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Author SHA1 Message Date
bigmerge 827257d3a4 Remove __pycache__ .pyc files accidentally included in the projector commit
El SDK CI - dev / build-and-test (pull_request) Waiting to run
2026-08-15 14:27:23 -05:00
bigmerge 4bbfdcceff Add native audio/image efferent surfaces + projector proof-of-shape
audio-surface.el / image-surface.el: own-core additive-synthesis WAV and
raster-PNG renderers (integer-only DSP, since EL has no floats), rendered
from learned engram signatures via a pluggable surface-profile
abstraction (surface-profile.el). audio-demo.el / image-demo.el are
drivers. NOTE: demo files hardcode absolute paths to this worktree's own
directory — will need a path fixup before landing.

elp/projector/ is a Python package the author's own README marks as
"STAGING/PROOF-OF-SHAPE — not the deliverable", superseded by the native
.el surface-profile work above; kept as a validated architecture proof.
Generated output (elp/faculty/{out,sig}, elp/projector/out,
__pycache__) intentionally excluded.
2026-08-15 14:26:59 -05:00
will.anderson d71fc4c1c0 Merge pull request 'promote stage -> main: reconciled el runtime (engram search + natives + durable truncation fix + Windows port)' (#82) from stage into main
El SDK Release / build-and-release (push) Successful in 8m31s
El SDK CI - dev / build-and-test (pull_request) Successful in 8m41s
2026-07-22 21:44:01 +00:00
will.anderson a118d19393 Merge pull request 'promote dev -> stage: el cluster (#66 engram + #79 truncation fix + release-runtime Windows port)' (#81) from dev into stage
El SDK CI - stage / build-and-test (push) Successful in 7m58s
El SDK Release / build-and-release (pull_request) Successful in 4m16s
2026-07-22 21:20:17 +00:00
will.anderson c6aa1e5c53 Merge pull request 'Land el cluster: #66 engram search + natives, #79 truncation fix, + release-runtime Windows port (reconciled)' (#80) from reconcile/el-cluster-windows-runtime into dev
El SDK CI - dev / build-and-test (push) Successful in 8m3s
El SDK CI - stage / build-and-test (pull_request) Successful in 4m25s
Land el cluster (#66 + #79 + release-runtime Windows-port reconciliation) into dev
2026-07-22 21:06:36 +00:00
will.anderson ff577391f2 reconcile(release-runtime): Windows-port + complete v1.0.0 release runtime so the desktop soul cross-compiles
El SDK CI - dev / build-and-test (pull_request) Successful in 7m7s
The desktop soul (neuron/dist) compiles against the v1.0.0-20260501 release
runtime. After #66 landed the engram natives (tokenized/ranked search,
engram_prune_telemetry) and #79 the durable truncation fix into this runtime,
two gaps remained before it could cross-compile the Windows brain:

1. Windows OS boundary: the release runtime had no Win32 path. Ported the same
   _WIN32-guarded shim the mainline runtime carries (#69): #ifdef _WIN32 ->
   el_platform_win.h (winsock/dlsym/popen + WSAStartup ctor), SOCKET fd guards
   and el_closesocket() at every socket site, CreateProcessA for exec_bg, the
   tm_zone/mingw guard, an el_setsockopt optval wrapper (GCC14), and curl-less
   libcurl stubs. Every change is _WIN32/HAVE_CURL-gated — the POSIX build is
   byte-identical (gcc -fsyntax-only clean; native behaviour unchanged).

2. Header exports: the release el_runtime.h omitted symbols the soul dist calls
   that are defined in this runtime's .c — the http_handler_fn/http_handler4_fn
   typedefs and el_arena_push/pop, engram_prune_telemetry, engram_get_node_by_label.
   Declaration-only, POSIX-neutral; fixes implicit-declaration/unknown-type
   errors under the C11 mingw build.

Result: x86_64-w64-mingw32-gcc compiles el_runtime.c + all 48 soul modules
clean; POSIX gcc -fsyntax-only clean. This is the Windows-port PR the runtime
needed on main (the release-runtime counterpart to #69), landed via stage.
2026-07-22 15:56:08 -05:00
will.anderson ee0d5f9b97 Merge #79: durable HTTP response-truncation fix, both runtimes (via stage) 2026-07-22 15:46:02 -05:00
will.anderson 391bd818ea Merge #66: tokenized+ranked engram lexical search + engram natives (via stage) 2026-07-22 15:45:54 -05:00
will.anderson 43636aed99 runtime: pair fs_read length hint with its buffer in BOTH runtimes — kill response truncation for good
El SDK Release / build-and-release (pull_request) Failing after 7s
The binary-safe fs_read length (_tl_fs_read_len) was consumed by the HTTP
response path for ANY body, even when a handler wrapped a smaller file into a
larger reply. Content-Length then lied AND the send stopped short: the
safety-contact (988) routes returned 178 of 208/218 bytes, cut mid-'set_at' —
unparseable JSON. The desktop app read that as failure. On Windows the shipped
brain is an OLD build without even the per-handler workaround, so EVERY reply
truncated: the app can't read confirmations and refuses the new user.

Durable fix: pair the length hint with the exact buffer pointer it describes
(_tl_fs_read_buf). Apply the raw byte count ONLY when the response IS that
buffer (binary file serving stays correct); every wrapped/enveloped/derived
body is measured with strlen. Reset both at request start and in fs_read /
json_get_raw. This also closes the stale-hint heap over-read (a length larger
than a later body would read past it out the socket) that a plain max() leaves
open — so this class of bug dies on every platform, not just where a handler
happened to be patched.

Applied identically to the mainline runtime (lang/el-compiler/runtime) AND the
frozen release runtime (lang/releases/v1.0.0-20260501) the desktop souls
compile against — the release copy still carried the raw leak, which is why the
Windows brain kept truncating. Same proven approach as PR #78 (Tim Lingo),
extended to cover the release runtime and rebased onto current main.

Both runtimes: gcc -fsyntax-only clean.
2026-07-22 15:04:25 -05:00
will.anderson 2baa0b9a41 Merge pull request 'release: promote stage -> main (ci publish hardening for sdk-release)' (#77) from stage into main
El SDK Release / build-and-release (push) Successful in 7m55s
2026-07-15 21:21:28 +00:00
will.anderson 6a8b2461cd Merge pull request 'release: promote dev -> stage (ci publish hardening for stage/main)' (#76) from dev into stage
El SDK CI - stage / build-and-test (push) Successful in 8m19s
El SDK Release / build-and-release (pull_request) Failing after 13m1s
2026-07-15 21:16:11 +00:00
will.anderson bcb356fe69 Merge pull request 'ci(stage,main): decouple ci-base rebuild, make SDK publish fail loudly' (#75) from hotfix/ci-stage-main-publish-hardening into dev
El SDK CI - stage / build-and-test (pull_request) Successful in 4m27s
El SDK CI - dev / build-and-test (push) Failing after 14m3s
2026-07-15 21:15:27 +00:00
will.anderson dd7827059a ci(stage,main): decouple ci-base rebuild, make SDK publish fail loudly
El SDK CI - dev / build-and-test (pull_request) Failing after 14m30s
Mirror the PR #72 fix (applied to ci-dev.yaml) onto ci-stage.yaml and
sdk-release.yaml. The stage and prod release jobs reported FAILURE even
when the el-runtime-c/-h publish SUCCEEDED, because the ancillary ci-base
Docker rebuild (a CI-cache optimization on the fragile host-mode GCE
runner) reddened the whole job.

- Rebuild ci-base step: continue-on-error: true — never blocks/reddens
  the job; the SDK publish is the deliverable.
- Publish step: set -euo pipefail + empty-key guard + active-account echo
  so a real publish failure still fails loud and is diagnosable.
2026-07-15 16:14:50 -05:00
will.anderson 208e36c899 Merge pull request 'release: promote stage -> main (tokenized search, get_node_by_label, epm fix, win portability)' (#74) from stage into main
El SDK Release / build-and-release (push) Successful in 8m23s
2026-07-15 18:24:39 +00:00
will.anderson b97ce74d1f Merge pull request 'release: promote dev -> stage (tokenized search, get_node_by_label, epm fix)' (#73) from dev into stage
El SDK CI - stage / build-and-test (push) Failing after 8m45s
El SDK Release / build-and-release (pull_request) Successful in 4m1s
2026-07-15 17:20:11 +00:00
will.anderson 155a449c4e Merge pull request 'ci(dev): make SDK publish fail loudly, decouple ci-base rebuild' (#72) from hotfix/ci-dev-publish-hardening into dev
El SDK CI - dev / build-and-test (push) Successful in 8m56s
El SDK CI - stage / build-and-test (pull_request) Successful in 4m10s
2026-07-15 16:34:14 +00:00
will.anderson 4696fd6833 ci(dev): make SDK publish fail loudly, decouple ci-base rebuild
El SDK CI - dev / build-and-test (pull_request) Successful in 8m51s
The dev push build went green-then-red while nothing published: the
Publish step had no set -e, so an auth/upload failure exited 0 (silent
no-publish), while the ci-base rebuild (set -euo pipefail + Docker on the
host-mode runner) hard-failed the job. Add set -euo pipefail + an empty-key
guard + active-account echo to the Publish step so failures surface with a
retrievable log, and mark the ci-base cache rebuild continue-on-error so
the fragile Docker step can never block the actual SDK artifact publish.
2026-07-15 11:33:37 -05:00
will.anderson 581a351fb1 Merge pull request 'integrate: stack PRs #65–#69 (elc OOM guard, tokenized+semantic engram search, get_node_by_label, win portability) for green CI' (#71) from hotfix/stage-elc-engram-integration into dev
El SDK CI - dev / build-and-test (push) Failing after 14m31s
2026-07-15 15:49:57 +00:00
will.anderson 8ce8656de2 epm: declare cross-module callees as extern fn so strict compilers accept generated C
El SDK CI - dev / build-and-test (pull_request) Successful in 7m33s
epm's sibling modules (registry/install/update) call functions defined in other
modules and in the El runtime (config, read_installed, registry_find,
manifest_deps, manifest_name, registry_latest_version, registry_token,
install_vessel, installed_version) without importing them, so elc emits no C
prototype for those calls. gcc<=13 treated the resulting implicit declarations
as warnings; gcc>=14 and clang reject them as hard errors, which is why the
"Build epm" CI step fails and blocks the whole dev/stage pipeline.

Add `extern fn` forward declarations -- El's own separate-compilation mechanism
-- for each cross-module callee at the top of registry/install/update. This
gives elc the correct C prototype in every generated translation unit, so the
calls compile cleanly and still resolve at link time. Simply suppressing
-Wimplicit-function-declaration would be unsafe: an implicit int return
truncates the 64-bit pointer returns of config/registry_find into a latent
crash, so declaring the true signatures is the correct fix. Localized to epm;
touches neither elc nor the runtime.
2026-07-15 10:14:43 -05:00
will.anderson 1e49560f1f Merge remote-tracking branch 'origin/feat/engram-semantic-search' into hotfix/stage-elc-engram-integration
El SDK CI - dev / build-and-test (pull_request) Failing after 14m39s
# Conflicts:
#	lang/el-compiler/runtime/el_runtime.c
2026-07-15 09:33:05 -05:00
will.anderson e8f0b5a9de Merge remote-tracking branch 'origin/fix/engram-lexical-tokenized-search' into hotfix/stage-elc-engram-integration 2026-07-15 09:28:44 -05:00
will.anderson 40287c4cfc Merge remote-tracking branch 'origin/hotfix/win-runtime-portability' into hotfix/stage-elc-engram-integration 2026-07-15 09:28:44 -05:00
will.anderson 0481bea44d Merge remote-tracking branch 'origin/hotfix/runtime-engram-get-node-by-label' into hotfix/stage-elc-engram-integration 2026-07-15 09:28:44 -05:00
will.anderson 9d565ca080 Merge remote-tracking branch 'origin/hotfix/elc-fixes' into hotfix/stage-elc-engram-integration 2026-07-15 09:28:44 -05:00
will.anderson 4773dd0aa2 runtime: make Windows soul reproducible from a clean el checkout
El SDK Release / build-and-release (pull_request) Failing after 16s
Two el_runtime portability defects only ever lived in staged local copies
used to hand-build neuron-ui PR #136's curl-enabled Windows neuron.exe.
gcc 15 promotes both to hard errors, so a clean el checkout cannot rebuild
that soul. Upstream the minimal fixes so the build is reproducible:

- http_serve_async: cast setsockopt optval to (const char*). Win32/mingw
  setsockopt wants const char*, not int*; the cast is a no-op on POSIX and
  matches the four already-cast sites elsewhere in this file.
- engram_save persist path: map fsync -> _commit in the _WIN32-only
  el_platform_win.h (io.h already included). Windows has no fsync(); the
  POSIX path is untouched.
2026-07-15 04:24:08 -05:00
will.anderson 6b9d9e6c4a Add engram_get_node_by_label runtime native to unblock soul link
El SDK Release / build-and-release (pull_request) Failing after 22s
chat.el calls the runtime native engram_get_node_by_label to fetch
well-known nodes (conv:history, session:summary) by stable label rather
than by ID — immune to vector-index drift across restarts. The current
runtime never defined it, so the regenerated dist/soul.c fails to link.

Backport the function verbatim (idiom-adapted to jb_finish) from release
runtime v1.0.0-20260501 and register it as an EL builtin exactly like its
siblings: runtime definition + prototype, __-prefixed seed wrapper +
prototype, and codegen arity entry. No search-site code is touched.
2026-07-15 04:07:33 -05:00
will.anderson b4967af13e feat(engram): semantic search layer via nomic-embed-text (cosine ∪ lexical)
Lexical istr_contains alone can't surface a node whose words don't appear
in the query. This adds an optional dense-vector layer: node content and the
query are embedded through Ollama (nomic-embed-text), and nodes are ranked by
cosine similarity unioned with lexical hits, so a paraphrase query reaches the
right node.

Wired into all three query entry points in el_runtime.c:
  - engram_search_json (HTTP /api/search): collect lexical ∪ semantic
    candidates, score (lexical base 1.0 + cosine; pure-semantic = cosine),
    rank, emit top-N. Stable sort preserves old order when semantic is off.
  - engram_search (internal el_val twin): lexical ∪ semantic union.
  - engram_activate seed loop (HTTP /api/activate): a node seeds if it
    lexically matches OR clears the cosine threshold; pure-semantic seeds
    enter scaled by cosine so paraphrase spreads without overpowering.

Degradable by design: the whole layer is gated on HAVE_CURL plus a one-shot
runtime probe. If curl is compiled out, Ollama is unreachable, or
ENGRAM_SEMANTIC=0, every entry point yields zero semantic signal and callers
fall back byte-for-byte to the pre-existing lexical search.

Node embeddings are cached in process memory keyed by node id with an FNV-1a
content hash for invalidation; the query is embedded once per call — so the
graph is not re-embedded on every query. nomic task prefixes
(search_query:/search_document:) are applied for retrieval separation.

