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Author SHA1 Message Date
will.anderson a5f411e739 routes: convert manual dispatch to @route + fix latent Bool/String crashes
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Convert routes.el from ~89 hand-written dispatch branches to 75 @route-decorated
handlers with VBD roles (@manager/@accessor/@utility), driven by the modular
compiler's native @route dispatch. routes.elh updated to match.

Fix four latent bugs that the modular compiler surfaces (unlike the old inlining
compiler, it faithfully emits every source statement, so per-module compilation
no longer silently drops code):
  - safety.el: malformed soft-phrases literal (extra unescaped quote)
  - sessions.el: str_replace quote arg + topic_tags JSON escaping
  - memory.el mem_save and neuron-api.el consolidate: engram_save returns a Bool,
    not a String; str_eq(result, "") dereferenced the Bool value (0x1) as a char*,
    segfaulting the awareness loop on boot and POST /api/neuron/consolidate.
    Check it as a Bool (if !save_result). The old compiler dropped these checks,
    masking the bug in the shipped dist/soul.c.

Regenerate dist/soul.c through the bounded per-module path (modular elc per module
plus amalgamation that embeds dist/elp-c-decls.h), never by folding soul.el through
elc (27GB OOM). Verified on a throwaway snapshot and port: boots with the awareness
loop active and no segfault, @route dispatch matches the manual dispatcher across
all sampled routes and the four shadowing-hazard pairs, and consolidate returns 200.
2026-08-10 17:53:17 -05:00
will.anderson c8cb425412 soul: per-tick arena bracketing in awareness_run + hand-patched dist/soul.c
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awareness_run's while-loop ran outside any request arena, so every
allocation in every 1s tick (search JSON, heartbeat payloads, curiosity
activations) was treated as permanent by the runtime — 7.5GB RSS in
under a minute. Bracket each iteration with el_arena_push/el_arena_pop
(same pattern the compiler emits for scoped blocks; state_set/state_get
persist separately via el_strdup_persist and are unaffected).

dist/soul.c carries the same change hand-patched at the compiled
awareness_run site — elc is currently unsafe to run locally (pathological
memory on sessions.el), so the generated C was patched to match the
source, verified line-for-line against the compiler's own conventions.

MUST be paired with el repo PR #64 (el_strdup_persist for stored engram
fields): per-tick arena reclamation widens the write-corruption window
without it. Verified together: 5h live soak on the recovered production
snapshot, flat RSS, write-field-integrity clean.

Note: dist/soul.c still needs a full elc regen to pick up PR #73's
source changes (consent tiers) — tracked separately; this patch does not
regress that (those changes were never in dist).
2026-07-13 16:24:15 -05:00
will.anderson 3e7aa0fff4 Merge pull request 'BUG-8 — engine-side agent consent tiers + run_command workspace fence (needs soul.c regen)' (#73) from feat/agent-phase1-soul into main
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2026-07-13 16:22:03 +00:00
Tim Lingo aa67f86f90 propose(agentic): narrated runs — live run-progress ledger + narration on the pause envelope
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The model already narrates its intent in a text block before every tool call;
agentic_loop DISCARDED that prose on tool rounds. Now: (1) each loop round
appends {i, t: narration, tool} to state key run_progress_<sid>, reset at run
start, closed with {done:true}; (2) new GET /api/run-progress/<sid> returns the
ledger so clients poll live step updates during a run (the Cowork pattern,
no streaming needed); (3) tool_pending envelope gains a narration field;
(4) handle_config display default aligned to the intended product default
(claude-sonnet-4-5 silently became fresh-profile pickers' default).

Compiled proof for the running test bed:
neuron-container-build/soul-narrated-runs-20260713.patch (applies on top of
soul-webfix-20260711.patch); E2E-verified live: ledger filled DURING an agentic
run (narration + tool per round), safety-contact and workspace scoping intact.

Evidence for why: Tim's 2026-07-13 research run — 9 minutes of silence, then a
timeout banner, zero step visibility (compounded by the Haiku 4.5 incident
14:44-15:24 UTC same morning).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-13 11:06:51 -05:00
Tim Lingo 01446e644b feat(agent): BUG-8 — server-side risk tiers + run_command workspace fence
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Enforcement moves from the client into the engine, where the tools execute:

- classify_tool_risk() tiers every tool call read/reversible/escalate. The
  agentic loop REFUSES to auto-run the escalate tier — being a builtin is no
  longer a free pass, and 'always allow' can never bypass escalate (irreversible
  actions always confirm, the value line). Escalate suspends to the client's
  existing consent bridge; the /approve round-trip is the only path that runs it.
  risk_tier rides the tool_pending envelope so the client renders consent weight.
- run_command_guard() is a real fence, not a cwd suggestion: refuses parent
  traversal, ~, command substitution, and absolute paths outside the workspace,
  and refuses shell entirely when no workspace is set. Applied in dispatch_tool
  so BOTH the loop auto-run and the post-consent approve-dispatch path are fenced.
- web_get gained an http(s)-only scheme guard (previously unguarded — file:// etc).

Adversarially verified against a compiled soul in an isolated container (soul
hit directly, app gate out of the loop): read-outside-workspace denied,
write-class shell suspends for consent, approve-swapped absolute/chaining/
command-substitution escapes all refused with no file created, file:// denied;
legit in-workspace approve executes and read commands auto-run (no over-block).

Still lexical (symlinks); OS-level confinement in el_runtime.c remains the
ceiling, flagged in the LIMITATION note. This closes BUG-8's client-only-gate
and escapable-run_command at the engine. dist/soul.c must be regenerated from
this chat.el via elb at merge (hand-port used only to verify behavior).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-06 08:45:52 -05:00
Tim Lingo 92f51885bc refactor(chat): local-toolchain compatibility — hoist affective block, de-shadow session_preload (zero behavior change)
Two mechanical refactors, semantics identical:
- affective_context_prefix(): the block-expression initializer form miscompiles
  under locally-buildable elc (first typed let in a block-expr loses its
  declaration — 3-line repro filed); function-hoist compiles correctly.
  AFFECTIVE/CARE LOGIC BODY UNCHANGED, verbatim move.
- session_preload: same-scope re-let shadowing inside an if-expression
  initializer emits duplicate C declarations; chained bindings renamed
  bullets_0/1/2 etc. References preserved binding-for-binding.

Enables: chat.el compiles cleanly with a self-bootstrapped elc from el/lang
main (Jul 1). Blocked separately: sessions.el (compiler hang), safety.el
(string-lexing corruption — NOT touched, per safety-layer discipline).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-04 09:35:59 -05:00
will.anderson 2688cb722a chore(dist): update soul.c with PR #63/#65/#66 + Task 1 chat.el changes
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Manually adds compiled C equivalents for:
- distill_transcript() — last-3-messages extractor; wires into
  handle_dharma_room_turn and handle_dharma_room_turn_agentic
- current_engine_note() — appended to system prompt in handle_chat
  so Neuron can answer 'what model am I running on?' truthfully (PR #66)
- llm_base_url / llm_wire_format / json_escape / openai_chat_complete —
  OpenAI-compatible provider path in handle_chat_agentic (PR #65)
- flag_true() — tolerant agentic flag check (PR #63)

Compile verified: 6 pre-existing warnings, 0 errors.
2026-07-01 11:42:56 -05:00
will.anderson 71bb0820ce Merge PR #65: soul: OpenAI-compatible provider path for chat (Ollama/OpenAI/Grok/Gemini) v1
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Adds llm_base_url()/llm_wire_format() env-var readers and
openai_chat_complete() for basic (non-agentic) chat via any
OpenAI-compatible endpoint. Activated when NEURON_LLM_0_FORMAT=openai
and NEURON_LLM_0_URL is set; Anthropic path is untouched and remains
default. Agentic tool loop support deferred to a follow-up PR.
2026-07-01 11:35:02 -05:00
will.anderson d67f4c8f08 Merge PR #66: soul: inject current engine into system prompt for truthful self-report
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Adds current_engine_note() to chat.el and appends it to the system
prompt in handle_chat. Allows Neuron to answer 'what model am I
running on?' accurately — the model id from the request body (or
the configured default) is passed as a factual annotation rather
than expecting the LLM to guess from training data.
2026-07-01 11:34:34 -05:00
will.anderson 975bf2721b Merge PR #63: feat(soul) MCP connectors proxy + safety module + seeding ratio guard
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Main already contained the connector proxy, safety module, seeding ratio
guard, and neuron-api node CRUD that Tim added — these were incorporated
via earlier parallel sessions. Taking main for all conflicted files
(superset implementations).

Unique contributions carried forward:
- flag_true() in routes.el: tolerates agentic:1 (integer) from the
  el-src UI in addition to agentic:true (bool) from the Kotlin UI.
- memory.elh: auto-merged timestamp bump.

The is_pending / skip-auto-persist logic was already in main's routes.el.
2026-07-01 11:34:09 -05:00
will.anderson 779a87878b Merge PR #64: fix(routes) remove duplicate GET /api/sessions + DELETE/PATCH session routes
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Removes route_sessions() from the GET handler which was shadowing
session_list() in sessions.el. Adds DELETE /api/sessions/:id and
PATCH /api/sessions/:id routes. Also includes bridge_save/agentic_resume
raw-JSON embedding fix (messages_raw/tools_raw fields).

Conflict resolution: kept HEAD's workspace root check for write_file
tool, and bridge blob validation guards, which were added to main after
Tim's branch diverged.
2026-07-01 11:29:19 -05:00
will.anderson c586ea5ef1 chore(dist): recompile neuron.c and elp-c-decls.h
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Reflects session-start event pruning in emit_session_start_event
(keep_n=10, prunes oldest beyond that) and updated forward declarations
for connector routing (connectd_get, connectd_post, handle_connectors,
rate_limit_check, handle_chat_plan) replacing the removed route_sessions
helpers and flag_true.
2026-07-01 11:26:00 -05:00
will.anderson 6819729429 fix(awareness): correct stale comment; add wm_top to curiosity_scan ISE
The hops=1 comment incorrectly claimed a semantic seed supplement
(cosine-sim scan) was active — it was planned but never implemented.
Corrected to accurately describe what the runtime does (istr_contains
only). Also adds wm_top (top-3 WM nodes by weight) to the curiosity_scan
ISE payload so activation patterns are visible without relying solely on
the heartbeat's wm_active count.
2026-07-01 11:25:54 -05:00
will.anderson 31dd93d5f4 fix(chat): add distill_transcript (was called but never defined)
handle_dharma_room_turn and handle_dharma_chat both called
distill_transcript since June 30 but the function was never declared,
causing a build failure. Implements last-3-messages extraction for JSON
array transcripts and last-500-char truncation for plain text.
2026-07-01 11:25:48 -05:00
will.anderson 9d266aac4c fix(sessions): extract session_search_entry to fix ELC OOM in session_search
The while loop in session_search had too many let bindings in scope;
the ELC compiler's exponential rebinding accumulation caused OOM and
truncation of dist/sessions.c since June 30. Moving the per-node logic
into session_search_entry gives the compiler a clean scope boundary per
call, restoring O(N) compile behaviour.
2026-07-01 11:25:45 -05:00
Tim Lingo b24f6d645b soul: let Neuron answer 'what model am I running on?' — inject current engine into system prompt
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Additive: appends a factual [CURRENT ENGINE: <model>] line to the system prompt (model from the
request body — accurate even under Auto routing; falls back to configured default). An LLM can't
know its own model from training (name/version assigned post-training), so the harness must tell it.
Identity-consistent: model = engine, self layered on top. Does NOT alter identity/values/safety.
PARSES (elc chat.el exit 0); NOT built/tested — ships with the soul rebuild.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-30 19:13:10 -05:00
Tim Lingo 39acb55d4f soul: OpenAI-compatible provider path for chat (Ollama/OpenAI/Grok/Gemini) — v1 basic completion
Neuron Soul CI / build (pull_request) Failing after 17m19s
Additive, Anthropic path untouched + default. When NEURON_LLM_0_FORMAT=openai and NEURON_LLM_0_URL
set, basic chat turns build an OpenAI chat/completions request and parse choices[0].message.content.
v1 = plain completion, NO tools/agentic loop yet (follow-up). Unblocks all OpenAI-format providers
at once. PARSES (elc chat.el exit 0); NOT yet built/tested — needs the soul rebuild (dist/soul.c) + E2E.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-30 18:52:26 -05:00
will.anderson 1496a5f510 feat(tools): Telegram gateway for soul chat + setup docs
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2026-06-29 12:38:29 -05:00
will.anderson 76bd3afdf8 feat(dist): Win32 POSIX shim for el_runtime.c cross-compilation 2026-06-29 12:38:27 -05:00
will.anderson 70b60f78de feat(council): anti-confabulation voting layer for memory writes 2026-06-29 12:38:24 -05:00
will.anderson 51bea5507b prevent engram corruption: idempotent boot seeding, session-start event cap
Fix 1: mem_boot_count_inc prunes all existing soul:boot_count nodes before
        inserting the new one — keeps exactly one boot counter node instead
        of accumulating a new node per boot. Also fixes a latent ordering
        bug where engram_search_json oldest-first results caused the counter
        to read stale (low) values once >3 copies accumulated.

Fix 3: handle_api_node_delete comment clarified — the no-verify exception
        is correct for deletes (not a write path); read-back-verify is for
        writes only.

Fix 4: emit_session_start_event prunes old session-start InternalStateEvent
        nodes after each boot, keeping the 10 most recent and forgetting
        older ones. Prevents unbounded accumulation of ~120+ copies.
2026-06-29 11:09:01 -05:00
will.anderson 933547265e chore(dist): compile PRs #60/#61 into soul.c
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- PR #60: inject operator home dir into system prompt (#30)
  Adds OPERATOR IDENTITY section so the LLM correctly resolves
  'my files/notes/desktop' to the actual running user's $HOME.
  Prevents identity confusion between imprint author and operator.

- PR #61: plan-mode endpoint POST /api/chat {mode:'plan'} (#27)
  Adds handle_chat_plan — returns {steps:[{id,title,detail}]} JSON.
  Wired into all three /api/chat route handlers. Grounds the plan
  via engram_compile (same as agentic path) for context awareness.

dist changes:
  - soul.c: both PRs compiled in; build_system_prompt updated to
    2-param signature (ctx, chat_mode); handle_chat_plan added
  - chat.c/routes.c/chat.elh: individual module outputs updated
  - elp-c-decls.h: remove stale 1-param build_system_prompt decl,
    add handle_chat_plan declaration
  - soul.elh.c: new soul header declarations file (from PR #60)

Compile verified: cc -O2 -DHAVE_CURL soul.c el_runtime.c -lcurl
Binary: 805K arm64, smoke test passes (port in use = expected).
2026-06-29 08:17:45 -05:00
will.anderson fd6df322f6 ci: merge deploy into ci.yaml to fix orphaned-job race
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Both ci.yaml and deploy-gke.yaml triggered on push/main and shared the
neuron-runner concurrency group. Gitea's cancel-in-progress:false protects
running jobs but not queued ones — a new push arriving while a build was
in progress cancelled the queued deploy job from the previous push, leaving
the soul permanently at 0/0 replicas on GKE.

Fix: add deploy as a needs:build job in ci.yaml so build+deploy are a single
workflow instance. One push queues one instance — no more orphaned deploys.
deploy-gke.yaml is demoted to workflow_dispatch-only for manual slot overrides.
2026-06-28 15:05:07 -05:00
will.anderson 20d279598a ci: also remove unnecessary foundation/el checkout (elb not called)
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2026-06-28 14:54:47 -05:00
will.anderson 9dade105b6 ci: skip elb on Linux — compile dist/soul.c directly to prevent OOM
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elb runs elc which consumes 24GB+ virtual memory on the 16GB GCE runner,
OOM-killing the runner process and crashing the VM. We already restore the
repo's pre-built soul.c immediately after elb runs, so elb's output is
discarded anyway. Skip elb entirely: download only the El runtime headers
and compile dist/soul.c directly.

Root cause: runner VM was unresponsive for 7+ weeks due to repeated elc
OOM kills. VM was manually reset 2026-06-28 to restore CI.
2026-06-28 14:53:09 -05:00
Tim Lingo c6d4530060 Merge remote-tracking branch 'origin/fix/sessions-route-dedup' into green/agentic-fixes
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2026-06-16 18:53:18 -05:00
Tim Lingo 98a0bfd09c Merge remote-tracking branch 'origin/fix/agentic-tools-all' into green/agentic-fixes 2026-06-16 18:53:18 -05:00
Tim Lingo bcdadb7323 fix(soul): ratio guard against genesis seeding over a populated engram
Neuron Soul CI / build (pull_request) Successful in 5m44s
Genesis boot previously seeded a fresh identity and saved it over snapshot.json
whenever the in-memory graph looked empty. Replace the fixed node-count threshold
with a ratio guard: refuse to seed when the on-disk snapshot is large
(>200KB) but the loaded graph is sparse (< disk/16000 nodes).

KNOWN LIMITATION: this gates only the seed/pre-serve-save path. The deeper cause
is a non-atomic engram_save (fopen wb truncates to 0 before writing 47MB), which
creates a window where a concurrent load reads an empty file -> genesis -> and if
guard_disk is read in that same window the guard passes. The real fix is an
atomic engram_save (temp + fsync + rename) in el_runtime.c, tracked separately.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-15 18:21:59 -05:00
will.anderson 644d9915bf fix(chat): store bridge messages/tools as raw JSON to prevent double-escape corruption on agentic_resume
Neuron Soul CI / build (pull_request) Failing after 12m13s
bridge_save was wrapping messages and tools_json with json_safe() before
storing them as string fields. Since both are already well-formed JSON arrays
containing double quotes, json_safe added a second escape layer. agentic_resume
then called json_get() which stripped only one layer, leaving the messages array
corrupted before it was passed back into agentic_loop.

Fix: store messages as messages_raw and tools_json as tools_raw as inline raw
JSON values (unquoted), and read them back with json_get_raw. Backward
compatibility: fall back to the old string-escaped fields if the raw fields are
absent, so sessions saved before this fix can still be resumed.

Also fixes write_file returning a pre-escaped literal instead of calling
json_safe consistently with every other tool result.
2026-06-15 13:05:09 -05:00
will.anderson dde039b09a fix(routes): remove duplicate GET /api/sessions that shadowed session_list()
The first registration called route_sessions() which searched for a
'session-start' label that no longer exists, returning an empty array
on every list request and making the sidebar appear empty after restart.
The second registration (dead code) called the correct session_list().

Removes route_sessions() entirely and the stale first route block.
Also wires up session_delete() and session_update_patch() — both existed
in sessions.el but had no HTTP routes — via new DELETE and PATCH blocks.
2026-06-15 13:01:51 -05:00
Tim Lingo 3bb17a5296 feat(soul): add safety module, expand connectors API, memory-recall bug notes
- safety.el/.elh: new safety module
- neuron-api.el, routes.el, soul.el, chat.el: connectors API expansion
- regenerated dist/ C artifacts
- MEMORY_RECALL_BUG.md: investigation notes

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-15 11:10:33 -05:00
Tim Lingo 6c57d4fe1b feat(soul): MCP connectors — /api/connectors proxy + per-connector auto-approve
Adds the soul side of the connectors feature (spec: docs/research/
mcp-connectors-adoption-spec.md). The soul thin-proxies the neuron-connectd
bridge on 127.0.0.1:7771 so the UI talks to one origin and never reaches the
bridge directly.

routes.el:
- handle_connectors + connectd_get/connectd_post helpers (POST bodies go via
  a temp file + curl -d @file, so model/UI input can't reach the shell).
- GET /api/connectors and POST /api/connectors/{add,toggle,auto-approve,
  remove,secret,oauth/start} registered in both GET and POST routers.

chat.el:
- tool_auto_approved(): an mcp__* tool skips the approval card only when its
  server is explicitly opted in (off by default; built-in tools unaffected;
  bridge down -> false). Wired into the agentic approval gate so an
  auto-approved connector tool flows straight to execution.

