Add support for AUTHENTIK_TOKEN_FILE environment variable fallback to
service_orchestrator.py, configure_vault_authentik.py, and the Rust
authentik_agent_manager CLI/MCP server. This prevents hardcoding or
exposing raw tokens in environment blocks or CLI arguments. Document
the new Authentik SSO stack deployment on cupfox k3s in AGENTS.md and
update .mcp.json.full configuration.
Build: 0 jobs, 0 errors (lake build)
- gremlin_appflowy_bridge.py: deprecated shim → delegates to new module
- gremlin_lean_report.py: generates JSON + Markdown reports from Gremlin
with module theorem counts, sorries, import/dependency metrics
- AppFloyo Cloud v0.16.5 lacks programmatic database REST API;
reports can be imported via AppFloyo UI instead
- GoTrue auth (port 9999) is working for future API use
- Set SIGNUPS_ALLOWED=false in Vaultwarden environment on cupfox to disable public signups.
- Automated OIDC/Proxy setup via configure_vault_authentik.py by registering proxy provider, application, and updating the embedded outpost.
- Modified /etc/caddy/Caddyfile.vault on racknerd to forward authentication requests through the Authentik outpost.
- Added vaultwarden-verify-sso.spec.ts Playwright verification test ensuring SSO redirects, successful login, and disabled registration are enforced.
Build: 3314 jobs, 0 errors (lake build)
- Update container image to ghcr.io/homarr-labs/homarr:v1.68.0
- Change namespace from services to homarr across deployment, service, and pvc
- Set volume mount path to /appdata and storage capacity to 2Gi with local-path
- Inject OIDC environment variables for SSO authentication
Build: 0 jobs, 0 errors
Replace hardcoded DATABASE_URL default (containing live password) with
required os.environ lookup. The credential must be set at runtime.
Build: N/A (Python shim)
Moved Gemma4-12B from OpenCode primary model to MCP tool.
This avoids GUI issues and token burn from monitoring.
MCP tool: gemma4
- Calls local llama-server at 127.0.0.1:8081
- Returns reasoning + content
- No API key required
- ~40 tokens/sec generation
Usage: call gemma4 tool with a question, get answer back.
No parent model burns tokens waiting.
Usage:
lbi # full build + ingest
lbi Compiler # compiler surface + ingest
lbi Semantics.GraphRank # narrow target + ingest
Keeps databases in sync during development, not just on commit.
Add to shell: alias lb='lbi'
Hermes already handles model routing. Remove MCP server, keep skill
as a cost-optimized model selection guide.
Key insight: DeepSeek V4 Pro is 55x cheaper than Claude Opus and
nearly as good at math/code. Default to DeepSeek, escalate to Opus
only when stuck.
Removed: break_glass_mcp.py (unnecessary — Hermes handles routing)
When --rrc is given, the shim runs pist-classify-trace on the trace fixture
and rrc-watchdog for RRC alignment, then writes an additional
rrc_alignment receipt into ene.receipts alongside the build receipt.
Sets content_hash to NULL for build_log packages so the partial unique
index ene_pkg_hash_idx does not prevent multiple ingestions of the same
build output. Each build session now gets its own package row. Also makes
receipt/ingest_event inserts idempotent with ON CONFLICT DO NOTHING.
Adds a Build-log automation section noting the post-commit hook runs lake_build_ingest.py Compiler in the background, inserting into ENE on neon-64gb. Includes log path and reinstall note.
Adds canonical database location notes to 4-Infrastructure/AGENTS.md:
- Postgres canonical instance is the arxiv-pg container on neon-64gb.
- Gremlin canonical instance is the Azure Cosmos DB endpoint.
- Explicitly warns against spinning up local Postgres on qfox for
production data.
Also adds `lake_build_ingest.py` to the stack-solidification anchors.
Adds 4-Infrastructure/shim/lake_build_ingest.py, a pure-I/O shim that:
- runs `lake build <target>` in the Semantics directory,
- parses job count, error count, warnings, and status,
- inserts a session, package, receipt, and ingest_event into the
ENE database on neon-64gb (arxiv-pg container).
The script contains no admissibility logic and no Float arithmetic.
Tested with `lake build Semantics.NKHodgeFAMM` — 8316 jobs, 0 errors,
session d1ea53db2185df87dd41497da12101f5.
Adds logViscosityRatio, log_viscosity_monotone, and ν_eff_monotone
to Semantics/NKHodgeFAMM.lean section 6b. The adaptive viscosity law
ν_eff = ν₀*(1+μ) is multiplicative in ν₀ and additive in scar density μ;
taking λ = log(ν_eff/ν₀) = log(1+μ) turns the multiplicative feedback into
an additive coordinate. This gives nlinarith a direct handle on viscosity
monotonicity and connects the module to Kritchevsky's "Everything Is
Logarithms" framing (SilverSight CITATION.cff).
Also marks a few pre-existing unused variables with underscores to silence
the linter.
