developer-instruction injection, memory citation parsing, and read-usage telemetry classification.
  • codex-rs/memories/write (codex-memories-write) owns the write path: Phase 1 and Phase 2 prompt rendering, filesystem artifact helpers, workspace diff helpers, and extension resource pruning.

Prompt Templates

Memory prompt templates live with the crate that uses them:

  • The undated template files are the canonical latest versions used at runtime:
    • read/templates/memories/read_path.md
    • write/templates/memories/stage_one_system.md
    • write/templates/memories/stage_one_input.md
    • write/templates/memories/consolidation.md
  • In codex, edit those undated template files in place.
  • The dated snapshot-copy workflow is used in the separate openai/project/agent_memory/write harness repo, not here.

When it runs

The pipeline is triggered when a root session starts, and only if:

  • the session is not ephemeral
  • the memory feature is enabled
  • the session is not a sub-agent session
  • the state DB is available

It runs asynchronously in the background and executes two phases in order: Phase 1, then Phase 2.

Phase 1: Rollout Extraction (per-thread)

Phase 1 finds recent eligible rollouts and extracts a structured memory from each one.

Eligible rollouts are selected from the state DB using startup claim rules. In practice this means the pipeline only considers rollouts that are:

  • from allowed interactive session sources
  • within the configured age window
  • idle long enough (to avoid summarizing still-active/fresh rollouts)
  • not already owned by another in-flight phase-1 worker
  • within startup scan/claim limits (bounded work per startup)

What it does:

  • claims a bounded set of rollout jobs from the state DB (startup claim)
  • filters rollout content down to memory-relevant response items
  • sends each rollout to a model (in parallel, with a concurrency cap)
  • expects structured output containing:
    • a detailed raw_memory
    • a compact rollout_summary
    • an optional rollout_slug
  • redacts secrets from the generated memory fields
  • stores successful outputs back into the state DB as stage-1 outputs

Concurrency / coordination:

  • Phase 1 runs multiple extraction jobs in parallel (with a fixed concurrency cap) so startup memory generation can process several rollouts at once.
  • Each job is leased/claimed in the state DB before processing, which prevents duplicate work across concurrent workers/startups.
  • Failed jobs are marked with retry backoff, so they are retried later instead of hot-looping.

Job outcomes:

  • succeeded (memory produced)
  • succeeded_no_output (valid run but nothing useful generated)
  • failed (with retry backoff/lease handling in DB)

Phase 1 is the stage that turns individual rollouts into DB-backed memory records.

Phase 2: Global Consolidation

Phase 2 consolidates the latest stage-1 outputs into the filesystem memory artifacts and then runs a dedicated consolidation agent.

What it does:

  • claims a single global phase-2 lock before touching the memories root (so only one consolidation inspects or mutates the workspace at a time)
  • loads a bounded set of stage-1 outputs from the state DB using phase-2 selection rules:
    • ignores memories whose last_usage falls outside the configured max_unused_days window
    • for memories with no last_usage, falls back to generated_at so fresh never-used memories can still be selected
    • ranks eligible memories by usage_count first, then by the most recent last_usage / generated_at
  • computes a completion watermark from the claimed watermark + newest input timestamps
  • syncs local memory artifacts under the memories root:
    • raw_memories.md (merged raw memories, stable ascending thread-id order)
    • rollout_summaries/ (one summary file per selected rollout)
  • keeps the memories root itself as a git-baseline directory, initialized under ~/.codex/memories/.git by codex-git-utils
  • prunes stale rollout summaries that are no longer selected
  • prunes memory extension resource files older than the extension retention window, so cleanup appears in the workspace diff
  • writes phase2_workspace_diff.md in the memories root with the git-style diff from the previous successful Phase 2 baseline to the current worktree
  • if the memory workspace has no changes after artifact sync/pruning, marks the job successful and exits

If the memory workspace has changes, it then:

  • spawns an internal consolidation sub-agent
  • builds the Phase 2 prompt with the path to the generated workspace diff
  • points the agent at phase2_workspace_diff.md for the detailed diff context
  • runs it with no approvals, no network, and local write access only
  • disables collab for that agent (to prevent recursive delegation)
  • watches the agent status and heartbeats the global job lease while it runs
  • resets the memory git baseline after the agent completes successfully; the generated diff file is removed before this reset so deleted content is not kept in the prompt artifact or unreachable git objects
  • marks the phase-2 job success/failure in the state DB when the agent finishes

Selection and workspace-diff behavior:

  • successful Phase 2 runs mark the exact stage-1 snapshots they consumed with selected_for_phase2 = 1 and persist the matching selected_for_phase2_source_updated_at
  • Phase 1 upserts preserve the previous selected_for_phase2 baseline until the next successful Phase 2 run rewrites it
  • Phase 2 loads only the current top-N selected stage-1 inputs, syncs rollout_summaries/ directly to that selection, renders raw_memories.md in stable ascending thread-id order to avoid usage-rank churn, then lets the git-style workspace diff surface additions, modifications, and deletions against the previous successful memory baseline
  • when the selected input set is empty, stale rollout_summaries/ files are removed and raw_memories.md is rewritten to the empty-input placeholder; consolidated outputs such as MEMORY.md, memory_summary.md, and skills/ are left for the agent to update

Watermark behavior:

  • The global phase-2 lock does not use DB watermarks as a dirty check; git workspace dirtiness decides whether an agent needs to run.
  • The global phase-2 job row still tracks an input watermark as bookkeeping for the latest DB input timestamp known when the job was claimed.
  • Phase 2 recomputes a new_watermark using the max of:
    • the claimed watermark
    • the newest source_updated_at timestamp in the stage-1 inputs it actually loaded
  • On success, Phase 2 stores that completion watermark in the DB.
  • This avoids moving the recorded completion watermark backwards, but does not decide whether Phase 2 has work.

In practice, this phase is responsible for refreshing the on-disk memory workspace and producing/updating the higher-level consolidated memory outputs.

Why it is split into two phases

  • Phase 1 scales across many rollouts and produces normalized per-rollout memory records.
  • Phase 2 serializes global consolidation so the shared memory artifacts are updated safely and consistently.