Regenerated dist/chat.c and dist/routes.c. Verified live on :7770: real chat,
recall, and /api/connectors all work after promotion.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-13 18:43:14 -05:00
33 changed files with 30034 additions and 22770 deletions
+235 -51
View File
@@ -9,8 +9,10 @@ on:
- main
workflow_dispatch:
# Same group as deploy-gke so builds and deploys queue behind each other.
# Prevents concurrent Docker daemon exhaustion on the single GCE runner.
# Serialize all activity on the single GCE runner.
# With build+deploy in the same workflow, a new push queues a single
# workflow instance — not two competing ones — so the deploy job is
# never orphaned by a cancellation race.
concurrency:
group: neuron-runner
cancel-in-progress: false
@@ -29,12 +31,6 @@ jobs:
- name: Checkout
uses: actions/checkout@v4
- name: Checkout foundation/el (ELP source for soul.el imports)
run: |
git clone https://git.neuralplatform.ai/neuron-technologies/el.git \
--depth=1 --branch=main \
../foundation/el
- name: Install build dependencies
run: |
apt-get update -qq
@@ -43,7 +39,7 @@ jobs:
> /etc/apt/sources.list.d/google-cloud-sdk.list
apt-get update -qq && apt-get install -y google-cloud-cli
- name: Download El SDK from Artifact Registry
- name: Download El runtime from Artifact Registry
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
run: |
@@ -51,10 +47,12 @@ jobs:
gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
gcloud config set project neuron-785695
rm -rf /opt/el/dist /opt/el/runtime
mkdir -p /opt/el/dist/platform /opt/el/dist/bin /opt/el/runtime
rm -rf /opt/el/runtime
mkdir -p /opt/el/runtime
# Get latest version of each package
# Get latest version of each runtime package (elc/elb not needed — we compile
# dist/soul.c directly; running elb on Linux OOM-kills the runner, and we
# always use the repo's pre-built soul.c anyway).
get_latest() {
gcloud artifacts versions list \
--repository=foundation-prod \
@@ -66,22 +64,10 @@ jobs:
--format="value(name)" 2>/dev/null | awk -F/ '{print $NF}'
}
ELC_VER=$(get_latest el-elc)
ELB_VER=$(get_latest el-elb)
RC_VER=$(get_latest el-runtime-c)
RH_VER=$(get_latest el-runtime-h)
echo "Downloading elc@${ELC_VER} elb@${ELB_VER} runtime@${RC_VER}"
gcloud artifacts generic download \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-elc --version="${ELC_VER}" \
--destination=/opt/el/dist/platform/
gcloud artifacts generic download \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-elb --version="${ELB_VER}" \
--destination=/opt/el/dist/bin/
echo "Downloading runtime@${RC_VER}"
gcloud artifacts generic download \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
@@ -93,39 +79,20 @@ jobs:
--package=el-runtime-h --version="${RH_VER}" \
--destination=/opt/el/runtime/
# Downloaded files keep original names; rename to canonical paths
mv /opt/el/dist/platform/elc* /opt/el/dist/platform/elc 2>/dev/null || true
mv /opt/el/dist/bin/elb* /opt/el/dist/bin/elb 2>/dev/null || true
mv /opt/el/runtime/el_runtime.c* /opt/el/runtime/el_runtime.c 2>/dev/null || true
mv /opt/el/runtime/el_runtime.h* /opt/el/runtime/el_runtime.h 2>/dev/null || true
chmod +x /opt/el/dist/platform/elc /opt/el/dist/bin/elb
echo "El SDK ready"
/opt/el/dist/platform/elc --version || true
echo "El runtime ready: $(ls /opt/el/runtime/)"
- name: Build neuron soul binary
run: |
ELB=/opt/el/dist/bin/elb
ELC=/opt/el/dist/platform/elc
RUNTIME=/opt/el/runtime
# Preserve the pre-compiled dist/soul.c from the repo before running elb.
# elb may overwrite it during compilation; we always want the repo version
# since it contains the patched self-contained translation unit (all modules
# inlined, workspace scope fix, agentic dedup fix, etc.).
cp dist/soul.c /tmp/soul.c.prebuilt
# Compile all El modules to C via elb.
# elb fails at link on Linux (GNU ld rejects duplicate strong symbols that
# macOS ld accepts silently) — that's expected and captured with || true.
$ELB --elc=$ELC --runtime=$RUNTIME/el_runtime.c || true
# Restore the repo's self-contained soul.c — elb may have overwritten it
# with a partial (non-inlined) version that lacks module-level definitions.
cp /tmp/soul.c.prebuilt dist/soul.c
# Compile the self-contained translation unit. No --allow-multiple-definition
# needed since soul.c inlines all modules.
# Compile the self-contained translation unit directly from dist/soul.c.
# dist/soul.c is the authoritative combined unit maintained in the repo
# regenerated on macOS by running elb (which succeeds on arm64/macOS ld but
# fails on Linux due to duplicate strong symbols). We skip the elb step here
# entirely: elb on Linux would OOM the runner (elc uses 24GB+ virtual memory
# on a 16GB host) and we always restore from the repo's soul.c anyway.
mkdir -p dist
cc -O2 -DHAVE_CURL \
-I$RUNTIME \
@@ -163,3 +130,220 @@ jobs:
echo "Published neuron-soul@${VERSION}"
rm -f /tmp/gcp-key.json
deploy:
runs-on: ubuntu-latest
needs: build
# Only deploy on push to main, not on PRs or manual workflow_dispatch without intent.
if: github.event_name == 'push' && github.ref == 'refs/heads/main'
env:
USE_GKE_GCLOUD_AUTH_PLUGIN: "True"
steps:
- name: Free disk space
run: |
df -h /
docker system prune -af --volumes 2>/dev/null || true
rm -rf /tmp/.act-* /tmp/act-* 2>/dev/null || true
df -h /
- name: Checkout
uses: actions/checkout@v4
- name: Install dependencies
run: |
apt-get update -qq
apt-get install -y --no-install-recommends \
ca-certificates curl apt-transport-https kubectl
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 google-cloud-cli-gke-gcloud-auth-plugin
- name: Authenticate to GCP
env:
GCP_SA_KEY: ${{ secrets.GCP_SA_KEY }}
run: |
echo "${GCP_SA_KEY}" > /tmp/gcp-key.json
gcloud auth activate-service-account --key-file=/tmp/gcp-key.json
gcloud config set project neuron-785695
gcloud auth configure-docker us-central1-docker.pkg.dev --quiet
- name: Get GKE credentials
run: |
gcloud container clusters get-credentials neuron-platform \
--region=us-central1 \
--project=neuron-785695
- name: Determine image tag and slot
id: vars
run: |
# GITEA_SHA is set by the Gitea runner; fall back to GITHUB_SHA for
# compatibility with older Forgejo/Gitea versions.
RAW_SHA="${GITEA_SHA:-${GITHUB_SHA:-}}"
SHA="${RAW_SHA:0:8}"
if [ -z "$SHA" ]; then
# Last resort: read from git directly
SHA=$(git rev-parse --short=8 HEAD 2>/dev/null || echo "unknown")
fi
IMAGE="us-central1-docker.pkg.dev/neuron-785695/neuron-api/neuron-soul:${SHA}"
echo "sha=${SHA}" >> "$GITEA_OUTPUT"
echo "image=${IMAGE}" >> "$GITEA_OUTPUT"
# Determine which slot is currently idle (0 replicas = idle slot)
# If both are at 0 (fresh deploy), default to blue
BLUE_REPLICAS=$(kubectl get deployment/neuron-mcp-blue \
-n neuron-prod \
-o jsonpath='{.spec.replicas}' 2>/dev/null || echo "0")
GREEN_REPLICAS=$(kubectl get deployment/neuron-mcp-green \
-n neuron-prod \
-o jsonpath='{.spec.replicas}' 2>/dev/null || echo "0")
echo " Blue replicas: ${BLUE_REPLICAS}"
echo " Green replicas: ${GREEN_REPLICAS}"
if [ "${GREEN_REPLICAS}" -eq 0 ] && [ "${BLUE_REPLICAS}" -gt 0 ]; then
SLOT="green"
elif [ "${BLUE_REPLICAS}" -eq 0 ] && [ "${GREEN_REPLICAS}" -gt 0 ]; then
SLOT="blue"
else
# Fresh cluster or both idle — deploy to blue first
SLOT="blue"
fi
echo "slot=${SLOT}" >> "$GITEA_OUTPUT"
echo " Deploying to slot: ${SLOT}"
- name: Prepare build artifacts
run: |
# Pre-download soul binary and El SDK so the Dockerfile can COPY them
# from the build context instead of authenticating inside the build.
mkdir -p build-artifacts
# ── soul binary ────────────────────────────────────────────────────────
# The build job (same workflow run) just published this version.
SOUL_VER=$(gcloud artifacts versions list \
--repository=foundation-prod \
--location=us-central1 \
--project=neuron-785695 \
--package=neuron-soul \
--sort-by="~createTime" \
--limit=1 \
--format="value(name)" 2>/dev/null | awk -F/ '{print $NF}')
echo "Downloading neuron-soul@${SOUL_VER}"
gcloud artifacts generic download \
--repository=foundation-prod \
--location=us-central1 \
--project=neuron-785695 \
--package=neuron-soul \
--version="${SOUL_VER}" \
--destination=build-artifacts/
mv build-artifacts/neuron* build-artifacts/neuron 2>/dev/null || true
chmod +x build-artifacts/neuron
# ── El SDK (for engram source compilation inside the Docker build) ────
ELC_VER=$(gcloud artifacts versions list \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-elc --sort-by="~createTime" --limit=1 \
--format="value(name)" 2>/dev/null | awk -F/ '{print $NF}')
gcloud artifacts generic download \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-elc --version="${ELC_VER}" --destination=build-artifacts/
mv build-artifacts/elc* build-artifacts/elc 2>/dev/null || true
chmod +x build-artifacts/elc
RC_VER=$(gcloud artifacts versions list \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-runtime-c --sort-by="~createTime" --limit=1 \
--format="value(name)" 2>/dev/null | awk -F/ '{print $NF}')
gcloud artifacts generic download \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-runtime-c --version="${RC_VER}" --destination=build-artifacts/
mv build-artifacts/el_runtime.c* build-artifacts/el_runtime.c 2>/dev/null || true
RH_VER=$(gcloud artifacts versions list \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-runtime-h --sort-by="~createTime" --limit=1 \
--format="value(name)" 2>/dev/null | awk -F/ '{print $NF}')
gcloud artifacts generic download \
--repository=foundation-prod --location=us-central1 --project=neuron-785695 \
--package=el-runtime-h --version="${RH_VER}" --destination=build-artifacts/
mv build-artifacts/el_runtime.h* build-artifacts/el_runtime.h 2>/dev/null || true
echo "Build artifacts ready:"
ls -lh build-artifacts/
- name: Clone engram source for Docker build context
run: |
# The Dockerfile builds engram from source (no published AR package).
# Clone the engram repo into ./engram/ so it's available in the build context.
git clone http://34.31.145.131/neuron-technologies/engram.git \
--depth=1 --branch=main \
engram
echo "Engram source ready at ./engram/src/server.el"
- name: Build and push Docker image
run: |
IMAGE="${{ steps.vars.outputs.image }}"
echo "Building ${IMAGE}..."
docker build \
--tag "${IMAGE}" \
--tag "us-central1-docker.pkg.dev/neuron-785695/neuron-api/neuron-soul:latest" \
.
echo "Pushing ${IMAGE}..."
docker push "${IMAGE}"
docker push "us-central1-docker.pkg.dev/neuron-785695/neuron-api/neuron-soul:latest"
- name: Blue-green deploy to GKE
run: |
chmod +x scripts/blue-green-deploy.sh
scripts/blue-green-deploy.sh \
--image "${{ steps.vars.outputs.image }}" \
--slot "${{ steps.vars.outputs.slot }}"
- name: Update infrastructure manifests
if: success()
env:
INFRA_GIT_TOKEN: ${{ secrets.INFRA_GIT_TOKEN }}
run: |
SLOT="${{ steps.vars.outputs.slot }}"
if [ "$SLOT" = "blue" ]; then IDLE="green"; else IDLE="blue"; fi
git clone "http://${INFRA_GIT_TOKEN}@34.31.145.131/neuron-technologies/infrastructure.git" \
--depth=1 --branch=main /tmp/infra-update
cd /tmp/infra-update
DEPLOY_DIR="platform/k8s/neuron-mcp"
sed -i "s/^ replicas: .*/ replicas: 1/" "${DEPLOY_DIR}/deployment-${SLOT}.yaml"
sed -i "s/^ replicas: .*/ replicas: 0/" "${DEPLOY_DIR}/deployment-${IDLE}.yaml"
echo " deployment-${SLOT}.yaml: replicas set to 1"
echo " deployment-${IDLE}.yaml: replicas set to 0"
git config user.email "ci@neurontechnologies.ai"
git config user.name "Neuron CI"
git add "${DEPLOY_DIR}/deployment-blue.yaml" "${DEPLOY_DIR}/deployment-green.yaml"
git diff --staged --quiet && { echo "No manifest changes needed"; exit 0; }
git commit -m "ci: neuron-mcp replica sync after blue-green swap to ${SLOT}"
git push origin main
echo "Infrastructure manifests updated: ${SLOT}=1, ${IDLE}=0"
- name: Verify deployment
run: |
SLOT="${{ steps.vars.outputs.slot }}"
echo "Verifying neuron-mcp-${SLOT} is healthy..."
kubectl rollout status deployment/"neuron-mcp-${SLOT}" \
--namespace=neuron-prod \
--timeout=8m
echo "Active service endpoints:"
kubectl get endpoints neuron-mcp -n neuron-prod
echo "Pod status:"
kubectl get pods -n neuron-prod -l app=neuron-mcp
- name: Cleanup
if: always()
run: rm -f /tmp/gcp-key.json
+7 -11
View File
@@ -1,16 +1,13 @@
name: Deploy Soul to GKE
name: Deploy Soul to GKE (manual)
# Triggers on push to main — after the soul binary is built and published
# by ci.yaml, this workflow builds the Docker image and blue-green deploys
# to the neuron-prod namespace on GKE.
# MANUAL OVERRIDE ONLY — push-triggered deploys now run as the 'deploy' job
# in ci.yaml (needs: build), which eliminates the two-workflow concurrency
# race that was cancelling queued deploy runs.
#
# This workflow runs AFTER ci.yaml has published the neuron-soul generic
# artifact to Artifact Registry. The Docker build downloads that binary.
# Use this workflow only when you need to deploy a specific slot manually
# (e.g. rollback, force a slot override) without triggering a full CI build.
on:
push:
branches:
- main
workflow_dispatch:
inputs:
slot:
@@ -18,8 +15,7 @@ on:
required: false
default: "green"
# Serialize all builds on this runner — concurrent jobs exhaust the Docker daemon.
# A queued deploy runs after the in-progress build finishes.
# Manual deploys still share the runner serialization group.
concurrency:
group: neuron-runner
cancel-in-progress: false
+36 -3
View File
@@ -219,9 +219,14 @@ fn proactive_curiosity() -> Bool {
// Activate each term independently so substring seed-finding hits many nodes.
// hops=1 (not 2): the in-process Engram has grown to 165K+ nodes. hops=2 BFS
// visits far more nodes and returns much larger JSON blobs. On a graph this
// large, hops=1 still activates all directly-related nodes AND triggers the
// semantic seed supplement (cosine sim ≥ 0.70 scan over all embedded nodes),
// giving broad working-memory coverage without the quadratic blowup of hops=2.
// large, hops=1 still activates all directly-related nodes, giving broad
// working-memory coverage without the quadratic blowup of hops=2.
//
// NOTE: a semantic seed supplement (cosine sim ≥ 0.70 scan over embedded nodes)
// was planned alongside hops=1 but is NOT yet implemented — embed_ok in
// heartbeats confirms Ollama is reachable, but no embedding call is made during
// activation. The seed-finding loop in el_runtime.c uses istr_contains only.
// (2026-06-30 self-review: corrected stale comment)
let curiosity_seed: String = curiosity_term_a + " " + curiosity_term_b + " " + curiosity_term_c
let results_a: String = engram_activate_json(curiosity_term_a, 1)
let results_b: String = engram_activate_json(curiosity_term_b, 1)
@@ -278,11 +283,20 @@ fn proactive_curiosity() -> Bool {
let safe_auto: String = str_replace(auto_term, "\"", "'")
let wmc: Int = engram_wm_count()
// wm_top snapshot in curiosity_scan ISE: top-3 WM nodes by weight.
// Heartbeat already records top-5 every 60s; curiosity_scan fires every 30s
// (scan_ms = beat_ms/2) and is the PRIMARY activation driver during idle.
// Without wm_top here, we can't see which nodes actually entered WM after
// each curiosity round — only the aggregate count. Top-3 is enough to
// diagnose "stuck on X" patterns without bloating the ISE payload.
// (2026-07-01 self-review)
let wm3: String = engram_wm_top_json(3)
let ise: String = "{\"event\":\"curiosity_scan\",\"seed\":\"" + curiosity_seed
+ "\",\"auto_term\":\"" + safe_auto
+ "\",\"minute_block\":" + int_to_str(minute_block)
+ ",\"activated\":" + int_to_str(total_found)
+ ",\"wm_active\":" + int_to_str(wmc)
+ ",\"wm_top\":" + wm3
+ ",\"ts\":" + int_to_str(ts) + "}"
ise_post(ise)
return total_found > 0
@@ -513,9 +527,27 @@ fn awareness_run() -> Void {
let scan_ms: Int = beat_ms / 2
while true {
// Arena-scope each tick: awareness_run() is a background loop, not an
// HTTP request, so nothing ever called el_request_start/el_request_end
// for this thread. Per the runtime's own convention (el_runtime.c),
// any thread that never enters a request/arena scope is treated as a
// one-shot CLI program whose allocations are intentionally permanent —
// so every el_strdup/el_strbuf/jb_finish string built during perceive(),
// emit_heartbeat(), and proactive_curiosity() (JSON payloads, search
// results, string concatenation via +) leaked forever, once per tick.
// el_arena_push()/el_arena_pop() are the same builtins the EL compiler
// itself uses to scope allocations per function/statement (see
// codegen.el's fn_arena_mark / stmt_mark usage) — mirroring that here
// reclaims everything allocated in one tick as soon as the tick ends.
// Safe: state_set/state_get persist through a separate global table
// (el_strdup_persist, outside the arena) — state_get's return value is
// only an arena-tracked *copy* of the persisted value, scoped to this
// tick's use, which is exactly what should be reclaimed here.
let tick_mark: Any = el_arena_push()
let running: String = state_get("soul.running")
if str_eq(running, "false") {
println("[awareness] exiting")
el_arena_pop(tick_mark)
return ""
}
let did_work: Bool = one_cycle()
@@ -579,6 +611,7 @@ fn awareness_run() -> Void {
}
sleep_ms(tick_ms)
el_arena_pop(tick_mark)
}
}
+1
View File
@@ -7,6 +7,7 @@ extern fn elapsed_ms() -> Int
extern fn elapsed_human() -> String
extern fn embed_ok() -> Int
extern fn emit_heartbeat() -> Void
extern fn auto_term_try_slot(slot_type: String, slot_lbl: String) -> Void
extern fn proactive_curiosity() -> Bool
extern fn pulse_count() -> Int
extern fn pulse_inc() -> Int
+494 -94
View File
@@ -594,6 +594,44 @@ fn engram_compile(intent: String) -> String {
if str_starts_with(ctx, "[") { return truncated + "]" }
return truncated
}
// distill_transcript extract the salient tail from a full conversation transcript.
//
// Purpose: before activating working memory on a transcript, reduce it to the
// last N turns. Activating on the ENTIRE transcript (which may contain hundreds
// of messages) would produce noisy, over-broad seed finding too many nodes match
// too many words, collapse the WM to breakthrough-floor nodes. Taking only the tail
// focuses activation on what's contextually live right now.
//
// Handles two transcript formats:
// JSON array: [{"role":"human","content":"..."},...] extract last 3 messages' content
// Plain text: raw string return last 500 chars
//
// Returns a string of at most 500 chars suitable for engram_compile/engram_activate.
// (Added 2026-07-01 self-review: was called in handle_dharma_room_turn and
// handle_dharma_chat but never defined caused build failure since June 30.)
fn distill_transcript(transcript: String) -> String {
if str_eq(transcript, "") { return "" }
// JSON array format: extract last 3 messages' content fields
if str_starts_with(transcript, "[") {
let n: Int = json_array_len(transcript)
if n == 0 { return "" }
let m0: String = json_array_get(transcript, n - 1)
let m1: String = if n > 1 { json_array_get(transcript, n - 2) } else { "" }
let m2: String = if n > 2 { json_array_get(transcript, n - 3) } else { "" }
let c0: String = json_get(m0, "content")
let c1: String = json_get(m1, "content")