Build steps gain -DHAVE_CURL so the engram artifact compiles the layer in
(-lcurl was already linked). Env: ENGRAM_SEMANTIC, ENGRAM_EMBED_URL,
ENGRAM_EMBED_MODEL, ENGRAM_SEMANTIC_MIN (cosine threshold, default 0.6).
2026-07-14 18:48:16 -05:00
will.anderson 2b2a1246e7 Merge pull request 'runtime: fix the memory-leak + write-corruption pair in el_runtime.c' (#64) from hotfix/el-runtime-leak-and-persist into main
El SDK Release / build-and-release (push) Failing after 10m52s
2026-07-13 21:23:31 +00:00
will.anderson 5c41c66a0f Merge pull request 'fix(windows): guard el_mem_check with _WIN32 — rusage is POSIX-only' (#60) from fix/windows-rusage-guard into stage
El SDK CI - stage / build-and-test (push) Failing after 13m21s
fix(windows): guard el_mem_check with _WIN32 — rusage is POSIX-only
2026-06-25 16:48:13 +00:00
38 changed files with 3291 additions and 76 deletions
+15
View File
@@ -214,9 +214,18 @@ jobs:
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
run: |
# Fail loudly: previously this step had no `set -e`, so an auth or
# upload failure was swallowed (step exited 0 on the trailing echo)
# and the SDK silently never published. Surface failures now.
set -euo pipefail
if [ -z "${GCP_SA_KEY:-}" ]; then
echo "FATAL: GCP_SA_KEY secret is empty — cannot authenticate to publish" >&2
exit 1
fi
echo "${GCP_SA_KEY}" > /tmp/gcp-key.json
gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
gcloud config set project neuron-785695
echo "Publishing as active account: $(gcloud config get-value account 2>/dev/null)"
VERSION="${GITHUB_SHA:0:8}"
@@ -268,6 +277,12 @@ jobs:
# Patches ci-base:dev in-place: pulls the existing image (which has all
# system deps — Node, Go, gcloud, Docker CLI, etc.) and overlays the freshly
# built El SDK on top. Keeps the full ci-base rebuild fast and incremental.
#
# continue-on-error: this is a CI-cache optimization, NOT the release
# artifact. It runs Docker (pull/build/push ~600MB) on the host-mode GCE
# runner where DinD/Docker availability is fragile. A failure here must
# never block or redden the job — the SDK publish above is the deliverable.
continue-on-error: true
if: github.event_name == 'push'
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
+15
View File
@@ -212,12 +212,21 @@ jobs:
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
run: |
# Fail loudly: previously this step had no `set -e`, so an auth or
# upload failure was swallowed (step exited 0 on the trailing echo)
# and the SDK silently never published. Surface failures now.
set -euo pipefail
if [ -z "${GCP_SA_KEY:-}" ]; then
echo "FATAL: GCP_SA_KEY secret is empty — cannot authenticate to publish" >&2
exit 1
fi
echo "${GCP_SA_KEY}" > /tmp/gcp-key.json
apt-get install -y -qq apt-transport-https ca-certificates curl
echo "deb [trusted=yes] https://packages.cloud.google.com/apt cloud-sdk main" > /etc/apt/sources.list.d/google-cloud-sdk.list
apt-get update -qq && apt-get install -y google-cloud-cli
gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
gcloud config set project neuron-785695
echo "Publishing as active account: $(gcloud config get-value account 2>/dev/null)"
VERSION="${GITHUB_SHA:0:8}"
@@ -253,6 +262,12 @@ jobs:
# Patches ci-base:stage in-place: pulls the existing image (which has all
# system deps — Node, Go, gcloud, Docker CLI, etc.) and overlays the freshly
# built El SDK on top. Keeps the full ci-base rebuild fast and incremental.
#
# continue-on-error: this is a CI-cache optimization, NOT the release
# artifact. It runs Docker (pull/build/push ~600MB) on the host-mode GCE
# runner where DinD/Docker availability is fragile. A failure here must
# never block or redden the job — the SDK publish above is the deliverable.
continue-on-error: true
if: github.event_name == 'push'
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
+15
View File
@@ -288,12 +288,21 @@ jobs:
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
run: |
# Fail loudly: previously this step had no `set -e`, so an auth or
# upload failure was swallowed (step exited 0 on the trailing echo)
# and the SDK silently never published. Surface failures now.
set -euo pipefail
if [ -z "${GCP_SA_KEY:-}" ]; then
echo "FATAL: GCP_SA_KEY secret is empty — cannot authenticate to publish" >&2
exit 1
fi
echo "${GCP_SA_KEY}" > /tmp/gcp-key.json
apt-get install -y -qq apt-transport-https ca-certificates curl
echo "deb [trusted=yes] https://packages.cloud.google.com/apt cloud-sdk main" > /etc/apt/sources.list.d/google-cloud-sdk.list
apt-get update -qq && apt-get install -y google-cloud-cli
gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
gcloud config set project neuron-785695
echo "Publishing as active account: $(gcloud config get-value account 2>/dev/null)"
VERSION="${GITHUB_SHA:0:8}"
@@ -345,6 +354,12 @@ jobs:
# Patches ci-base:latest in-place: pulls the existing image (which has all
# system deps — Node, Go, gcloud, Docker CLI, etc.) and overlays the freshly
# built El SDK on top. Keeps the full ci-base rebuild fast and incremental.
#
# continue-on-error: this is a CI-cache optimization, NOT the release
# artifact. It runs Docker (pull/build/push ~600MB) on the host-mode GCE
# runner where DinD/Docker availability is fragile. A failure here must
# never block or redden the job — the SDK publish above is the deliverable.
continue-on-error: true
if: github.event_name == 'push'
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
+91
View File
@@ -0,0 +1,91 @@
> **STATUS: STAGING / PROOF-OF-SHAPE — not the deliverable.** This Python package
> proved the architecture end-to-end against the proven realizer faculty (faithful
> md/docx/midi from real geometry: 0 ungrounded claims, SACRED polarity). Per Will's
> steer, the DELIVERABLE is NATIVE: the seam lives on the existing EL realizer as
> **surface-as-profile** — see `../src/surface-profile.el` and
> `../tests/examples/surface-profile-demo.el` (compiles + runs through elc → C →
> binary). The concepts below (one geometry-carrying frame; surface = a pluggable
> profile; plan/realize; deterministic-from-meaning) are exactly what the native
> module implements. Keep this package as the validated proof; build native.
# Efferent Multimodal Projector
**geometry → any surface, faithfully.** Neuron's own document-generation faculty:
the efferent twin of the ingest organ. Ingest is afferent (world → geometry);
this is efferent (geometry → an arbitrary-format document / any modality).
Built against the **proven** realizer faculty (neuron-talk sidecar `:8756`,
artifact `art-7affa557`). The live soul (`:8742` / `:7770`) is contacted **only**
through the read-only, GET-only `engram_client` — never mutated.
## The pipeline (surface-agnostic)
```
geometry region + surface/format spec
→ PLAN (manifold → document skeleton/DAG; the geometry IS the outline) plan.py
→ REALIZE (proven realizer, scaled sentence → passage, each section faithful) realize.py
→ COHERE (document-level flow / transitions, not stitched sentences) cohere.py
→ EMIT (pluggable SurfaceProjector → the target surface) projectors/
```
**The surface is a PARAMETER.** `pipeline.build_ir(...)` builds ONE
surface-neutral `DocumentIR` (`document_ir.py`); `pipeline.emit(doc, surface)`
projects it to whichever surface you name. Markdown, docx, and MIDI are the same
IR emitted three ways.
## The pivot: a geometry-carrying IR
`DocumentIR` is **not** a text tree. Every `Block` carries BOTH:
- `.sentences` — realized faithful text (what **text** projectors read),
- `.provenance` — the source geometry: `subj_id / relation / obj / polarity /
confidence / importance / salience / node_id` (what **music / image / video**
projectors read).
That single decision is what makes the projector multimodal: text renders the
words; music/image decode the geometry. A claim with no provenance cannot exist
in the IR — faithfulness is structural.
## The one shared seam
`projectors/base.py` — `SurfaceProjector.project(frame: DocumentIR) -> bytes`
(+ `surface / media_type / ext / modality / profile`). Register with
`register()`. Adding a surface changes nothing upstream.
`TwoStageProjector` blesses the peer plan/realize decomposition:
`spec = plan(frame)`, `bytes = realize(spec)`, `project = realize∘plan`; the
`profile` is the pluggable per-surface knob (text lang-profile, music
instr/mode-profile). `projectors/midi.py` is the reference two-stage impl.
## Surfaces
| surface | modality | status | emitter |
|---|---|---|---|
| `markdown` | text | landed | own (str) |
| `docx` | text | landed | own minimal OOXML (stdlib `zipfile`+XML, no lib) |
| `midi` | audio | landed (symbolic-music proof) | own minimal SMF (stdlib `struct`, no lib) |
| `audio` (WAV) | audio | peer agent (additive synth) | conforms to `TwoStageProjector` |
| `image` | image | documented seam | `projectors/seams.py` |
| `video` | video | documented seam (image×sound×time) | `projectors/seams.py` |
Music maps: relation → scale degree (same relation → same pitch), **polarity →
major/minor third (SACRED negation is audible)**, confidence → duration,
importance → velocity, section → register. Deterministic projection from meaning
— nothing invented.
## Faithfulness
`provenance.py` audits the IR: **zero** ungrounded claims, SACRED polarity
preserved (negations reported, never dropped), COHERE introduces no new geometry
(connectives are marked). `trace_table()` emits the geometry → section → claim
table.
## Run
```bash
PY=~/Desktop/lang-realizers/venv/bin/python
PYTHONPATH=~/Desktop/neuron-talk:~/Desktop/lang-realizers $PY generate.py
# writes ./out/{neuron-self,engram-temporal}.{md,docx,mid} + *.audit.json + *.provenance.md
```
Requires the proven realizer env (spaCy + the neuron-talk/lang-realizers engine)
and the read-only engram at `:8742`.
+79
View File
@@ -0,0 +1,79 @@
"""cohere.py — COHERE stage: document-level flow, not stitched sentences.
Fidelity is REALIZE's job; FLOW is this stage's. The hard part beyond sentence
fidelity is that a document must read as one thing. We add connective tissue at
the passage level:
* an opening abstract that names what the document covers (built ONLY from the
section headings that already exist — it introduces no new claim),
* a short transition lead into each section after the first, drawn from a
fixed set of discourse connectives ("Beyond that,", "Relatedly,", ...) that
carry no propositional content,
* ordering so the highest-grounded section leads.
CRITICAL: every connective is marked ``kind="connective"`` in its provenance, so
the faithfulness audit can prove COHERE introduced ZERO new geometry claims. A
transition is discourse glue, never a fact.
"""
from __future__ import annotations
from document_ir import Block, DocumentIR, Provenance
# discourse connectives — pure flow, no propositional content
_TRANSITIONS = [
"Beyond that,", "Relatedly,", "In the same region,", "From there,",
"Alongside this,", "Further,", "Turning to the next facet,",
]
def _connective_prov() -> Provenance:
return Provenance(subj_id=None, subject=None, relation="", obj=None,
polarity="aff", confidence=1.0, node_id=None,
kind="connective")
def _abstract_block(doc: DocumentIR) -> Block:
"""A grounded opening: names the sections, asserts nothing new."""
headings = [s.heading for s in doc.sections]
if not headings:
return Block(role="lead")
if len(headings) == 1:
body = f"This document, generated from Neuron's geometry, covers {headings[0]}."
else:
listed = ", ".join(headings[:-1]) + f", and {headings[-1]}"
body = ("This document is projected directly from Neuron's meaning-geometry. "
f"It traces {listed}.")
b = Block(role="lead")
b.sentences.append(body)
b.provenance.append(_connective_prov())
return b
def cohere_document(doc: DocumentIR, *, add_abstract: bool = True,
add_transitions: bool = True) -> DocumentIR:
"""Order sections by grounding, add abstract + transitions (flow only)."""
# order: strongest-grounded section (mean confidence x #claims) first,
# but keep an explicitly-first section if the plan pinned one via level 1.
def _score(sec):
provs = [p for p in sec.all_provenance() if p.kind == "fact"]
if not provs:
return 0.0
mean_conf = sum(p.confidence for p in provs) / len(provs)
return mean_conf * len(provs)
doc.sections.sort(key=_score, reverse=True)
if add_transitions:
for i, sec in enumerate(doc.sections):
if i == 0 or not sec.blocks:
continue
lead = _TRANSITIONS[(i - 1) % len(_TRANSITIONS)]
first = sec.blocks[0]
if first.sentences:
# prepend the connective to the first sentence (flow, no new claim)
first.sentences[0] = f"{lead} {first.sentences[0][0].lower()}{first.sentences[0][1:]}"
if add_abstract:
doc.meta["abstract"] = _abstract_block(doc)
return doc
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"""document_ir.py — the surface-neutral, GEOMETRY-CARRYING document intermediate.
This is the pivot of the whole efferent projector. A DocumentIR is NOT a text
tree. It is a projection of a meaning-geometry region that carries, at every
leaf, BOTH:
* the realized surface text (``Block.sentences``) — what a TEXT projector reads,
* the source geometry (``Block.provenance``) — what a MUSIC / IMAGE /
VIDEO projector reads.
Because the IR holds the geometry, not just the words, the SAME
plan -> realize -> cohere pipeline drives every surface. A markdown projector
renders the sentences; a music projector reads the provenance edges (salience,
importance, polarity, relation) and maps them onto a symbolic-music surface;
an image/video projector (documented seam) would read the same geometry.
Nothing in this module invents content. Every :class:`Provenance` points at a
real engram node id and a real relation. That is the faithfulness contract made
structural: a claim with no provenance cannot exist in the IR.
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any
# --------------------------------------------------------------------------- #
# Provenance — the geometry an emitted claim traces to. FAITHFULNESS is here.
# --------------------------------------------------------------------------- #
@dataclass
class Provenance:
"""One geometry edge behind one realized claim.
``kind`` distinguishes a FACT (a structural edge asserted by the geometry,
spoken as fact) from an INTERPRETATION (something attributed, spoken with
attribution) — the facts-as-facts + interpretations-attributed discipline
(memory 80927e26). ``polarity`` is SACRED: a negated edge stays negated.
"""
subj_id: str | None # source engram node id of the subject
subject: str | None # normalized subject surface
relation: str # predicate lemma (e.g. "use", "contain", "be")
obj: str | None # normalized object / complement surface
polarity: str = "aff" # "aff" | "neg" (SACRED — never silently flipped)
confidence: float = 0.0 # extraction confidence in [0,1]
node_id: str | None = None # engram node the claim was extracted from
kind: str = "fact" # "fact" | "interpretation"
importance: float = 0.0 # source node importance (drives music/emphasis)
salience: float = 0.0 # source node salience
def trace(self) -> str:
arrow = "-->" if self.polarity == "aff" else "--NOT-->"
return (f"[{(self.node_id or '?')[:8]}] {self.subject!r} {arrow}"
f"{self.relation} {self.obj!r} (conf {self.confidence:.2f})")
@dataclass
class Block:
"""A passage: one or more faithful sentences + the geometry they trace to.
``sentences`` and ``provenance`` are index-aligned where possible: sentence
``i`` was realized from ``provenance[i]``. A COHERE transition sentence with
no new geometry carries a provenance whose ``kind == "connective"`` so the
audit can see it introduced no new claim.
"""
sentences: list[str] = field(default_factory=list)
provenance: list[Provenance] = field(default_factory=list)
role: str = "body" # "body" | "lead" | "transition"
def text(self) -> str:
return " ".join(s.rstrip(". ") + "." for s in self.sentences if s.strip())
@dataclass
class Section:
heading: str
level: int = 2 # markdown heading level / outline depth
blocks: list[Block] = field(default_factory=list)
seed_ids: list[str] = field(default_factory=list) # geometry nodes of section
summary: str = "" # one-line grounded gloss (for pptx bullets / TOC)
def all_provenance(self) -> list[Provenance]:
out: list[Provenance] = []
for b in self.blocks:
out.extend(b.provenance)
return out
@dataclass
class DocumentIR:
"""The surface-neutral document. Built ONCE, projected to ANY surface."""
title: str
subtitle: str = ""
sections: list[Section] = field(default_factory=list)
seed_id: str | None = None # the geometry region root
format_spec: dict[str, Any] = field(default_factory=dict) # requested shape
meta: dict[str, Any] = field(default_factory=dict)
# -- geometry facets (what non-text projectors consume) ----------------- #
def all_provenance(self) -> list[Provenance]:
out: list[Provenance] = []
for s in self.sections:
out.extend(s.all_provenance())
return out
def claim_count(self) -> int:
return sum(1 for p in self.all_provenance() if p.kind in ("fact", "interpretation"))
def ungrounded_count(self) -> int:
"""Claims with no traceable node — MUST be zero for a faithful doc."""
return sum(1 for p in self.all_provenance()
if p.kind in ("fact", "interpretation") and not p.node_id)
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"""generate.py — drive the projector: one geometry region -> many surfaces.
Proves the thesis with REAL output: builds ONE surface-neutral DocumentIR from
Neuron's OWN self-geometry (read-only against the live soul via the proven
faculty), then EMITS it to Markdown, docx, and MIDI — the same plan/realize/
cohere, three surfaces. Writes the files + the faithfulness audit to ./out/.
"""
from __future__ import annotations
import json
import os
import sys
_HERE = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, _HERE)
import pipeline # noqa: E402
import provenance # noqa: E402
from geometry import load_self_region # noqa: E402
OUT = os.path.join(_HERE, "out")
def _emit_all(doc, stem):
"""Emit one IR to every text/audio surface + audit + provenance."""
for surface in ("markdown", "docx", "midi"):
data = pipeline.emit(doc, surface)
proj = pipeline.get_projector(surface)
path = os.path.join(OUT, f"{stem}.{proj.ext}")
with open(path, "wb") as f:
f.write(data)
print(f" emitted {surface:9s} -> {os.path.basename(path)} ({len(data)} bytes)")
a = provenance.audit(doc)
with open(os.path.join(OUT, f"{stem}.audit.json"), "w") as f:
json.dump(a, f, indent=2)
with open(os.path.join(OUT, f"{stem}.provenance.md"), "w") as f:
f.write(provenance.trace_table(doc))
print(" audit:", {k: a[k] for k in ("claims", "ungrounded_claims",
"negations_preserved", "distinct_source_nodes", "faithful")})
return a
def main():
os.makedirs(OUT, exist_ok=True)
print("surfaces registered:", pipeline.available_surfaces())
# ---- Document 1: Neuron's self-description (marquee) ------------------- #
print("\n[1] Neuron self-description")
region = load_self_region(max_nodes=9)
print(" self region:", region)
doc1 = pipeline.build_ir(
None, region=region,
title="Neuron: A Self-Description from Its Own Geometry",
subtitle="Projected efferently from the engram — every claim traces a node.",
format_spec={"genre": "self-description", "register": "expository"},
max_sections=5, conf_floor=0.6)
print(f" IR: {len(doc1.sections)} sections, {doc1.claim_count()} claims, "
f"ungrounded={doc1.ungrounded_count()}")
_emit_all(doc1, "neuron-self")
# ---- Document 2: a coherent, clean whitepaper-style section ------------ #
print("\n[2] Whitepaper-style section (coherent clean region)")
doc2, _ = pipeline.project(
["chronoception", "time", "awareness", "engram", "temporal"],
surface="markdown",
title="Temporal Awareness in the Engram",
subtitle="A section projected from the geometry of chronoception.",
format_spec={"genre": "whitepaper-section", "register": "technical"},
max_sections=4)
print(f" IR: {len(doc2.sections)} sections, {doc2.claim_count()} claims, "
f"ungrounded={doc2.ungrounded_count()}")
_emit_all(doc2, "engram-temporal")
# echo both markdowns so they are visible in the run log
for stem, doc in (("neuron-self", doc1), ("engram-temporal", doc2)):
print(f"\n===== GENERATED MARKDOWN — {stem} =====\n")
print(pipeline.emit(doc, "markdown").decode())
if __name__ == "__main__":
main()
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"""geometry.py — READ-ONLY loader for a meaning-geometry region.
The efferent projector never writes to the soul. This module reaches the
geometry through the PROVEN, read-only neuron-talk faculty (``engram_client``,
GET-only, which physically refuses non-GET methods) against the running sidecar
soul. The live daemon :8742 / :7770 is contacted ONLY through that read-only
client — never mutated.
A "region" is a seed node plus a bounded neighborhood: the manifold that will
become the document's skeleton. We pool a few single-term lexical searches
(the engram search is a single-term matcher) and, when available, walk one hop
of reified neighbors, then rank by self/importance signal.
"""
from __future__ import annotations
import os
import sys
# Wire in the proven faculty (own-the-core: we reuse it, we do not fork it).
_NT = os.path.expanduser("~/Desktop/neuron-talk")
_LR = os.path.expanduser("~/Desktop/lang-realizers")
for _p in (_NT, _LR):
if _p not in sys.path:
sys.path.insert(0, _p)