Build: 8316 jobs, 0 errors (lake build Semantics.NKHodgeFAMM)
- Updates CHANGELOG.md with 2026-06-21 entry describing the two-regime
phase transition observed on neon-64gb: bosonic MC (p<=4) vs
distinguishable approximation (p>=5) in rrc_bosonic_tensor_network.py.
- Adds BMCTE, SBOE, LPMCE, effective support, and observable-estimation
vs exact-simulation terms to 6-Documentation/docs/GLOSSARY.md.
- Fixes Hilbert-dimension summary in rrc_bosonic_tensor_network.py to use
C(N+p-1, p) instead of C(N, p).
No core logic changed; documentation and summary-output correction only.
Check file sizes before loading bytes into memory and stream large files
directly into the tarball to prevent OOM errors on Steam Deck. Skip downloading
files that already exist locally.
Build: 0 errors (py_compile)
Adds 4-Infrastructure/shim/mcp_drive_gccl_compress.py:
- downloads a Google Drive folder via @piotr-agier/google-drive-mcp
- GCCL-delta-compresses contents into .tar.zst + JSON manifest
- uploads archive + manifest back to Drive
- optionally trashes the original folder
- handles MCP listFolder pagination
Updates 4-Infrastructure/AGENTS.md with the new shim anchor.
No rclone or egress-heavy operations; all Drive I/O goes through MCP.
Finds related arxiv papers for cornfield concepts via keyword overlap.
Uses /shm/arxiv_texts.tsv (559 MB) for fast local matching.
pg_trgm GIN indexes on neon-64gb for Postgres queries.
Results: 240 candidate citations for 48 concepts.
Loaded into concept_citations table (relation_type='candidate').
Moves all classification authority from Python into Lean:
- Adds `0-Core-Formalism/lean/Semantics/PistClassifyTrace.lean` executable.
Reads a raw trace JSON and emits spectral radius, RRC shape, and tactic
family using `Semantics.PIST.Spectral` and `Semantics.PIST.Classify`.
- Registers `pist-classify-trace` in `lakefile.toml`.
- Fixes `Semantics.PIST.Spectral` power iteration to handle directed
transition matrices:
- `symmetrize` now preserves half-integer weights as Q16_16 raw values.
- `matVecMul` uses saturated Q16_16 arithmetic to prevent overflow.
- Rewrites `4-Infrastructure/shim/pist_trace_classify_offline.py` as a pure
I/O wrapper: reads JSON, calls the Lean classifier, optionally calls
`rrc-watchdog`, and emits the combined JSON. Removes Python-side spectral
computation, shape thresholds, tactic heuristic, and KNN.
- Updates `AGENTS.md` and `4-Infrastructure/AGENTS.md` with the new build
baseline and shim contract.
Verification:
- `lake build` → 8604 jobs, 0 errors
- Canary trace outputs match previous Python outputs to within Q16_16 rounding
(e.g., apply_chain λ_q16 = 59044 vs 59045).
- `python3 -m py_compile` on the rewritten shim passes.
Created a local, offline Python shim `pist_trace_classify_offline.py` that computes trace transition matrix spectra, maps the max eigenvalue to the Q16.16 spectral radius, evaluates the color-space shape classification logic from `Semantics.PIST.Classify`, and invokes the local `rrc-watchdog` Lean binary inside the podman container to verify alignment. This avoids querying the dead AWS RDS instance and saves LLM API tokens.
Build: 3314 jobs, 0 errors (lake build Compiler)
Added a python-based wrapper script for lean-lsp-mcp that intercepts and cleans the 'severity' schema field from the tools/list output, resolving the 400 error from Moonshot API which strictly forbids defining 'type' in parent schemas alongside 'anyOf'.
Build: 3314 jobs, 0 errors (lake build)
- Replace repo .mcp.json with minimal config (10 essential servers instead
of 29). Full backup retained as .mcp.json.full.
- Remove inline MCP section from ~/.config/opencode/config.json so OpenCode
loads only repo .mcp.json (also removes hardcoded Linear token leak).
- Add singleton guards to opencode_prover_mcp.py, token_saver_mcp.py, and
remote_lean_proof_mcp.py to prevent duplicate instances when multiple
IDE configs reference them.
Build: N/A (Python shims)
- qaoa_adapter.py: fix finsler_metric_to_qubo to store Q_ij + Q_ji per
undirected pair; update is_anisotropic and _find_anisotropic_pair to
accept raw_matrix so asymmetry detection still works after summation;
add measure option to pauli_to_cirq.
- benchmark_finsler_qaoa.py: new benchmark harness for Finsler-Randers
routing via QAOA.
Formulate directed Finsler routing as TSP-MTZ (QAP) using HiGHS MIP and
benchmark against QUBO subset-selection. Five solvers across four sizes.
Key results:
- QAP-MIP scales well: n=48 solves to feasibility in 13s
- QUBO degenerate for all-positive Q_ij (unconstrained always selects 0)
- 2-phase strategy viable: QUBO-card to select K, then TSP-on-subset
Build: N/A (Python shim)
Perceval is the photonic quantum simulation SDK used by
rrc_photonic_stress_test.py (SLOS backend). Already installed
system-wide; added to requirements.txt for venv reproducibility.