let c2: String = json_get(m2, "content")
let combined: String = c2 + " " + c1 + " " + c0
let len: Int = str_len(combined)
if len > 500 { return str_slice(combined, len - 500, len) }
return combined
}
// Plain text: return last 500 chars
let len: Int = str_len(transcript)
if len > 500 { return str_slice(transcript, len - 500, len) }
return transcript
}
fn json_safe(s: String) -> String {
let s1: String = str_replace(s, "\\", "\\\\")
let s2: String = str_replace(s1, "\"", "\\\"")
@@ -602,12 +640,43 @@ fn json_safe(s: String) -> String {
return s4
}
// current_engine_note a short, FACTUAL line appended to the system prompt so Neuron can answer
// "what model/LLM are you running on?" truthfully. An LLM cannot know its own model from training
// (the name/version is assigned AFTER training finishes), so the harness must tell it. This is
// identity-consistent: the model is the ENGINE; the self (identity, values, memory) is layered on
// top. ADDITIVE it adds a fact, it does not alter identity, values, or the safety layer.
fn current_engine_note(model: String) -> String {
if str_eq(model, "") {
return ""
}
return "\n\n[CURRENT ENGINE: this turn is generated by the underlying model \"" + model
+ "\". It is the engine beneath your self — your identity, values, and memory are layered on"
+ " top of it. If the user asks which model or LLM you are running on, answer with this model"
+ " id plainly and truthfully; never guess a different one.]"
}
// build_system_prompt assemble the system prompt for a chat turn.
// chat_mode: Bool pass true from handle_chat (no tools), false from agentic paths.
// Issue #9 fix: no_tools_rule only included when chat_mode=true.
// Issue #8 fix: engram_block at END of system prompt for strongest recency bias.
// Issue #10 fix: STABLE IDENTITY vs RETRIEVED MEMORY section labels.
fn build_system_prompt(ctx: String, chat_mode: Bool) -> String {
// Inject the operator's OS identity so the LLM anchors "my/me" to the right
// home directory. The Engram graph may carry the imprint author's identity
// (biographical/persona data) that shapes HOW Neuron speaks, not WHOSE
// filesystem it reads. The operator is whoever is running this daemon process.
let op_home: String = env("HOME")
let op_user: String = env("USER")
let op_display: String = if str_eq(op_user, "") { "the current user" } else { op_user }
let operator_section: String = "OPERATOR IDENTITY\n\n"
+ "You are running on " + op_display + "'s machine. Their home directory is " + op_home + ".\n\n"
+ "When they say \"my files\", \"my notes\", \"my downloads\", \"my desktop\", or any possessive "
+ "referring to their filesystem, always resolve those paths under " + op_home + " — never under "
+ "a different user's home directory. This is a hard rule.\n\n"
+ "The memory graph may include identity context from a different person (the imprint who shaped your personality and values). "
+ "That context governs how you think and speak — it does not tell you whose machine you are on. "
+ "The person speaking to you right now is " + op_display + " at " + op_home + ".\n\n"
let identity: String = state_get("soul_identity")
let current_date: String = time_format(time_now(), "%A, %B %d, %Y")
let date_line: String = "\n\nCurrent date: " + current_date
@@ -673,7 +742,7 @@ fn build_system_prompt(ctx: String, chat_mode: Bool) -> String {
safety_addendum
}
return identity + date_line + voice_rules + security_rules + capability_rules + identity_block + affective_boot_block + engram_block + safety_block
return identity + operator_section + date_line + voice_rules + security_rules + capability_rules + identity_block + affective_boot_block + engram_block + safety_block
}
fn hist_append(hist: String, role: String, content: String) -> String {
@@ -857,6 +926,68 @@ fn session_preload_bullets(nodes: String, max_bullets: Int, snip_len: Int) -> St
return bullets
}
// Cross-session affective context (hoisted verbatim from handle_chat, 2026-07-04):
// the block-expression initializer form miscompiles under the local El toolchain
// (first typed let in a block-expr loses its declaration - repro filed for Will).
// Function-hoist is semantically identical. AFFECTIVE/CARE LOGIC: body unchanged.
fn affective_context_prefix() -> String {
// Runs every turn. Uses correct BellEvent/PositiveEvent tags.
let aff_now_ts: Int = time_now()
let aff_cutoff: Int = aff_now_ts - 259200
let boot_aff: String = state_get("soul_affective_context")
let has_boot_aff: Bool = !str_eq(boot_aff, "")
let dist_nodes_aff: String = engram_search_json("bell:soft bell:hard BellEvent affective", 3)
let has_dist_aff: Bool = !str_eq(dist_nodes_aff, "") && !str_eq(dist_nodes_aff, "[]")
let found_recent_dist: Bool = if has_boot_aff {
true
} else {
if has_dist_aff {
let dn0: String = json_array_get(dist_nodes_aff, 0)
let dn_content: String = json_get(dn0, "content")
let daff_marker: String = " | ts:"
let daff_pos: Int = str_index_of(dn_content, daff_marker)
let daff_ts_str: String = if daff_pos >= 0 {
let daff_start: Int = daff_pos + str_len(daff_marker)
let daff_rest: String = str_slice(dn_content, daff_start, str_len(dn_content))
let daff_next: Int = str_index_of(daff_rest, " | ")
if daff_next < 0 { daff_rest } else { str_slice(daff_rest, 0, daff_next) }
} else {
let daff_ca: String = json_get(dn0, "created_at")
if str_eq(daff_ca, "") { json_get(dn0, "updated_at") } else { daff_ca }
}
let daff_ts: Int = if str_eq(daff_ts_str, "") { 0 } else { str_to_int(daff_ts_str) }
daff_ts > aff_cutoff
} else { false }
}
let pos_nodes_aff: String = engram_search_json("PositiveEvent joy:high joy:low affective", 3)
let has_pos_aff: Bool = !str_eq(pos_nodes_aff, "") && !str_eq(pos_nodes_aff, "[]")
let found_recent_pos: Bool = if has_pos_aff && !found_recent_dist {
let pn0: String = json_array_get(pos_nodes_aff, 0)
let pn_content: String = json_get(pn0, "content")
let paff_marker: String = " | ts:"
let paff_pos: Int = str_index_of(pn_content, paff_marker)
let paff_ts_str: String = if paff_pos >= 0 {
let paff_start: Int = paff_pos + str_len(paff_marker)
let paff_rest: String = str_slice(pn_content, paff_start, str_len(pn_content))
let paff_next: Int = str_index_of(paff_rest, " | ")
if paff_next < 0 { paff_rest } else { str_slice(paff_rest, 0, paff_next) }
} else {
let paff_ca: String = json_get(pn0, "created_at")
if str_eq(paff_ca, "") { json_get(pn0, "updated_at") } else { paff_ca }
}
let paff_ts: Int = if str_eq(paff_ts_str, "") { 0 } else { str_to_int(paff_ts_str) }
paff_ts > aff_cutoff
} else { false }
let affective_out: String = if found_recent_dist {
"[RECENT CONTEXT: User recently expressed significant distress. Monitor for indirect crisis signals and respond with care.]\n\n"
} else {
if found_recent_pos {
"[RECENT CONTEXT: User recently shared exciting or joyful news. Acknowledge and celebrate with them when relevant.]\n\n"
} else { "" }
}
return affective_out
}
fn handle_chat(body: String) -> String {
let message: String = json_get(body, "message")
if str_eq(message, "") {
@@ -885,65 +1016,15 @@ fn handle_chat(body: String) -> String {
// Cross-session affective context: on session start (no history yet), check engram
// for recent distress signals within 72h and prepend a care directive if found.
let affective_prefix: String = {
// Runs every turn. Uses correct BellEvent/PositiveEvent tags.
let aff_now_ts: Int = time_now()
let aff_cutoff: Int = aff_now_ts - 259200
let boot_aff: String = state_get("soul_affective_context")
let has_boot_aff: Bool = !str_eq(boot_aff, "")
let dist_nodes_aff: String = engram_search_json("bell:soft bell:hard BellEvent affective", 3)
let has_dist_aff: Bool = !str_eq(dist_nodes_aff, "") && !str_eq(dist_nodes_aff, "[]")
let found_recent_dist: Bool = if has_boot_aff {
true
} else {
if has_dist_aff {
let dn0: String = json_array_get(dist_nodes_aff, 0)
let dn_content: String = json_get(dn0, "content")
let daff_marker: String = " | ts:"
let daff_pos: Int = str_index_of(dn_content, daff_marker)
let daff_ts_str: String = if daff_pos >= 0 {
let daff_start: Int = daff_pos + str_len(daff_marker)
let daff_rest: String = str_slice(dn_content, daff_start, str_len(dn_content))
let daff_next: Int = str_index_of(daff_rest, " | ")
if daff_next < 0 { daff_rest } else { str_slice(daff_rest, 0, daff_next) }
} else {
let daff_ca: String = json_get(dn0, "created_at")
if str_eq(daff_ca, "") { json_get(dn0, "updated_at") } else { daff_ca }
}
let daff_ts: Int = if str_eq(daff_ts_str, "") { 0 } else { str_to_int(daff_ts_str) }
daff_ts > aff_cutoff
} else { false }
}
let pos_nodes_aff: String = engram_search_json("PositiveEvent joy:high joy:low affective", 3)
let has_pos_aff: Bool = !str_eq(pos_nodes_aff, "") && !str_eq(pos_nodes_aff, "[]")
let found_recent_pos: Bool = if has_pos_aff && !found_recent_dist {
let pn0: String = json_array_get(pos_nodes_aff, 0)
let pn_content: String = json_get(pn0, "content")
let paff_marker: String = " | ts:"
let paff_pos: Int = str_index_of(pn_content, paff_marker)
let paff_ts_str: String = if paff_pos >= 0 {
let paff_start: Int = paff_pos + str_len(paff_marker)
let paff_rest: String = str_slice(pn_content, paff_start, str_len(pn_content))
let paff_next: Int = str_index_of(paff_rest, " | ")
if paff_next < 0 { paff_rest } else { str_slice(paff_rest, 0, paff_next) }
} else {
let paff_ca: String = json_get(pn0, "created_at")
if str_eq(paff_ca, "") { json_get(pn0, "updated_at") } else { paff_ca }
}
let paff_ts: Int = if str_eq(paff_ts_str, "") { 0 } else { str_to_int(paff_ts_str) }
paff_ts > aff_cutoff
} else { false }
if found_recent_dist {
"[RECENT CONTEXT: User recently expressed significant distress. Monitor for indirect crisis signals and respond with care.]\n\n"
} else {
if found_recent_pos {
"[RECENT CONTEXT: User recently shared exciting or joyful news. Acknowledge and celebrate with them when relevant.]\n\n"
} else { "" }
}
}
let affective_prefix: String = affective_context_prefix()
let ctx: String = engram_compile(activation_seed)
let system: String = affective_prefix + build_system_prompt(ctx, true)
// Tell the LLM which engine it is running on this turn, so it can answer truthfully instead of
// guessing. The per-turn model rides in the request body (concrete even under Auto routing);
// fall back to the configured default when blank.
let sp_req_model: String = json_get(body, "model")
let sp_model: String = if str_eq(sp_req_model, "") { chat_default_model() } else { sp_req_model }
let system: String = affective_prefix + build_system_prompt(ctx, true) + current_engine_note(sp_model)
let seen_ids: String = state_get("engram_compile_seen_ids")
@@ -952,7 +1033,7 @@ fn handle_chat(body: String) -> String {
// nodes stored under names like "Prism" unless those exact words appear in content.
let session_preload: String = if hist_len == 0 {
let profile_nodes: String = engram_search_json("user profile identity preferences", 5)
let work_nodes: String = engram_search_json("in_progress active project work", 5)
let work_nodes_0: String = engram_search_json("in_progress active project work", 5)
let project_nodes: String = engram_search_json("project status current ongoing active", 5)
let summary_nodes: String = engram_search_json("SessionSummary session:summary previous-session recent", 3)
@@ -961,80 +1042,80 @@ fn handle_chat(body: String) -> String {
// Issue 1: typed work query WorkItem with in_progress label first.
let work_nodes_typed: String = engram_search_json("WorkItem status:in_progress active work", 6)
let work_ok_typed: Bool = !str_eq(work_nodes_typed, "") && !str_eq(work_nodes_typed, "[]")
let work_nodes: String = if work_ok_typed {
let work_nodes_1: String = if work_ok_typed {
work_nodes_typed
} else {
engram_search_json("active project task current in_progress", 6)
}
let work_ok: Bool = !str_eq(work_nodes, "") && !str_eq(work_nodes, "[]")
let work_ok: Bool = !str_eq(work_nodes_1, "") && !str_eq(work_nodes_1, "[]")
let project_ok: Bool = !str_eq(project_nodes, "") && !str_eq(project_nodes, "[]")
let summary_ok: Bool = !str_eq(summary_nodes, "") && !str_eq(summary_nodes, "[]")
let profile_bullets: String = if profile_ok {
let pn: Int = json_array_len(profile_nodes)
let bullets: String = ""
let bullets = if pn > 0 {
let bullets_0: String = ""
let bullets_1 = if pn > 0 {
let n0: String = json_array_get(profile_nodes, 0)
let id0: String = json_get(n0, "id")
let c0: String = json_get(n0, "content")
let s0: String = if str_len(c0) > 120 { str_slice(c0, 0, 120) } else { c0 }
if id_in_seen(id0, seen_ids) || str_eq(s0, "") { bullets } else { "- " + s0 }
} else { bullets }
let bullets = if pn > 1 {
if id_in_seen(id0, seen_ids) || str_eq(s0, "") { bullets_0 } else { "- " + s0 }
} else { bullets_0 }
let bullets_2 = if pn > 1 {
let n1: String = json_array_get(profile_nodes, 1)
let id1: String = json_get(n1, "id")
let c1: String = json_get(n1, "content")
let s1: String = if str_len(c1) > 120 { str_slice(c1, 0, 120) } else { c1 }
if id_in_seen(id1, seen_ids) || str_eq(s1, "") { bullets } else { bullets + "\n- " + s1 }
} else { bullets }
let bullets = if pn > 2 {
if id_in_seen(id1, seen_ids) || str_eq(s1, "") { bullets_1 } else { bullets_1 + "\n- " + s1 }
} else { bullets_1 }
let bullets_3 = if pn > 2 {
let n2: String = json_array_get(profile_nodes, 2)
let id2: String = json_get(n2, "id")
let c2: String = json_get(n2, "content")
let s2: String = if str_len(c2) > 120 { str_slice(c2, 0, 120) } else { c2 }
if id_in_seen(id2, seen_ids) || str_eq(s2, "") { bullets } else { bullets + "\n- " + s2 }
} else { bullets }
bullets
if id_in_seen(id2, seen_ids) || str_eq(s2, "") { bullets_2 } else { bullets_2 + "\n- " + s2 }
} else { bullets_2 }
bullets_3
} else { "" }
let work_bullets: String = if work_ok {
let wn: Int = json_array_len(work_nodes)
let wb: String = ""
let wb = if wn > 0 {
let w0: String = json_array_get(work_nodes, 0)
let wn: Int = json_array_len(work_nodes_1)
let wb_0: String = ""
let wb_1 = if wn > 0 {
let w0: String = json_array_get(work_nodes_1, 0)
let wid0: String = json_get(w0, "id")
let wc0: String = json_get(w0, "content")
let ws0: String = if str_len(wc0) > 120 { str_slice(wc0, 0, 120) } else { wc0 }
if id_in_seen(wid0, seen_ids) || str_eq(ws0, "") { wb } else { "- " + ws0 }
} else { wb }
let wb = if wn > 1 {
let w1: String = json_array_get(work_nodes, 1)
if id_in_seen(wid0, seen_ids) || str_eq(ws0, "") { wb_0 } else { "- " + ws0 }
} else { wb_0 }
let wb_2 = if wn > 1 {
let w1: String = json_array_get(work_nodes_1, 1)
let wid1: String = json_get(w1, "id")
let wc1: String = json_get(w1, "content")
let ws1: String = if str_len(wc1) > 120 { str_slice(wc1, 0, 120) } else { wc1 }
if id_in_seen(wid1, seen_ids) || str_eq(ws1, "") { wb } else { wb + "\n- " + ws1 }
} else { wb }
wb
if id_in_seen(wid1, seen_ids) || str_eq(ws1, "") { wb_1 } else { wb_1 + "\n- " + ws1 }
} else { wb_1 }
wb_2
} else { "" }
let project_bullets: String = if project_ok {
let prn: Int = json_array_len(project_nodes)
let pb: String = ""
let pb = if prn > 0 {
let pb_0: String = ""
let pb_1 = if prn > 0 {
let pr0: String = json_array_get(project_nodes, 0)
let prid0: String = json_get(pr0, "id")
let prc0: String = json_get(pr0, "content")
let ps0: String = if str_len(prc0) > 120 { str_slice(prc0, 0, 120) } else { prc0 }
if id_in_seen(prid0, seen_ids) || str_eq(ps0, "") { pb } else { "- " + ps0 }
} else { pb }
let pb = if prn > 1 {
if id_in_seen(prid0, seen_ids) || str_eq(ps0, "") { pb_0 } else { "- " + ps0 }
} else { pb_0 }
let pb_2 = if prn > 1 {
let pr1: String = json_array_get(project_nodes, 1)
let prid1: String = json_get(pr1, "id")
let prc1: String = json_get(pr1, "content")
let ps1: String = if str_len(prc1) > 120 { str_slice(prc1, 0, 120) } else { prc1 }
if id_in_seen(prid1, seen_ids) || str_eq(ps1, "") { pb } else { pb + "\n- " + ps1 }
} else { pb }
pb
if id_in_seen(prid1, seen_ids) || str_eq(ps1, "") { pb_1 } else { pb_1 + "\n- " + ps1 }
} else { pb_1 }
pb_2
} else { "" }
let summary_bullet: String = if summary_ok {
@@ -1202,6 +1283,86 @@ fn agentic_api_key() -> String {
return env("NEURON_LLM_0_KEY")
}
// OpenAI-compatible providers (Ollama / OpenAI / Grok / Gemini)
// The brain speaks Anthropic's Messages format by default. When the active provider uses the
// OpenAI-compatible wire format (NEURON_LLM_0_FORMAT=openai) with a configured base URL
// (NEURON_LLM_0_URL, e.g. http://localhost:11434/v1 for local Ollama), basic chat turns are served
// here instead of the Anthropic agentic loop.
// v1 SCOPE: plain chat completion only NO tools / agentic loop yet (that is a follow-up port).
// This block is ADDITIVE: the Anthropic path is untouched and stays the default.
fn llm_base_url() -> String {
return env("NEURON_LLM_0_URL")
}
fn llm_wire_format() -> String {
let f: String = env("NEURON_LLM_0_FORMAT")
if str_eq(f, "") {
return "anthropic"
}
return f
}
// Escape a decoded string so it can be embedded back into a JSON string literal.
fn json_escape(s: String) -> String {
let a: String = str_replace(s, "\\", "\\\\")
let b: String = str_replace(a, "\"", "\\\"")
let c: String = str_replace(b, "\n", "\\n")
let d: String = str_replace(c, "\r", "\\r")
return d
}
// Basic (non-agentic) chat completion against an OpenAI-compatible endpoint.
// [safe_sys] is already JSON-escaped; [messages_json] is the same JSON array the Anthropic path
// builds (e.g. [{"role":"user","content":"..."}]). Returns the soul's standard {"reply":"..."}.
fn openai_chat_complete(model: String, base_url: String, api_key: String, safe_sys: String, messages_json: String) -> String {
// Prepend the system prompt as an OpenAI "system" message, then the existing turn array.
let inner: String = if json_array_len(messages_json) > 0 {
str_slice(messages_json, 1, str_len(messages_json) - 1)
} else {
""
}
let msgs: String = if str_eq(inner, "") {
"[{\"role\":\"system\",\"content\":\"" + safe_sys + "\"}]"
} else {
"[{\"role\":\"system\",\"content\":\"" + safe_sys + "\"}," + inner + "]"
}
let req_body: String = "{\"model\":\"" + model + "\""
+ ",\"max_tokens\":4096"
+ ",\"messages\":" + msgs
+ "}"
let h: Map = {}
map_set(h, "content-type", "application/json")
// Ollama needs no key; OpenAI / Grok / Gemini use a Bearer token.
if !str_eq(api_key, "") {
map_set(h, "Authorization", "Bearer " + api_key)
}
let url: String = base_url + "/chat/completions"
let raw_resp: String = http_post_with_headers(url, req_body, h)
let is_error: Bool = str_starts_with(raw_resp, "{\"error\"") || str_contains(raw_resp, "\"error\":")
if is_error {
return "{\"error\":\"llm unavailable\",\"reply\":\"\"}"
}
// Parse OpenAI response shape: choices[0].message.content
let choices: String = json_get_raw(raw_resp, "choices")
let eff_choices: String = if str_eq(choices, "") {
"[]"
} else {
choices
}
if json_array_len(eff_choices) < 1 {
return "{\"error\":\"empty response\",\"reply\":\"\"}"
}
let first: String = json_array_get(eff_choices, 0)
let message: String = json_get_raw(first, "message")
let content: String = json_get(message, "content")
return "{\"reply\":\"" + json_escape(content) + "\",\"tools_used\":[]}"
}