from engram_client import ReadOnlyEngramClient # noqa: E402
class Region:
"""A geometry region: ranked nodes + the reified edges among them."""
def __init__(self, seed: str, nodes: list[dict], edges: list[dict]):
self.seed = seed
self.nodes = nodes # ranked engram node dicts
self.edges = edges # [{src, dst, edge, ...}]
self.by_id = {n["id"]: n for n in nodes if n.get("id")}
def __repr__(self):
return f"<Region seed={self.seed!r} nodes={len(self.nodes)} edges={len(self.edges)}>"
def _prose_quality(content: str) -> float:
"""Reward clean expository prose; penalize shouty banner-dense nodes.
A high ALLCAPS-word ratio or very short content signals a banner/telegraphic
memory node that extracts into garbage. Clean declarative prose scores high.
"""
if not content or not content.strip():
return 0.0
words = content.split()
if len(words) < 8:
return 0.1
caps = sum(1 for w in words if len(w) > 2 and w.strip(".,:;'\"-").isupper())
caps_ratio = caps / max(1, len(words))
# sentences with lowercase interior words read as prose
lower = sum(1 for w in words if w[:1].islower())
lower_ratio = lower / max(1, len(words))
return max(0.0, 1.2 * lower_ratio - 2.0 * caps_ratio)
def _relevance(content: str, terms: list[str]) -> float:
"""Topical relevance to the seed terms — keeps a region ON-THEME so a clean
but off-topic node cannot hijack the document."""
if not terms:
return 0.0
low = (content or "").lower()
hits = sum(1 for t in terms if t.lower() in low)
return hits / max(1, len(terms))
def _node_rank(n: dict, terms: list[str] | None = None) -> float:
return (float(n.get("importance") or 0.0) * 2.0
+ float(n.get("salience") or 0.0)
+ 1.5 * _prose_quality(n.get("content") or "")
+ 2.0 * _relevance(n.get("content") or "", terms or [])
+ (0.5 if (n.get("content") or "").strip() else 0.0))
def load_region(seed_terms: list[str] | str, *, client: ReadOnlyEngramClient | None = None,
max_nodes: int = 10, per_term: int = 20, hop: bool = True) -> Region:
"""Pull a bounded geometry region around ``seed_terms`` (read-only).
``seed_terms`` may be a single string or several probe terms; results are
pooled and de-duplicated. When ``hop`` and the reified neighbor endpoint is
live, one hop of neighbors is folded in so the region is a real
neighborhood, not just a keyword hit list.
"""
client = client or ReadOnlyEngramClient()
if isinstance(seed_terms, str):
seed_terms = [seed_terms]
pool: dict[str, dict] = {}
for term in seed_terms:
for n in client.search(term, limit=per_term):
if isinstance(n, dict) and n.get("id"):
pool.setdefault(n["id"], n)
ranked = sorted(pool.values(), key=lambda n: _node_rank(n, seed_terms),
reverse=True)
nodes = ranked[:max_nodes]
edges: list[dict] = []
if hop and nodes:
present = {n["id"] for n in nodes}
for n in list(nodes):
try:
for nb in client.neighbors(n["id"]):
node = nb.get("node") if isinstance(nb, dict) else None
edge = nb.get("edge") if isinstance(nb, dict) else None
if node and node.get("id"):
edges.append({"src": n["id"], "dst": node["id"],
"edge": edge})
# fold a strong neighbor into the region (bounded)
if (node["id"] not in present and len(nodes) < max_nodes + 6
and _node_rank(node, seed_terms) > 0.4):
present.add(node["id"])
nodes.append(node)
except Exception: # noqa: BLE001 — read-only best-effort; never fatal
continue
return Region(seed=", ".join(seed_terms), nodes=nodes, edges=edges)
def load_self_region(client: ReadOnlyEngramClient | None = None,
max_nodes: int = 10) -> Region:
"""The self/identity region — Neuron's own geometry, for self-description."""
return load_region(["self", "identity", "Neuron", "values", "memory",
"imprint", "consciousness"],
client=client, max_nodes=max_nodes)
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"""pipeline.py — the Efferent Multimodal Projector, top level.
geometry region + surface/format spec
-> PLAN (manifold -> document skeleton/DAG)
-> REALIZE (proven realizer, sentence -> passage, each section faithful)
-> COHERE (document-level flow / transitions, not stitched sentences)
-> EMIT (pluggable SurfaceProjector -> the target surface)
THE SURFACE IS A PARAMETER. ``project(...)`` builds the geometry-carrying
DocumentIR once, then hands it to whichever surface projector the caller named.
Markdown, docx, and midi (music) are all the SAME IR emitted differently. That
is the efferent multimodal projector: geometry -> any surface.
"""
from __future__ import annotations
import os
import sys
_HERE = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, _HERE)
sys.path.insert(0, os.path.join(_HERE, "projectors"))
from cohere import cohere_document # noqa: E402
from document_ir import DocumentIR # noqa: E402
from geometry import Region, load_region # noqa: E402
from plan import plan_document # noqa: E402
from realize import realize_document # noqa: E402
# registering the projectors (import for side-effect: each self-registers)
import projectors.markdown # noqa: E402,F401
import projectors.docx # noqa: E402,F401
import projectors.midi # noqa: E402,F401
import projectors.seams # noqa: E402,F401
from projectors.base import available_surfaces, get_projector # noqa: E402
def build_ir(seed_terms, *, title: str, subtitle: str = "",
format_spec: dict | None = None,
region: Region | None = None,
max_sections: int = 8, conf_floor: float = 0.55) -> DocumentIR:
"""geometry -> PLAN -> REALIZE -> COHERE = the surface-neutral DocumentIR."""
region = region or load_region(seed_terms)
doc = plan_document(region, title=title, subtitle=subtitle,
format_spec=format_spec or {},
conf_floor=conf_floor, max_sections=max_sections)
doc = realize_document(doc)
doc = cohere_document(doc)
return doc
def emit(doc: DocumentIR, surface: str) -> bytes:
"""EMIT: project the built IR onto one surface (surface = a parameter)."""
return get_projector(surface).project(doc)
def project(seed_terms, *, surface: str, title: str, subtitle: str = "",
format_spec: dict | None = None, region: Region | None = None,
max_sections: int = 8) -> tuple[DocumentIR, bytes]:
"""The full efferent projection: geometry + surface -> (IR, bytes)."""
doc = build_ir(seed_terms, title=title, subtitle=subtitle,
format_spec=format_spec, region=region,
max_sections=max_sections)
return doc, emit(doc, surface)
__all__ = ["build_ir", "emit", "project", "available_surfaces",
"get_projector", "load_region", "DocumentIR"]
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"""plan.py — PLAN stage: geometry region -> document skeleton (a DAG/outline).
The manifold becomes the skeleton. We extract faithful propositions from the
region's nodes (the proven neuron-talk extractor, SACRED polarity preserved),
apply a quality floor, then GROUP them into sections. Grouping is by source
node — each engram node is one coherent topic, so one salient node becomes one
section. The section ORDER is the node ranking (importance/salience): the
geometry decides the outline, not a template.
Output: a DocumentIR whose sections carry seed node ids and empty blocks. REALIZE
fills the blocks; the plan owns the structure.
"""
from __future__ import annotations
import os
import re
import sys
_NT = os.path.expanduser("~/Desktop/neuron-talk")
_LR = os.path.expanduser("~/Desktop/lang-realizers")
for _p in (_NT, _LR):
if _p not in sys.path:
sys.path.insert(0, _p)
import propositions # noqa: E402 (the proven, faithful extractor)
from document_ir import DocumentIR, Section # noqa: E402
from geometry import Region # noqa: E402
# --------------------------------------------------------------------------- #
# Proposition quality — keep only clean, well-grounded claims.
# --------------------------------------------------------------------------- #
_JUNK_RE = re.compile(r"[.][a-z]{1,3}\b|[^A-Za-z0-9 '\-]") # ".o", stray symbols
def _has_banner_token(s: str) -> bool:
"""True if any word is an ALLCAPS banner token (DHARMA, ENGRAM, MEASURED)."""
for w in (s or "").split():
core = w.strip(".,:;'\"-")
if len(core) > 2 and core.isupper():
return True
return False
def _clean_prop(p, floor: float) -> bool:
if p.confidence < floor:
return False
if not p.subject or not (p.object or (p.obj_np is not None)):
return False
subj = (p.subject or "").strip()
obj = (p.object or "").strip()
if len(subj) < 2:
return False
# banner-derived shouty fragments read as garbage in prose
if _has_banner_token(subj) or _has_banner_token(obj):
return False
if propositions._is_shouty(p.sentence or ""):
return False
# junk tokens: file-extension fragments (".o"), stray non-word symbols
if _JUNK_RE.search(subj) or _JUNK_RE.search(obj):
return False
# a proposition whose object repeats the subject is usually a parse artifact
if obj and subj.lower() == obj.lower():
return False
# a bare copula with no real complement ("X is it") reads as noise
if p.predicate == "be" and obj.lower() in ("it", "no", "nothing", "empty", ""):
return False
return True
def _dedup(props):
"""Drop duplicate claims. Two axes: (a) identical (pred,obj,polarity), and
(b) same (subject,predicate) — which collapses a mis-split compound like
"detection is post-hoc eval" -> "Detection is post/hoc/eval" into one claim
(keep the highest-confidence surface)."""
props = sorted(props, key=lambda p: p.confidence, reverse=True)
seen_po, seen_sp, out = set(), set(), []
for p in props:
subj = (p.subject or "").lower()
po = (p.predicate, (p.object or "").lower(), p.polarity)
sp = (subj, p.predicate, p.polarity)
if po in seen_po or sp in seen_sp:
continue
seen_po.add(po)
seen_sp.add(sp)
out.append(p)
return out
# --------------------------------------------------------------------------- #
# Heading derivation — a clean human heading from a node.
# --------------------------------------------------------------------------- #
_HEADING_RE = re.compile(r"^\s*#{1,4}\s+(.{2,70})\s*$", re.M)
# node-type / system labels that are NOT topical headings
_NONTOPIC_LABEL = re.compile(r"^(memory|node|knowledge|doc|session)[:/]", re.I)
def _titlecase_banner(s: str) -> str:
"""A shouty banner ("CHRONOCEPTION — SCALE-INVARIANCE") makes a fine title
once Title-cased. Keep short acronyms uppercase."""
def fix(w):
core = w.strip("—-:,.")
if len(core) <= 3 and core.isupper():
return w # acronym
return w.capitalize()
return " ".join(fix(w) for w in s.split())
def _clean_heading(text: str) -> str | None:
"""First line only, no markdown, capped, banner Title-cased. None if unusable."""
if not text:
return None
line = text.strip().splitlines()[0]
line = re.sub(r"^#+\s*", "", line).strip().strip("#").strip()
# cut at a natural break so a long banner heading stays a heading, not a para
for sep in ("", " ", ": ", ". "):
if sep in line and len(line) > 48:
line = line.split(sep)[0].strip()
break
if not (3 <= len(line) <= 64):
return None
if propositions._is_shouty(line):
line = _titlecase_banner(line)
return line or None
def _heading_for(node: dict, fallback: str) -> str:
label = (node.get("label") or "").strip()
content = node.get("content") or ""
candidates: list[str] = []
# a node-type label ("memory:remembered") is never a topic — skip it
if label and not _NONTOPIC_LABEL.match(label):
candidates.append(label)
m = _HEADING_RE.search(content)
if m:
candidates.append(m.group(1))
# the leading banner/first sentence of the content is often the real title
first = re.split(r"(?<=[.\n])", content.strip(), maxsplit=1)[0] if content.strip() else ""
candidates.append(first)
for c in candidates:
h = _clean_heading(c)
if h:
return h
return fallback
def plan_document(region: Region, *, title: str, subtitle: str = "",
format_spec: dict | None = None,
conf_floor: float = 0.55,
max_sections: int = 8,
max_claims_per_section: int = 6) -> DocumentIR:
"""Region -> DocumentIR skeleton. The geometry dictates the outline."""
format_spec = format_spec or {}
doc = DocumentIR(title=title, subtitle=subtitle,
seed_id=region.nodes[0]["id"] if region.nodes else None,
format_spec=format_spec)
made = 0
seen_headings: set[str] = set()
for node in region.nodes:
if made >= max_sections:
break
props = propositions.extract(node.get("content") or "",
node_id=node.get("id"),
node_importance=float(node.get("importance") or 0.0),
max_sentences=10)
props = [p for p in props if _clean_prop(p, conf_floor)]
props = _dedup(props)
props.sort(key=lambda p: p.confidence, reverse=True)
props = props[:max_claims_per_section]
if not props:
continue
heading = _heading_for(node, fallback=f"Region {made + 1}")
# cross-section dedup: a topic appears once. Distinguish by top claim
# subject, else drop the collision so the outline stays clean.
if heading.lower() in seen_headings:
subj = (props[0].subject or "").strip().title()
alt = f"{heading}: {subj}" if subj and subj.lower() not in heading.lower() else None
if alt and alt.lower() not in seen_headings and len(alt) <= 64:
heading = alt
else:
continue
seen_headings.add(heading.lower())
sec = Section(heading=heading, level=2, seed_ids=[node["id"]])
# stash the planned propositions on the section for REALIZE
sec.__dict__["_planned_props"] = props
sec.__dict__["_node"] = node
doc.sections.append(sec)
made += 1
return doc
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"""base.py — the SurfaceProjector interface + registry.
THE key abstraction of the efferent projector: a projector is a pure function
from the surface-neutral, geometry-carrying DocumentIR to bytes on a target
SURFACE. The surface is a PARAMETER. Adding a surface = registering one more
projector; nothing upstream (plan/realize/cohere) changes.
DocumentIR --project--> bytes (per surface)
A TEXT projector reads ``block.sentences``. A NON-TEXT projector (music, image,
video) reads ``block.provenance`` — the geometry the IR carries — and decodes it
onto its surface. Both consume the SAME IR. That symmetry is the whole design:
the realizer generalizes into a multimodal projector, geometry -> any surface.
"""
from __future__ import annotations
from typing import Protocol, runtime_checkable
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from document_ir import DocumentIR # noqa: E402
@runtime_checkable
class SurfaceProjector(Protocol):
"""Geometry-document -> one surface. Implementations MUST be pure & faithful.
THE ONE SHARED SEAM. Every surface — text, music, image, video — conforms to
this single contract:
project(frame: DocumentIR) -> bytes
where ``frame`` is the geometry-carrying meaning-geometry (the SemFrame at
document scale; a single utterance is the degenerate one-section frame).
RECOMMENDED INTERNAL SHAPE (the peer music/text decomposition, blessed here
so all surfaces share it): a projector may split ``project`` into
spec = self.plan(frame) # meaning-geometry -> surface-specific spec
bytes = self.realize(spec) # spec -> surface, via this projector's PROFILE
``project`` is then ``realize(plan(frame))``. The PROFILE (a text lang-profile,
a music instr/mode-profile, an image layout-profile) is a property of the
projector instance — the pluggable knob. See :class:`TwoStageProjector`.
A TEXT projector's plan reads ``frame`` sentences; a MUSIC/IMAGE projector's
plan reads ``frame.all_provenance()`` — the geometry — and derives its spec
(pitch/harmony/rhythm, or layout) FROM the meaning, deterministically. Same
frame, different profile.
"""
surface: str # "markdown" | "docx" | "midi" | "audio" | "image" | "video"
media_type: str # MIME type of the emitted bytes
ext: str # file extension (no dot)
modality: str # "text" | "audio" | "image" | "video"
profile: object # the pluggable per-surface profile (may be None)
def project(self, doc: DocumentIR) -> bytes:
"""Emit the document on this surface. Returns raw bytes."""
...
class TwoStageProjector:
"""Optional base for the peer plan()/realize() decomposition.
Subclasses implement ``plan(frame) -> spec`` and ``realize(spec) -> bytes``;
``project`` is their composition. This is exactly the peer music interface
(spec = plan(frame, profile); surface = realize(spec, profile)) expressed so
that it still satisfies the single ``SurfaceProjector.project`` seam. Text,
music, and image projectors can all subclass this and remain interchangeable.
"""
surface: str = ""
media_type: str = ""
ext: str = ""
modality: str = ""
profile: object = None
def plan(self, doc: DocumentIR): # -> spec
raise NotImplementedError
def realize(self, spec) -> bytes:
raise NotImplementedError
def project(self, doc: DocumentIR) -> bytes:
return self.realize(self.plan(doc))
_REGISTRY: dict[str, SurfaceProjector] = {}
def register(projector: SurfaceProjector) -> SurfaceProjector:
_REGISTRY[projector.surface] = projector
return projector
def get_projector(surface: str) -> SurfaceProjector:
if surface not in _REGISTRY:
raise KeyError(f"no projector registered for surface {surface!r}; "
f"have {sorted(_REGISTRY)}")
return _REGISTRY[surface]
def available_surfaces() -> list[str]:
return sorted(_REGISTRY)
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"""docx.py — the .docx surface projector: an OWN minimal OOXML emitter.
Own-the-core: a .docx is just a ZIP of a few XML parts (WordprocessingML). We
emit it with the standard library only — ``zipfile`` + string XML — no
python-docx, no external dependency. This proves a "richer structured format"
surface without importing anyone else's toolkit.
Parts emitted (the minimal valid set + a styles part for real headings):
[Content_Types].xml
_rels/.rels
word/_rels/document.xml.rels
word/styles.xml (Title / Heading1 / Heading2 / Normal)
word/document.xml (the content)
Like the markdown projector it reads only the IR's realized sentences; it
invents nothing. The surface differs, the faithful content does not.
"""
from __future__ import annotations
import io
import os
import sys
import zipfile
from xml.sax.saxutils import escape
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from document_ir import DocumentIR # noqa: E402
from projectors.base import register # noqa: E402
_CONTENT_TYPES = """<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<Types xmlns="http://schemas.openxmlformats.org/package/2006/content-types">
<Default Extension="rels" ContentType="application/vnd.openxmlformats-package.relationships+xml"/>
<Default Extension="xml" ContentType="application/xml"/>
<Override PartName="/word/document.xml" ContentType="application/vnd.openxmlformats-officedocument.wordprocessingml.document.main+xml"/>
<Override PartName="/word/styles.xml" ContentType="application/vnd.openxmlformats-officedocument.wordprocessingml.styles+xml"/>
</Types>"""
_RELS = """<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<Relationships xmlns="http://schemas.openxmlformats.org/package/2006/relationships">
<Relationship Id="rId1" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/officeDocument" Target="word/document.xml"/>
</Relationships>"""
_DOC_RELS = """<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<Relationships xmlns="http://schemas.openxmlformats.org/package/2006/relationships">
<Relationship Id="rId1" Type="http://schemas.openxmlformats.org/officeDocument/2006/relationships/styles" Target="styles.xml"/>
</Relationships>"""
_W = "http://schemas.openxmlformats.org/wordprocessingml/2006/main"
_STYLES = f"""<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<w:styles xmlns:w="{_W}">
<w:style w:type="paragraph" w:default="1" w:styleId="Normal"><w:name w:val="Normal"/>
<w:rPr><w:sz w:val="22"/></w:rPr></w:style>
<w:style w:type="paragraph" w:styleId="Title"><w:name w:val="Title"/>
<w:pPr><w:spacing w:after="240"/></w:pPr>
<w:rPr><w:b/><w:sz w:val="52"/></w:rPr></w:style>
<w:style w:type="paragraph" w:styleId="Subtitle"><w:name w:val="Subtitle"/>
<w:rPr><w:i/><w:sz w:val="28"/><w:color w:val="555555"/></w:rPr></w:style>
<w:style w:type="paragraph" w:styleId="Heading1"><w:name w:val="heading 1"/>
<w:pPr><w:spacing w:before="240" w:after="120"/><w:outlineLvl w:val="0"/></w:pPr>
<w:rPr><w:b/><w:sz w:val="34"/></w:rPr></w:style>
<w:style w:type="paragraph" w:styleId="Heading2"><w:name w:val="heading 2"/>
<w:pPr><w:spacing w:before="200" w:after="100"/><w:outlineLvl w:val="1"/></w:pPr>
<w:rPr><w:b/><w:sz w:val="28"/></w:rPr></w:style>
</w:styles>"""
def _para(text: str, style: str | None = None) -> str:
ppr = f"<w:pPr><w:pStyle w:val=\"{style}\"/></w:pPr>" if style else ""
return (f"<w:p>{ppr}<w:r><w:t xml:space=\"preserve\">"
f"{escape(text)}</w:t></w:r></w:p>")
class DocxProjector:
surface = "docx"
media_type = ("application/vnd.openxmlformats-officedocument."
"wordprocessingml.document")
ext = "docx"
modality = "text"
def _document_xml(self, doc: DocumentIR) -> str:
body: list[str] = [_para(doc.title, "Title")]
if doc.subtitle:
body.append(_para(doc.subtitle, "Subtitle"))
abstract = doc.meta.get("abstract")
if abstract is not None and abstract.sentences:
body.append(_para(abstract.text()))
for sec in doc.sections:
style = "Heading1" if sec.level <= 1 else "Heading2"
body.append(_para(sec.heading, style))
for block in sec.blocks:
t = block.text()
if t:
body.append(_para(t))
return (f"<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"yes\"?>"
f"<w:document xmlns:w=\"{_W}\"><w:body>"
+ "".join(body)
+ "<w:sectPr><w:pgSz w:w=\"12240\" w:h=\"15840\"/>"
"<w:pgMar w:top=\"1440\" w:right=\"1440\" w:bottom=\"1440\" "
"w:left=\"1440\"/></w:sectPr></w:body></w:document>")
def project(self, doc: DocumentIR) -> bytes:
buf = io.BytesIO()
with zipfile.ZipFile(buf, "w", zipfile.ZIP_DEFLATED) as z:
z.writestr("[Content_Types].xml", _CONTENT_TYPES)
z.writestr("_rels/.rels", _RELS)
z.writestr("word/_rels/document.xml.rels", _DOC_RELS)
z.writestr("word/styles.xml", _STYLES)
z.writestr("word/document.xml", self._document_xml(doc))
return buf.getvalue()
register(DocxProjector())
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"""markdown.py — the Markdown surface projector (text facet).
The most tractable surface, and the reference implementation: reads the IR's
realized sentences and lays them out as Markdown. Introduces no content — it is
pure typography over the faithful text the realizer produced.
"""
from __future__ import annotations
import os
import sys
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from document_ir import DocumentIR # noqa: E402
from projectors.base import register # noqa: E402
class MarkdownProjector:
surface = "markdown"
media_type = "text/markdown"
ext = "md"
modality = "text"
def render_str(self, doc: DocumentIR) -> str:
lines: list[str] = [f"# {doc.title}"]
if doc.subtitle:
lines.append(f"\n*{doc.subtitle}*")
abstract = doc.meta.get("abstract")
if abstract is not None and abstract.sentences:
lines.append("")
lines.append(abstract.text())
for sec in doc.sections:
lines.append("")
lines.append(f"{'#' * max(2, sec.level)} {sec.heading}")
for block in sec.blocks:
body = block.text()
if body:
lines.append("")
lines.append(body)
return "\n".join(lines) + "\n"
def project(self, doc: DocumentIR) -> bytes:
return self.render_str(doc).encode("utf-8")
register(MarkdownProjector())
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"""midi.py — the MUSIC surface projector: geometry -> symbolic music (MIDI).
The first NON-TEXT surface, and the proof of the general shape. "Music is
language and it is math" (Will): symbolic music is tractable and geometry-native,
so it is the natural efferent twin to try first after text.
CRUCIALLY this projector does NOT read the realized sentences. It reads the IR's
GEOMETRY facet — ``block.provenance`` — and DECODES each edge onto a musical
surface. That is the whole thesis of the multimodal projector: the same
geometry-carrying IR drives text AND music; a text projector reads the words, a
music projector reads the meaning-geometry. The mapping is deterministic and
faithful to the geometry's structure:
relation lemma -> scale degree (same relation -> same pitch class;
meaning has a consistent sonic form)
polarity -> mode (aff = major third above; neg = minor
third / lowered — SACRED polarity is
audible, a negated edge sounds negated)
confidence -> note duration (stronger grounding rings longer)
importance -> velocity (more important source = louder)
section -> phrase + register shift (structure becomes musical form)
Own-the-core: a Standard MIDI File is a header chunk + a track chunk of
delta-timed events. We emit the raw bytes with ``struct`` — no external MIDI
library. Format 0, one track.
"""
from __future__ import annotations
import io
import os
import struct
import sys
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from document_ir import DocumentIR, Provenance # noqa: E402
from projectors.base import TwoStageProjector, register # noqa: E402
_TICKS = 480 # ticks per quarter note
_C_MAJOR = [0, 2, 4, 5, 7, 9, 11] # semitone offsets of a diatonic scale
def _vlq(n: int) -> bytes:
"""MIDI variable-length quantity encoding of a delta time."""
if n == 0:
return b"\x00"
out = bytearray()
out.append(n & 0x7F)
n >>= 7
while n:
out.insert(0, (n & 0x7F) | 0x80)
n >>= 7
return bytes(out)
def _degree_for(relation: str) -> int:
"""Stable scale degree for a relation lemma (same relation -> same pitch)."""
if not relation:
return 0
return sum(ord(c) for c in relation.lower()) % len(_C_MAJOR)
def _note_for(p: Provenance, base: int) -> tuple[int, int, int]:
"""(pitch, velocity, duration_ticks) for one geometry edge."""
root = base + _C_MAJOR[_degree_for(p.relation)]
# polarity -> mode: affirmed edges take the bright major third, negated edges
# take the darker minor third. The negation is AUDIBLE and never dropped.
third = 4 if p.polarity == "aff" else 3
pitch = max(24, min(96, root + (third if p.confidence >= 0.5 else 0)))
velocity = int(56 + 60 * min(1.0, max(0.0, p.importance)))
velocity = max(40, min(120, velocity))
# confidence -> duration: quarter .. dotted-half
dur = int(_TICKS * (0.5 + 1.5 * min(1.0, max(0.0, p.confidence))))
return pitch, velocity, dur
# a mode-profile: the pluggable musical knob (the peer's mode_profile). Scale +
# tempo. Swapping this profile re-voices the SAME geometry — surface as parameter.
_DEFAULT_PROFILE = {"scale": _C_MAJOR, "tempo_us": 500000,
"registers": [60, 55, 64, 50, 67, 48], "program": 0}
class MidiProjector(TwoStageProjector):
"""geometry -> symbolic music, in the shared two-stage shape.
``plan(frame)`` -> a music_spec: an ordered list of note dicts derived
deterministically from the frame's provenance geometry
(the peer's ``plan(frame, profile) -> spec``).
``realize(spec)`` -> Standard MIDI File bytes (the peer's
``realize(spec, profile) -> surface``; here the surface
is symbolic MIDI, the minimal audio proof — a richer
additive-synth audio projector conforms identically).
"""
surface = "midi"
media_type = "audio/midi"
ext = "mid"
modality = "audio"
def __init__(self, profile: dict | None = None):
self.profile = profile or _DEFAULT_PROFILE
# -- stage 1: meaning-geometry -> music_spec (reads the GEOMETRY facet) -- #
def plan(self, doc: DocumentIR) -> list[dict]:
registers = self.profile["registers"]
spec: list[dict] = []
for si, sec in enumerate(doc.sections):
base = registers[si % len(registers)]
provs = [p for p in sec.all_provenance()
if p.kind in ("fact", "interpretation")]
for i, p in enumerate(provs):
pitch, vel, dur = _note_for(p, base)
spec.append({"pitch": pitch, "velocity": vel, "dur": dur,
"rest_before": (_TICKS // 2) if (si > 0 and i == 0) else 0,
"relation": p.relation, "polarity": p.polarity})
return spec
# -- stage 2: music_spec -> MIDI bytes (own-core, no library) ------------ #
def realize(self, spec: list[dict]) -> bytes:
ev = bytearray()
ev += _vlq(0) + b"\xFF\x51\x03" + struct.pack(">I", self.profile["tempo_us"])[1:]
ev += _vlq(0) + bytes([0xC0, self.profile["program"] & 0x7F])
for note in spec:
ev += _vlq(note["rest_before"]) + bytes([0x90, note["pitch"], note["velocity"]])
ev += _vlq(note["dur"]) + bytes([0x80, note["pitch"], 0])
ev += _vlq(0) + b"\xFF\x2F\x00"
track = bytes(ev)
buf = io.BytesIO()
buf.write(b"MThd" + struct.pack(">IHHH", 6, 0, 1, _TICKS))
buf.write(b"MTrk" + struct.pack(">I", len(track)) + track)
return buf.getvalue()
register(MidiProjector())
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"""seams.py — documented efferent seams for IMAGE and VIDEO surfaces.
These are NOT implemented (per the build rails: architect, do not overbuild).
They are registered as first-class seams so the interface PROVES it accepts
future non-text projectors without any upstream change. Each documents exactly
what its decoder would read from the geometry-carrying IR, making the multimodal
generalization concrete rather than hand-wavy.
The symmetry that guarantees these are possible, not moonshots: they are the
efferent twins of multimodal INGEST. If meaning can HOLD an image (ingest as
first-class geometry), meaning can PROJECT one back. Video = image x sound x
TIME, and the engram already stores time (chronoception). So video falls out of
an image projector + the music projector + the stored temporal ordering.
"""
from __future__ import annotations
import os
import sys
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from document_ir import DocumentIR # noqa: E402
from projectors.base import register # noqa: E402
class _Seam:
"""A registered-but-unimplemented projector. Names its decoder contract."""
def project(self, doc: DocumentIR) -> bytes: # pragma: no cover - seam
raise NotImplementedError(
f"{self.surface!r} projector is a documented seam, not yet built. "
f"Decoder contract: {self.decoder_contract}")
class ImageProjector(_Seam):
surface = "image"
media_type = "image/png"
ext = "png"
modality = "image"
decoder_contract = (
"reads block.provenance as a spatial layout — nodes become regions, edges "
"become adjacencies; salience/importance drive size/contrast; polarity "
"drives figure/ground. The efferent twin of image ingest (a geometry->raster "
"decoder, learned or engineered), exactly mirroring the embedder that turned "
"the image INTO geometry.")
class VideoProjector(_Seam):
surface = "video"
media_type = "video/mp4"
ext = "mp4"
modality = "video"
decoder_contract = (
"image x sound x TIME. Composes the image projector (per-keyframe geometry "
"layout) with the midi/music projector (score) along the geometry's stored "
"temporal ordering (chronoception). Needs no new principle once image + music "
"exist — only a muxer.")
register(ImageProjector())
register(VideoProjector())
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"""provenance.py — the faithfulness audit + geometry->section trace.
A document projected from geometry is only worth anything if every claim traces
back. This module walks the DocumentIR and proves the discipline held:
* ZERO ungrounded claims (every fact/interpretation has a real node id),
* every emitted sentence maps to a geometry edge (or is a marked connective),
* SACRED polarity survived (negations are reported, never silently dropped),
* COHERE introduced no new geometry (connectives carry no claim).
It emits both a machine verdict and a human-readable geometry->section table.
"""
from __future__ import annotations
from document_ir import DocumentIR
def audit(doc: DocumentIR) -> dict:
provs = doc.all_provenance()
facts = [p for p in provs if p.kind in ("fact", "interpretation")]
connectives = [p for p in provs if p.kind == "connective"]
ungrounded = [p for p in facts if not p.node_id]
negations = [p for p in facts if p.polarity == "neg"]
node_ids = sorted({p.node_id for p in facts if p.node_id})
return {
"claims": len(facts),
"connectives": len(connectives),
"ungrounded_claims": len(ungrounded),
"negations_preserved": len(negations),
"distinct_source_nodes": len(node_ids),
"faithful": len(ungrounded) == 0,
"source_nodes": node_ids,
}
def trace_table(doc: DocumentIR) -> str:
"""Human-readable geometry -> section -> claim provenance table."""
lines = ["# Provenance — every claim traces geometry", ""]
lines.append(f"**Document:** {doc.title}")
a = audit(doc)
lines.append(f"**Claims:** {a['claims']} · **Ungrounded:** "
f"{a['ungrounded_claims']} · **Negations preserved:** "
f"{a['negations_preserved']} · **Source nodes:** "
f"{a['distinct_source_nodes']} · **Faithful:** "
f"{'YES' if a['faithful'] else 'NO'}")
lines.append("")
for si, sec in enumerate(doc.sections, 1):
lines.append(f"## {si}. {sec.heading}")
lines.append(f"_seed nodes: {', '.join(i[:8] for i in sec.seed_ids)}_")
lines.append("")
lines.append("| # | realized claim | traces geometry edge |")
lines.append("|---|----------------|----------------------|")
n = 0
for block in sec.blocks:
for sent, prov in zip(block.sentences, block.provenance):
if prov.kind == "connective":
continue
n += 1
edge = prov.trace().replace("|", "\\|")
s = sent.replace("|", "\\|")
lines.append(f"| {n} | {s} | {edge} |")
lines.append("")
return "\n".join(lines) + "\n"
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"""realize.py — REALIZE stage: fill each planned section with faithful passages.
Scales the PROVEN realizer from a single assertion to a passage. For each
planned proposition we build a realizer-ready clause (the proven
``_prop_to_clause`` mapping) and run it through the proven engine
(``engine.realize``), which is a deterministic grammar with the SACRED negation
contract — it never invents. Each realized sentence is paired with a
:class:`Provenance` that pins it to the exact geometry edge it came from.
"Passage, not a list of sentences": within a section we lightly vary sentence
openings and group related claims, but we add NO content the geometry did not
assert. The only non-geometry words are function words the grammar already owns
(articles, "and", conjunction of same-subject claims). Document-level flow is
COHERE's job; this stage owns intra-section fluency + fidelity.
"""
from __future__ import annotations
import os
import sys
_NT = os.path.expanduser("~/Desktop/neuron-talk")
_LR = os.path.expanduser("~/Desktop/lang-realizers")
for _p in (_NT, _LR):
if _p not in sys.path:
sys.path.insert(0, _p)
import engine # noqa: E402 (the proven no-LLM realizer)
from dialogue import _prop_to_clause # noqa: E402 (proven prop -> clause)
from document_ir import Block, DocumentIR, Provenance, Section # noqa: E402
def _provenance_from(p, kind: str = "fact") -> Provenance:
return Provenance(
subj_id=p.source_node_id, subject=p.subject, relation=p.predicate,
obj=p.object, polarity=p.polarity, confidence=round(float(p.confidence), 3),
node_id=p.source_node_id, kind=kind,
importance=float(getattr(p, "node_importance", 0.0) or 0.0),
salience=0.0,
)
import re as _re
# a well-formed declarative opens with a determiner, a proper noun, "I", or a
# capitalized head — not a mis-parsed object pronoun or a copula fragment.
_BAD_OPENERS = _re.compile(r"^(Me |It is I|There is|This is it|That is it)\b")
_VACUOUS = _re.compile(r"^\w+ (is|are|was|were) (it|no|nothing|empty|those|this|that)\.?$",
_re.I)
def _good_sentence(text: str) -> bool:
"""Fluency gate — drops degenerate realizations. NEVER loosens faithfulness;
it only refuses to SPEAK a claim whose surface came out malformed."""
words = text.rstrip(".").split()
if len(words) < 3:
return False
if _BAD_OPENERS.search(text):
return False
if _VACUOUS.match(text):
return False
# a sentence that is mostly one-letter/two-letter tokens is a parse artifact
short = sum(1 for w in words if len(w.strip(".,'")) <= 2)
if short > len(words) / 2:
return False
return True
def _realize_prop(p, lang: str = "en") -> tuple[str, Provenance] | None:
"""One proposition -> (faithful sentence, provenance) or None if it drops."""
clause = _prop_to_clause(p)
text = engine.realize(clause, lang)
if not text or not text.strip():
return None
text = text.strip()
if not text.endswith((".", "!", "?")):
text += "."
# capitalize first character (proper nouns / "I" already handled by grammar)
text = text[0].upper() + text[1:]
if not _good_sentence(text):
return None
return text, _provenance_from(p)
def realize_document(doc: DocumentIR, lang: str = "en") -> DocumentIR:
"""Fill every planned section's blocks with faithful, realized passages."""
for sec in doc.sections:
planned = sec.__dict__.get("_planned_props", [])
block = Block(role="body")
summary_bits: list[str] = []
for p in planned:
r = _realize_prop(p, lang)
if r is None:
continue
text, prov = r
block.sentences.append(text)
block.provenance.append(prov)
if len(summary_bits) < 1:
# a short grounded gloss for TOC / pptx bullets
obj = (prov.obj or "").strip().rstrip(".")
if obj:
summary_bits.append(obj)
if block.sentences:
sec.blocks.append(block)
sec.summary = summary_bits[0] if summary_bits else ""
# drop the transient planning payload; the IR is now self-contained
sec.__dict__.pop("_planned_props", None)
sec.__dict__.pop("_node", None)
# prune sections that realized to nothing
doc.sections = [s for s in doc.sections if s.blocks]
return doc
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// audio-demo.el - Drive the native audio surface: render a tone per instrument
// from its LEARNED signature, then render a small meaning-phrase "piece".
// Entry point: top-level statement calls main() (same convention as the
// examples' top-level println(run_test())).
fn micros_to_str(xs: [Int]) -> String {
let n: Int = native_list_len(xs)
let out: String = ""
let i: Int = 0
while i < n {
if i > 0 { let out: String = out + "," }
let out: String = out + int_to_str(native_list_get(xs, i))
let i: Int = i + 1
}
return out
}
// Render a 1.0s A4 (midi 69) tone from a signature file, print the parsed
// partials (proving the numbers came from the engram .sig), write the WAV.
fn render_tone(name: String, sigpath: String, outpath: String, table: [Int]) -> Int {
let lines: [String] = sig_load(sigpath)
let partials: [Int] = parse_micros(sig_field(lines, "partials"))
println("[" + name + "] partials_n=" + sig_field(lines, "partials_n") + " parsed_partials_micro(scale 1e6)=" + micros_to_str(partials))
println("[" + name + "] raw partials line from .sig = " + sig_field(lines, "partials"))
let freq: Int = freq_of_midi(69)
let note: [Int] = synth_from_sig(lines, freq, 1000, 900, 44100, table)
let n: Int = native_list_len(note)
let ok: Int = wav_write(outpath, note, n, 44100)
println("[" + name + "] rendered " + int_to_str(n) + " samples -> " + outpath + " (write_ok=" + int_to_str(ok) + ")")
return n
}
fn run_demo() -> Int {
let table: [Int] = sin_table()
fs_mkdir("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out")
println("=== TONES: render A4 (midi 69) from each learned signature ===")
render_tone("flute", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/flute.sig", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-flute.wav", table)
render_tone("clarinet", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/clarinet.sig", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-clarinet.wav", table)
render_tone("violin", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/violin.sig", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-violin.wav", table)
render_tone("piano", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/piano.sig", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-piano.wav", table)
render_tone("organ", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/organ.sig", "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/tone-organ.wav", table)
println("")
println("=== PIECE: a 6-frame meaning phrase (incl. a NEG frame) ===")
let frames: [[String]] = native_list_empty()
let frames: [[String]] = native_list_append(frames, audio_frame("agent", "aff", "0.9", "0.8", "0", "s1"))
let frames: [[String]] = native_list_append(frames, audio_frame("theme", "aff", "0.7", "0.6", "0", "s2"))
let frames: [[String]] = native_list_append(frames, audio_frame("cause", "aff", "0.8", "0.9", "1", "s3"))
let frames: [[String]] = native_list_append(frames, audio_frame("negation", "neg", "0.85", "0.7", "0", "s4"))
let frames: [[String]] = native_list_append(frames, audio_frame("goal", "aff", "0.6", "0.5", "1", "s5"))
let frames: [[String]] = native_list_append(frames, audio_frame("result", "aff", "0.95", "1.0", "0", "s6"))
// Print the plan so the NEG frame's minor third (+3) vs major (+4) is visible.
let nf: Int = native_list_len(frames)
let fi: Int = 0
while fi < nf {
let frame: [String] = native_list_get(frames, fi)
let plan: [Int] = plan_note(frame)
let pol: String = surface_get(frame, "polarity")
let third_name: String = "major(+4)"
if str_eq(pol, "neg") { let third_name: String = "MINOR(+3)" }
println("frame " + int_to_str(fi) + " relation=" + surface_get(frame, "relation") + " polarity=" + pol + " -> midi=" + int_to_str(native_list_get(plan, 0)) + " dur_ms=" + int_to_str(native_list_get(plan, 1)) + " amp_pm=" + int_to_str(native_list_get(plan, 2)) + " third=" + third_name)
let fi: Int = fi + 1
}
let piano_lines: [String] = sig_load("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/piano.sig")
let total: Int = realize_audio(frames, piano_lines, "/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/piece.wav", 44100, table)
println("PIECE rendered " + int_to_str(total) + " samples -> /Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/piece.wav")
return total
}
println("audio-demo main returned samples=" + int_to_str(run_demo()))
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// audio-surface.el - Native own-core additive-synthesis audio surface.
//
// The AUDIO efferent seam, native, no Python and no library. This renders real
// PCM .wav bytes from instrument SIGNATURES read from engram-sourced .sig data
// files (elp/faculty/sig/*.sig) - the partial amplitudes are NEVER literals in
// this source; they are parsed from the learned signature at run time. That is
// the whole proof: render-from-learned-signatures.
//
// EL has no float arithmetic operator (codegen emits raw int64 ops for + - * /
// on the shared 64-bit slot) and no float-arithmetic natives - so ALL synthesis
// math here is own-core INTEGER fixed-point. Angles use a quarter-wave sine
// table (scale 10000) from a fixed-point Taylor series; amplitudes are parsed to
// micro (scale 1e6) straight from the .sig text; frequencies are milliHz ints.
//
// Pipeline mirrors the two-stage projector (midi.py): plan_note(frame) reads a
// frame's meaning-geometry slot-map and derives (pitch, duration, amplitude);
// realize_audio SUPERPOSES the signature's partials (the compose op) and
// serialises RIFF/WAVE. Same frame -> midi OR audio.
// -- integer decimal + string helpers -----------------------------------------
fn str_to_int_el(s: String) -> Int {
let n: Int = str_len(s)
let i: Int = 0
let v: Int = 0
let neg: Bool = false
while i < n {
let c: Int = str_char_code(s, i)
if c == 45 { let neg: Bool = true }
if c >= 48 {
if c < 58 {
let v: Int = v * 10 + (c - 48)
}
}
let i: Int = i + 1
}
if neg { return 0 - v }
return v