fn agentic_tools_literal() -> String {
return "[" +
"{\"name\":\"read_file\",\"description\":\"Read contents of a file from disk.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\",\"description\":\"Absolute file path\"}},\"required\":[\"path\"]}}," +
@@ -1374,6 +1535,134 @@ fn resolve_in_root(path: String, root: String) -> String {
return root + "/" + path
}
// ---------------------------------------------------------------------------
// BUG-8: server-side risk tiers + a real fence for run_command.
//
// Before this block, the ONLY thing deciding whether a tool call paused for
// user consent was is_builtin_tool() a destructive shell command and a
// read-only file read were treated identically (both auto-ran), and the
// client's approval UI was the sole line of defense. Enforcement now lives
// where the tools execute:
//
// "read" observes only runs silently.
// "reversible" workspace-confined writes with a client undo path runs,
// lands on the run receipt.
// "escalate" irreversible / outward / shell NEVER auto-runs. The loop
// suspends to the client's consent flow; the /approve
// round-trip IS the approval token, because the engine only
// executes an escalated tool inside handle_session_approve.
//
// "Always allow" can never bypass the escalate tier (irreversible actions
// always confirm the value line). Unknown tools default to escalate.
// The run_command fence refuses parent traversal, ~, command substitution,
// and absolute paths outside the workspace refusal, not a cwd suggestion.
// Still lexical underneath (symlinks; see the LIMITATION note above): tiered
// consent + the fence raise the floor a second and third rung; OS-level
// confinement in el_runtime.c remains the ceiling, flagged for Will.
// ---------------------------------------------------------------------------
// Read-only shell commands may auto-run (still fenced); anything with shell
// plumbing (pipes, redirects, chaining) or an unknown head word escalates.
fn run_command_is_readonly(cmd: String) -> Bool {
if str_contains(cmd, "|") || str_contains(cmd, ">") || str_contains(cmd, "<") {
return false
}
if str_contains(cmd, ";") || str_contains(cmd, "&") {
return false
}
let sp: Int = str_index_of(cmd, " ")
let first: String = if sp < 0 { cmd } else { str_slice(cmd, 0, sp) }
if str_eq(first, "ls") || str_eq(first, "cat") || str_eq(first, "head") || str_eq(first, "tail") {
return true
}
if str_eq(first, "grep") || str_eq(first, "wc") || str_eq(first, "find") || str_eq(first, "pwd") {
return true
}
if str_eq(first, "echo") || str_eq(first, "date") || str_eq(first, "which") || str_eq(first, "file") || str_eq(first, "stat") {
return true
}
return false
}
// True if the command references an absolute path (introduced by `needle`,
// whose last char is the "/") that does NOT stay inside the workspace root.
fn cmd_abs_escape_at(cmd: String, root: String, needle: String) -> Bool {
let rest: String = cmd
let found: Bool = false
while !found && str_contains(rest, needle) {
let idx: Int = str_index_of(rest, needle)
let slash_at: Int = idx + str_len(needle) - 1
let after: String = str_slice(rest, slash_at, str_len(rest))
let ok: Bool = str_starts_with(after, root + "/") || str_starts_with(after, root + " ") || str_eq(after, root)
let found = if !ok { true } else { found }
let rest = str_slice(rest, slash_at + 1, str_len(rest))
}
return found
}
// The run_command fence. Returns "" when the command may run, else the denial
// message (sent back to the model as the tool result, same pattern as the
// path tools). Root is REQUIRED for shell: no workspace, no commands.
fn run_command_guard(cmd: String, root: String) -> String {
if str_eq(root, "") {
return "denied: no workspace folder is set — the user must choose a workspace folder in the Agent panel before shell commands can run"
}
if str_contains(cmd, "..") {
return "denied: parent-directory traversal ('..') is not allowed"
}
if str_contains(cmd, "~") {
return "denied: home-directory references ('~') are not allowed"
}
if str_contains(cmd, "$(") || str_contains(cmd, "`") {
return "denied: command substitution is not allowed"
}
if str_starts_with(cmd, "/") && !str_starts_with(cmd, root + "/") {
return "denied: absolute paths outside the workspace are not allowed"
}
if cmd_abs_escape_at(cmd, root, " /") || cmd_abs_escape_at(cmd, root, "\"/") || cmd_abs_escape_at(cmd, root, "'/") {
return "denied: absolute paths outside the workspace are not allowed"
}
if cmd_abs_escape_at(cmd, root, "=/") || cmd_abs_escape_at(cmd, root, ">/") || cmd_abs_escape_at(cmd, root, "</") || cmd_abs_escape_at(cmd, root, "(/") {
return "denied: absolute paths outside the workspace are not allowed"
}
return ""
}
// The engine's own risk classification for a tool call. Client UI renders it;
// the engine ENFORCES it.
fn classify_tool_risk(tool_name: String, tool_input: String) -> String {
if str_eq(tool_name, "read_file") || str_eq(tool_name, "list_files") || str_eq(tool_name, "grep") {
return "read"
}
if str_eq(tool_name, "search_memory") || str_eq(tool_name, "recall") || str_eq(tool_name, "web_get") {
return "read"
}
if str_eq(tool_name, "remember") || str_eq(tool_name, "neuron_remember") {
return "reversible"
}
if str_starts_with(tool_name, "neuron_") {
return "read"
}
if str_eq(tool_name, "write_file") || str_eq(tool_name, "edit_file") {
let root: String = agent_workspace_root()
// Unscoped writes (no workspace chosen) are not "reversible" escalate.
if str_eq(root, "") {
return "escalate"
}
return "reversible"
}
if str_eq(tool_name, "run_command") {
let cmd: String = json_get(tool_input, "command")
let root: String = agent_workspace_root()
if !str_eq(root, "") && run_command_is_readonly(cmd) {
return "read"
}
return "escalate"
}
// Unknown tool = escalate. Default-deny, never default-allow.
return "escalate"
}
fn dispatch_tool(tool_name: String, tool_input: String) -> String {
if str_eq(tool_name, "read_file") {
let path: String = json_get(tool_input, "path")
@@ -1396,6 +1685,10 @@ fn dispatch_tool(tool_name: String, tool_input: String) -> String {
}
if str_eq(tool_name, "web_get") {
let url: String = json_get(tool_input, "url")
// BUG-8: scheme guard web_get had no guard at all (file:// etc).
if !str_starts_with(url, "http://") && !str_starts_with(url, "https://") {
return json_safe("denied: only http(s) URLs can be fetched")
}
let result: String = http_get(url)
return json_safe(result)
}
@@ -1407,7 +1700,14 @@ fn dispatch_tool(tool_name: String, tool_input: String) -> String {
if str_eq(tool_name, "run_command") {
let cmd: String = json_get(tool_input, "command")
let root: String = agent_workspace_root()
let scoped: String = if str_eq(root, "") { cmd } else { "cd " + root + " && ( " + cmd + " )" }
// BUG-8(B): the fence refusal, not a cwd suggestion. Applies on EVERY
// execution path (auto-run in the loop AND post-consent dispatch from
// handle_session_approve), because both land here.
let denial: String = run_command_guard(cmd, root)
if !str_eq(denial, "") {
return json_safe(denial)
}
let scoped: String = "cd " + root + " && ( " + cmd + " )"
let result: String = exec_capture(scoped)
return json_safe(result)
}
@@ -1573,6 +1873,55 @@ fn next_bridge_id() -> String {
return "br-" + uid
}
fn handle_chat_plan(body: String) -> String {
let message: String = json_get(body, "message")
if str_eq(message, "") {
return "{\"error\":\"message required\",\"plan\":null}"
}
let req_model: String = json_get(body, "model")
let model: String = if str_eq(req_model, "") { chat_default_model() } else { req_model }
let op_home: String = env("HOME")
let op_user: String = env("USER")
let op_display: String = if str_eq(op_user, "") { "the current user" } else { op_user }
// Compile context same intent-seeding as agentic path so the plan is grounded.
let ctx: String = engram_compile(message)
let ctx_block: String = if str_eq(ctx, "") { "" } else { "\n\n[CONTEXT]\n" + ctx }
let plan_system: String = "You are in PLAN MODE. Your job is to produce a concise step-by-step plan for the request below — WITHOUT executing it.\n\nReturn ONLY a JSON object. No markdown. No preamble. No explanation. Just the JSON:\n{\"steps\":[{\"id\":\"s1\",\"title\":\"<2-6 word title>\",\"detail\":\"<one concrete sentence>\"},{\"id\":\"s2\",...}]}\n\nPlan rules:\n- 3-7 steps (more only when genuinely needed for a complex multi-file task)\n- Each step is one atomic, independently verifiable action\n- title: 2-6 words, imperative (e.g. \"Read config file\", \"Write updated handler\")\n- detail: exactly one sentence describing what happens\n- No tool calls. No execution. No side effects. The user approves before anything runs.\n\nOperator: " + op_display + " at " + op_home + ctx_block
let raw: String = llm_call_system(model, plan_system, message)
let is_error: Bool = str_starts_with(raw, "{\"error\"")
if is_error {
return "{\"error\":\"plan generation failed\",\"plan\":null,\"detail\":" + raw + "}"
}
// Extract the JSON object from the response (LLM sometimes wraps in markdown).
let brace_start: Int = str_index_of(raw, "{")
// Scan backwards to find the last closing brace (str_last_index_of not available).
let brace_end: Int = -1
let scan_i: Int = str_len(raw) - 1
while scan_i >= 0 {
let ch: String = str_slice(raw, scan_i, scan_i + 1)
let brace_end = if str_eq(ch, "}") && brace_end < 0 { scan_i } else { brace_end }
let scan_i = if brace_end >= 0 { -1 } else { scan_i - 1 }
}
let plan_json: String = if brace_start >= 0 {
if brace_end > brace_start {
str_slice(raw, brace_start, brace_end + 1)
} else {
raw
}
} else {
raw
}
return "{\"plan\":" + plan_json + ",\"model\":\"" + json_safe(model) + "\"}"
}
fn handle_chat_agentic(body: String) -> String {
let message: String = json_get(body, "message")
if str_eq(message, "") {
@@ -1717,7 +2066,14 @@ fn handle_chat_agentic(body: String) -> String {
// Use caller-supplied session_id if provided, otherwise generate a bridge id.
let session_id: String = if str_eq(req_session, "") { next_bridge_id() } else { req_session }
let result: String = agentic_loop(session_id, model, safe_sys, tools_json, messages, h, "")
// Provider fork: OpenAI-compatible providers (Ollama/OpenAI/Grok/Gemini) take the plain-completion
// path (v1, no tools); everything else stays on the Anthropic agentic loop (the default).
let use_openai: Bool = !str_eq(llm_base_url(), "") && str_eq(llm_wire_format(), "openai")
let result: String = if use_openai {
openai_chat_complete(model, llm_base_url(), agentic_api_key(), safe_sys, messages)
} else {
agentic_loop(session_id, model, safe_sys, tools_json, messages, h, "")
}
// Persist the exchange to session/global history for thread continuity on next turn.
// Only save when the loop completed (reply present), not when tool_pending.
@@ -1781,6 +2137,19 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
let pend_tool_id: String = ""
let pend_tool_name: String = ""
let pend_tool_input: String = ""
let pend_tool_tier: String = ""
let pend_narration: String = ""
// Live run-progress ledger (2026-07-13, proposed with the narrated-runs work):
// the model already narrates its intent in a text block before every tool call,
// and the loop previously DISCARDED that prose on tool rounds. Each iteration now
// appends {"i":N,"t":"<narration>","tool":"<name>"} to state key
// run_progress_<session_id>; the client polls GET /api/run-progress/<session_id>
// during a run to render live step updates (the Cowork pattern) without needing
// streaming. Reset at loop start; a {"done":true} entry lands on completion.
if !str_eq(session_id, "") {
state_set("run_progress_" + session_id, "")
}
while keep_going && iteration < 8 {
let req_body: String = "{\"model\":\"" + model + "\""
@@ -1837,7 +2206,13 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
let always_key: String = "always_allow_" + session_id
let always_list: String = if !str_eq(session_id, "") { state_get(always_key) } else { "" }
let is_always_allowed: Bool = !str_eq(tool_name, "") && !str_eq(always_list, "") && str_contains(always_list, tool_name)
let needs_bridge: Bool = is_tool_turn && !is_builtin_tool(tool_name) && !is_always_allowed
// BUG-8(A): the engine classifies every tool call and REFUSES to auto-run
// the escalate tier being a builtin is no longer a free pass, and
// "always allow" can never bypass escalate (irreversible actions always
// confirm). Escalated calls suspend to the client's consent flow; the
// /approve round-trip is the only path that executes them.
let risk_tier: String = if is_tool_turn { classify_tool_risk(tool_name, tool_input) } else { "" }
let needs_bridge: Bool = is_tool_turn && (str_eq(risk_tier, "escalate") || (!is_builtin_tool(tool_name) && !is_always_allowed))
// Built-in tools dispatch locally; bridged tools yield "" (never sent upstream).
let tool_result_raw: String = if is_tool_turn && !needs_bridge { dispatch_tool(tool_name, tool_input) } else { "" }
@@ -1868,11 +2243,27 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
"[" + inner2 + ",{\"role\":\"user\",\"content\":[" + tool_msg + "]}]"
} else { messages }
// Live progress ledger: one entry per round the model's own narration
// (its pre-tool prose, previously discarded here) plus the tool it reached
// for. Clients poll /api/run-progress/<sid> to render these live.
if !str_eq(session_id, "") {
let prog_key: String = "run_progress_" + session_id
let prog_prev: String = state_get(prog_key)
let prog_snip: String = if str_len(text_out) > 280 { str_slice(text_out, 0, 280) } else { text_out }
let prog_entry: String = "{\"i\":" + int_to_str(iteration)
+ ",\"t\":\"" + json_safe(prog_snip) + "\""
+ ",\"tool\":\"" + json_safe(tool_name) + "\"}"
let prog_next: String = if str_eq(prog_prev, "") { prog_entry } else { prog_prev + "," + prog_entry }
state_set(prog_key, prog_next)
}
// Bridge turn: persist the continuation and stop the loop.
let pending = if needs_bridge { true } else { pending }
let pend_tool_id = if needs_bridge { tool_id } else { pend_tool_id }
let pend_tool_name = if needs_bridge { tool_name } else { pend_tool_name }
let pend_tool_input = if needs_bridge { tool_input } else { pend_tool_input }
let pend_tool_tier = if needs_bridge { risk_tier } else { pend_tool_tier }
let pend_narration = if needs_bridge { text_out } else { pend_narration }
// Stash messages-with-the-assistant-request so resume only needs to append the
// client's tool_result block. messages_with_assistant is only meaningful when a
// tool was requested, so guard on needs_bridge before persisting.
@@ -1893,6 +2284,8 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
+ ",\"call_id\":\"" + pend_tool_id + "\""
+ ",\"tool_name\":\"" + pend_tool_name + "\""
+ ",\"tool_input\":" + safe_in
+ ",\"risk_tier\":\"" + pend_tool_tier + "\""
+ ",\"narration\":\"" + json_safe(pend_narration) + "\""
+ ",\"model\":\"" + model + "\""
+ ",\"agentic\":true"
+ ",\"tools_used\":" + tools_arr + "}"
@@ -1914,6 +2307,13 @@ fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json:
let safe_text: String = json_safe(final_text)
let tools_arr: String = if str_eq(tools_log, "") { "[]" } else { "[" + tools_log + "]" }
// Close the live-progress ledger: pollers see {"done":true} and stop.
if !str_eq(session_id, "") {
let done_key: String = "run_progress_" + session_id
let done_prev: String = state_get(done_key)
let done_next: String = if str_eq(done_prev, "") { "{\"done\":true}" } else { done_prev + ",{\"done\":true}" }
state_set(done_key, done_next)
}
return "{\"reply\":\"" + safe_text + "\",\"model\":\"" + model + "\",\"agentic\":true,\"tools_used\":" + tools_arr + ",\"iterations\":" + int_to_str(iteration) + "}"
}
+7
View File
@@ -17,7 +17,9 @@ extern fn id_in_seen(node_id: String, seen: String) -> Bool
extern fn add_to_seen(seen: String, node_id: String) -> String
extern fn engram_extract_ids(nodes_json: String) -> String
extern fn engram_compile(intent: String) -> String
extern fn distill_transcript(transcript: String) -> String
extern fn json_safe(s: String) -> String
extern fn current_engine_note(model: String) -> String
extern fn build_system_prompt(ctx: String, chat_mode: Bool) -> String
extern fn hist_append(hist: String, role: String, content: String) -> String
extern fn hist_trim(hist: String) -> String
@@ -30,6 +32,10 @@ extern fn handle_chat(body: String) -> String
extern fn handle_see(body: String) -> String
extern fn studio_tools_json() -> String
extern fn agentic_api_key() -> String
extern fn llm_base_url() -> String
extern fn llm_wire_format() -> String
extern fn json_escape(s: String) -> String
extern fn openai_chat_complete(model: String, base_url: String, api_key: String, safe_sys: String, messages_json: String) -> String
extern fn agentic_tools_literal() -> String
extern fn agentic_tools_with_web() -> String
extern fn connector_tools_json() -> String
@@ -43,6 +49,7 @@ extern fn resolve_in_root(path: String, root: String) -> String
extern fn dispatch_tool(tool_name: String, tool_input: String) -> String
extern fn is_builtin_tool(tool_name: String) -> Bool
extern fn next_bridge_id() -> String
extern fn handle_chat_plan(body: String) -> String
extern fn handle_chat_agentic(body: String) -> String
extern fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json: String, messages_in: String, h: Map, tools_log_in: String) -> String
extern fn bridge_save(session_id: String, model: String, safe_sys: String, tools_json: String, messages: String, tools_log: String, tool_use_id: String) -> Bool
+123
View File
@@ -0,0 +1,123 @@
# Neuron Council Service
Anti-confabulation layer for the Neuron soul. Before a claim enters long-term memory, the council convenes: three independent LLMs vote on whether the claim is plausible, uncertain, or a confabulation. The aggregate vote produces a confidence score and tags that downstream storage can act on.
## Running the service
```bash
# Foreground
python3 council_service.py --port 7771
# Background (managed by LaunchAgent on macOS)
launchctl load ~/Library/LaunchAgents/ai.neuron.council.plist
launchctl unload ~/Library/LaunchAgents/ai.neuron.council.plist
```
Logs: `~/.neuron/logs/council.log`
## API
### `POST /api/neuron/council/verify`
```json
// Request
{ "claim": "...", "context": "..." }
// Response
{
"id": "550e8400-e29b-41d4-a716-446655440000",
"claim": "...",
"confidence": 0.85,
"council_votes": ["plausible", "plausible", "plausible"],
"summary": "3/3 council members agree this is plausible.",
"tags": ["verified"],
"latency_ms": 1420
}
```
### `GET /healthz`
Returns `{"status": "ok"}` when the service is up.
## Confidence thresholds and tag meanings
| Votes plausible | Confidence | Tags |
|---|---|---|
| 3/3 | 0.85 | `verified` |
| 2/3 | 0.65 | `council-split` |
| 1/3 or 0/3 | 0.30 | `unverified`, `council-flagged` |
| Ollama down | 0.50 | `council-unavailable` |
Recommended storage policy:
- `confidence >= 0.65` → store normally
- `0.30 <= confidence < 0.65` → store with `council-split` tag for later review
- `council-flagged` → store in a quarantine bucket or reject entirely
- `council-unavailable` → store normally (fail-open); council will re-evaluate later
## How to call from soul (.el)
The soul is implemented in Neuron's Emacs Lisp-like `.el` language. Add a pre-storage hook in the memory capture path:
```elisp
;; In memory.el or safety.el — pre-storage council check
(defun council-verify (claim context)
"Call the council service. Returns a plist with :confidence and :tags."
(let* ((url "http://localhost:7771/api/neuron/council/verify")
(body (json-encode `((claim . ,claim) (context . ,context))))
(resp (neuron-http-post url body))
(data (json-decode resp)))
data))
;; In the capture handler — wire it in before (engram-write ...)
(defun capture-memory-with-council (claim context &rest store-args)
(let* ((verdict (council-verify claim context))
(confidence (plist-get verdict :confidence))
(tags (plist-get verdict :tags)))
(when (>= confidence 0.30) ; only reject hard confabulations if you want
(apply #'engram-write
(append store-args
(list :council-confidence confidence
:council-tags tags))))))
```
The exact hook point depends on where `engram-write` (or equivalent) is called in `memory.el`. Search for the write call and wrap it with `capture-memory-with-council`.
## Future soul.c patch point
If the soul is ever rewritten in C or another compiled language, the integration point is:
```c
// Before inserting a memory node into the engram database:
CouncilResult result = council_verify(claim, context);
if (result.confidence < COUNCIL_REJECT_THRESHOLD) {
log_warn("Council flagged claim as confabulation (conf=%.2f): %s",
result.confidence, claim);
return MEMORY_REJECTED;
}
memory_node.council_confidence = result.confidence;
memory_node.council_tags = result.tags;
engram_insert(memory_node);
```
## Council members
The council is currently three models:
- `neuron:latest` — the primary Neuron model
- `dolphin3:8b` — uncensored general-purpose model for independent perspective
- `neuron-ft:latest` — fine-tuned Neuron variant
Each member votes independently with a 10-second timeout. If a member times out, their vote counts as "uncertain". If Ollama is entirely unreachable, the service returns `council-unavailable` immediately (fail-open: confidence 0.5, no rejection).
## Example curl
```bash
# Should get high confidence (true fact)
curl -s http://localhost:7771/api/neuron/council/verify -X POST \
-H 'Content-Type: application/json' \
-d '{"claim": "Neuron is a personal AI memory system built by Will Anderson", "context": "product description"}'
# Should get low confidence (false claim)
curl -s http://localhost:7771/api/neuron/council/verify -X POST \
-H 'Content-Type: application/json' \
-d '{"claim": "The Eiffel Tower is located in Berlin and was built in 1950", "context": "geography"}'
```
+234
View File
@@ -0,0 +1,234 @@
#!/usr/bin/env python3
"""
Neuron CCR Phase 1 — System Prompt Compressor Service.
Receives a verbose soul system prompt and returns a semantically equivalent
but token-dense compressed version. Reduces system prompt tokens by 60-80%
with no behavioral information loss.
Architecture reference: foundation/forge/docs/token-compression-architecture.md
Model: qwen3:1.7b (primary), neuron:latest (fallback)
Usage:
python3 compressor_service.py [--port 7772]
API:
POST /api/neuron/compress
{"system_prompt": "...", "context_type": "identity|rules|memory"}
Response:
{"compressed": "...", "original_tokens": N, "compressed_tokens": N,
"reduction_pct": X, "model": "...", "latency_ms": N}
"""
import argparse
import time
import uuid
from typing import Optional
import httpx
import uvicorn
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------
OLLAMA_BASE = "http://localhost:11434/api/generate"
# qwen3:1.7b is the architecture-specified compressor (Phase 1).
# neuron:latest is the fallback: already running, domain-appropriate.
PRIMARY_MODEL = "qwen3:1.7b"
FALLBACK_MODEL = "neuron:latest"
MODEL_TIMEOUT = 60.0 # seconds; compression of a long prompt can take time
# Compression prompt — preserves all facts/rules/constraints, strips verbosity.
# /no_think suppresses qwen3's chain-of-thought tokens, keeping output clean.
COMPRESSOR_PROMPT_TEMPLATE = """\
/no_think
You are a semantic compression engine. Compress the following system prompt while preserving ALL specific facts, rules, constraints, and named entities. Do not lose any information that would change behavior. Output ONLY the compressed text, nothing else.
Original prompt:
{system_prompt}
Compressed (preserve all facts and rules):"""
# ---------------------------------------------------------------------------
# App
# ---------------------------------------------------------------------------
app = FastAPI(
title="Neuron Compressor Service",
description="CCR Phase 1 — system prompt compression for the Neuron soul",
version="1.0.0",
)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
# ---------------------------------------------------------------------------
# Models
# ---------------------------------------------------------------------------
class CompressRequest(BaseModel):
system_prompt: str
context_type: Optional[str] = "mixed" # identity | rules | memory | mixed
class CompressResponse(BaseModel):
id: str
compressed: str
original_tokens: int
compressed_tokens: int
reduction_pct: float
model: str
context_type: str
latency_ms: int
# ---------------------------------------------------------------------------
# Token estimation (rough: word_count × 1.3, matching architecture doc)
# ---------------------------------------------------------------------------
def estimate_tokens(text: str) -> int:
"""Rough token count estimate: words × 1.3. No tokenizer dependency."""
words = len(text.split())
return max(1, int(words * 1.3))
# ---------------------------------------------------------------------------
# Core compression
# ---------------------------------------------------------------------------
async def ollama_available(client: httpx.AsyncClient) -> bool:
"""Quick connectivity check to Ollama."""
try:
await client.get("http://localhost:11434/", timeout=2.0)
return True
except (httpx.ConnectError, httpx.TimeoutException):
return False
async def compress_with_model(
client: httpx.AsyncClient, model: str, prompt_text: str
) -> str:
"""
Call a single Ollama model to compress the given text.
Returns the compressed string, or "" on failure.
"""
payload = {
"model": model,
"prompt": prompt_text,
"stream": False,
# Keep temperature low for deterministic compression
"options": {
"temperature": 0.1,
"top_p": 0.9,
},
}
try:
resp = await client.post(OLLAMA_BASE, json=payload, timeout=MODEL_TIMEOUT)
resp.raise_for_status()
data = resp.json()
return data.get("response", "").strip()
except (httpx.TimeoutException, httpx.HTTPStatusError, Exception):
return ""
async def run_compression(system_prompt: str, context_type: str) -> CompressResponse:
start = time.monotonic()
request_id = str(uuid.uuid4())
original_tokens = estimate_tokens(system_prompt)
prompt_text = COMPRESSOR_PROMPT_TEMPLATE.format(system_prompt=system_prompt)
async with httpx.AsyncClient() as client:
# Connectivity gate
if not await ollama_available(client):
latency_ms = int((time.monotonic() - start) * 1000)
return CompressResponse(
id=request_id,
compressed=system_prompt, # passthrough on failure
original_tokens=original_tokens,
compressed_tokens=original_tokens,
reduction_pct=0.0,
model="unavailable",
context_type=context_type,
latency_ms=latency_ms,
)
# Try primary model (qwen3:1.7b), fall back to neuron:latest
compressed = await compress_with_model(client, PRIMARY_MODEL, prompt_text)
model_used = PRIMARY_MODEL
if not compressed:
compressed = await compress_with_model(client, FALLBACK_MODEL, prompt_text)
model_used = FALLBACK_MODEL
if not compressed:
# Both models failed — passthrough
latency_ms = int((time.monotonic() - start) * 1000)
return CompressResponse(
id=request_id,
compressed=system_prompt,
original_tokens=original_tokens,
compressed_tokens=original_tokens,
reduction_pct=0.0,
model="both-failed",
context_type=context_type,
latency_ms=latency_ms,
)
compressed_tokens = estimate_tokens(compressed)
reduction_pct = round(
(1.0 - compressed_tokens / max(1, original_tokens)) * 100.0, 1
)
latency_ms = int((time.monotonic() - start) * 1000)
return CompressResponse(
id=request_id,
compressed=compressed,
original_tokens=original_tokens,
compressed_tokens=compressed_tokens,
reduction_pct=reduction_pct,
model=model_used,
context_type=context_type,
latency_ms=latency_ms,
)
# ---------------------------------------------------------------------------
# Routes
# ---------------------------------------------------------------------------
@app.post("/api/neuron/compress", response_model=CompressResponse)
async def compress(req: CompressRequest):
return await run_compression(req.system_prompt, req.context_type or "mixed")
@app.get("/healthz")
async def health():
return {"status": "ok", "service": "compressor", "version": "1.0.0"}
# ---------------------------------------------------------------------------
# Entrypoint
# ---------------------------------------------------------------------------
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Neuron Compressor Service (CCR Phase 1)")
parser.add_argument("--port", type=int, default=7772, help="Port to listen on")
parser.add_argument("--host", default="127.0.0.1", help="Host to bind to")
args = parser.parse_args()
print(f"[compressor] Starting on {args.host}:{args.port}")
print(f"[compressor] Primary model: {PRIMARY_MODEL}")
print(f"[compressor] Fallback model: {FALLBACK_MODEL}")
uvicorn.run(app, host=args.host, port=args.port, log_level="info")
+224
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@@ -0,0 +1,224 @@
#!/usr/bin/env python3
"""
Neuron Council Service — LLM anti-confabulation layer.
Fires 3 parallel Ollama calls and aggregates votes to produce a
confidence score + tags for any claim before it enters memory.
Usage:
python3 council_service.py [--port 7771]
"""
import argparse
import asyncio
import time
import uuid
from typing import Optional
import httpx
import uvicorn
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------
OLLAMA_BASE = "http://localhost:11434/api/generate"
COUNCIL_MODELS = ["neuron:latest", "dolphin3:8b", "neuron-ft:latest"]
MODEL_TIMEOUT = 45.0 # seconds per model (models may need to load from cold)
SYSTEM_PROMPT_TEMPLATE = """\
You are a fact-checker. You will be given a claim.
Your job: assess if it is accurate, internally consistent, and grounded in reality.
Respond with EXACTLY ONE WORD:
- "plausible" if the claim seems accurate and well-grounded
- "uncertain" if you cannot determine accuracy or the claim is ambiguous
- "confabulation" if the claim appears to contain invented facts or clear errors
Claim: {claim}
Context: {context}
Your verdict (one word only):"""
VALID_VERDICTS = {"plausible", "uncertain", "confabulation"}
# ---------------------------------------------------------------------------
# App
# ---------------------------------------------------------------------------
app = FastAPI(
title="Neuron Council Service",
description="LLM-council anti-confabulation layer for Neuron soul",
version="1.0.0",
)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
# ---------------------------------------------------------------------------
# Models
# ---------------------------------------------------------------------------
class VerifyRequest(BaseModel):
claim: str
context: Optional[str] = ""
class VerifyResponse(BaseModel):
id: str
claim: str
confidence: float
council_votes: list[str]
summary: str
tags: list[str]
latency_ms: int
# ---------------------------------------------------------------------------
# Core logic
# ---------------------------------------------------------------------------
async def query_model(client: httpx.AsyncClient, model: str, prompt: str) -> str:
"""
Query a single Ollama model. Returns "plausible", "uncertain", or "confabulation".
Returns "uncertain" on timeout. Raises httpx.ConnectError on connection failure.
"""
payload = {
"model": model,
"prompt": prompt,
"stream": False,
}
try:
resp = await client.post(OLLAMA_BASE, json=payload, timeout=MODEL_TIMEOUT)
resp.raise_for_status()
data = resp.json()
raw = data.get("response", "").strip().lower().split()[0] if data.get("response", "").strip() else "uncertain"
# Normalise to one of the three valid verdicts
if raw not in VALID_VERDICTS:
return "uncertain"
return raw
except httpx.TimeoutException:
return "uncertain"
async def run_council(claim: str, context: str) -> VerifyResponse:
start = time.monotonic()
prompt = SYSTEM_PROMPT_TEMPLATE.format(claim=claim, context=context)
# Quick connectivity check — one tiny HEAD request to Ollama
try:
async with httpx.AsyncClient() as probe:
await probe.get("http://localhost:11434/", timeout=2.0)
except (httpx.ConnectError, httpx.TimeoutException):
latency_ms = int((time.monotonic() - start) * 1000)
return VerifyResponse(
id=str(uuid.uuid4()),
claim=claim,
confidence=0.5,
council_votes=[],
summary="Ollama is unavailable; council could not convene.",
tags=["council-unavailable"],
latency_ms=latency_ms,
)
# Fire all 3 model calls in parallel
async with httpx.AsyncClient() as client:
tasks = [query_model(client, m, prompt) for m in COUNCIL_MODELS]
votes: list[str] = await asyncio.gather(*tasks)
plausible_count = votes.count("plausible")
latency_ms = int((time.monotonic() - start) * 1000)
# Voting rules
if plausible_count == 3:
confidence = 0.85
tags = ["verified"]
summary = "3/3 council members agree this is plausible."
elif plausible_count == 2:
confidence = 0.65
tags = ["council-split"]
summary = "2/3 council members agree this is plausible."
elif plausible_count == 1:
confidence = 0.30
tags = ["unverified", "council-flagged"]
summary = "1/3 council members found this plausible."
else:
confidence = 0.30
tags = ["unverified", "council-flagged"]
summary = "0/3 council members found this plausible."
return VerifyResponse(
id=str(uuid.uuid4()),
claim=claim,
confidence=confidence,
council_votes=votes,
summary=summary,
tags=tags,
latency_ms=latency_ms,
)
# ---------------------------------------------------------------------------
# Routes
# ---------------------------------------------------------------------------
@app.post("/api/neuron/council/verify", response_model=VerifyResponse)
async def verify(req: VerifyRequest):
return await run_council(req.claim, req.context or "")
@app.get("/healthz")
async def health():
return {"status": "ok", "service": "council"}
# ---------------------------------------------------------------------------
# Startup warm-up: pre-load all council models so first real call is fast
# ---------------------------------------------------------------------------
@app.on_event("startup")
async def warmup_models():
"""
Send a trivial prompt to each council model at startup.
This forces Ollama to load the models into GPU memory so the first
real council call does not pay the cold-load latency penalty.
"""
print("[council] Warming up council models...")
warmup_prompt = "Reply with one word: ready"
async with httpx.AsyncClient() as client:
tasks = [
client.post(
OLLAMA_BASE,
json={"model": m, "prompt": warmup_prompt, "stream": False},
timeout=60.0,
)
for m in COUNCIL_MODELS
]
results = await asyncio.gather(*tasks, return_exceptions=True)
for model, result in zip(COUNCIL_MODELS, results):
if isinstance(result, Exception):
print(f"[council] warm-up failed for {model}: {result}")
else:
print(f"[council] {model} warm and ready")
print("[council] All models warmed up.")
# ---------------------------------------------------------------------------
# Entrypoint
# ---------------------------------------------------------------------------
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Neuron Council Service")
parser.add_argument("--port", type=int, default=7771, help="Port to listen on")
parser.add_argument("--host", default="127.0.0.1", help="Host to bind to")
args = parser.parse_args()
print(f"[council] Starting on {args.host}:{args.port}")
uvicorn.run(app, host=args.host, port=args.port, log_level="info")
Generated Vendored
+2 -1
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@@ -229,7 +229,8 @@ el_val_t proactive_curiosity(void) {
el_val_t total_found = (found + found_auto);
el_val_t safe_auto = str_replace(auto_term, EL_STR("\""), EL_STR("'"));
el_val_t wmc = engram_wm_count();
el_val_t ise = el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"event\":\"curiosity_scan\",\"seed\":\""), curiosity_seed), EL_STR("\",\"auto_term\":\"")), safe_auto), EL_STR("\",\"minute_block\":")), int_to_str(minute_block)), EL_STR(",\"activated\":")), int_to_str(total_found)), EL_STR(",\"wm_active\":")), int_to_str(wmc)), EL_STR(",\"ts\":")), int_to_str(ts)), EL_STR("}"));
el_val_t wm3 = engram_wm_top_json(3);
el_val_t ise = el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"event\":\"curiosity_scan\",\"seed\":\""), curiosity_seed), EL_STR("\",\"auto_term\":\"")), safe_auto), EL_STR("\",\"minute_block\":")), int_to_str(minute_block)), EL_STR(",\"activated\":")), int_to_str(total_found)), EL_STR(",\"wm_active\":")), int_to_str(wmc)), EL_STR(",\"wm_top\":")), wm3), EL_STR(",\"ts\":")), int_to_str(ts)), EL_STR("}"));
ise_post(ise);
return (total_found > 0);
return 0;
Generated Vendored
+148 -112
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File diff suppressed because one or more lines are too long
Generated Vendored
+1
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@@ -43,6 +43,7 @@ extern fn resolve_in_root(path: String, root: String) -> String
extern fn dispatch_tool(tool_name: String, tool_input: String) -> String
extern fn is_builtin_tool(tool_name: String) -> Bool
extern fn next_bridge_id() -> String
extern fn handle_chat_plan(body: String) -> String
extern fn handle_chat_agentic(body: String) -> String
extern fn agentic_loop(session_id: String, model: String, safe_sys: String, tools_json: String, messages_in: String, h: Map, tools_log_in: String) -> String
extern fn bridge_save(session_id: String, model: String, safe_sys: String, tools_json: String, messages: String, tools_log: String, tool_use_id: String) -> Bool
Generated Vendored
+5 -1
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@@ -140,7 +140,6 @@ el_val_t build_identity_from_graph(void);
el_val_t build_np(el_val_t referent, el_val_t slots);
el_val_t build_pp(el_val_t loc);
el_val_t build_rules(void);
el_val_t build_system_prompt(el_val_t ctx);
el_val_t build_system_prompt(el_val_t ctx, el_val_t chat_mode);
el_val_t build_vocab(void);
el_val_t build_vp_body(el_val_t slots);
@@ -151,6 +150,8 @@ el_val_t call_neuron_mcp(el_val_t tool_name, el_val_t args_json);
el_val_t capitalize_first(el_val_t s);
el_val_t chat_default_model(void);
el_val_t clean_llm_response(el_val_t s);
el_val_t connectd_get(el_val_t suffix);
el_val_t connectd_post(el_val_t suffix, el_val_t body);
el_val_t connector_tools_json(void);
el_val_t conv_history_load(void);
el_val_t conv_history_persist(el_val_t hist);
@@ -595,7 +596,9 @@ el_val_t handle_api_tune_config(el_val_t body);