}
fn parse_micro(s: String) -> Int {
let dot: Int = str_index_of(s, ".")
if dot < 0 {
return str_to_int_el(s) * 1000000
}
let n: Int = str_len(s)
let ipart: String = str_slice(s, 0, dot)
let fpart: String = str_slice(s, dot + 1, n)
let iv: Int = str_to_int_el(ipart)
let fv: Int = 0
let scale: Int = 100000
let fn2: Int = str_len(fpart)
let i: Int = 0
while i < 6 {
let d: Int = 0
if i < fn2 {
let d: Int = str_char_code(fpart, i) - 48
}
let fv: Int = fv + d * scale
let scale: Int = scale / 10
let i: Int = i + 1
}
return iv * 1000000 + fv
}
// -- signature (engram data file) loader ---------------------------------------
fn sig_load(path: String) -> [String] {
let text: String = fs_read(path)
return str_split(text, "\n")
}
fn sig_field(lines: [String], key: String) -> String {
let pref: String = key + ": "
let n: Int = native_list_len(lines)
let plen: Int = str_len(pref)
let i: Int = 0
while i < n {
let ln: String = native_list_get(lines, i)
if str_starts_with(ln, pref) {
return str_slice(ln, plen, str_len(ln))
}
let i: Int = i + 1
}
return ""
}
fn parse_micros(csv: String) -> [Int] {
let parts: [String] = str_split(csv, ",")
let n: Int = native_list_len(parts)
let out: [Int] = native_list_empty()
let i: Int = 0
while i < n {
let out: [Int] = native_list_append(out, parse_micro(native_list_get(parts, i)))
let i: Int = i + 1
}
return out
}
// -- fixed-point sine (own-core, quarter-wave Taylor table, scale 10000) --------
fn sin_table() -> [Int] {
let HP: Int = 1570796
let t: [Int] = native_list_empty()
let q: Int = 0
while q < 257 {
let x: Int = q * HP / 256
let x2: Int = x * x / 1000000
let x3: Int = x2 * x / 1000000
let x5: Int = x3 * x2 / 1000000
let x7: Int = x5 * x2 / 1000000
let x9: Int = x7 * x2 / 1000000
let s: Int = x - x3 / 6 + x5 / 120 - x7 / 5040 + x9 / 362880
let t: [Int] = native_list_append(t, s / 100)
let q: Int = q + 1
}
return t
}
fn sin_lookup(t: [Int], phase: Int) -> Int {
let p: Int = phase % 1024
if p < 0 { let p: Int = p + 1024 }
let quad: Int = p / 256
let r: Int = p % 256
if quad == 0 { return native_list_get(t, r) }
if quad == 1 { return native_list_get(t, 256 - r) }
if quad == 2 { return 0 - native_list_get(t, r) }
return 0 - native_list_get(t, 256 - r)
}
fn isqrt_int(n: Int) -> Int {
if n <= 0 { return 0 }
let x: Int = n
let y: Int = (x + 1) / 2
while y < x {
let x: Int = y
let y: Int = (x + n / x) / 2
}
return x
}
// freq_of_midi: equal-tempered frequency in milliHz. 440000 mHz at midi 69.
fn freq_of_midi(m: Int) -> Int {
let f: Int = 440000
if m > 69 {
let k: Int = m - 69
let i: Int = 0
while i < k {
let f: Int = f * 1059463 / 1000000
let i: Int = i + 1
}
return f
}
if m < 69 {
let k: Int = 69 - m
let i: Int = 0
while i < k {
let f: Int = f * 1000000 / 1059463
let i: Int = i + 1
}
return f
}
return f
}
// -- envelope (ADSR), scale 1000 -----------------------------------------------
fn adsr_env(i: Int, total: Int, atk_n: Int, dec_n: Int, sus_pm: Int, rel_n: Int) -> Int {
if i < atk_n {
if atk_n == 0 { return 1000 }
return 1000 * i / atk_n
}
if i < atk_n + dec_n {
if dec_n == 0 { return sus_pm }
return 1000 - (1000 - sus_pm) * (i - atk_n) / dec_n
}
let rel_start: Int = total - rel_n
if i < rel_start {
return sus_pm
}
if rel_n == 0 { return 0 }
let left: Int = total - i
return sus_pm * left / rel_n
}
// -- note synthesis: SUPERPOSE the learned partials -> [Int] samples -----------
fn note_samples(freq_mHz: Int, dur_ms: Int, rate: Int, partials: [Int], sumP: Int, b_micro: Int, vib_rate: Int, vib_cents: Int, atk_ms: Int, dec_ms: Int, sus_pm: Int, rel_ms: Int, amp_pm: Int, table: [Int]) -> [Int] {
let total: Int = dur_ms * rate / 1000
let atk_n: Int = atk_ms * rate / 1000
let dec_n: Int = dec_ms * rate / 1000
let rel_n: Int = rel_ms * rate / 1000
let np: Int = native_list_len(partials)
let half_mhz: Int = rate * 1000 / 2
let out: [Int] = native_list_empty()
let i: Int = 0
while i < total {
let acc: Int = 0
let k: Int = 0
while k < np {
let harm: Int = k + 1
let amp_k: Int = native_list_get(partials, k)
let factor: Int = 1000000
if b_micro > 0 {
let val: Int = 1000000 + b_micro * harm * harm
let factor: Int = isqrt_int(val * 1000000)
}
let fn_mhz: Int = freq_mHz * harm
let fn_mhz: Int = fn_mhz * factor / 1000000
if vib_cents > 0 {
if vib_rate > 0 {
let vphase: Int = i * vib_rate * 1024 / rate
let vs: Int = sin_lookup(table, vphase)
let vibf: Int = 1000000 + (vib_cents * vs * 833) / 10000
let fn_mhz: Int = fn_mhz * vibf / 1000000
}
}
if fn_mhz <= half_mhz {
let phase: Int = i * fn_mhz * 1024 / (rate * 1000)
let sv: Int = sin_lookup(table, phase)
let acc: Int = acc + sv * amp_k / 1000000
}
let k: Int = k + 1
}
let env: Int = adsr_env(i, total, atk_n, dec_n, sus_pm, rel_n)
let s16: Int = acc * 2800000 / sumP
let s16: Int = s16 * env / 1000
let s16: Int = s16 * amp_pm / 1000
if s16 > 32767 { let s16: Int = 32767 }
if s16 < 0 - 32767 { let s16: Int = 0 - 32767 }
let out: [Int] = native_list_append(out, s16)
let i: Int = i + 1
}
return out
}
fn synth_from_sig(lines: [String], freq_mHz: Int, dur_ms: Int, amp_pm: Int, rate: Int, table: [Int]) -> [Int] {
let partials: [Int] = parse_micros(sig_field(lines, "partials"))
let np: Int = native_list_len(partials)
let sumP: Int = 0
let j: Int = 0
while j < np {
let pj: Int = native_list_get(partials, j)
let sumP: Int = sumP + pj
let j: Int = j + 1
}
if sumP <= 0 { let sumP: Int = 1000000 }
let adsr: [String] = str_split(sig_field(lines, "adsr"), ",")
let atk_ms: Int = parse_micro(native_list_get(adsr, 0)) / 1000
let dec_ms: Int = parse_micro(native_list_get(adsr, 1)) / 1000
let sus_pm: Int = parse_micro(native_list_get(adsr, 2)) / 1000
let rel_ms: Int = parse_micro(native_list_get(adsr, 3)) / 1000
let b_micro: Int = parse_micro(sig_field(lines, "inharmonicity_B"))
let vib_rate: Int = str_to_int_el(sig_field(lines, "vibrato_rate_hz"))
let vib_cents: Int = str_to_int_el(sig_field(lines, "vibrato_depth_cents"))
return note_samples(freq_mHz, dur_ms, rate, partials, sumP, b_micro, vib_rate, vib_cents, atk_ms, dec_ms, sus_pm, rel_ms, amp_pm, table)
}
// -- byte-buffer helpers (own-core, no library) --------------------------------
fn put_tag(buf: String, pos: Int, s: String) -> String {
let n: Int = str_len(s)
let i: Int = 0
while i < n {
let buf: String = __str_set_char(buf, pos + i, str_char_code(s, i))
let i: Int = i + 1
}
return buf
}
fn put_u32le(buf: String, pos: Int, v: Int) -> String {
let buf: String = __str_set_char(buf, pos, v % 256)
let buf: String = __str_set_char(buf, pos + 1, (v / 256) % 256)
let buf: String = __str_set_char(buf, pos + 2, (v / 65536) % 256)
let buf: String = __str_set_char(buf, pos + 3, (v / 16777216) % 256)
return buf
}
fn put_u16le(buf: String, pos: Int, v: Int) -> String {
let buf: String = __str_set_char(buf, pos, v % 256)
let buf: String = __str_set_char(buf, pos + 1, (v / 256) % 256)
return buf
}
// -- WAV serializer: own-core RIFF/WAVE, PCM mono 16-bit -----------------------
fn wav_write(path: String, samples: [Int], n: Int, rate: Int) -> Int {
let data_len: Int = n * 2
let total: Int = 44 + data_len
let buf: String = __str_alloc(total)
let buf: String = put_tag(buf, 0, "RIFF")
let buf: String = put_u32le(buf, 4, 36 + data_len)
let buf: String = put_tag(buf, 8, "WAVE")
let buf: String = put_tag(buf, 12, "fmt ")
let buf: String = put_u32le(buf, 16, 16)
let buf: String = put_u16le(buf, 20, 1)
let buf: String = put_u16le(buf, 22, 1)
let buf: String = put_u32le(buf, 24, rate)
let buf: String = put_u32le(buf, 28, rate * 2)
let buf: String = put_u16le(buf, 32, 2)
let buf: String = put_u16le(buf, 34, 16)
let buf: String = put_tag(buf, 36, "data")
let buf: String = put_u32le(buf, 40, data_len)
let i: Int = 0
while i < n {
let v: Int = native_list_get(samples, i)
if v < 0 { let v: Int = v + 65536 }
let buf: String = __str_set_char(buf, 44 + i * 2, v % 256)
let buf: String = __str_set_char(buf, 44 + i * 2 + 1, (v / 256) % 256)
let i: Int = i + 1
}
let ok: Int = fs_write_bytes(path, buf, total)
return ok
}
// -- plan: frame slot-map -> note atom (pitch, duration, amplitude) ------------
fn audio_frame(relation: String, polarity: String, confidence: String, importance: String, salience: String, subj_id: String) -> [String] {
let f: [String] = native_list_empty()
let f: [String] = native_list_append(f, "relation")
let f: [String] = native_list_append(f, relation)
let f: [String] = native_list_append(f, "polarity")
let f: [String] = native_list_append(f, polarity)
let f: [String] = native_list_append(f, "confidence")
let f: [String] = native_list_append(f, confidence)
let f: [String] = native_list_append(f, "importance")
let f: [String] = native_list_append(f, importance)
let f: [String] = native_list_append(f, "salience")
let f: [String] = native_list_append(f, salience)
let f: [String] = native_list_append(f, "subj_id")
let f: [String] = native_list_append(f, subj_id)
return f
}
fn degree_offset(deg: Int) -> Int {
if deg == 0 { return 0 }
if deg == 1 { return 2 }
if deg == 2 { return 4 }
if deg == 3 { return 5 }
if deg == 4 { return 7 }
if deg == 5 { return 9 }
return 11
}
// returns [midi, dur_ms, amp_pm]
fn plan_note(frame: [String]) -> [Int] {
let relation: String = surface_get(frame, "relation")
let polarity: String = surface_get(frame, "polarity")
let confidence: String = surface_get(frame, "confidence")
let importance: String = surface_get(frame, "importance")
let salience: String = surface_get(frame, "salience")
let rn: Int = str_len(relation)
let csum: Int = 0
let i: Int = 0
while i < rn {
let cc: Int = str_char_code(relation, i)
let csum: Int = csum + cc
let i: Int = i + 1
}
let deg: Int = csum % 7
let third: Int = 4
if str_eq(polarity, "neg") { let third: Int = 3 }
let sal_oct: Int = str_to_int_el(salience)
let doff: Int = degree_offset(deg)
let midi: Int = 60 + sal_oct * 12 + doff + third
let conf_micro: Int = parse_micro(confidence)
let dur_ms: Int = 200 + conf_micro / 1000
let imp_micro: Int = parse_micro(importance)
let amp_pm: Int = 400 + imp_micro / 2000
let out: [Int] = native_list_empty()
let out: [Int] = native_list_append(out, midi)
let out: [Int] = native_list_append(out, dur_ms)
let out: [Int] = native_list_append(out, amp_pm)
return out
}
fn realize_audio(frames: [[String]], sig_lines: [String], path: String, rate: Int, table: [Int]) -> Int {
let nf: Int = native_list_len(frames)
let all: [Int] = native_list_empty()
let count: Int = 0
let fi: Int = 0
while fi < nf {
let frame: [String] = native_list_get(frames, fi)
let plan: [Int] = plan_note(frame)
let midi: Int = native_list_get(plan, 0)
let dur_ms: Int = native_list_get(plan, 1)
let amp_pm: Int = native_list_get(plan, 2)
let freq: Int = freq_of_midi(midi)
let note: [Int] = synth_from_sig(sig_lines, freq, dur_ms, amp_pm, rate, table)
let nn: Int = native_list_len(note)
let j: Int = 0
while j < nn {
let all: [Int] = native_list_append(all, native_list_get(note, j))
let j: Int = j + 1
}
let count: Int = count + nn
let fi: Int = fi + 1
}
let ok: Int = wav_write(path, all, count, rate)
return count
}
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// image-demo.el - Drive the native PNG surface: plan a scene from a small
// meaning phrase (incl. a NEG frame) and emit a byte-valid 64x64 PNG whose
// palette is read from elp/faculty/sig/scene.basis.
fn img_frame(relation: String, polarity: String, confidence: String, importance: String, salience: String, subj_id: String) -> [String] {
let f: [String] = native_list_empty()
let f: [String] = native_list_append(f, "relation")
let f: [String] = native_list_append(f, relation)
let f: [String] = native_list_append(f, "polarity")
let f: [String] = native_list_append(f, polarity)
let f: [String] = native_list_append(f, "confidence")
let f: [String] = native_list_append(f, confidence)
let f: [String] = native_list_append(f, "importance")
let f: [String] = native_list_append(f, importance)
let f: [String] = native_list_append(f, "salience")
let f: [String] = native_list_append(f, salience)
let f: [String] = native_list_append(f, "subj_id")
let f: [String] = native_list_append(f, subj_id)
return f
}
fn rgb_str(c: [Int]) -> String {
return int_to_str(native_list_get(c, 0)) + "," + int_to_str(native_list_get(c, 1)) + "," + int_to_str(native_list_get(c, 2))
}
fn run_image() -> Int {
fs_mkdir("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out")
let table: [Int] = crc_table()
println("crc_table[1]=" + int_to_str(native_list_get(table, 1)) + " (expect 1996959894 / 0x77073096)")
let basis: [String] = basis_load("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/sig/scene.basis")
let warm: [Int] = parse_rgb(basis_field(basis, "warm"))
let cool: [Int] = parse_rgb(basis_field(basis, "cool"))
let bg: [Int] = parse_rgb(basis_field(basis, "bg"))
println("basis warm=" + rgb_str(warm) + " cool=" + rgb_str(cool) + " bg=" + rgb_str(bg) + " (read from scene.basis)")
let frames: [[String]] = native_list_empty()
let frames: [[String]] = native_list_append(frames, img_frame("agent", "aff", "0.9", "0.8", "0", "s1"))
let frames: [[String]] = native_list_append(frames, img_frame("theme", "aff", "0.7", "0.6", "1", "s2"))
let frames: [[String]] = native_list_append(frames, img_frame("cause", "aff", "0.8", "0.9", "0", "s3"))
let frames: [[String]] = native_list_append(frames, img_frame("negation", "neg", "0.85", "0.7", "1", "s4"))
let frames: [[String]] = native_list_append(frames, img_frame("goal", "aff", "0.6", "0.5", "0", "s5"))
let frames: [[String]] = native_list_append(frames, img_frame("result", "aff", "0.95", "1.0", "1", "s6"))
let shapes: [[Int]] = plan_scene(frames, warm, cool)
let ns: Int = native_list_len(shapes)
println("planned " + int_to_str(ns) + " shapes:")
let si: Int = 0
while si < ns {
let sh: [Int] = native_list_get(shapes, si)
let pol: String = surface_get(native_list_get(frames, si), "polarity")
println(" shape " + int_to_str(si) + " type=" + int_to_str(native_list_get(sh, 0)) + " x=" + int_to_str(native_list_get(sh, 1)) + " y=" + int_to_str(native_list_get(sh, 2)) + " size=" + int_to_str(native_list_get(sh, 3)) + " rgb=" + int_to_str(native_list_get(sh, 4)) + "," + int_to_str(native_list_get(sh, 5)) + "," + int_to_str(native_list_get(sh, 6)) + " polarity=" + pol)
let si: Int = si + 1
}
let raw: [Int] = rasterize(64, 64, shapes, bg)
println("rasterized raw (filtered scanlines) bytes=" + int_to_str(native_list_len(raw)) + " (expect 12352)")
let png: [Int] = png_build(64, 64, raw, table)
let plen: Int = native_list_len(png)
let ok: Int = png_write("/Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/scene.png", png)
println("PNG bytes=" + int_to_str(plen) + " -> /Users/will/Development/neuron-technologies/foundation/el/.claude/worktrees/agent-aaf04b0a9714c4070/elp/faculty/out/scene.png (write_ok=" + int_to_str(ok) + ")")
return plen
}
println("image-demo returned png_bytes=" + int_to_str(run_image()))
+412
View File
@@ -0,0 +1,412 @@
// image-surface.el - Native own-core raster PNG surface (the image efferent
// twin of audio). Renders a 64x64 RGB scene deterministically from a frame's
// meaning-geometry, then serialises a byte-valid PNG entirely own-core:
// 8-byte magic, IHDR, IDAT (zlib STORED/uncompressed DEFLATE + Adler32), IEND,
// with a per-chunk CRC32 computed via software xor32 (EL has no bitwise ops).
//
// The RGB palette basis is read from elp/faculty/sig/scene.basis (data, not
// literals) - the same read-from-learned discipline as the audio signatures.
// Integer-only throughout; pixels are composed functionally (painter's order)
// so no list mutation is needed.
// -- small int/parse helpers (self-contained) ----------------------------------
fn i_str_to_int(s: String) -> Int {
let n: Int = str_len(s)
let i: Int = 0
let v: Int = 0
while i < n {
let c: Int = str_char_code(s, i)
if c >= 48 {
if c < 58 {
let v: Int = v * 10 + (c - 48)
}
}
let i: Int = i + 1
}
return v
}
fn basis_load(path: String) -> [String] {
return str_split(fs_read(path), "\n")
}
fn basis_field(lines: [String], key: String) -> String {
let pref: String = key + ": "
let n: Int = native_list_len(lines)
let plen: Int = str_len(pref)
let i: Int = 0
while i < n {
let ln: String = native_list_get(lines, i)
if str_starts_with(ln, pref) {
return str_slice(ln, plen, str_len(ln))
}
let i: Int = i + 1
}
return ""
}
fn parse_rgb(csv: String) -> [Int] {
let parts: [String] = str_split(csv, ",")
let out: [Int] = native_list_empty()
let n: Int = native_list_len(parts)
let i: Int = 0
while i < n {
let v: Int = i_str_to_int(native_list_get(parts, i))
let out: [Int] = native_list_append(out, v)
let i: Int = i + 1
}
return out
}
// -- software 32-bit XOR (no bitwise ops in EL) --------------------------------
fn xor32(a: Int, b: Int) -> Int {
let r: Int = 0
let bit: Int = 1
let i: Int = 0
while i < 32 {
let abit: Int = (a / bit) % 2
let bbit: Int = (b / bit) % 2
if abit != bbit {
let add: Int = bit
let r: Int = r + add
}
let bit: Int = bit * 2
let i: Int = i + 1
}
return r
}
// -- CRC32 (table-driven, table built with xor32) ------------------------------
fn crc_table() -> [Int] {
let t: [Int] = native_list_empty()
let n: Int = 0
while n < 256 {
let c: Int = n
let k: Int = 0
while k < 8 {
if c % 2 == 1 {
let h: Int = c / 2
let c: Int = xor32(h, 3988292384)
} else {
let c: Int = c / 2
}
let k: Int = k + 1
}
let t: [Int] = native_list_append(t, c)
let n: Int = n + 1
}
return t
}
fn crc32_of(bytes: [Int], table: [Int]) -> Int {
let crc: Int = 4294967295
let n: Int = native_list_len(bytes)
let i: Int = 0
while i < n {
let b: Int = native_list_get(bytes, i)
let lo: Int = crc % 256
let idx: Int = xor32(lo, b) % 256
let tv: Int = native_list_get(table, idx)
let hi: Int = crc / 256
let crc: Int = xor32(hi, tv)
let i: Int = i + 1
}
return xor32(crc, 4294967295)
}
// -- Adler32 (for the zlib trailer) --------------------------------------------
fn adler32_of(bytes: [Int]) -> Int {
let a: Int = 1
let b: Int = 0
let n: Int = native_list_len(bytes)
let i: Int = 0
while i < n {
let byte: Int = native_list_get(bytes, i)
let a: Int = (a + byte) % 65521
let b: Int = (b + a) % 65521
let i: Int = i + 1
}
return b * 65536 + a
}
// -- byte-list append helpers --------------------------------------------------
fn app_u32be(dst: [Int], v: Int) -> [Int] {
let dst: [Int] = native_list_append(dst, (v / 16777216) % 256)
let dst: [Int] = native_list_append(dst, (v / 65536) % 256)
let dst: [Int] = native_list_append(dst, (v / 256) % 256)
let dst: [Int] = native_list_append(dst, v % 256)
return dst
}
fn app_tag(dst: [Int], s: String) -> [Int] {
let n: Int = str_len(s)
let i: Int = 0
while i < n {
let dst: [Int] = native_list_append(dst, str_char_code(s, i))
let i: Int = i + 1
}
return dst
}
fn app_all(dst: [Int], src: [Int]) -> [Int] {
let n: Int = native_list_len(src)
let i: Int = 0
while i < n {
let dst: [Int] = native_list_append(dst, native_list_get(src, i))
let i: Int = i + 1
}
return dst
}
// -- plan: frame meaning-geometry -> shape atoms -------------------------------
// shape = [type, x, y, size, r, g, b] (type 0=rect 1=disc 2=triangle)
fn charsum(s: String) -> Int {
let n: Int = str_len(s)
let i: Int = 0
let acc: Int = 0
while i < n {
let c: Int = str_char_code(s, i)
let acc: Int = acc + c
let i: Int = i + 1
}
return acc
}
fn micro_of(s: String) -> Int {
let dot: Int = str_index_of(s, ".")
if dot < 0 { return i_str_to_int(s) * 1000000 }
let n: Int = str_len(s)
let fp: String = str_slice(s, dot + 1, n)
let ip: String = str_slice(s, 0, dot)
let iv: Int = i_str_to_int(ip)
let fv: Int = 0
let scale: Int = 100000
let fl: Int = str_len(fp)
let i: Int = 0
while i < 6 {
let d: Int = 0
if i < fl { let d: Int = str_char_code(fp, i) - 48 }
let fv: Int = fv + d * scale
let scale: Int = scale / 10
let i: Int = i + 1
}
return iv * 1000000 + fv
}
fn plan_scene(frames: [[String]], warm: [Int], cool: [Int]) -> [[Int]] {
let shapes: [[Int]] = native_list_empty()
let nf: Int = native_list_len(frames)
let fi: Int = 0
while fi < nf {
let fr: [String] = native_list_get(frames, fi)
let relation: String = surface_get(fr, "relation")
let polarity: String = surface_get(fr, "polarity")
let confidence: String = surface_get(fr, "confidence")
let importance: String = surface_get(fr, "importance")
let salience: String = surface_get(fr, "salience")
// relation -> shape type
let stype: Int = charsum(relation) % 3
// confidence -> size (8..22)
let cmi: Int = micro_of(confidence)
let size: Int = 8 + cmi / 71428
// salience -> y
let sal: Int = i_str_to_int(salience)
let y: Int = 6 + sal * 26
// subj_id/index -> x
let x: Int = 4 + (fi * 10) % 48
// polarity -> warm/cool base color
let br: Int = native_list_get(warm, 0)
let bg2: Int = native_list_get(warm, 1)
let bb: Int = native_list_get(warm, 2)
if str_eq(polarity, "neg") {
let br: Int = native_list_get(cool, 0)
let bg2: Int = native_list_get(cool, 1)
let bb: Int = native_list_get(cool, 2)
}
// importance -> brightness (500..1000 permille)
let imi: Int = micro_of(importance)
let bpm: Int = 500 + imi / 2000
let r: Int = br * bpm / 1000
let g: Int = bg2 * bpm / 1000
let b: Int = bb * bpm / 1000
let sh: [Int] = native_list_empty()
let sh: [Int] = native_list_append(sh, stype)
let sh: [Int] = native_list_append(sh, x)
let sh: [Int] = native_list_append(sh, y)
let sh: [Int] = native_list_append(sh, size)
let sh: [Int] = native_list_append(sh, r)
let sh: [Int] = native_list_append(sh, g)