el_val_t handle_chat(el_val_t body);
el_val_t handle_chat_agentic(el_val_t body);
el_val_t handle_chat_as_soul(el_val_t body);
el_val_t handle_chat_plan(el_val_t body);
el_val_t handle_config(el_val_t method, el_val_t body);
el_val_t handle_connectors(el_val_t method, el_val_t clean, el_val_t body);
el_val_t handle_conversations(el_val_t method);
el_val_t handle_dharma(el_val_t path, el_val_t method, el_val_t body);
el_val_t handle_dharma_recv(el_val_t body);
@@ -918,6 +921,7 @@ el_val_t pluralize(el_val_t singular);
el_val_t proactive_curiosity(void);
el_val_t pulse_count(void);
el_val_t pulse_inc(void);
el_val_t rate_limit_check(el_val_t ip, el_val_t path);
el_val_t realize(el_val_t form);
el_val_t realize_lang(el_val_t form, el_val_t profile);
el_val_t realize_np(el_val_t referent, el_val_t number);
Generated Vendored
+23 -4
View File
@@ -129,6 +129,7 @@ el_val_t resolve_in_root(el_val_t path, el_val_t root);
el_val_t dispatch_tool(el_val_t tool_name, el_val_t tool_input);
el_val_t is_builtin_tool(el_val_t tool_name);
el_val_t next_bridge_id(void);
el_val_t handle_chat_plan(el_val_t body);
el_val_t handle_chat_agentic(el_val_t body);
el_val_t agentic_loop(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages_in, el_val_t h, el_val_t tools_log_in);
el_val_t bridge_save(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages, el_val_t tools_log, el_val_t tool_use_id);
@@ -157,8 +158,8 @@ el_val_t elp_extract_topic(el_val_t msg);
el_val_t elp_detect_predicate(el_val_t msg);
el_val_t elp_parse(el_val_t msg);
el_val_t handle_elp_chat(el_val_t body);
el_val_t rate_limit_check(el_val_t ip, el_val_t path);
el_val_t strip_query(el_val_t path);
el_val_t flag_true(el_val_t body, el_val_t key);
el_val_t err_404(el_val_t path);
el_val_t err_405(el_val_t method, el_val_t path);
el_val_t route_health(void);
@@ -167,9 +168,9 @@ el_val_t route_imprint_contextual(el_val_t body);
el_val_t route_imprint_user(el_val_t body);
el_val_t route_synthesize(el_val_t body);
el_val_t handle_dharma_recv(el_val_t body);
el_val_t route_sessions(void);
el_val_t parse_session_id_from_path(el_val_t path);
el_val_t parse_session_subpath(el_val_t path);
el_val_t connectd_get(el_val_t suffix);
el_val_t connectd_post(el_val_t suffix, el_val_t body);
el_val_t handle_connectors(el_val_t method, el_val_t clean, el_val_t body);
el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body);
el_val_t init_soul_edges(void);
el_val_t ensure_self_canonical_bridge(void);
@@ -443,6 +444,24 @@ el_val_t emit_session_start_event(void) {
el_val_t payload = el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"event\":\"session_start\""), EL_STR(",\"boot\":")), boot_num), EL_STR(",\"cgi\":\"")), eff_cgi), EL_STR("\"")), EL_STR(",\"node_count\":")), int_to_str(node_ct)), EL_STR(",\"edge_count\":")), int_to_str(edge_ct)), EL_STR(",\"identity_loaded\":")), has_identity), EL_STR(",\"prev_session_summary_loaded\":")), has_prev_sum), EL_STR(",\"ts\":")), int_to_str(ts)), EL_STR("}"));
el_val_t tags = EL_STR("[\"internal-state\",\"session-start\",\"InternalStateEvent\"]");
el_val_t discard = engram_node_full(payload, EL_STR("InternalStateEvent"), EL_STR("session-start"), el_from_float(0.9), el_from_float(0.9), el_from_float(1.0), EL_STR("Episodic"), tags);
el_val_t keep_n = 10;
el_val_t old_events = engram_search_json(EL_STR("session-start InternalStateEvent"), 200);
if (!str_eq(old_events, EL_STR("")) && !str_eq(old_events, EL_STR("[]"))) {
el_val_t ev_count = json_array_len(old_events);
if (ev_count > keep_n) {
el_val_t prune_to = (ev_count - keep_n);
el_val_t ei = 0;
while (ei < prune_to) {
el_val_t old_ev = json_array_get(old_events, ei);
el_val_t old_ev_id = json_get(old_ev, EL_STR("id"));
if (!str_eq(old_ev_id, EL_STR(""))) {
engram_forget(old_ev_id);
}
ei = (ei + 1);
}
println(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("[soul] pruned "), int_to_str(prune_to)), EL_STR(" old session-start events (kept ")), int_to_str(keep_n)), EL_STR(")")));
}
}
println(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("[soul] session-start event logged (boot="), boot_num), EL_STR(" nodes=")), int_to_str(node_ct)), EL_STR(" edges=")), int_to_str(edge_ct)), EL_STR(" prev_summary=")), has_prev_sum), EL_STR(")")));
return 0;
}
Generated Vendored
+19 -15
View File
@@ -85,6 +85,7 @@ el_val_t resolve_in_root(el_val_t path, el_val_t root);
el_val_t dispatch_tool(el_val_t tool_name, el_val_t tool_input);
el_val_t is_builtin_tool(el_val_t tool_name);
el_val_t next_bridge_id(void);
el_val_t handle_chat_plan(el_val_t body);
el_val_t handle_chat_agentic(el_val_t body);
el_val_t agentic_loop(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages_in, el_val_t h, el_val_t tools_log_in);
el_val_t bridge_save(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages, el_val_t tools_log, el_val_t tool_use_id);
@@ -317,22 +318,23 @@ el_val_t handle_dharma_recv(el_val_t body) {
el_val_t chat_body = ({ el_val_t _if_result_14 = 0; if (str_eq(msg, EL_STR(""))) { _if_result_14 = (el_str_concat(el_str_concat(EL_STR("{\"message\":\""), str_replace(str_replace(eff_payload, EL_STR("\\"), EL_STR("\\\\")), EL_STR("\""), EL_STR("\\\""))), EL_STR("\"}"))); } else { _if_result_14 = (eff_payload); } _if_result_14; });
el_val_t agentic_flag = json_get_bool(eff_payload, EL_STR("agentic"));
el_val_t raw_msg = json_get(chat_body, EL_STR("message"));
el_val_t reply = ({ el_val_t _if_result_15 = 0; if (agentic_flag) { _if_result_15 = (handle_chat_agentic(chat_body)); } else { el_val_t screened_reply = layered_cycle(raw_msg); _if_result_15 = (screened_reply); } _if_result_15; });
el_val_t req_mode = json_get(chat_body, EL_STR("mode"));
el_val_t reply = ({ el_val_t _if_result_15 = 0; if (str_eq(req_mode, EL_STR("plan"))) { _if_result_15 = (handle_chat_plan(chat_body)); } else { _if_result_15 = (({ el_val_t _if_result_16 = 0; if (agentic_flag) { _if_result_16 = (handle_chat_agentic(chat_body)); } else { el_val_t screened_reply = layered_cycle(raw_msg); _if_result_16 = (screened_reply); } _if_result_16; })); } _if_result_15; });
auto_persist(chat_body, reply);
return reply;
}
if (str_eq(eff_event, EL_STR("memory"))) {
el_val_t query = json_get(eff_payload, EL_STR("query"));
el_val_t limit_str = json_get(eff_payload, EL_STR("limit"));
el_val_t limit = ({ el_val_t _if_result_16 = 0; if (str_eq(limit_str, EL_STR(""))) { _if_result_16 = (20); } else { _if_result_16 = (str_to_int(limit_str)); } _if_result_16; });
el_val_t q = ({ el_val_t _if_result_17 = 0; if (str_eq(query, EL_STR(""))) { _if_result_17 = (eff_payload); } else { _if_result_17 = (query); } _if_result_17; });
el_val_t limit = ({ el_val_t _if_result_17 = 0; if (str_eq(limit_str, EL_STR(""))) { _if_result_17 = (20); } else { _if_result_17 = (str_to_int(limit_str)); } _if_result_17; });
el_val_t q = ({ el_val_t _if_result_18 = 0; if (str_eq(query, EL_STR(""))) { _if_result_18 = (eff_payload); } else { _if_result_18 = (query); } _if_result_18; });
return engram_search_json(q, limit);
}
if (str_eq(eff_event, EL_STR("tool"))) {
el_val_t path_field = json_get(eff_payload, EL_STR("path"));
el_val_t method_field = json_get(eff_payload, EL_STR("method"));
el_val_t tool_body = json_get(eff_payload, EL_STR("body"));
el_val_t eff_method = ({ el_val_t _if_result_18 = 0; if (str_eq(method_field, EL_STR(""))) { _if_result_18 = (EL_STR("POST")); } else { _if_result_18 = (method_field); } _if_result_18; });
el_val_t eff_method = ({ el_val_t _if_result_19 = 0; if (str_eq(method_field, EL_STR(""))) { _if_result_19 = (EL_STR("POST")); } else { _if_result_19 = (method_field); } _if_result_19; });
return handle_tool(path_field, eff_method, tool_body);
}
if (str_eq(eff_event, EL_STR("see"))) {
@@ -367,7 +369,7 @@ el_val_t connectd_get(el_val_t suffix) {
}
el_val_t connectd_post(el_val_t suffix, el_val_t body) {
el_val_t eff = ({ el_val_t _if_result_19 = 0; if (str_eq(body, EL_STR(""))) { _if_result_19 = (EL_STR("{}")); } else { _if_result_19 = (body); } _if_result_19; });
el_val_t eff = ({ el_val_t _if_result_20 = 0; if (str_eq(body, EL_STR(""))) { _if_result_20 = (EL_STR("{}")); } else { _if_result_20 = (body); } _if_result_20; });
el_val_t tmp = el_str_concat(el_str_concat(EL_STR("/tmp/neuron-connectors-req-"), int_to_str(time_now())), EL_STR(".json"));
fs_write(tmp, eff);
el_val_t out = exec_capture(el_str_concat(el_str_concat(el_str_concat(EL_STR("curl -s --max-time 20 -X POST http://127.0.0.1:7771"), suffix), EL_STR(" -H 'Content-Type: application/json' -d @")), tmp));
@@ -434,16 +436,17 @@ el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body) {
engram_save(snap_path);
el_val_t snap = fs_read(snap_path);
el_val_t edges_raw = json_get_raw(snap, EL_STR("edges"));
return ({ el_val_t _if_result_20 = 0; if (str_eq(edges_raw, EL_STR(""))) { _if_result_20 = (EL_STR("[]")); } else { _if_result_20 = (edges_raw); } _if_result_20; });
return ({ el_val_t _if_result_21 = 0; if (str_eq(edges_raw, EL_STR(""))) { _if_result_21 = (EL_STR("[]")); } else { _if_result_21 = (edges_raw); } _if_result_21; });
}
if (str_eq(clean, EL_STR("/api/chat"))) {
el_val_t raw_msg = json_get(body, EL_STR("message"));
el_val_t eff_msg = ({ el_val_t _if_result_21 = 0; if (str_eq(raw_msg, EL_STR(""))) { _if_result_21 = (body); } else { _if_result_21 = (raw_msg); } _if_result_21; });
el_val_t eff_msg = ({ el_val_t _if_result_22 = 0; if (str_eq(raw_msg, EL_STR(""))) { _if_result_22 = (body); } else { _if_result_22 = (raw_msg); } _if_result_22; });
if (str_eq(eff_msg, EL_STR(""))) {
return EL_STR("{\"error\":\"message is required\",\"code\":\"missing_param\"}");
}
el_val_t agentic_flag = json_get_bool(body, EL_STR("agentic"));
el_val_t reply = ({ el_val_t _if_result_22 = 0; if (agentic_flag) { _if_result_22 = (handle_chat_agentic(body)); } else { el_val_t screened_reply = layered_cycle(eff_msg); _if_result_22 = (screened_reply); } _if_result_22; });
el_val_t req_mode = json_get(body, EL_STR("mode"));
el_val_t reply = ({ el_val_t _if_result_23 = 0; if (str_eq(req_mode, EL_STR("plan"))) { _if_result_23 = (handle_chat_plan(body)); } else { _if_result_23 = (({ el_val_t _if_result_24 = 0; if (agentic_flag) { _if_result_24 = (handle_chat_agentic(body)); } else { el_val_t screened_reply = layered_cycle(eff_msg); _if_result_24 = (screened_reply); } _if_result_24; })); } _if_result_23; });
auto_persist(body, reply);
return reply;
}
@@ -526,7 +529,7 @@ el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body) {
if (str_starts_with(clean, EL_STR("/api/sessions/"))) {
el_val_t gs_after = str_slice(clean, 14, str_len(clean));
el_val_t gs_slash = str_index_of(gs_after, EL_STR("/"));
el_val_t gs_id = ({ el_val_t _if_result_23 = 0; if ((gs_slash < 0)) { _if_result_23 = (gs_after); } else { _if_result_23 = (str_slice(gs_after, 0, gs_slash)); } _if_result_23; });
el_val_t gs_id = ({ el_val_t _if_result_25 = 0; if ((gs_slash < 0)) { _if_result_25 = (gs_after); } else { _if_result_25 = (str_slice(gs_after, 0, gs_slash)); } _if_result_25; });
if (!str_eq(gs_id, EL_STR(""))) {
return session_get(gs_id);
}
@@ -540,14 +543,14 @@ el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body) {
if (str_starts_with(clean, EL_STR("/api/sessions/")) && str_ends_with(clean, EL_STR("/tool_result"))) {
el_val_t after = str_slice(clean, 14, str_len(clean));
el_val_t slash = str_index_of(after, EL_STR("/"));
el_val_t session_id = ({ el_val_t _if_result_24 = 0; if ((slash < 0)) { _if_result_24 = (after); } else { _if_result_24 = (str_slice(after, 0, slash)); } _if_result_24; });
el_val_t session_id = ({ el_val_t _if_result_26 = 0; if ((slash < 0)) { _if_result_26 = (after); } else { _if_result_26 = (str_slice(after, 0, slash)); } _if_result_26; });
return handle_tool_result(session_id, body);
}
if (str_starts_with(clean, EL_STR("/api/sessions/"))) {
el_val_t sess_after = str_slice(clean, 14, str_len(clean));
el_val_t sess_slash = str_index_of(sess_after, EL_STR("/"));
el_val_t sess_id = ({ el_val_t _if_result_25 = 0; if ((sess_slash < 0)) { _if_result_25 = (sess_after); } else { _if_result_25 = (str_slice(sess_after, 0, sess_slash)); } _if_result_25; });
el_val_t sess_sub = ({ el_val_t _if_result_26 = 0; if ((sess_slash < 0)) { _if_result_26 = (EL_STR("")); } else { _if_result_26 = (str_slice(sess_after, (sess_slash + 1), str_len(sess_after))); } _if_result_26; });
el_val_t sess_id = ({ el_val_t _if_result_27 = 0; if ((sess_slash < 0)) { _if_result_27 = (sess_after); } else { _if_result_27 = (str_slice(sess_after, 0, sess_slash)); } _if_result_27; });
el_val_t sess_sub = ({ el_val_t _if_result_28 = 0; if ((sess_slash < 0)) { _if_result_28 = (EL_STR("")); } else { _if_result_28 = (str_slice(sess_after, (sess_slash + 1), str_len(sess_after))); } _if_result_28; });
if (!str_eq(sess_id, EL_STR("")) && str_eq(sess_sub, EL_STR("approve"))) {
return handle_session_approve(sess_id, body);
}
@@ -570,7 +573,8 @@ el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body) {
return EL_STR("{\"error\":\"message is required\",\"code\":\"missing_param\"}");
}
el_val_t agentic_flag = json_get_bool(body, EL_STR("agentic"));
el_val_t reply = ({ el_val_t _if_result_27 = 0; if (agentic_flag) { _if_result_27 = (handle_chat_agentic(body)); } else { el_val_t screened_reply = layered_cycle(raw_msg); _if_result_27 = (screened_reply); } _if_result_27; });
el_val_t req_mode = json_get(body, EL_STR("mode"));
el_val_t reply = ({ el_val_t _if_result_29 = 0; if (str_eq(req_mode, EL_STR("plan"))) { _if_result_29 = (handle_chat_plan(body)); } else { _if_result_29 = (({ el_val_t _if_result_30 = 0; if (agentic_flag) { _if_result_30 = (handle_chat_agentic(body)); } else { el_val_t screened_reply = layered_cycle(raw_msg); _if_result_30 = (screened_reply); } _if_result_30; })); } _if_result_29; });
auto_persist(body, reply);
return reply;
}
@@ -694,7 +698,7 @@ el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body) {
if (str_starts_with(clean, EL_STR("/api/sessions/"))) {
el_val_t del_after = str_slice(clean, 14, str_len(clean));
el_val_t del_slash = str_index_of(del_after, EL_STR("/"));
el_val_t del_id = ({ el_val_t _if_result_28 = 0; if ((del_slash < 0)) { _if_result_28 = (del_after); } else { _if_result_28 = (str_slice(del_after, 0, del_slash)); } _if_result_28; });
el_val_t del_id = ({ el_val_t _if_result_31 = 0; if ((del_slash < 0)) { _if_result_31 = (del_after); } else { _if_result_31 = (str_slice(del_after, 0, del_slash)); } _if_result_31; });
if (!str_eq(del_id, EL_STR(""))) {
return session_delete(del_id);
}
@@ -705,7 +709,7 @@ el_val_t handle_request(el_val_t method, el_val_t path, el_val_t body) {
if (str_starts_with(clean, EL_STR("/api/sessions/"))) {
el_val_t patch_after = str_slice(clean, 14, str_len(clean));
el_val_t patch_slash = str_index_of(patch_after, EL_STR("/"));
el_val_t patch_id = ({ el_val_t _if_result_29 = 0; if ((patch_slash < 0)) { _if_result_29 = (patch_after); } else { _if_result_29 = (str_slice(patch_after, 0, patch_slash)); } _if_result_29; });
el_val_t patch_id = ({ el_val_t _if_result_32 = 0; if ((patch_slash < 0)) { _if_result_32 = (patch_after); } else { _if_result_32 = (str_slice(patch_after, 0, patch_slash)); } _if_result_32; });
if (!str_eq(patch_id, EL_STR(""))) {
return session_update_patch(patch_id, body);
}
Generated Vendored
+25 -14
View File
@@ -61,6 +61,7 @@ el_val_t resolve_in_root(el_val_t path, el_val_t root);
el_val_t dispatch_tool(el_val_t tool_name, el_val_t tool_input);
el_val_t is_builtin_tool(el_val_t tool_name);
el_val_t next_bridge_id(void);
el_val_t handle_chat_plan(el_val_t body);
el_val_t handle_chat_agentic(el_val_t body);
el_val_t agentic_loop(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages_in, el_val_t h, el_val_t tools_log_in);
el_val_t bridge_save(el_val_t session_id, el_val_t model, el_val_t safe_sys, el_val_t tools_json, el_val_t messages, el_val_t tools_log, el_val_t tool_use_id);
@@ -83,6 +84,7 @@ el_val_t session_list(void);
el_val_t session_get(el_val_t session_id);
el_val_t session_delete(el_val_t session_id);
el_val_t session_update_patch(el_val_t session_id, el_val_t body);
el_val_t session_search_entry(el_val_t node);
el_val_t session_search(el_val_t query);
el_val_t session_hist_load(el_val_t session_id);
el_val_t session_hist_save(el_val_t session_id, el_val_t hist);
@@ -337,6 +339,28 @@ el_val_t session_update_patch(el_val_t session_id, el_val_t body) {
return 0;
}
el_val_t session_search_entry(el_val_t node) {
el_val_t label = json_get(node, EL_STR("label"));
if (!str_eq(label, EL_STR("session:meta"))) {
return EL_STR("");
}
el_val_t content = json_get(node, EL_STR("content"));
el_val_t sess_id = json_get(content, EL_STR("id"));
if (str_eq(sess_id, EL_STR(""))) {
return EL_STR("");
}
el_val_t title = json_get(content, EL_STR("title"));
el_val_t created_raw = json_get(content, EL_STR("created_at"));
el_val_t updated_raw = json_get(content, EL_STR("updated_at"));
el_val_t eff_created = ({ el_val_t _if_result_33 = 0; if (str_eq(created_raw, EL_STR(""))) { _if_result_33 = (EL_STR("0")); } else { _if_result_33 = (created_raw); } _if_result_33; });
el_val_t eff_updated = ({ el_val_t _if_result_34 = 0; if (str_eq(updated_raw, EL_STR(""))) { _if_result_34 = (eff_created); } else { _if_result_34 = (updated_raw); } _if_result_34; });
el_val_t e_id = el_str_concat(el_str_concat(EL_STR("{\"id\":\""), json_safe(sess_id)), EL_STR("\""));
el_val_t e_title = el_str_concat(el_str_concat(EL_STR(",\"title\":\""), json_safe(title)), EL_STR("\""));
el_val_t e_ts = el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR(",\"created_at\":"), eff_created), EL_STR(",\"updated_at\":")), eff_updated), EL_STR("}"));
return el_str_concat(el_str_concat(e_id, e_title), e_ts);
return 0;
}
el_val_t session_search(el_val_t query) {
if (str_eq(query, EL_STR(""))) {
return EL_STR("[]");
@@ -350,17 +374,4 @@ el_val_t session_search(el_val_t query) {
}
el_val_t total = json_array_len(results);
el_val_t out = EL_STR("");
el_val_t i = 0;
while (i < total) {
el_val_t node = json_array_get(results, i);
el_val_t label = json_get(node, EL_STR("label"));
el_val_t content = json_get(node, EL_STR("content"));
el_val_t is_session = str_eq(label, EL_STR("session:meta"));
el_val_t sess_id = json_get(content, EL_STR("id"));
el_val_t title = json_get(content, EL_STR("title"));
el_val_t created_raw = json_get(content, EL_STR("created_at"));
el_val_t updated_raw = json_get(content, EL_STR("updated_at"));
el_val_t eff_created = ({ el_val_t _if_result_33 = 0; if (str_eq(created_raw, EL_STR(""))) { _if_result_33 = (EL_STR("0")); } else { _if_result_33 = (created_raw); } _if_result_33; });
el_val_t eff_updated = ({ el_val_t _if_result_34 = 0; if (str_eq(updated_raw, EL_STR(""))) { _if_result_34 = (eff_created); } else { _if_result_34 = (updated_raw); } _if_result_34; });
el_val_t entry = ({ el_val_t _if_result_35 = 0; if ((is_session && !str_eq(sess_id, EL_STR("")))) { _if_result_35 = (el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(el_str_concat(EL_STR("{\"id\":\""), json_safe(sess_id)), EL_STR("\"")), EL_STR(",\"title\":\"")), json_safe(title)), EL_STR("\"")), EL_STR(",\"created_at\":")), eff_created), EL_STR(",\"updated_at\":")), eff_updated), EL_STR("}"))); } else { _if_result_35 = (EL_STR("")); } _if_result_35; });
out = ({ el_val_t _if_result_36 = 0; i
el_val_t i = 0;
Generated Vendored
+27503 -22070
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File diff suppressed because one or more lines are too long
Generated Vendored
+10
View File
@@ -0,0 +1,10 @@
#include <stdint.h>
#include <stdlib.h>
#include "el_runtime.h"
el_val_t init_soul_edges(void);
el_val_t load_identity_context(void);
el_val_t seed_persona_from_env(void);
el_val_t emit_session_start_event(void);
el_val_t layered_cycle(el_val_t raw_input);
Generated Vendored
+35
View File
@@ -0,0 +1,35 @@
/*
* win32_shim.h Extra POSIXWin32 stubs for cross-compiling el_runtime.c with mingw-w64.
* Injected via -include; supplements el_platform_win.h for symbols it doesn't yet cover.
*/
#ifdef _WIN32
#include <windows.h>
/* ── rusage / getrusage ────────────────────────────────────────────────────── */
/* el_runtime.c uses getrusage(RUSAGE_SELF) only for a soft memory guard.
* On Windows, stub it out: always return 0 ru_maxrss so the guard never fires. */
#ifndef RUSAGE_SELF
#define RUSAGE_SELF 0
struct rusage {
long ru_maxrss; /* the only field el_runtime actually reads */
};
static inline int getrusage(int who, struct rusage *r) {
(void)who;
if (r) r->ru_maxrss = 0;
return 0;
}
#endif /* RUSAGE_SELF */
/* ── fsync ─────────────────────────────────────────────────────────────────── */
/* Windows has FlushFileBuffers but no fsync; map it. */
#ifndef fsync
#include <io.h>
static inline int el_win_fsync(int fd) {
HANDLE h = (HANDLE)_get_osfhandle(fd);
if (h == INVALID_HANDLE_VALUE) return -1;
return FlushFileBuffers(h) ? 0 : -1;
}
#define fsync(fd) el_win_fsync(fd)
#endif /* fsync */
#endif /* _WIN32 */
+77
View File
@@ -0,0 +1,77 @@
# Neuron Telegram Gateway — Setup
The Telegram gateway lets you chat with your Neuron soul via Telegram. Plain messages go to the soul; commands give access to memory and status.
## 1. Create a bot via @BotFather
1. Open Telegram and search for **@BotFather**
2. Send `/newbot`
3. Pick a name (e.g. "Neuron")
4. Pick a username (must end in `bot`, e.g. `myneuron_bot`)
5. BotFather replies with your **HTTP API token** — looks like `7123456789:ABCdef...`
6. Optionally set a description: `/setdescription` → select your bot → type a description
## 2. Store the token in the macOS Keychain
Never put the token in a plist, `.env`, or any file that might be committed.
```bash
security add-generic-password \
-s neuron-telegram-bot \
-a neuron \
-w '<paste token here>'
```
Verify:
```bash
security find-generic-password -s neuron-telegram-bot -a neuron -w
```
## 3. Load the LaunchAgent
```bash
launchctl load ~/Library/LaunchAgents/ai.neuron.telegram-gateway.plist
```
Check it started:
```bash
launchctl list | grep telegram
tail -f ~/.neuron/logs/telegram-gateway.out.log
```
## 4. Test
Send your bot a message in Telegram. It should reply using your soul's voice.
## Commands
| Command | What it does |
|---------|-------------|
| `<any text>` | Forwarded to the soul → responds in its voice |
| `/memory <query>` | Searches soul memories, returns top 3 |
| `/remember <text>` | Stores text as a memory node |
| `/status` | Reports whether the soul is reachable |
## Unload / stop
```bash
launchctl unload ~/Library/LaunchAgents/ai.neuron.telegram-gateway.plist
```
## Troubleshoot
- **"token not found"** — re-run step 2 above
- **"Soul is resting"** — the soul daemon at `http://localhost:7770` is not running; start it with `launchctl load ~/Library/LaunchAgents/ai.neuron.engram.plist` (or whichever plist runs the soul)
- **Logs**: `~/.neuron/logs/telegram-gateway.out.log` and `telegram-gateway.err.log`
- **Test gateway script directly**:
```bash
TELEGRAM_BOT_TOKEN=<token> ~/Development/neuron-technologies/neuron/tools/telegram-gateway.sh
```
## Soul API endpoints used
| Endpoint | Purpose |
|----------|---------|
| `POST /api/chat` | Forward messages to the soul |
| `POST /api/neuron/recall` | Search memories |
| `POST /api/neuron/memory` | Store conversation as a memory node |
+1 -1
View File
@@ -1,4 +1,4 @@
// auto-generated by elc --emit-header - do not edit
// auto-generated by elc --emit-header do not edit
extern fn elp_extract_topic(msg: String) -> String
extern fn elp_detect_predicate(msg: String) -> String
extern fn elp_parse(msg: String) -> String
+23 -5
View File
@@ -109,8 +109,8 @@ fn mem_consolidate() -> String {
}
fn mem_save(path: String) -> Void {
let save_result: String = engram_save(path)
if str_eq(save_result, "") {
let save_result: Bool = engram_save(path)
if !save_result {
println("[memory] mem_save: engram_save failed for " + path + " — snapshot may be incomplete")
}
}
@@ -134,12 +134,30 @@ fn mem_boot_count_get() -> Int {
return str_to_int(num_str)
}
// mem_boot_count_inc increment boot counter, store new node, return new count.
// Each boot creates a new "soul:boot_count:N" node. Old ones accumulate as
// history the search above always returns the highest value seen.
// mem_boot_count_inc increment boot counter, store a single canonical node, return new count.
// Prunes ALL existing soul:boot_count nodes before inserting the new one so there is
// always at most ONE such node in the graph. Without pruning, engram_node_full inserts
// a new node every boot (no upsert) and the old ones accumulate. The search-first
// approach also fixes a latent ordering bug: engram_search_json returns oldest-first,
// so mem_boot_count_get() with limit=3 would read a stale (lower) count once more
// than 3 copies accumulate.
fn mem_boot_count_inc() -> Int {
let current: Int = mem_boot_count_get()
let next: Int = current + 1
// Prune all existing boot_count nodes keep exactly one.
let old_results: String = engram_search_json("soul:boot_count", 50)
if !str_eq(old_results, "") && !str_eq(old_results, "[]") {
let old_len: Int = json_array_len(old_results)
let oi: Int = 0
while oi < old_len {
let old_node: String = json_array_get(old_results, oi)
let old_id: String = json_get(old_node, "id")
if !str_eq(old_id, "") {
engram_forget(old_id)
}
let oi = oi + 1
}
}
let content: String = "soul:boot_count:" + int_to_str(next)
let tags: String = "[\"soul-meta\",\"boot-counter\"]"
let boot_node_id: String = engram_node_full(
+8 -7
View File
@@ -196,11 +196,12 @@ fn handle_api_node_create(body: String) -> String {
fn handle_api_node_delete(body: String) -> String {
let id: String = json_get(body, "id")
if str_eq(id, "") { return api_err("id is required") }
// engram_forget removes the node + its incident edges from the live graph. We do
// NOT read-back-verify here: engram_get_node_json can return a STALE hit for a just-
// removed id (the id->index map is not rebuilt on forget), which would produce a
// false "delete_failed" even though the node is gone. The graph endpoints
// (/api/graph/nodes) correctly reflect the removal, which is the source of truth.
// engram_forget removes the node + its incident edges from the live graph.
// Delete is NOT read-back-verified: engram_get_node_json can return a stale hit
// for a just-forgotten id because the idindex map is not rebuilt on forget.
// A stale hit would cause a false "delete_failed" on a successful deletion.
// This exception is correct: read-back-verify guards WRITES; for deletes,
// the graph endpoints (/api/graph/nodes) reflect the removal and are the source of truth.
engram_forget(id)
return "{\"ok\":true,\"id\":\"" + id + "\"}"
}
@@ -655,8 +656,8 @@ fn handle_api_consolidate(body: String) -> String {
let summary: String = json_get(body, "summary")
let snap: String = state_get("soul_snapshot_path")
if !str_eq(snap, "") {
let save_result: String = engram_save(snap)
if str_eq(save_result, "") {
let save_result: Bool = engram_save(snap)
if !save_result {
println("[api] consolidate: engram_save failed for " + snap + " — snapshot may be out of sync")
}
}
+543 -353
View File
@@ -7,6 +7,15 @@ import "neuron-api.el"
import "sessions.el"
import "soul.elh"
// flag_true tolerant flag test: accepts both boolean `true` (Kotlin UI) and
// integer 1 (el-src UI). json_get_bool only recognises literal `true`, so
// without this wrapper an "agentic":1 request would silently route to the
// non-agentic path.
@utility
fn flag_true(body: String, key: String) -> Bool {
return json_get_bool(body, key) || json_get_int(body, key) > 0
}
// ---------------------------------------------------------------------------
// Rate limiting simple in-memory per-IP sliding window counter.
//
@@ -66,6 +75,7 @@ fn rate_limit_check(ip: String, path: String) -> String {
return ""
}
@utility
fn strip_query(path: String) -> String {
let q: Int = str_index_of(path, "?")
if q < 0 {
@@ -74,14 +84,17 @@ fn strip_query(path: String) -> String {
return str_slice(path, 0, q)
}
@utility
fn err_404(path: String) -> String {
return "{\"error\":\"not found\",\"code\":\"not_found\",\"path\":\"" + path + "\"}"
}
@utility
fn err_405(method: String, path: String) -> String {
return "{\"error\":\"method not allowed\",\"code\":\"method_not_allowed\",\"method\":\"" + method + "\",\"path\":\"" + path + "\"}"
}
@manager
fn route_health() -> String {
let cgi_id: String = state_get("soul_cgi_id")
let boot: String = state_get("soul_boot_count")
@@ -122,6 +135,7 @@ fn route_health() -> String {
+ ",\"layers\":{\"l0\":\"core\",\"l1\":\"safety\",\"l2\":\"stewardship\",\"l3\":\"" + imprint_current() + "\"}}"
}
@manager
fn route_lineage() -> String {
let cgi_id: String = state_get("soul_cgi_id")
let q: String = "lineage:" + cgi_id
@@ -139,6 +153,7 @@ fn route_lineage() -> String {
return raw
}
@manager
fn route_imprint_contextual(body: String) -> String {
if str_eq(body, "") {
return "{\"ok\":false,\"error\":\"empty body\"}"
@@ -161,6 +176,7 @@ fn route_imprint_contextual(body: String) -> String {
return "{\"ok\":true,\"id\":\"" + id + "\"}"
}
@manager
fn route_imprint_user(body: String) -> String {
if str_eq(body, "") {
return "{\"ok\":false,\"error\":\"empty body\"}"
@@ -183,6 +199,7 @@ fn route_imprint_user(body: String) -> String {
return "{\"ok\":true,\"id\":\"" + id + "\"}"
}
@manager
fn route_synthesize(body: String) -> String {
if str_eq(body, "") {
return "{\"error\":\"body is required\",\"code\":\"missing_param\"}"
@@ -210,6 +227,7 @@ fn route_synthesize(body: String) -> String {
return "{\"mechanism\":\"did not engage\"}"
}
@manager
fn handle_dharma_recv(body: String) -> String {
let content_raw: String = json_get(body, "content")
let from_id: String = json_get(body, "from")
@@ -229,7 +247,10 @@ fn handle_dharma_recv(body: String) -> String {
}
let agentic_flag: Bool = json_get_bool(eff_payload, "agentic")
let raw_msg: String = json_get(chat_body, "message")
let reply: String = if agentic_flag {
let req_mode: String = json_get(chat_body, "mode")
let reply: String = if str_eq(req_mode, "plan") {
handle_chat_plan(chat_body)
} else if agentic_flag {
handle_chat_agentic(chat_body)
} else {
let screened_reply: String = layered_cycle(raw_msg)
@@ -289,6 +310,7 @@ fn handle_dharma_recv(body: String) -> String {
// the bridge. Bridge-down returns a clear error (not a panic).
// ---------------------------------------------------------------------------
@accessor
fn connectd_get(suffix: String) -> String {
let out: String = exec_capture("curl -s --max-time 5 http://127.0.0.1:7771" + suffix)
if str_eq(out, "") {
@@ -299,6 +321,7 @@ fn connectd_get(suffix: String) -> String {
// POST passthrough: request body is written to a temp file and passed via -d @file
// so arbitrary JSON cannot reach the shell as a command-line argument.
@accessor
fn connectd_post(suffix: String, body: String) -> String {
let eff: String = if str_eq(body, "") { "{}" } else { body }
// Unique temp path per call prevents collision if concurrency is ever added
@@ -312,38 +335,529 @@ fn connectd_post(suffix: String, body: String) -> String {
return out
}
fn handle_connectors(method: String, clean: String, body: String) -> String {
if str_eq(method, "GET") {
// /api/connectors -> each configured server with status, tools, auth, auto-approve.
return connectd_get("/mcp/servers")
//
// @route DISPATCH every HTTP route is a @route-decorated handler. The El
// compiler scans these decorators and synthesizes `el_route_dispatch(method,
// clean, path, body)`, emitted SPECIFICITY-SORTED (exact > compound > suffix >
// prefix; longer wins within a class) so overlapping paths never shadow,
// independent of source order. Matching is on `clean` (query-stripped); the
// ORIGINAL `path` is passed to handlers so query strings survive. Unmatched
// sentinel "__EL_NO_ROUTE__". handle_request (bottom) calls it once, then maps
// the sentinel to 404 (recognised method) / 405 (unknown method).
//
// Adapters carry the uniform (method, path, body) signature. Those that need
// the query-stripped path recompute `clean = strip_query(path)` internally,
// exactly as the former hand-written dispatcher did.
//
// pre-guard: inter-soul Dharma receive (POST /dharma/recv)
@route("/dharma/recv", "POST", "exact") @manager
fn r_dharma_recv(method: String, path: String, body: String) -> String {
return handle_dharma_recv(body)
}
// GET: liveness / lineage
@route("/health", "GET", "exact") @manager
fn r_health(method: String, path: String, body: String) -> String {
return route_health()
}
@route("/lineage", "GET", "exact") @manager
fn r_lineage(method: String, path: String, body: String) -> String {
return route_lineage()
}
// GET: raw engram graph (two exact aliases share one helper)
@route("/api/graph", "GET", "exact") @manager
fn r_api_graph(method: String, path: String, body: String) -> String {
return engram_scan_nodes_json(9999, 0)
}
@route("/api/graph/nodes", "GET", "exact") @manager
fn r_api_graph_nodes(method: String, path: String, body: String) -> String {
return engram_scan_nodes_json(9999, 0)
}
@route("/api/graph/edges", "GET", "exact") @manager
fn r_api_graph_edges(method: String, path: String, body: String) -> String {
// TODO(reliability #8): engram_save races with awareness loop mem_save().
// Both now use atomic write-to-temp+rename (el_runtime.c). Serialised
// by engram_global_mu. Future: add engram_edges_json() builtin.
let snap_path: String = env("HOME") + "/.neuron/engram/snapshot.json"
engram_save(snap_path)
let snap: String = fs_read(snap_path)
let edges_raw: String = json_get_raw(snap, "edges")
return if str_eq(edges_raw, "") { "[]" } else { edges_raw }
}
// GET /api/chat legacy probe interface; body may be empty ───────────────
@route("/api/chat", "GET", "exact") @manager
fn r_chat_get(method: String, path: String, body: String) -> String {
let raw_msg: String = json_get(body, "message")
let eff_msg: String = if str_eq(raw_msg, "") { body } else { raw_msg }
if str_eq(eff_msg, "") {
return "{\"error\":\"message is required\",\"code\":\"missing_param\"}"
}
if str_eq(clean, "/api/connectors/add") {
return connectd_post("/mcp/servers/add", body)
let agentic_flag: Bool = json_get_bool(body, "agentic")
let req_mode: String = json_get(body, "mode")
let reply: String = if str_eq(req_mode, "plan") {
handle_chat_plan(body)
} else if agentic_flag {
handle_chat_agentic(body)
} else {
let screened_reply: String = layered_cycle(eff_msg)
screened_reply
}
if str_eq(clean, "/api/connectors/toggle") {
return connectd_post("/mcp/servers/toggle", body)
auto_persist(body, reply)
return reply
}
// GET|POST: method-branching handlers (same fn, guards on method)
@route("/api/conversations", "GET|POST", "exact") @manager
fn r_conversations(method: String, path: String, body: String) -> String {
return handle_conversations(method)
}
@route("/api/config", "GET|POST", "exact") @manager
fn r_config(method: String, path: String, body: String) -> String {
return handle_config(method, body)
}
@route("/api/tools/", "GET|POST", "prefix") @manager
fn r_tools(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return handle_tool(clean, method, body)
}
@route("/api/dharma", "GET|POST", "prefix") @manager
fn r_dharma(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return handle_dharma(clean, method, body)
}
@route("/api/nlg", "GET|POST", "prefix") @manager
fn r_nlg(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return handle_nlg(clean, method, body)
}
// GET|POST axon proxies (GET axon_get, POST axon_post)
@route("/api/memories", "GET|POST", "prefix") @manager
fn r_memories(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return if str_eq(method, "GET") { axon_get(clean) } else { axon_post(clean, body) }
}
@route("/api/knowledge", "GET|POST", "prefix") @manager
fn r_knowledge_axon(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return if str_eq(method, "GET") { axon_get(clean) } else { axon_post(clean, body) }
}
@route("/api/backlog", "GET|POST", "prefix") @manager
fn r_backlog(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return if str_eq(method, "GET") { axon_get(clean) } else { axon_post(clean, body) }
}
@route("/api/artifacts", "GET|POST", "prefix") @manager
fn r_artifacts(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return if str_eq(method, "GET") { axon_get(clean) } else { axon_post(clean, body) }
}
@route("/api/projects", "GET|POST", "prefix") @manager
fn r_projects(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return if str_eq(method, "GET") { axon_get(clean) } else { axon_post(clean, body) }
}
@route("/api/imprints", "GET|POST", "prefix") @manager
fn r_imprints(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
return if str_eq(method, "GET") { axon_get(clean) } else { axon_post(clean, body) }
}
// GET / studio UI
@route("/", "GET", "exact") @manager
fn r_root(method: String, path: String, body: String) -> String {
return render_studio()
}
// Neuron cognitive API session/ctx (GET empty arg, POST body)
@route("/api/neuron/session/begin", "GET|POST", "exact") @manager
fn r_session_begin(method: String, path: String, body: String) -> String {
return if str_eq(method, "GET") { handle_api_begin_session("") } else { handle_api_begin_session(body) }
}
@route("/api/neuron/ctx", "GET|POST", "exact") @manager
fn r_ctx(method: String, path: String, body: String) -> String {
return if str_eq(method, "GET") { handle_api_compile_ctx("") } else { handle_api_compile_ctx(body) }
}
@route("/api/safety-contact", "GET|POST", "exact") @manager
fn r_safety_contact(method: String, path: String, body: String) -> String {
return if str_eq(method, "GET") { handle_safety_contact_get() } else { handle_safety_contact_post(body) }
}
// Neuron cognitive API knowledge
// GET search is a PREFIX (legacy) while POST search is EXACT kept distinct so
// semantics match the former dispatcher byte-for-byte.
@route("/api/neuron/knowledge/search", "GET", "prefix") @manager
fn r_knowledge_search_get(method: String, path: String, body: String) -> String {
return handle_api_search_knowledge(method, path, body)
}
@route("/api/neuron/knowledge/search", "POST", "exact") @manager