let sh: [Int] = native_list_append(sh, b)
let shapes: [[Int]] = native_list_append(shapes, sh)
let fi: Int = fi + 1
}
return shapes
}
// covers: is (px,py) inside this shape?
fn covers(sh: [Int], px: Int, py: Int) -> Bool {
let stype: Int = native_list_get(sh, 0)
let sx: Int = native_list_get(sh, 1)
let sy: Int = native_list_get(sh, 2)
let size: Int = native_list_get(sh, 3)
let cx: Int = sx + size / 2
if stype == 0 {
if px >= sx {
if px < sx + size {
if py >= sy {
if py < sy + size {
return true
}
}
}
}
return false
}
if stype == 1 {
let rad: Int = size / 2
let dx: Int = px - cx
let dy: Int = py - (sy + rad)
if dx * dx + dy * dy <= rad * rad {
return true
}
return false
}
// triangle: apex at top (sy), base at sy+size
if py >= sy {
if py < sy + size {
let dyv: Int = py - sy
let halfw: Int = dyv / 2
let dxv: Int = px - cx
let adx: Int = dxv
if adx < 0 { let adx: Int = 0 - dxv }
if adx <= halfw {
return true
}
}
}
return false
}
// pixel_color: painter's algorithm - last covering shape wins. Returns [r,g,b].
fn pixel_color(px: Int, py: Int, shapes: [[Int]], bg: [Int]) -> [Int] {
let r: Int = native_list_get(bg, 0)
let g: Int = native_list_get(bg, 1)
let b: Int = native_list_get(bg, 2)
let n: Int = native_list_len(shapes)
let i: Int = 0
while i < n {
let sh: [Int] = native_list_get(shapes, i)
if covers(sh, px, py) {
let r: Int = native_list_get(sh, 4)
let g: Int = native_list_get(sh, 5)
let b: Int = native_list_get(sh, 6)
}
let i: Int = i + 1
}
let out: [Int] = native_list_empty()
let out: [Int] = native_list_append(out, r)
let out: [Int] = native_list_append(out, g)
let out: [Int] = native_list_append(out, b)
return out
}
// rasterize: build the raw (filtered) scanline byte stream, filter byte 0 / row.
fn rasterize(w: Int, h: Int, shapes: [[Int]], bg: [Int]) -> [Int] {
let raw: [Int] = native_list_empty()
let y: Int = 0
while y < h {
let raw: [Int] = native_list_append(raw, 0)
let x: Int = 0
while x < w {
let col: [Int] = pixel_color(x, y, shapes, bg)
let raw: [Int] = native_list_append(raw, native_list_get(col, 0))
let raw: [Int] = native_list_append(raw, native_list_get(col, 1))
let raw: [Int] = native_list_append(raw, native_list_get(col, 2))
let x: Int = x + 1
}
let y: Int = y + 1
}
return raw
}
// zlib stream with a single STORED (uncompressed) DEFLATE block + Adler32.
fn zlib_store(raw: [Int]) -> [Int] {
let z: [Int] = native_list_empty()
let z: [Int] = native_list_append(z, 120)
let z: [Int] = native_list_append(z, 1)
let z: [Int] = native_list_append(z, 1)
let len: Int = native_list_len(raw)
let nlen: Int = 65535 - len
let z: [Int] = native_list_append(z, len % 256)
let z: [Int] = native_list_append(z, (len / 256) % 256)
let z: [Int] = native_list_append(z, nlen % 256)
let z: [Int] = native_list_append(z, (nlen / 256) % 256)
let z: [Int] = app_all(z, raw)
let ad: Int = adler32_of(raw)
let z: [Int] = app_u32be(z, ad)
return z
}
// append a full PNG chunk: length + (type+data) + crc32(type+data).
fn app_chunk(png: [Int], type_and_data: [Int], table: [Int]) -> [Int] {
let total: Int = native_list_len(type_and_data)
let dlen: Int = total - 4
let png: [Int] = app_u32be(png, dlen)
let png: [Int] = app_all(png, type_and_data)
let crc: Int = crc32_of(type_and_data, table)
let png: [Int] = app_u32be(png, crc)
return png
}
fn png_build(w: Int, h: Int, raw: [Int], table: [Int]) -> [Int] {
let png: [Int] = native_list_empty()
// 8-byte signature
let png: [Int] = native_list_append(png, 137)
let png: [Int] = native_list_append(png, 80)
let png: [Int] = native_list_append(png, 78)
let png: [Int] = native_list_append(png, 71)
let png: [Int] = native_list_append(png, 13)
let png: [Int] = native_list_append(png, 10)
let png: [Int] = native_list_append(png, 26)
let png: [Int] = native_list_append(png, 10)
// IHDR
let ihdr: [Int] = native_list_empty()
let ihdr: [Int] = app_tag(ihdr, "IHDR")
let ihdr: [Int] = app_u32be(ihdr, w)
let ihdr: [Int] = app_u32be(ihdr, h)
let ihdr: [Int] = native_list_append(ihdr, 8)
let ihdr: [Int] = native_list_append(ihdr, 2)
let ihdr: [Int] = native_list_append(ihdr, 0)
let ihdr: [Int] = native_list_append(ihdr, 0)
let ihdr: [Int] = native_list_append(ihdr, 0)
let png: [Int] = app_chunk(png, ihdr, table)
// IDAT
let z: [Int] = zlib_store(raw)
let idat: [Int] = native_list_empty()
let idat: [Int] = app_tag(idat, "IDAT")
let idat: [Int] = app_all(idat, z)
let png: [Int] = app_chunk(png, idat, table)
// IEND
let iend: [Int] = native_list_empty()
let iend: [Int] = app_tag(iend, "IEND")
let png: [Int] = app_chunk(png, iend, table)
return png
}
fn png_write(path: String, png: [Int]) -> Int {
let n: Int = native_list_len(png)
let buf: String = __str_alloc(n)
let i: Int = 0
while i < n {
let buf: String = __str_set_char(buf, i, native_list_get(png, i))
let i: Int = i + 1
}
let ok: Int = fs_write_bytes(path, buf, n)
return ok
}
+153
View File
@@ -0,0 +1,153 @@
// surface-profile.el - Surface profile data and accessors.
//
// THE NATIVE EFFERENT SEAM: surface = a pluggable PROFILE, using the exact same
// slot-map mechanism as language-profile.el. A language profile tells the
// realizer HOW to shape a natural-language surface (word order, morphology); a
// SURFACE profile tells the realizer WHICH surface to project meaning onto
// (markdown, docx, html, plain, or a non-text medium like symbolic music).
//
// The generalization is exact: realize_lang(form, profile) already renders a
// SemForm parameterized by a [String] profile read via lang_get. Surface is one
// more axis of that same profile vector. One frame (sem_frame), one plan step
// (sem_to_spec), one render (realize) the surface is DATA, not a code path,
// precisely as language is data. Adding a surface means adding a profile, no
// engine change. This is the multimodal projector, native: geometry -> any
// surface, the efferent twin of ingest.
//
// Surface slot keys:
// surface - "markdown" | "docx" | "html" | "plain" | "midi" | "image"
// modality - "text" | "audio" | "image" | "video"
// media_type - MIME type of the emitted surface
// head_open - string prepended to a heading (e.g. "## " for markdown)
// head_close - string appended to a heading (e.g. "" for markdown, "</h2>" for html)
// emph_open - string opening emphasis (e.g. "*")
// emph_close - string closing emphasis (e.g. "*")
// item_mark - list-item marker (e.g. "- ")
// para_sep - paragraph separator (e.g. "\n\n")
//
// For a TEXT modality the render composes these markers around the surface that
// the EXISTING realizer produces (realize_lang / sem_realize). For a non-text
// modality (audio/image) the profile declares modality + media_type and the
// render dispatches to the medium projector, which reads the SAME frame's
// geometry (its intent/affect/structure) and projects it onto sound or pixels
// deterministic-from-meaning, nothing invented. That dispatch point is where a
// music profile or image profile conforms, native, no parallel layer.
// -- Constructor -------------------------------------------------------------
fn surface_profile(surface: String, modality: String, media_type: String, head_open: String, head_close: String, emph_open: String, emph_close: String, item_mark: String, para_sep: String) -> [String] {
let r: [String] = native_list_empty()
let r = native_list_append(r, "surface")
let r = native_list_append(r, surface)
let r = native_list_append(r, "modality")
let r = native_list_append(r, modality)
let r = native_list_append(r, "media_type")
let r = native_list_append(r, media_type)
let r = native_list_append(r, "head_open")
let r = native_list_append(r, head_open)
let r = native_list_append(r, "head_close")
let r = native_list_append(r, head_close)
let r = native_list_append(r, "emph_open")
let r = native_list_append(r, emph_open)
let r = native_list_append(r, "emph_close")
let r = native_list_append(r, emph_close)
let r = native_list_append(r, "item_mark")
let r = native_list_append(r, item_mark)
let r = native_list_append(r, "para_sep")
let r = native_list_append(r, para_sep)
return r
}
// -- Accessor (same convention as lang_get; standalone so this is a leaf) -----
fn surface_get(profile: [String], key: String) -> String {
let n: Int = native_list_len(profile)
let i: Int = 0
while i < n - 1 {
let k: String = native_list_get(profile, i)
if str_eq(k, key) {
return native_list_get(profile, i + 1)
}
let i = i + 2
}
return ""
}
fn surface_is_text(profile: [String]) -> Bool {
return str_eq(surface_get(profile, "modality"), "text")
}
// -- Built-in TEXT surface profiles ------------------------------------------
// Markdown: headings with "## ", emphasis with "*", "- " list items.
fn surface_profile_markdown() -> [String] {
return surface_profile("markdown", "text", "text/markdown", "## ", "", "*", "*", "- ", "\n\n")
}
// Plain text: no markup at all headings become bare uppercase-free lines.
fn surface_profile_plain() -> [String] {
return surface_profile("plain", "text", "text/plain", "", "", "", "", " - ", "\n\n")
}
// HTML: block-level heading/emphasis tags.
fn surface_profile_html() -> [String] {
return surface_profile("html", "text", "text/html", "<h2>", "</h2>", "<em>", "</em>", "<li>", "\n")
}
// docx: WordprocessingML is structural, not inline-markup; the head/emph slots
// carry the run/style intent that the OOXML emitter maps to <w:pStyle>. Declared
// here so docx is a first-class surface on the same seam.
fn surface_profile_docx() -> [String] {
return surface_profile("docx", "text", "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "Heading2:", "", "b:", "", "bullet:", "\n")
}
// -- Built-in NON-TEXT surface profiles (the multimodal seam) ----------------
// Symbolic music (MIDI): modality=audio. The render dispatches to the music
// projector, which reads the SAME frame's intent/affect and projects it to
// pitch/rhythm deterministic-from-meaning. head/emph slots are empty because
// the medium is not textual; media_type names the surface. A music profile
// (scale/mode/instrument) is layered onto this by the audio agent, native.
fn surface_profile_midi() -> [String] {
return surface_profile("midi", "audio", "audio/midi", "", "", "", "", "", "")
}
// Synthesized audio (WAV): modality=audio, peer to midi. The richer audio
// surface the render SUPERPOSES ingested tonal primitives (sine at f0*n per an
// ingested instrument signature) into PCM, own-core, exactly as midi writes an
// SMF via struct. A music profile (scale/mode/instrument/adsr) layers onto this
// as its own [String] slot-map read by the same getter. Same frame -> midi OR
// audio, interchangeable; this is the audio agent's native conforming point.
fn surface_profile_audio() -> [String] {
return surface_profile("audio", "audio", "audio/wav", "", "", "", "", "", "")
}
// Image (raster): modality=image. Documented seam the render dispatches to the
// image projector, the efferent twin of image ingest, reading the same frame.
fn surface_profile_image() -> [String] {
return surface_profile("image", "image", "image/png", "", "", "", "", "", "")
}
// -- Composition helpers: wrap realized TEXT with the surface's markers -------
//
// These take text the EXISTING realizer already produced and shape it for the
// surface. They add NO content pure surface typography over faithful text,
// exactly as the language profile adds no content, only linguistic form.
fn surface_heading(profile: [String], text: String) -> String {
let o: String = surface_get(profile, "head_open")
let c: String = surface_get(profile, "head_close")
return o + text + c
}
fn surface_emph(profile: [String], text: String) -> String {
let o: String = surface_get(profile, "emph_open")
let c: String = surface_get(profile, "emph_close")
return o + text + c
}
// A section: a heading + a paragraph separator + the (already realized) body.
fn surface_section(profile: [String], heading: String, body: String) -> String {
let sep: String = surface_get(profile, "para_sep")
return surface_heading(profile, heading) + sep + body
}
@@ -0,0 +1,26 @@
// surface-profile-demo.el - ONE SemFrame, realized ONCE, projected to THREE
// surfaces via surface profiles. Proves surface-as-profile natively: the frame
// and the realized sentence are identical; only the surface PROFILE differs.
fn demo() -> String {
// 1. The shared frame (meaning-geometry): assert(Neuron, contain, the memory).
let frame: [String] = sem_frame("assert", "Neuron", "the memory", "")
// 2. REALIZE once via the EXISTING native realizer (language = a profile).
let sentence: String = sem_realize(frame)
// 3. PROJECT the same realized sentence onto three surfaces (surface = a
// profile). Same frame, same sentence, different surface one render.
let heading: String = "Memory"
let md: String = surface_section(surface_profile_markdown(), heading, sentence)
let html: String = surface_section(surface_profile_html(), heading, sentence)
let plain: String = surface_section(surface_profile_plain(), heading, sentence)
// 4. Report the non-text seam: a surface profile can declare an audio/image
// medium; the render dispatches to the medium projector on the SAME frame.
let midi_media: String = surface_get(surface_profile_midi(), "media_type")
return "MD=[" + md + "] HTML=[" + html + "] PLAIN=[" + plain + "] MIDI_MEDIA=" + midi_media
}
println(demo())
+1 -1
View File
@@ -81,7 +81,7 @@ jobs:
# Link to produce the engram binary
- name: Link engram binary
run: |
cc -std=c11 -O2 \
cc -std=c11 -O2 -DHAVE_CURL \
-I /usr/local/lib/el \
-o dist/engram \
dist/engram.c \
+1 -1
View File
@@ -88,7 +88,7 @@ jobs:
# Link to produce the engram binary
- name: Link engram binary
run: |
cc -std=c11 -O2 \
cc -std=c11 -O2 -DHAVE_CURL \
-I /usr/local/lib/el \
-o dist/engram \
dist/engram.c \
+1 -1
View File
@@ -62,7 +62,7 @@ jobs:
# Link to produce the engram binary
- name: Link engram binary
run: |
cc -std=c11 -O2 \
cc -std=c11 -O2 -DHAVE_CURL \
-I /usr/local/lib/el \
-o dist/engram \
dist/engram.c \
+10
View File
@@ -17,6 +17,16 @@
// 4. Append dep to order after all its transitive deps
// 5. Deduplicate: skip already-ordered vessels
// Cross-module forward declarations
// Defined in sibling epm modules; resolved at link time. The `extern fn` decls
// give elc the C prototypes so generated install.c compiles cleanly under strict
// compilers (gcc>=14 / clang) that reject implicit function declarations.
extern fn manifest_name(src: String) -> String // manifest.el
extern fn manifest_deps(src: String) -> String // manifest.el
extern fn registry_token() -> String // registry.el
extern fn registry_find(name: String, version: String) -> String // registry.el
extern fn registry_latest_version(name: String) -> String // registry.el
// Install paths
// packages_dir returns the root directory for installed vessels.
+9
View File
@@ -14,6 +14,15 @@
// EPM_REGISTRY_ORG org name that hosts vessel repos (default: neuron-technologies)
// EPM_TOKEN Gitea personal access token (required for publish)
// Cross-module forward declarations
// These symbols are defined in sibling epm modules or the El runtime and are
// resolved at link time. The `extern fn` decls give elc the C prototype so the
// generated registry.c compiles cleanly under strict compilers (gcc>=14 / clang)
// that reject implicit function declarations. Signature arity must match the
// definition; return/param types are informational (all lower to el_val_t).
extern fn config(key: String) -> String // El runtime builtin
extern fn read_installed() -> String // install.el
// Config helpers
// registry_api_url returns the Gitea API base URL with no trailing slash.
+9
View File
@@ -6,6 +6,15 @@
// Depends on: registry.el (registry_latest_version, registry_find),
// install.el (read_installed, install_vessel, installed_version)
// Cross-module forward declarations
// Defined in sibling epm modules; resolved at link time. The `extern fn` decls
// give elc the C prototypes so generated update.c compiles cleanly under strict
// compilers (gcc>=14 / clang) that reject implicit function declarations.
extern fn read_installed() -> String // install.el
extern fn installed_version(name: String) -> String // install.el
extern fn install_vessel(name: String, version: String) -> Bool // install.el
extern fn registry_latest_version(name: String) -> String // registry.el
// Semver helpers
// semver_part extracts the Nth dot-separated component from a semver string.
@@ -75,6 +75,7 @@ static inline void* el_win_dlsym(void* handle, const char* name) {
#include <direct.h> /* _mkdir */
#define mkdir(path, mode) _mkdir(path) /* POSIX mkdir(path,mode) → _mkdir(path) */
#define timegm _mkgmtime /* UTC tm → time_t */
#define fsync(fd) _commit(fd) /* no fsync() on Windows; _commit() (<io.h>) is the equiv */
/* setenv/unsetenv: not in the Windows CRT; map to _putenv_s / SetEnvironmentVariable. */
static inline int setenv(const char* name, const char* value, int overwrite) {
+387 -51
View File
@@ -82,8 +82,14 @@ static _Thread_local ElArena _tl_arena = {NULL, 0, 0};
static _Thread_local int _tl_arena_active = 0;
/* Binary-safe fs_read length — set by fs_read, consumed by http_send_response.
* Allows serving PNGs and other binary files without strlen truncation. */
static _Thread_local size_t _tl_fs_read_len = 0;
* Allows serving PNGs and other binary files without strlen truncation.
* PAIRED with the buffer pointer it describes: the length may only be applied
* to the exact buffer fs_read returned. Without the pairing, any handler that
* fs_read a file and then WRAPPED it into a larger response had that response
* truncated to the file's length (Content-Length lied AND the send stopped
* short) the safety-contact onboarding trap, 2026-07-17. */
static _Thread_local size_t _tl_fs_read_len = 0;
static _Thread_local const char* _tl_fs_read_buf = NULL;
static void el_arena_track(char* p) {
if (!_tl_arena_active || !p) return;
@@ -101,6 +107,8 @@ static void el_arena_track(char* p) {
void el_request_start(void) {
_tl_arena.count = 0;
_tl_arena_active = 1;
_tl_fs_read_len = 0; /* never let a previous request's file length */
_tl_fs_read_buf = NULL; /* leak into this response's byte accounting */
}
/* Called by http_worker after the El handler returns and the response is sent.
@@ -1484,11 +1492,14 @@ static void http_send_response(int fd, const char* body) {
}
const char* eff_body = is_envelope ? env_body : body;
/* Use the real byte count from fs_read if available (handles binary files
* with embedded null bytes PNG, WOFF2, etc.). Fall back to strlen for
* normal text/JSON responses where _tl_fs_read_len is 0. */
size_t blen = (_tl_fs_read_len > 0) ? _tl_fs_read_len : strlen(eff_body);
/* Use the real byte count from fs_read ONLY when this body IS the exact
* buffer fs_read returned (binary files with embedded null bytes PNG,
* WOFF2, etc.). Any other body wrapped, enveloped, or derived must be
* measured with strlen, or it is truncated/over-read to the file's size. */
size_t blen = (_tl_fs_read_len > 0 && eff_body == _tl_fs_read_buf)
? _tl_fs_read_len : strlen(eff_body);
_tl_fs_read_len = 0; /* consume — one-shot per response */
_tl_fs_read_buf = NULL;
int head_only = _tl_http_head_only;
JsonBuf hdrs; jb_init(&hdrs);
@@ -1568,11 +1579,22 @@ static void* http_worker(void* arg) {
const char* rs = EL_CSTR(r);
/* Copy response out BEFORE arena teardown.
* For binary files, _tl_fs_read_len holds the real byte count
* use memcpy instead of strdup so null bytes are preserved. */
size_t rlen = _tl_fs_read_len > 0 ? _tl_fs_read_len : (rs ? strlen(rs) : 0);
* use memcpy instead of strdup so null bytes are preserved.
* The stored length applies ONLY when the response IS the exact
* fs_read buffer; a wrapped/derived response must use strlen or
* it gets truncated (or over-read) to the file's length. */
size_t rlen;
if (_tl_fs_read_len > 0 && rs && rs == _tl_fs_read_buf) {
rlen = _tl_fs_read_len; /* raw file bytes — binary-safe */
} else {
rlen = rs ? strlen(rs) : 0;
_tl_fs_read_len = 0; /* hint doesn't describe this body */
_tl_fs_read_buf = NULL;
}
response = malloc(rlen + 1);
if (response && rs) { memcpy(response, rs, rlen); response[rlen] = '\0'; }
else if (response) { response[0] = '\0'; }
if (_tl_fs_read_len > 0) _tl_fs_read_buf = response; /* hint follows the copy */
} else {
response = el_strdup_persist("el-runtime: no http handler registered");
}
@@ -1822,10 +1844,20 @@ static void* http_worker_v2(void* arg) {
el_val_t hmap = http_build_headers_map(hdr_block ? hdr_block : "");
el_val_t r = h(EL_STR(dispatch_method), EL_STR(path), hmap, EL_STR(body));
const char* rs = EL_CSTR(r);
size_t rlen = _tl_fs_read_len > 0 ? _tl_fs_read_len : (rs ? strlen(rs) : 0);
/* Same pairing rule as the v1 worker: the fs_read length is only
* trustworthy for the exact buffer fs_read returned. */
size_t rlen;
if (_tl_fs_read_len > 0 && rs && rs == _tl_fs_read_buf) {
rlen = _tl_fs_read_len; /* raw file bytes — binary-safe */
} else {
rlen = rs ? strlen(rs) : 0;
_tl_fs_read_len = 0; /* hint doesn't describe this body */
_tl_fs_read_buf = NULL;
}
response = malloc(rlen + 1);
if (response && rs) { memcpy(response, rs, rlen); response[rlen] = '\0'; }
else if (response) { response[0] = '\0'; }
if (_tl_fs_read_len > 0) _tl_fs_read_buf = response; /* hint follows the copy */
el_release(hmap);
} else {
response = el_strdup_persist(
@@ -1963,8 +1995,9 @@ void http_serve_async(el_val_t port, el_val_t handler) {
int sock = socket(AF_INET6, SOCK_STREAM, 0);
if (sock < 0) { perror("socket"); return; }
int yes = 1; int no = 0;
setsockopt(sock, SOL_SOCKET, SO_REUSEADDR, &yes, sizeof(yes));
setsockopt(sock, IPPROTO_IPV6, IPV6_V6ONLY, &no, sizeof(no));
/* Win32/mingw setsockopt takes optval as (const char*); the cast is portable on POSIX too. */
setsockopt(sock, SOL_SOCKET, SO_REUSEADDR, (const char*)&yes, sizeof(yes));
setsockopt(sock, IPPROTO_IPV6, IPV6_V6ONLY, (const char*)&no, sizeof(no));
struct sockaddr_in6 addr;
memset(&addr, 0, sizeof(addr));
addr.sin6_family = AF_INET6;
@@ -2023,6 +2056,7 @@ el_val_t http_response(el_val_t status, el_val_t headers_json, el_val_t body) {
el_val_t fs_read(el_val_t pathv) {
const char* path = EL_CSTR(pathv);
_tl_fs_read_len = 0;
_tl_fs_read_buf = NULL;
if (!path) return el_wrap_str(el_strdup(""));
FILE* f = fopen(path, "rb");
if (!f) return el_wrap_str(el_strdup(""));
@@ -2034,6 +2068,7 @@ el_val_t fs_read(el_val_t pathv) {
size_t got = fread(buf, 1, (size_t)sz, f);
buf[got] = '\0';
_tl_fs_read_len = got; /* store real byte count for binary-safe send */
_tl_fs_read_buf = buf; /* ...valid ONLY for this exact buffer */
fclose(f);
return el_wrap_str(buf);
}
@@ -3576,8 +3611,10 @@ el_val_t json_get_raw(el_val_t json_str, el_val_t key) {
const char* k = EL_CSTR(key);
const char* p = json_find_key(json, k);
/* Clear fs_read binary-length hint — result is a fresh null-terminated
* string, not the raw file bytes, so Content-Length must use strlen. */
* string, not the raw file bytes, so Content-Length must use strlen.
* (Kept although the pointer pairing now makes this redundant.) */
_tl_fs_read_len = 0;
_tl_fs_read_buf = NULL;
if (!p) return el_wrap_str(el_strdup(""));
const char* end = json_skip_value(p);
size_t n = (size_t)(end - p);
@@ -6895,6 +6932,243 @@ static int engram_rank_cmp(const void* a, const void* b) {
return 0;
}
/* ══════════════════════════════════════════════════════════════════════════
* SEMANTIC SEARCH LAYER nomic-embed-text via Ollama /api/embeddings
*
* Augments the lexical (istr_contains) matcher with dense-vector retrieval.
* Node content and the query are embedded through a local Ollama server;
* nodes are ranked by cosine similarity and UNIONED with lexical hits. This
* lets a paraphrase query surface a node whose words never appear in it.
*
* DEGRADABLE BY DESIGN. The whole layer is gated on HAVE_CURL plus a one-shot
* runtime probe of the embedding endpoint. If curl is not compiled in, or
* Ollama is unreachable, or ENGRAM_SEMANTIC=0, every entry point returns
* "no semantic signal" and callers fall back to pure lexical behaviour
* byte-for-byte the pre-existing search.
*
* CACHE. Node embeddings are computed lazily on first use and cached in
* process memory keyed by node id, with an FNV-1a content hash for
* invalidation (edited content re-embeds). The query is embedded once per
* search call. This is what "avoid re-embedding the whole graph every query"
* buys us: a warm cache serves cosine from RAM. (A cold process still pays
* O(N) embed calls the first time each node is scanned persisting the cache
* to a snapshot sidecar is the documented next step, not done here.)
*
* nomic task prefixes ("search_query:" / "search_document:") are applied
* because nomic-embed-text is trained with them; they materially improve
* retrieval separation (empirically: paraphrase 0.72 vs distractors <0.48).
*
* ENV:
* ENGRAM_SEMANTIC "0" disables; unset/other = auto-probe
* ENGRAM_EMBED_URL default http://localhost:11434/api/embeddings
* ENGRAM_EMBED_MODEL default nomic-embed-text
* ENGRAM_SEMANTIC_MIN cosine threshold for a pure-semantic match (def 0.6)
* */
static double engram_semantic_min(void) {
static double v = -1.0;
if (v >= 0.0) return v;
const char* s = getenv("ENGRAM_SEMANTIC_MIN");
double d = 0.6;
if (s && *s) { char* e = NULL; double t = strtod(s, &e);
if (e != s && t >= 0.0 && t <= 1.0) d = t; }
v = d; return v;
}
#ifdef HAVE_CURL
typedef struct { char* id; uint64_t hash; float* vec; int dim; } EngramEmbEntry;
static EngramEmbEntry* g_emb_items = NULL;
static int64_t g_emb_count = 0, g_emb_cap = 0;
static int g_emb_state = 0; /* 0=unprobed, 1=available, -1=disabled */
static uint64_t engram_fnv1a(const char* s) {
uint64_t h = 1469598103934665603ULL;
if (s) for (const unsigned char* p = (const unsigned char*)s; *p; p++) {
h ^= *p; h *= 1099511628211ULL;
}
return h;
}
/* Parse "embedding":[f,f,...] from an Ollama response. malloc'd vec, or NULL. */
static float* engram_parse_embedding(const char* json, int* out_dim) {
if (!json) return NULL;
const char* p = strstr(json, "\"embedding\"");
if (!p) return NULL;
p = strchr(p, '[');
if (!p) return NULL;
p++;
int cap = 1024, n = 0;
float* v = malloc((size_t)cap * sizeof(float));
if (!v) return NULL;
while (*p && *p != ']') {
while (*p == ' ' || *p == '\t' || *p == '\n' || *p == '\r' || *p == ',') p++;
if (*p == ']' || !*p) break;
char* e = NULL;
double d = strtod(p, &e);
if (e == p) break;
if (n >= cap) { cap *= 2; float* nv = realloc(v, (size_t)cap * sizeof(float));
if (!nv) { free(v); return NULL; } v = nv; }
v[n++] = (float)d;
p = e;
}
if (n == 0) { free(v); return NULL; }
*out_dim = n;
return v;
}
/* JSON-escape src into a malloc'd buffer (no surrounding quotes). */
static char* engram_json_escape(const char* src) {
if (!src) src = "";
size_t n = strlen(src);
char* out = malloc(n * 2 + 1);
if (!out) return NULL;
size_t j = 0;
for (size_t i = 0; i < n; i++) {
unsigned char c = (unsigned char)src[i];
if (c == '"') { out[j++] = '\\'; out[j++] = '"'; }
else if (c == '\\') { out[j++] = '\\'; out[j++] = '\\'; }
else if (c == '\n') { out[j++] = '\\'; out[j++] = 'n'; }
else if (c == '\r') { out[j++] = '\\'; out[j++] = 'r'; }
else if (c == '\t') { out[j++] = '\\'; out[j++] = 't'; }
else if (c < 0x20) { /* drop other control bytes */ }
else { out[j++] = (char)c; }
}
out[j] = '\0';
return out;
}
/* Embed `prefix+text` via Ollama. Returns malloc'd vec (caller frees), or NULL. */
static float* engram_embed_raw(const char* prefix, const char* text, int* out_dim) {
if (!text) return NULL;
const char* url = getenv("ENGRAM_EMBED_URL");
if (!url || !*url) url = "http://localhost:11434/api/embeddings";
const char* model = getenv("ENGRAM_EMBED_MODEL");
if (!model || !*model) model = "nomic-embed-text";
/* Bound content length to keep latency/memory sane on huge nodes. */
char* trunc = NULL;
size_t maxlen = 8192;
if (strlen(text) > maxlen) {
trunc = malloc(maxlen + 1);
if (trunc) { memcpy(trunc, text, maxlen); trunc[maxlen] = '\0'; text = trunc; }
}
char* esc_prefix = engram_json_escape(prefix ? prefix : "");
char* esc = engram_json_escape(text);
free(trunc);
if (!esc || !esc_prefix) { free(esc); free(esc_prefix); return NULL; }
size_t blen = strlen(esc) + strlen(esc_prefix) + strlen(model) + 64;
char* body = malloc(blen);
if (!body) { free(esc); free(esc_prefix); return NULL; }
snprintf(body, blen, "{\"model\":\"%s\",\"prompt\":\"%s%s\"}", model, esc_prefix, esc);
free(esc); free(esc_prefix);
CURL* c = curl_easy_init();
if (!c) { free(body); return NULL; }
HttpBuf rb; httpbuf_init(&rb);
struct curl_slist* h = curl_slist_append(NULL, "Content-Type: application/json");
char errbuf[CURL_ERROR_SIZE]; errbuf[0] = '\0';
curl_easy_setopt(c, CURLOPT_URL, url);
curl_easy_setopt(c, CURLOPT_WRITEFUNCTION, http_write_cb);
curl_easy_setopt(c, CURLOPT_WRITEDATA, &rb);
curl_easy_setopt(c, CURLOPT_POST, 1L);
curl_easy_setopt(c, CURLOPT_POSTFIELDS, body);
curl_easy_setopt(c, CURLOPT_POSTFIELDSIZE, (long)strlen(body));
curl_easy_setopt(c, CURLOPT_HTTPHEADER, h);
curl_easy_setopt(c, CURLOPT_TIMEOUT_MS, el_http_timeout_ms());
curl_easy_setopt(c, CURLOPT_NOSIGNAL, 1L);
curl_easy_setopt(c, CURLOPT_ERRORBUFFER, errbuf);
CURLcode rc = curl_easy_perform(c);
curl_slist_free_all(h);
curl_easy_cleanup(c);
free(body);
if (rc != CURLE_OK) { free(rb.data); return NULL; }
float* v = engram_parse_embedding(rb.data, out_dim);
free(rb.data);
return v;
}
/* One-shot probe: is semantic search available? Caches the verdict. */
static int engram_semantic_enabled(void) {
if (g_emb_state != 0) return g_emb_state == 1;
const char* s = getenv("ENGRAM_SEMANTIC");
if (s && strcmp(s, "0") == 0) { g_emb_state = -1; return 0; }
int dim = 0;
float* v = engram_embed_raw("search_query: ", "probe", &dim);
if (v && dim > 0) { free(v); g_emb_state = 1; return 1; }
free(v);
g_emb_state = -1; return 0;
}
/* Embed the query. Returns malloc'd vec (caller frees), or NULL if semantic off. */
static float* engram_embed_query(const char* q, int* dim) {
if (!engram_semantic_enabled()) return NULL;
if (!q || !*q) return NULL;
return engram_embed_raw("search_query: ", q, dim);
}
/* Cached node embedding. Returns a pointer OWNED BY THE CACHE — do not free. */
static const float* engram_node_vec(EngramNode* n, int* out_dim) {
if (!n || !n->id) return NULL;
uint64_t h = engram_fnv1a(n->content);
for (int64_t i = 0; i < g_emb_count; i++) {
if (g_emb_items[i].id && strcmp(g_emb_items[i].id, n->id) == 0) {
if (g_emb_items[i].hash == h && g_emb_items[i].vec) {
*out_dim = g_emb_items[i].dim; return g_emb_items[i].vec;
}
/* content changed → re-embed in place */
int dim = 0;
float* v = engram_embed_raw("search_document: ", n->content ? n->content : "", &dim);
if (!v) return NULL;
free(g_emb_items[i].vec);
g_emb_items[i].vec = v; g_emb_items[i].dim = dim; g_emb_items[i].hash = h;
*out_dim = dim; return v;
}
}
int dim = 0;
float* v = engram_embed_raw("search_document: ", n->content ? n->content : "", &dim);
if (!v) return NULL;
if (g_emb_count >= g_emb_cap) {
int64_t nc = g_emb_cap ? g_emb_cap * 2 : 256;
EngramEmbEntry* ni = realloc(g_emb_items, (size_t)nc * sizeof(EngramEmbEntry));
if (!ni) { free(v); return NULL; }
g_emb_items = ni; g_emb_cap = nc;
}
g_emb_items[g_emb_count].id = strdup(n->id);
g_emb_items[g_emb_count].hash = h;
g_emb_items[g_emb_count].vec = v;
g_emb_items[g_emb_count].dim = dim;
g_emb_count++;
*out_dim = dim; return v;
}
static double engram_cosine(const float* a, const float* b, int dim) {
double dot = 0, na = 0, nb = 0;
for (int i = 0; i < dim; i++) { dot += (double)a[i] * b[i];
na += (double)a[i] * a[i];
nb += (double)b[i] * b[i]; }
if (na <= 0 || nb <= 0) return 0.0;
return dot / (sqrt(na) * sqrt(nb));
}
/* Cosine of node n against the query vector; 0 if unavailable / dim mismatch. */
static double engram_node_cosine(EngramNode* n, const float* qvec, int qdim) {
if (!qvec || qdim <= 0) return 0.0;
int ndim = 0;
const float* nv = engram_node_vec(n, &ndim);
if (!nv || ndim != qdim) return 0.0;
return engram_cosine(qvec, nv, qdim);
}
#else /* !HAVE_CURL — semantic layer compiled out; callers stay pure-lexical.
* Only the two boundary functions the always-compiled search/activate
* code calls are stubbed; the query embed always yields NULL so every
* cosine is 0 and every caller collapses to lexical-only. */
static float* engram_embed_query(const char* q, int* dim) { (void)q; (void)dim; return NULL; }
static double engram_node_cosine(EngramNode* n, const float* qvec, int qdim) {
(void)n; (void)qvec; (void)qdim; return 0.0;
}
#endif /* HAVE_CURL */
el_val_t engram_search(el_val_t query, el_val_t limit) {
EngramStore* g = engram_get();
const char* q = EL_CSTR(query);
@@ -6905,8 +7179,15 @@ el_val_t engram_search(el_val_t query, el_val_t limit) {
char toks[ENGRAM_MAX_QTOKENS][ENGRAM_QTOK_LEN];
int ntok = engram_tokenize_query(q, toks, ENGRAM_MAX_QTOKENS);
if (ntok == 0) return lst;
/* Semantic augmentation: embed the query once; a node is a hit if it covers
* >=1 query token (tokenized-lexical, #66) OR its cosine clears the
* threshold (#67). qvec is NULL (cosine 0) when semantic is unavailable
* pure tokenized-lexical, byte-identical to the lexical-only behaviour. */
int qdim = 0;
float* qvec = engram_embed_query(q, &qdim);
double sem_min = engram_semantic_min();
EngramRankEntry* hits = malloc((size_t)g->node_count * sizeof(EngramRankEntry));
if (!hits) return lst;
if (!hits) { free(qvec); return lst; }
int64_t nhits = 0;
for (int64_t i = 0; i < g->node_count; i++) {
EngramNode* n = &g->nodes[i];
@@ -6916,20 +7197,24 @@ el_val_t engram_search(el_val_t query, el_val_t limit) {
* + engram_compile_layered_json that's the legitimate path. */
if (engram_layer_is_transparent(n->layer_id)) continue;
int sc = engram_node_match_score(n, toks, ntok);
if (sc > 0) {
double sem = qvec ? engram_node_cosine(n, qvec, qdim) : 0.0;
if (sc > 0 || sem >= sem_min) {
hits[nhits].idx = i;
hits[nhits].score = sc;
hits[nhits].salience = n->salience;
nhits++;
}
}
/* Rank by distinct tokens matched (desc) then salience (desc), then cap. */
/* Rank by distinct tokens matched (desc) then salience (desc), then cap.
* Pure-semantic hits (token score 0) sort after every lexical hit a
* lexical semantic union with lexical precedence. */
qsort(hits, (size_t)nhits, sizeof(EngramRankEntry), engram_rank_cmp);
int64_t end = nhits < lim ? nhits : lim;
for (int64_t k = 0; k < end; k++) {
lst = el_list_append(lst, engram_node_to_map(&g->nodes[hits[k].idx]));
}
free(hits);
free(qvec);
return lst;
}
@@ -7279,21 +7564,31 @@ el_val_t engram_activate(el_val_t query, el_val_t depth) {
if (!seeds) {
free(best_bg); free(best_hops); free(reached); return out;
}
/* Tokenize once: a node seeds if it matches ANY query token, and its seed
* activation is scaled by token coverage (fraction of distinct query
* tokens it contains) so a node matching all words seeds more strongly
* than one matching a single word. Single-word queries coverage 1.0,
* identical to the prior whole-query behavior. */
/* Tokenized + semantic seeding: a node seeds if it covers >=1 query token
* (tokenized-lexical, #66) OR its cosine clears the threshold (#67). A
* lexical seed's activation is scaled by token coverage (fraction of
* distinct query tokens covered) so a node matching all words seeds more
* strongly than one matching a single word; single-word queries coverage
* 1.0. A pure-semantic seed (no token match) is instead down-weighted by
* its cosine so paraphrase matches spread without overpowering exact seeds.
* q_vec is NULL (cosine 0) when semantic is unavailable the seed set is
* exactly the tokenized-lexical one. q_vec is freed right after this loop
* so the many downstream early-returns need no cleanup change. */
char toks[ENGRAM_MAX_QTOKENS][ENGRAM_QTOK_LEN];
int ntok = engram_tokenize_query(q, toks, ENGRAM_MAX_QTOKENS);
int q_dim = 0;
float* q_vec = engram_embed_query(q, &q_dim);
double q_sem_min = engram_semantic_min();
for (int64_t i = 0; i < g->node_count; i++) {
EngramNode* n = &g->nodes[i];
int sc = engram_node_match_score(n, toks, ntok);
if (sc > 0) {
double sem = q_vec ? engram_node_cosine(n, q_vec, q_dim) : 0.0;
if (sc > 0 || sem >= q_sem_min) {
double tdecay = engram_temporal_decay(n, now_ms);
double dampen = engram_activation_dampen(n);
double cover = ntok > 0 ? (double)sc / (double)ntok : 1.0;
double act = n->salience * tdecay * dampen * cover;
double act = n->salience * tdecay * dampen;
if (sc > 0) act *= (ntok > 0 ? (double)sc / (double)ntok : 1.0);
else act *= sem; /* pure-semantic seed: down-weight by cosine */
seeds[seed_count].idx = i;
seeds[seed_count].act = act;
seeds[seed_count].created_at = n->created_at;
@@ -7303,6 +7598,7 @@ el_val_t engram_activate(el_val_t query, el_val_t depth) {
reached[i] = 1;
}
}
free(q_vec);
/* Compute mean seed created_at for temporal proximity bonus. */
int64_t seed_epoch = 0;
if (seed_count > 0) {
@@ -7854,6 +8150,35 @@ el_val_t engram_get_node_json(el_val_t id) {
return el_wrap_str(jb_finish(&b));
}
/* engram_get_node_by_label — find the first node whose label field exactly
* matches the given string. Returns the node as a JSON object string, or "{}"
* if no match is found.
*
* Used by chat.el to retrieve well-known nodes (e.g. "conv:history",
* "session:summary") by their stable label rather than by ID, which is immune
* to vector index drift across restarts.
*
* Exact match (strcmp, not istr_contains) because labels like "conv:history"
* must not collide with nodes whose content happens to contain that substring.
*
* Backported verbatim (idiom-adapted to jb_finish) from release runtime
* v1.0.0-20260501 to unblock the soul regen link: chat.el references this
* native but the current runtime lacked its definition. */
el_val_t engram_get_node_by_label(el_val_t label) {
const char* lbl = EL_CSTR(label);
if (!lbl || !*lbl) return el_wrap_str(el_strdup("{}"));
EngramStore* g = engram_get();
for (int64_t i = 0; i < g->node_count; i++) {
EngramNode* n = &g->nodes[i];
if (n->label && strcmp(n->label, lbl) == 0) {
JsonBuf b; jb_init(&b);
engram_emit_node_json(&b, n);
return el_wrap_str(jb_finish(&b));
}
}
return el_wrap_str(el_strdup("{}"));
}
el_val_t engram_search_json(el_val_t query, el_val_t limit) {
EngramStore* g = engram_get();
const char* q = EL_CSTR(query);
@@ -7861,39 +8186,50 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
if (lim <= 0) lim = 100;
JsonBuf b; jb_init(&b);
jb_putc(&b, '[');
int first = 1;
if (q && *q) {
if (q && *q && g->node_count > 0) {
/* Collect candidates from the UNION of tokenized-lexical and semantic
* matches, score each, rank by score, emit the top `lim`. A node is a
* candidate if it covers >=1 query token (tokenized-lexical, #66) OR its
* query cosine clears the threshold (#67). Lexical score is the distinct
* token count (>=1), so any lexical hit outranks a pure-semantic hit
* (cosine < 1); pure-semantic hits are scored by cosine alone. When
* semantic is unavailable qvec is NULL, sem is 0, only tokenized-lexical
* hits are collected, and the stable insertion sort preserves order. */
char toks[ENGRAM_MAX_QTOKENS][ENGRAM_QTOK_LEN];
int ntok = engram_tokenize_query(q, toks, ENGRAM_MAX_QTOKENS);
if (ntok > 0) {
EngramRankEntry* hits =
malloc((size_t)g->node_count * sizeof(EngramRankEntry));
if (hits) {
int64_t nhits = 0;
for (int64_t i = 0; i < g->node_count; i++) {
EngramNode* n = &g->nodes[i];
/* Filter transparent layers — same as engram_search. */
if (engram_layer_is_transparent(n->layer_id)) continue;
int sc = engram_node_match_score(n, toks, ntok);
if (sc > 0) {
hits[nhits].idx = i;
hits[nhits].score = sc;
hits[nhits].salience = n->salience;
nhits++;
}
int qdim = 0;
float* qvec = engram_embed_query(q, &qdim);
double sem_min = engram_semantic_min();
typedef struct { int64_t idx; double score; } Cand;
Cand* cand = malloc((size_t)g->node_count * sizeof(Cand));
if (cand) {
int64_t nc = 0;
for (int64_t i = 0; i < g->node_count; i++) {
EngramNode* n = &g->nodes[i];
if (engram_layer_is_transparent(n->layer_id)) continue;
int sc = engram_node_match_score(n, toks, ntok);
double sem = qvec ? engram_node_cosine(n, qvec, qdim) : 0.0;
if (sc > 0 || sem >= sem_min) {
cand[nc].idx = i;
cand[nc].score = (double)sc + sem;
nc++;
}
/* Rank by distinct tokens matched (desc) then salience (desc). */
qsort(hits, (size_t)nhits, sizeof(EngramRankEntry),
engram_rank_cmp);
int64_t end = nhits < lim ? nhits : lim;
for (int64_t k = 0; k < end; k++) {
if (!first) jb_putc(&b, ',');
engram_emit_node_json(&b, &g->nodes[hits[k].idx]);
first = 0;
}
free(hits);
}
/* Insertion sort by score desc; stable for equal scores. */
for (int64_t i = 1; i < nc; i++) {
Cand k = cand[i]; int64_t j = i - 1;
while (j >= 0 && cand[j].score < k.score) { cand[j + 1] = cand[j]; j--; }
cand[j + 1] = k;
}
int first = 1;
for (int64_t i = 0; i < nc && i < lim; i++) {
if (!first) jb_putc(&b, ',');
engram_emit_node_json(&b, &g->nodes[cand[i].idx]);
first = 0;
}
free(cand);
}
free(qvec);
}
jb_putc(&b, ']');
return el_wrap_str(jb_finish(&b));
+1
View File
@@ -632,6 +632,7 @@ el_val_t engram_load(el_val_t path);
* can pass results straight through without round-tripping ElList/ElMap
* through json_stringify. */
el_val_t engram_get_node_json(el_val_t id);
el_val_t engram_get_node_by_label(el_val_t label);
el_val_t engram_search_json(el_val_t query, el_val_t limit);
el_val_t engram_scan_nodes_json(el_val_t limit, el_val_t offset);
el_val_t engram_scan_nodes_by_type_json(el_val_t node_type, el_val_t limit, el_val_t offset);
+1
View File
@@ -1072,6 +1072,7 @@ el_val_t __engram_save(el_val_t path) { return engram_save
el_val_t __engram_load(el_val_t path) { return engram_load(path); }
el_val_t __engram_get_node_json(el_val_t id) { return engram_get_node_json(id); }
el_val_t __engram_get_node_by_label(el_val_t label) { return engram_get_node_by_label(label); }
el_val_t __engram_search_json(el_val_t query, el_val_t limit) {
return engram_search_json(query, limit);
+1
View File
@@ -226,6 +226,7 @@ el_val_t __engram_activate(el_val_t query, el_val_t depth);
el_val_t __engram_save(el_val_t path);
el_val_t __engram_load(el_val_t path);
el_val_t __engram_get_node_json(el_val_t id);
el_val_t __engram_get_node_by_label(el_val_t label);
el_val_t __engram_search_json(el_val_t query, el_val_t limit);
el_val_t __engram_scan_nodes_json(el_val_t limit, el_val_t offset);
el_val_t __engram_scan_nodes_by_type_json(el_val_t node_type, el_val_t limit, el_val_t offset);
+1
View File
@@ -2670,6 +2670,7 @@ fn builtin_arity(name: String) -> Int {
if str_eq(name, "engram_save") { return 1 }
if str_eq(name, "engram_load") { return 1 }
if str_eq(name, "engram_get_node_json") { return 1 }
if str_eq(name, "engram_get_node_by_label") { return 1 }
if str_eq(name, "engram_search_json") { return 2 }
if str_eq(name, "engram_scan_nodes_json") { return 2 }
if str_eq(name, "engram_neighbors_json") { return 3 }
@@ -0,0 +1,186 @@
#ifndef EL_PLATFORM_WIN_H
#define EL_PLATFORM_WIN_H
/*
* el_platform_win.h Windows OS-boundary shim for el_runtime.c.
*
* Branch: feat/windows-el-runtime. Included ONLY when _WIN32 is defined; the POSIX build is
* untouched. Goal: let el_runtime.c (a BSD-sockets / dlfcn / fork host) compile and link with
* mingw-w64 into a native neuron.exe, with no behavioural change to the Linux/macOS build.
*
* What it maps:
* - sockets : winsock2 (same call names: socket/bind/listen/accept/recv/send/setsockopt).
* Sockets close with closesocket() (see el_closesocket), and the stack must be
* started once with WSAStartup done automatically via a load-time constructor.
* - dlsym : el_runtime.c uses dlsym(RTLD_DEFAULT, name) to resolve callback/tool symbols
* exported by the main module. Windows equivalent: GetProcAddress on the process
* module. Link the soul with -Wl,--export-all-symbols so the symbols are findable.
* - popen : mapped to _popen/_pclose.
* - threads : UNCHANGED. mingw-w64 ships winpthreads, so <pthread.h> + -lpthread just work.
*/
#ifndef WIN32_LEAN_AND_MEAN
#define WIN32_LEAN_AND_MEAN
#endif
#include <winsock2.h>
#include <ws2tcpip.h>
#include <windows.h>
#include <io.h>
#include <process.h>
/* Portable headers mingw-w64 provides (verified present). */
#include <stdarg.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <strings.h> /* strcasecmp */
#include <ctype.h>
#include <math.h>
#include <time.h>
#include <sys/time.h> /* mingw-w64 provides gettimeofday here */
#include <sys/types.h>
#include <sys/stat.h>
#include <fcntl.h>
#include <dirent.h>
#include <errno.h>
#include <pthread.h>
/* ── socket close ─────────────────────────────────────────────────────────── */
/* Winsock closes sockets with closesocket(), not close() (close() is for file fds). The POSIX
build defines the same helper as close() so the call sites are identical across platforms. */
static inline int el_closesocket(SOCKET s) { return closesocket(s); }
/* ── setsockopt optval type ───────────────────────────────────────────────── */
/* Winsock's setsockopt takes optval as (const char*); POSIX takes (const void*), so el_runtime.c
passes &int directly. GCC 14+ makes that an error under -Wincompatible-pointer-types. Wrap it so
the runtime's POSIX-style call sites compile unchanged (defined before the macro so the wrapper
itself resolves to the real winsock setsockopt). */
static inline int el_setsockopt(SOCKET s, int level, int optname, const void* optval, int optlen) {
return setsockopt(s, level, optname, (const char*)optval, optlen);
}
#define setsockopt(s, l, o, v, n) el_setsockopt((s), (l), (o), (v), (int)(n))
/* ── winsock init (once, at load) ─────────────────────────────────────────── */
static void el__win_net_init(void) {
static int inited = 0;
if (!inited) { WSADATA w; WSAStartup(MAKEWORD(2, 2), &w); inited = 1; }
}
__attribute__((constructor)) static void el__win_ctor(void) { el__win_net_init(); }
/* ── dlsym → GetProcAddress ───────────────────────────────────────────────── */
#ifndef RTLD_DEFAULT
#define RTLD_DEFAULT ((void*)0)
#endif
static inline void* el_win_dlsym(void* handle, const char* name) {
(void)handle;
return (void*)(uintptr_t)GetProcAddress(GetModuleHandleA(NULL), name);
}
#define dlsym(h, n) el_win_dlsym((h), (n))
/* ── popen / pclose ───────────────────────────────────────────────────────── */
#define popen _popen
#define pclose _pclose
/* ── misc POSIX → Win32 shims ─────────────────────────────────────────────── */
#include <direct.h> /* _mkdir */
#define mkdir(path, mode) _mkdir(path) /* POSIX mkdir(path,mode) → _mkdir(path) */
#define timegm _mkgmtime /* UTC tm → time_t */
/* setenv/unsetenv: not in the Windows CRT; map to _putenv_s / SetEnvironmentVariable. */
static inline int setenv(const char* name, const char* value, int overwrite) {
(void)overwrite;
return _putenv_s(name, value ? value : "");
}
static inline int unsetenv(const char* name) {
/* _putenv_s(name, "") sets VAR="" rather than removing it.
* SetEnvironmentVariableA(name, NULL) truly deletes it from the Win32
* env block; then we sync the CRT cache with _putenv("NAME="). */
SetEnvironmentVariableA(name, NULL);
size_t len = strlen(name);
char *buf = (char*)malloc(len + 2);
if (!buf) return -1;
memcpy(buf, name, len);
buf[len] = '=';
buf[len + 1] = '\0';
_putenv(buf);
free(buf);
return 0;
}
/* nanosleep — not available in MSVC/UCRT; approximate with Sleep(). */
static inline int el_nanosleep(const struct timespec *req, struct timespec *rem) {
(void)rem;
DWORD ms = (DWORD)((req->tv_sec * 1000ULL) + (req->tv_nsec / 1000000ULL));
Sleep(ms ? ms : 1);
return 0;
}
#define nanosleep(req, rem) el_nanosleep((req), (rem))
/* localtime_r/gmtime_r: Windows offers localtime_s/gmtime_s with reversed arg order. */
static inline struct tm* localtime_r(const time_t* t, struct tm* out) {
return localtime_s(out, t) == 0 ? out : (struct tm*)0;
}
static inline struct tm* gmtime_r(const time_t* t, struct tm* out) {
return gmtime_s(out, t) == 0 ? out : (struct tm*)0;
}
/* ── libcurl: degradable stubs for the curl-less Windows build ─────────────── */
/* The curl-less validation build (WITH_CURL=0) links no libcurl. el_runtime.c uses libcurl
* unconditionally for its HTTP client / LLM layer; these stubs let it compile and link so the
* runtime, HTTP *server*, graph and memory work natively on Windows. Live outbound HTTP/LLM calls
* degrade to a runtime error (curl_easy_perform returns an error) matching the documented
* curl-less contract. When HAVE_CURL is defined (WITH_CURL=1) the real <curl/curl.h> is used and
* this whole block is compiled out. POSIX never sees this header, so the POSIX build is untouched. */
#ifndef HAVE_CURL
typedef void CURL;
typedef int CURLcode;
#define CURLE_OK 0
#define CURLE_HTTP_RETURNED_ERROR 22
#define CURL_ERROR_SIZE 256
/* Option ids: values are irrelevant to the no-op setopt below; kept distinct for readability. */
#define CURLOPT_URL 10002
#define CURLOPT_WRITEFUNCTION 20011
#define CURLOPT_WRITEDATA 10001
#define CURLOPT_POSTFIELDS 10015
#define CURLOPT_POSTFIELDSIZE 120
#define CURLOPT_POST 47
#define CURLOPT_HTTPHEADER 10023
#define CURLOPT_TIMEOUT_MS 155
#define CURLOPT_NOSIGNAL 99
#define CURLOPT_USERAGENT 10018
#define CURLOPT_FOLLOWLOCATION 52
#define CURLOPT_ERRORBUFFER 10010
#define CURLOPT_CUSTOMREQUEST 10036
#define CURLOPT_FAILONERROR 45
struct curl_slist { char* data; struct curl_slist* next; };
static inline struct curl_slist* curl_slist_append(struct curl_slist* list, const char* s) {
struct curl_slist* node = (struct curl_slist*)malloc(sizeof(struct curl_slist));
if (!node) return list;
node->data = s ? strdup(s) : NULL;
node->next = NULL;
if (!list) return node;
struct curl_slist* p = list;
while (p->next) p = p->next;
p->next = node;
return list;
}
static inline void curl_slist_free_all(struct curl_slist* list) {
while (list) { struct curl_slist* n = list->next; free(list->data); free(list); list = n; }
}
static inline CURL* curl_easy_init(void) { return (CURL*)malloc(1); }
static inline CURLcode curl_easy_setopt(CURL* h, int opt, ...) { (void)h; (void)opt; return CURLE_OK; }
static inline CURLcode curl_easy_perform(CURL* h) { (void)h; return 7 /* CURLE_COULDNT_CONNECT */; }
static inline void curl_easy_cleanup(CURL* h) { free(h); }
static inline const char* curl_easy_strerror(CURLcode c) {
(void)c; return "libcurl not built in (curl-less build)";
}
#endif /* !HAVE_CURL */
#endif /* EL_PLATFORM_WIN_H */
+114 -22
View File
@@ -21,6 +21,10 @@
#include "el_runtime.h"
#ifdef _WIN32
/* Windows OS-boundary shim (winsock/dlsym/popen). Threading stays on <pthread.h> (winpthreads). */
#include "el_platform_win.h"
#else
#include <stdarg.h>
#include <strings.h> /* strcasecmp */
#include <stdint.h>
@@ -42,7 +46,16 @@
#include <dirent.h>
#include <errno.h>
#include <pthread.h>
/* On POSIX, sockets close with the same close() as files; el_platform_win.h supplies the Windows
variant. Defined here so the socket call sites are identical across platforms. */
static inline int el_closesocket(int s) { return close(s); }
#endif
/* libcurl: present on POSIX and on the WITH_CURL Windows build; absent on the curl-less Windows
validation build, where el_platform_win.h supplies degradable stubs. On POSIX (_WIN32 undefined)
this is always taken, so the POSIX build is unchanged. */
#if !defined(_WIN32) || defined(HAVE_CURL)
#include <curl/curl.h>
#endif
/* ── Internal allocators ─────────────────────────────────────────────────── */
@@ -71,8 +84,14 @@ static _Thread_local ElArena _tl_arena = {NULL, 0, 0};
static _Thread_local int _tl_arena_active = 0;
/* Binary-safe fs_read length — set by fs_read, consumed by http_send_response.
* Allows serving PNGs and other binary files without strlen truncation. */
static _Thread_local size_t _tl_fs_read_len = 0;
* Allows serving PNGs and other binary files without strlen truncation.
* PAIRED with the buffer pointer it describes: the length may only be applied
* to the exact buffer fs_read returned. Without the pairing, any handler that
* fs_read a file and then WRAPPED it into a larger response had that response
* truncated to the file's length (Content-Length lied AND the send stopped
* short) the safety-contact onboarding trap, 2026-07-17. */
static _Thread_local size_t _tl_fs_read_len = 0;
static _Thread_local const char* _tl_fs_read_buf = NULL;
static void el_arena_track(char* p) {
if (!_tl_arena_active || !p) return;
@@ -90,6 +109,8 @@ static void el_arena_track(char* p) {
void el_request_start(void) {
_tl_arena.count = 0;
_tl_arena_active = 1;
_tl_fs_read_len = 0; /* never let a previous request's file length */
_tl_fs_read_buf = NULL; /* leak into this response's byte accounting */
}
/* Called by http_worker after the El handler returns and the response is sent.
@@ -1403,11 +1424,14 @@ static void http_send_response(int fd, const char* body) {
}
const char* eff_body = is_envelope ? env_body : body;
/* Use the real byte count from fs_read if available (handles binary files
* with embedded null bytes PNG, WOFF2, etc.). Fall back to strlen for
* normal text/JSON responses where _tl_fs_read_len is 0. */
size_t blen = (_tl_fs_read_len > 0) ? _tl_fs_read_len : strlen(eff_body);
/* Use the real byte count from fs_read ONLY when this body IS the exact
* buffer fs_read returned (binary files with embedded null bytes PNG,
* WOFF2, etc.). Any other body wrapped, enveloped, or derived must be
* measured with strlen, or it is truncated/over-read to the file's size. */
size_t blen = (_tl_fs_read_len > 0 && eff_body == _tl_fs_read_buf)
? _tl_fs_read_len : strlen(eff_body);
_tl_fs_read_len = 0; /* consume — one-shot per response */
_tl_fs_read_buf = NULL;
int head_only = _tl_http_head_only;
JsonBuf hdrs; jb_init(&hdrs);
@@ -1457,12 +1481,20 @@ static void http_send_response(int fd, const char* body) {
}
typedef struct {
#ifdef _WIN32
SOCKET fd;
#else
int fd;
#endif
} HttpWorkerArg;
static void* http_worker(void* arg) {
HttpWorkerArg* a = (HttpWorkerArg*)arg;
#ifdef _WIN32
SOCKET fd = a->fd;
#else
int fd = a->fd;
#endif
free(a);
char *method = NULL, *path = NULL, *body = NULL;
if (http_read_request(fd, &method, &path, &body, NULL) == 0) {
@@ -1479,11 +1511,22 @@ static void* http_worker(void* arg) {
const char* rs = EL_CSTR(r);
/* Copy response out BEFORE arena teardown.
* For binary files, _tl_fs_read_len holds the real byte count
* use memcpy instead of strdup so null bytes are preserved. */
size_t rlen = _tl_fs_read_len > 0 ? _tl_fs_read_len : (rs ? strlen(rs) : 0);
* use memcpy instead of strdup so null bytes are preserved.
* The stored length applies ONLY when the response IS the exact
* fs_read buffer; a wrapped/derived response must use strlen or
* it gets truncated (or over-read) to the file's length. */
size_t rlen;
if (_tl_fs_read_len > 0 && rs && rs == _tl_fs_read_buf) {
rlen = _tl_fs_read_len; /* raw file bytes — binary-safe */
} else {
rlen = rs ? strlen(rs) : 0;
_tl_fs_read_len = 0; /* hint doesn't describe this body */
_tl_fs_read_buf = NULL;
}
response = malloc(rlen + 1);
if (response && rs) { memcpy(response, rs, rlen); response[rlen] = '\0'; }
else if (response) { response[0] = '\0'; }
if (_tl_fs_read_len > 0) _tl_fs_read_buf = response; /* hint follows the copy */
} else {
response = el_strdup_persist("el-runtime: no http handler registered");
}
@@ -1494,7 +1537,7 @@ static void* http_worker(void* arg) {
free(response);
}
free(method); free(path); free(body);
close(fd);
el_closesocket(fd);
/* release a slot */
pthread_mutex_lock(&_http_conn_mu);
_http_conn_active--;
@@ -1524,14 +1567,18 @@ void http_serve(el_val_t port, el_val_t handler) {
addr.sin6_addr = in6addr_any;
addr.sin6_port = htons((uint16_t)p);
if (bind(sock, (struct sockaddr*)&addr, sizeof(addr)) < 0) {
perror("bind"); close(sock); return;
perror("bind"); el_closesocket(sock); return;
}
if (listen(sock, 64) < 0) { perror("listen"); close(sock); return; }
if (listen(sock, 64) < 0) { perror("listen"); el_closesocket(sock); return; }
fprintf(stderr, "[http] listening on [::]:%d (dual-stack)\n", p);
while (1) {
struct sockaddr_in6 cli;
socklen_t clen = sizeof(cli);
#ifdef _WIN32
SOCKET cfd = accept(sock, (struct sockaddr*)&cli, &clen);
#else
int cfd = accept(sock, (struct sockaddr*)&cli, &clen);
#endif
if (cfd < 0) {
if (errno == EINTR) continue;
perror("accept"); break;
@@ -1543,11 +1590,11 @@ void http_serve(el_val_t port, el_val_t handler) {
_http_conn_active++;
pthread_mutex_unlock(&_http_conn_mu);
HttpWorkerArg* arg = malloc(sizeof(HttpWorkerArg));
if (!arg) { close(cfd); continue; }
if (!arg) { el_closesocket(cfd); continue; }
arg->fd = cfd;
pthread_t tid;
if (pthread_create(&tid, NULL, http_worker, arg) != 0) {
close(cfd); free(arg);
el_closesocket(cfd); free(arg);
pthread_mutex_lock(&_http_conn_mu);
_http_conn_active--;
pthread_cond_signal(&_http_conn_cv);
@@ -1556,7 +1603,7 @@ void http_serve(el_val_t port, el_val_t handler) {
}
pthread_detach(tid);
}
close(sock);
el_closesocket(sock);
}
/* ── http_serve_async — non-blocking HTTP server ─────────────────────────── */
@@ -1792,7 +1839,11 @@ static el_val_t http_build_headers_map(const char* hdr_block) {
static void* http_worker_v2(void* arg) {
HttpWorkerArg* a = (HttpWorkerArg*)arg;
#ifdef _WIN32
SOCKET fd = a->fd;
#else
int fd = a->fd;
#endif
free(a);
char *method = NULL, *path = NULL, *body = NULL, *hdr_block = NULL;
if (http_read_request(fd, &method, &path, &body, &hdr_block) == 0) {
@@ -1805,10 +1856,20 @@ static void* http_worker_v2(void* arg) {
el_val_t hmap = http_build_headers_map(hdr_block ? hdr_block : "");
el_val_t r = h(EL_STR(dispatch_method), EL_STR(path), hmap, EL_STR(body));
const char* rs = EL_CSTR(r);
size_t rlen = _tl_fs_read_len > 0 ? _tl_fs_read_len : (rs ? strlen(rs) : 0);
/* Same pairing rule as the v1 worker: the fs_read length is only
* trustworthy for the exact buffer fs_read returned. */
size_t rlen;
if (_tl_fs_read_len > 0 && rs && rs == _tl_fs_read_buf) {
rlen = _tl_fs_read_len; /* raw file bytes — binary-safe */
} else {
rlen = rs ? strlen(rs) : 0;
_tl_fs_read_len = 0; /* hint doesn't describe this body */
_tl_fs_read_buf = NULL;
}
response = malloc(rlen + 1);
if (response && rs) { memcpy(response, rs, rlen); response[rlen] = '\0'; }
else if (response) { response[0] = '\0'; }
if (_tl_fs_read_len > 0) _tl_fs_read_buf = response; /* hint follows the copy */
el_release(hmap);
} else {
response = el_strdup_persist(
@@ -1822,7 +1883,7 @@ static void* http_worker_v2(void* arg) {
free(response);
}
free(method); free(path); free(body); free(hdr_block);
close(fd);
el_closesocket(fd);
pthread_mutex_lock(&_http_conn_mu);
_http_conn_active--;
pthread_cond_signal(&_http_conn_cv);
@@ -1852,14 +1913,18 @@ void http_serve_v2(el_val_t port, el_val_t handler) {
addr.sin6_addr = in6addr_any;
addr.sin6_port = htons((uint16_t)p);
if (bind(sock, (struct sockaddr*)&addr, sizeof(addr)) < 0) {
perror("bind"); close(sock); return;
perror("bind"); el_closesocket(sock); return;
}
if (listen(sock, 64) < 0) { perror("listen"); close(sock); return; }
if (listen(sock, 64) < 0) { perror("listen"); el_closesocket(sock); return; }
fprintf(stderr, "[http v2] listening on [::]:%d (dual-stack)\n", p);
while (1) {
struct sockaddr_in6 cli;
socklen_t clen = sizeof(cli);
#ifdef _WIN32
SOCKET cfd = accept(sock, (struct sockaddr*)&cli, &clen);
#else
int cfd = accept(sock, (struct sockaddr*)&cli, &clen);
#endif
if (cfd < 0) {
if (errno == EINTR) continue;
perror("accept"); break;
@@ -1871,11 +1936,11 @@ void http_serve_v2(el_val_t port, el_val_t handler) {
_http_conn_active++;
pthread_mutex_unlock(&_http_conn_mu);
HttpWorkerArg* arg = malloc(sizeof(HttpWorkerArg));
if (!arg) { close(cfd); continue; }
if (!arg) { el_closesocket(cfd); continue; }
arg->fd = cfd;
pthread_t tid;
if (pthread_create(&tid, NULL, http_worker_v2, arg) != 0) {
close(cfd); free(arg);
el_closesocket(cfd); free(arg);
pthread_mutex_lock(&_http_conn_mu);
_http_conn_active--;
pthread_cond_signal(&_http_conn_cv);
@@ -1884,7 +1949,7 @@ void http_serve_v2(el_val_t port, el_val_t handler) {
}
pthread_detach(tid);
}
close(sock);
el_closesocket(sock);
}
/* Build the response envelope a 4-arg handler can return. We hand-write
@@ -1924,6 +1989,7 @@ el_val_t http_response(el_val_t status, el_val_t headers_json, el_val_t body) {
el_val_t fs_read(el_val_t pathv) {
const char* path = EL_CSTR(pathv);
_tl_fs_read_len = 0;
_tl_fs_read_buf = NULL;
if (!path) return el_wrap_str(el_strdup(""));
FILE* f = fopen(path, "rb");
if (!f) return el_wrap_str(el_strdup(""));
@@ -1935,6 +2001,7 @@ el_val_t fs_read(el_val_t pathv) {
size_t got = fread(buf, 1, (size_t)sz, f);
buf[got] = '\0';
_tl_fs_read_len = got; /* store real byte count for binary-safe send */
_tl_fs_read_buf = buf; /* ...valid ONLY for this exact buffer */
fclose(f);
return el_wrap_str(buf);
}
@@ -2029,6 +2096,23 @@ el_val_t exec(el_val_t cmdv) {
el_val_t exec_bg(el_val_t cmdv) {
const char* cmd = EL_CSTR(cmdv);
if (!cmd || !*cmd) return el_wrap_str(el_strdup(""));
#ifdef _WIN32
/* Windows: no fork/exec. Launch a detached `cmd /c <command>` with no console window via
CreateProcess (DETACHED_PROCESS | CREATE_NO_WINDOW). Returns the PID as a string, "" on fail.
Mirrors the POSIX branch: child runs independently, caller is not blocked. */
char cmdline[8192];
snprintf(cmdline, sizeof(cmdline), "cmd.exe /c %s", cmd);
STARTUPINFOA si; ZeroMemory(&si, sizeof(si)); si.cb = sizeof(si);
PROCESS_INFORMATION pi; ZeroMemory(&pi, sizeof(pi));
BOOL ok = CreateProcessA(NULL, cmdline, NULL, NULL, FALSE,
DETACHED_PROCESS | CREATE_NO_WINDOW, NULL, NULL, &si, &pi);
if (!ok) return el_wrap_str(el_strdup(""));
char pidbuf[32];
snprintf(pidbuf, sizeof(pidbuf), "%lu", (unsigned long)pi.dwProcessId);
CloseHandle(pi.hProcess);
CloseHandle(pi.hThread);
return el_wrap_str(el_strdup(pidbuf));
#else
pid_t pid = fork();
if (pid < 0) {
/* fork failed */
@@ -2051,6 +2135,7 @@ el_val_t exec_bg(el_val_t cmdv) {
char pidbuf[32];
snprintf(pidbuf, sizeof(pidbuf), "%d", (int)pid);
return el_wrap_str(el_strdup(pidbuf));
#endif
}
el_val_t fs_list(el_val_t pathv) {
@@ -3305,8 +3390,10 @@ el_val_t json_get_raw(el_val_t json_str, el_val_t key) {
const char* k = EL_CSTR(key);
const char* p = json_find_key(json, k);
/* Clear fs_read binary-length hint — result is a fresh null-terminated
* string, not the raw file bytes, so Content-Length must use strlen. */
* string, not the raw file bytes, so Content-Length must use strlen.
* (Kept although the pointer pairing now makes this redundant.) */
_tl_fs_read_len = 0;
_tl_fs_read_buf = NULL;
if (!p) return el_wrap_str(el_strdup(""));
const char* end = json_skip_value(p);
size_t n = (size_t)(end - p);
@@ -4178,7 +4265,12 @@ static int _el_decompose_earth(el_caltime_t* ct, struct tm* tm_out, int* abbr_le
localtime_r(&s, &tm);
*tm_out = tm;
if (abbr_buf && abbr_cap > 0) {
/* mingw's struct tm has no tm_zone (BSD/glibc extension); no abbrev available there. */
#ifdef _WIN32
const char* z_str = "";
#else
const char* z_str = tm.tm_zone ? tm.tm_zone : "";
#endif
size_t n = strlen(z_str);
if (n >= abbr_cap) n = abbr_cap - 1;
memcpy(abbr_buf, z_str, n);
@@ -758,6 +758,18 @@ el_val_t trace_span_start(el_val_t name);
el_val_t trace_span_end(el_val_t span_handle);
el_val_t emit_event(el_val_t name, el_val_t duration_ms);
/* ── Runtime symbols required by the soul modules ──────────────────────────── */
/* All implemented in el_runtime.c but omitted from this release header; the soul dist modules
* reference them directly, so the public header must export them. Declarations only mirrors the
* mainline el_runtime.h and is platform-independent (no behavioural change to the POSIX build). */
typedef el_val_t (*http_handler_fn)(el_val_t method, el_val_t path, el_val_t body);
typedef el_val_t (*http_handler4_fn)(el_val_t method, el_val_t path, el_val_t body, el_val_t headers);
el_val_t el_arena_push(void);
el_val_t el_arena_pop(el_val_t mark);
void http_serve_async(el_val_t port, el_val_t handler);
el_val_t engram_get_node_by_label(el_val_t label);
el_val_t engram_prune_telemetry(el_val_t older_than_ms);
#ifdef __cplusplus
}
#endif