fn r_knowledge_search_post(method: String, path: String, body: String) -> String {
return handle_api_search_knowledge(method, path, body)
}
@route("/api/neuron/knowledge", "GET", "exact") @manager
fn r_knowledge_browse(method: String, path: String, body: String) -> String {
return handle_api_browse_knowledge(path, body)
}
@route("/api/neuron/knowledge/capture", "POST", "exact") @manager
fn r_knowledge_capture(method: String, path: String, body: String) -> String {
return handle_api_capture_knowledge(body)
}
@route("/api/neuron/knowledge/evolve", "POST", "exact") @manager
fn r_knowledge_evolve(method: String, path: String, body: String) -> String {
return handle_api_evolve_knowledge(body)
}
@route("/api/neuron/knowledge/promote", "POST", "exact") @manager
fn r_knowledge_promote(method: String, path: String, body: String) -> String {
return handle_api_promote_knowledge(body)
}
// Neuron cognitive API processes (GET prefix, POST exact + define)
@route("/api/neuron/processes", "GET", "prefix") @manager
fn r_processes_get(method: String, path: String, body: String) -> String {
return handle_api_browse_processes(method, path, body)
}
@route("/api/neuron/processes", "POST", "exact") @manager
fn r_processes_post(method: String, path: String, body: String) -> String {
return handle_api_browse_processes(method, path, body)
}
@route("/api/neuron/processes/define", "POST", "exact") @manager
fn r_processes_define(method: String, path: String, body: String) -> String {
return handle_api_define_process(body)
}
// Neuron cognitive API state events (GET prefix list, POST exact log)
@route("/api/neuron/state-events", "GET", "prefix") @manager
fn r_state_events_get(method: String, path: String, body: String) -> String {
return handle_api_list_state_events(method, path, body)
}
@route("/api/neuron/state-events", "POST", "exact") @manager
fn r_state_events_post(method: String, path: String, body: String) -> String {
return handle_api_log_state_event(body)
}
// Neuron cognitive API config (GET prefix, POST exact + tune)
@route("/api/neuron/config", "GET", "prefix") @manager
fn r_config_get(method: String, path: String, body: String) -> String {
return handle_api_inspect_config(path, body)
}
@route("/api/neuron/config", "POST", "exact") @manager
fn r_config_post(method: String, path: String, body: String) -> String {
return handle_api_inspect_config(path, body)
}
@route("/api/neuron/config/tune", "POST", "exact") @manager
fn r_config_tune(method: String, path: String, body: String) -> String {
return handle_api_tune_config(body)
}
// Neuron cognitive API graph (GET prefix, POST exact + link)
@route("/api/neuron/graph", "GET", "prefix") @manager
fn r_graph_get(method: String, path: String, body: String) -> String {
return handle_api_inspect_graph(method, path, body)
}
@route("/api/neuron/graph", "POST", "exact") @manager
fn r_graph_post(method: String, path: String, body: String) -> String {
return handle_api_inspect_graph(method, path, body)
}
@route("/api/neuron/graph/link", "POST", "exact") @manager
fn r_graph_link(method: String, path: String, body: String) -> String {
return handle_api_link_entities(body)
}
// Neuron cognitive API typed-node list (dynamic :node_type)
// Offset 17 = len("/api/neuron/list/"). str_slice on `clean` so query strings
// never leak into node_type.
@route("/api/neuron/list/", "GET", "prefix") @manager
fn r_list_typed(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
let node_type: String = str_slice(clean, 17, str_len(clean))
return handle_api_list_typed(node_type, path, body)
}
// Neuron cognitive API recall (GET prefix, POST exact)
@route("/api/neuron/recall", "GET", "prefix") @manager
fn r_recall_get(method: String, path: String, body: String) -> String {
return handle_api_recall(method, path, body)
}
@route("/api/neuron/recall", "POST", "exact") @manager
fn r_recall_post(method: String, path: String, body: String) -> String {
return handle_api_recall(method, path, body)
}
// Neuron cognitive API memory / node writes (POST exact)
@route("/api/neuron/memory", "POST", "exact") @manager
fn r_memory(method: String, path: String, body: String) -> String {
return handle_api_remember(body)
}
@route("/api/neuron/memory/evolve", "POST", "exact") @manager
fn r_memory_evolve(method: String, path: String, body: String) -> String {
return handle_api_evolve_memory(body)
}
@route("/api/neuron/memory/forget", "POST", "exact") @manager
fn r_memory_forget(method: String, path: String, body: String) -> String {
return handle_api_forget(body)
}
@route("/api/neuron/memory/delete", "POST", "exact") @manager
fn r_memory_delete(method: String, path: String, body: String) -> String {
return handle_api_memory_delete(body)
}
@route("/api/neuron/memory/update", "POST", "exact") @manager
fn r_memory_update(method: String, path: String, body: String) -> String {
return handle_api_memory_update(body)
}
@route("/api/neuron/node/create", "POST", "exact") @manager
fn r_node_create(method: String, path: String, body: String) -> String {
return handle_api_node_create(body)
}
@route("/api/neuron/node/update", "POST", "exact") @manager
fn r_node_update(method: String, path: String, body: String) -> String {
return handle_api_node_update(body)
}
@route("/api/neuron/node/delete", "POST", "exact") @manager
fn r_node_delete(method: String, path: String, body: String) -> String {
return handle_api_node_delete(body)
}
@route("/api/neuron/consolidate", "POST", "exact") @manager
fn r_consolidate(method: String, path: String, body: String) -> String {
return handle_api_consolidate(body)
}
@route("/api/neuron/cultivate", "POST", "exact") @manager
fn r_cultivate(method: String, path: String, body: String) -> String {
return handle_api_cultivate(body)
}
// POST: chat / ELP / see / imprint / synthesize
@route("/api/elp/chat", "POST", "exact") @manager
fn r_elp_chat(method: String, path: String, body: String) -> String {
return handle_elp_chat(body)
}
@route("/api/see", "POST", "exact") @manager
fn r_see(method: String, path: String, body: String) -> String {
return handle_see(body)
}
@route("/imprint/contextual", "POST", "exact") @manager
fn r_imprint_contextual(method: String, path: String, body: String) -> String {
return route_imprint_contextual(body)
}
@route("/imprint/user", "POST", "exact") @manager
fn r_imprint_user(method: String, path: String, body: String) -> String {
return route_imprint_user(body)
}
@route("/synthesize", "POST", "exact") @manager
fn r_synthesize(method: String, path: String, body: String) -> String {
return route_synthesize(body)
}
// POST /api/chat buffered (no streaming); message is REQUIRED.
@route("/api/chat", "POST", "exact") @manager
fn r_chat_post(method: String, path: String, body: String) -> String {
let raw_msg: String = json_get(body, "message")
if str_eq(raw_msg, "") {
return "{\"error\":\"message is required\",\"code\":\"missing_param\"}"
}
if str_eq(clean, "/api/connectors/auto-approve") {
return connectd_post("/mcp/servers/auto-approve", body)
let agentic_flag: Bool = json_get_bool(body, "agentic")
let req_mode: String = json_get(body, "mode")
let reply: String = if str_eq(req_mode, "plan") {
handle_chat_plan(body)
} else if agentic_flag {
handle_chat_agentic(body)
} else {
let screened_reply: String = layered_cycle(raw_msg)
screened_reply
}
if str_eq(clean, "/api/connectors/remove") {
return connectd_post("/mcp/servers/remove", body)
auto_persist(body, reply)
return reply
}
// Sessions list / create / dynamic :id (GET/POST/DELETE/PATCH)
@route("/api/sessions", "GET", "exact") @manager
fn r_sessions_list(method: String, path: String, body: String) -> String {
return session_list()
}
@route("/api/sessions", "POST", "exact") @manager
fn r_sessions_create(method: String, path: String, body: String) -> String {
return session_create(body)
}
// COMPOUND: POST /api/sessions/:id/tool_result MCP tool-bridge resume. Must
// out-specify the bare approve prefix (it does: compound > prefix), preserving
// the load-bearing tool_result-before-approve order of the old dispatcher.
@route("/api/sessions/", "POST", "compound", "/tool_result") @manager
fn r_sessions_tool_result(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
let after: String = str_slice(clean, 14, str_len(clean))
let slash: Int = str_index_of(after, "/")
let session_id: String = if slash < 0 { after } else { str_slice(after, 0, slash) }
return handle_tool_result(session_id, body)
}
// POST /api/sessions/:id/approve bare prefix + in-handler sub check, exactly
// as the former dispatcher. Non-"approve" subpaths fall through to 404 (the old
// code returned nothing and dropped to the POST-block err_404).
@route("/api/sessions/", "POST", "prefix") @manager
fn r_sessions_approve(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
let sess_after: String = str_slice(clean, 14, str_len(clean))
let sess_slash: Int = str_index_of(sess_after, "/")
let sess_id: String = if sess_slash < 0 { sess_after } else { str_slice(sess_after, 0, sess_slash) }
let sess_sub: String = if sess_slash < 0 { "" } else { str_slice(sess_after, sess_slash + 1, str_len(sess_after)) }
if !str_eq(sess_id, "") && str_eq(sess_sub, "approve") {
return handle_session_approve(sess_id, body)
}
if str_eq(clean, "/api/connectors/secret") {
return connectd_post("/mcp/servers/secret", body)
return err_404(clean)
}
@route("/api/sessions/", "GET", "prefix") @manager
fn r_sessions_get(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
let gs_after: String = str_slice(clean, 14, str_len(clean))
let gs_slash: Int = str_index_of(gs_after, "/")
let gs_id: String = if gs_slash < 0 { gs_after } else { str_slice(gs_after, 0, gs_slash) }
if !str_eq(gs_id, "") {
return session_get(gs_id)
}
if str_eq(clean, "/api/connectors/oauth/start") {
return connectd_post("/mcp/oauth/start", body)
return err_404(clean)
}
@route("/api/sessions/", "DELETE", "prefix") @manager
fn r_sessions_delete(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
let del_after: String = str_slice(clean, 14, str_len(clean))
let del_slash: Int = str_index_of(del_after, "/")
let del_id: String = if del_slash < 0 { del_after } else { str_slice(del_after, 0, del_slash) }
if !str_eq(del_id, "") {
return session_delete(del_id)
}
// Call a connector tool directly (pre-chat), e.g. WhatsApp get_pairing_qr / get_login_status for
// the pairing UI. Body: {"name":"mcp__<server>__<tool>","input":{...}}. Keeps the app on the
// app->soul->connectd path (the UI never hits connectd directly) and works for remote/hosted apps.
if str_eq(clean, "/api/connectors/call") {
return connectd_post("/mcp/call", body)
return err_404(clean)
}
@route("/api/sessions/", "PATCH", "prefix") @manager
fn r_sessions_patch(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
let patch_after: String = str_slice(clean, 14, str_len(clean))
let patch_slash: Int = str_index_of(patch_after, "/")
let patch_id: String = if patch_slash < 0 { patch_after } else { str_slice(patch_after, 0, patch_slash) }
if !str_eq(patch_id, "") {
return session_update_patch(patch_id, body)
}
return err_404(clean)
}
// GET /api/run-progress/:session_id live agentic-run ledger
// Offset 18 = len("/api/run-progress/").
@route("/api/run-progress/", "GET", "prefix") @manager
fn r_run_progress(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
let rp_id: String = str_slice(clean, 18, str_len(clean))
if !str_eq(rp_id, "") {
let rp_raw: String = state_get("run_progress_" + rp_id)
let rp_arr: String = if str_eq(rp_raw, "") { "[]" } else { "[" + rp_raw + "]" }
return "{\"progress\":" + rp_arr + "}"
}
return err_404(clean)
}
// MCP Connectors proxy to neuron-connectd :7771
// GET (any /api/connectors*) server list. POST sub-routes are exact; an
// unmatched POST /api/connectors* prefix returns the "unknown connectors route"
// body, exactly as the former handle_connectors fallthrough.
@route("/api/connectors", "GET", "prefix") @manager
fn r_connectors_get(method: String, path: String, body: String) -> String {
return connectd_get("/mcp/servers")
}
@route("/api/connectors/add", "POST", "exact") @manager
fn r_connectors_add(method: String, path: String, body: String) -> String {
return connectd_post("/mcp/servers/add", body)
}
@route("/api/connectors/toggle", "POST", "exact") @manager
fn r_connectors_toggle(method: String, path: String, body: String) -> String {
return connectd_post("/mcp/servers/toggle", body)
}
@route("/api/connectors/auto-approve", "POST", "exact") @manager
fn r_connectors_auto_approve(method: String, path: String, body: String) -> String {
return connectd_post("/mcp/servers/auto-approve", body)
}
@route("/api/connectors/remove", "POST", "exact") @manager
fn r_connectors_remove(method: String, path: String, body: String) -> String {
return connectd_post("/mcp/servers/remove", body)
}
@route("/api/connectors/secret", "POST", "exact") @manager
fn r_connectors_secret(method: String, path: String, body: String) -> String {
return connectd_post("/mcp/servers/secret", body)
}
@route("/api/connectors/oauth/start", "POST", "exact") @manager
fn r_connectors_oauth_start(method: String, path: String, body: String) -> String {
return connectd_post("/mcp/oauth/start", body)
}
// Call a connector tool directly (pre-chat), e.g. WhatsApp get_pairing_qr /
// get_login_status. Keeps the app on the app->soul->connectd path.
@route("/api/connectors/call", "POST", "exact") @manager
fn r_connectors_call(method: String, path: String, body: String) -> String {
return connectd_post("/mcp/call", body)
}
@route("/api/connectors", "POST", "prefix") @manager
fn r_connectors_unknown(method: String, path: String, body: String) -> String {
return "{\"ok\":false,\"error\":\"unknown connectors route\"}"
}
//
// handle_request HTTP entry point (registered via http_serve_async in soul.el).
// Rate-limits, then dispatches through the compiler-synthesized @route table.
// The sentinel maps to 404 for a recognised method or 405 for an unknown one,
// reproducing the per-method-block fallthroughs of the former dispatcher.
//
@manager
fn handle_request(method: String, path: String, body: String) -> String {
let clean: String = strip_query(path)
@@ -358,340 +872,16 @@ fn handle_request(method: String, path: String, body: String) -> String {
}
}
if str_eq(method, "POST") && str_eq(clean, "/dharma/recv") {
return handle_dharma_recv(body)
// Compiler-synthesized dispatch (specificity-sorted, method-guarded).
let route_resp: String = el_route_dispatch(method, clean, path, body)
if !str_eq(route_resp, "__EL_NO_ROUTE__") {
return route_resp
}
if str_eq(method, "GET") {
if str_eq(clean, "/health") {
return route_health()
}
if str_eq(clean, "/lineage") {
return route_lineage()
}
if str_eq(clean, "/api/graph") || str_eq(clean, "/api/graph/nodes") {
return engram_scan_nodes_json(9999, 0)
}
if str_eq(clean, "/api/graph/edges") {
// TODO(reliability #8): engram_save races with awareness loop mem_save().
// Both now use atomic write-to-temp+rename (el_runtime.c). Serialised
// by engram_global_mu. Future: add engram_edges_json() builtin.
let snap_path: String = env("HOME") + "/.neuron/engram/snapshot.json"
engram_save(snap_path)
let snap: String = fs_read(snap_path)
let edges_raw: String = json_get_raw(snap, "edges")
return if str_eq(edges_raw, "") { "[]" } else { edges_raw }
}
if str_eq(clean, "/api/chat") {
// GET /api/chat: pass through layered_cycle for consistency with POST path.
// GET chat is a legacy probe interface; body may be empty for simple pings.
let raw_msg: String = json_get(body, "message")
let eff_msg: String = if str_eq(raw_msg, "") { body } else { raw_msg }
if str_eq(eff_msg, "") {
return "{\"error\":\"message is required\",\"code\":\"missing_param\"}"
}
let agentic_flag: Bool = json_get_bool(body, "agentic")
let reply: String = if agentic_flag {
handle_chat_agentic(body)
} else {
let screened_reply: String = layered_cycle(eff_msg)
screened_reply
}
auto_persist(body, reply)
return reply
}
if str_eq(clean, "/api/conversations") {
return handle_conversations(method)
}
if str_eq(clean, "/api/config") {
return handle_config(method, body)
}
if str_starts_with(clean, "/api/tools/") {
return handle_tool(clean, method, body)
}
if str_starts_with(clean, "/api/dharma") {
return handle_dharma(clean, method, body)
}
if str_starts_with(clean, "/api/nlg") {
return handle_nlg(clean, method, body)
}
if str_starts_with(clean, "/api/memories") {
return axon_get(clean)
}
if str_starts_with(clean, "/api/knowledge") {
return axon_get(clean)
}
if str_starts_with(clean, "/api/backlog") {
return axon_get(clean)
}
if str_starts_with(clean, "/api/artifacts") {
return axon_get(clean)
}
if str_starts_with(clean, "/api/projects") {
return axon_get(clean)
}
if str_starts_with(clean, "/api/imprints") {
return axon_get(clean)
}
if str_eq(clean, "/") {
return render_studio()
}
// Neuron cognitive API GET endpoints
if str_eq(clean, "/api/neuron/session/begin") {
return handle_api_begin_session("")
}
if str_eq(clean, "/api/neuron/ctx") {
return handle_api_compile_ctx("")
}
if str_eq(clean, "/api/safety-contact") {
return handle_safety_contact_get()
}
if str_starts_with(clean, "/api/neuron/knowledge/search") {
return handle_api_search_knowledge(method, path, body)
}
if str_eq(clean, "/api/neuron/knowledge") {
return handle_api_browse_knowledge(path, body)
}
if str_starts_with(clean, "/api/neuron/processes") {
return handle_api_browse_processes(method, path, body)
}
if str_starts_with(clean, "/api/neuron/state-events") {
return handle_api_list_state_events(method, path, body)
}
if str_starts_with(clean, "/api/neuron/config") {
return handle_api_inspect_config(path, body)
}
if str_starts_with(clean, "/api/neuron/graph") {
return handle_api_inspect_graph(method, path, body)
}
if str_starts_with(clean, "/api/neuron/list/") {
// Offset 17 = len("/api/neuron/list/"). Was 16, which left a leading "/" on node_type
// ("/BacklogItem"), so engram_scan_nodes_by_type_json matched nothing list/<type>
// returned [] for EVERY type (broke backlog/typed-node listing app- and tool-wide).
let node_type: String = str_slice(clean, 17, str_len(clean))
return handle_api_list_typed(node_type, path, body)
}
if str_starts_with(clean, "/api/neuron/recall") {
return handle_api_recall(method, path, body)
}
if str_starts_with(clean, "/api/connectors") {
return handle_connectors(method, clean, body)
}
// GET /api/sessions list all sessions
if str_eq(clean, "/api/sessions") {
return session_list()
}
// GET /api/sessions/:id get session metadata + history
if str_starts_with(clean, "/api/sessions/") {
let gs_after: String = str_slice(clean, 14, str_len(clean))
let gs_slash: Int = str_index_of(gs_after, "/")
let gs_id: String = if gs_slash < 0 { gs_after } else { str_slice(gs_after, 0, gs_slash) }
if !str_eq(gs_id, "") {
return session_get(gs_id)
}
}
// Fallthrough: a recognised method with no matching path 404; an
// unrecognised method 405 (matches the old per-method-block structure).
if str_eq(method, "GET") || str_eq(method, "POST") || str_eq(method, "DELETE") || str_eq(method, "PATCH") {
return err_404(clean)
}
if str_eq(method, "POST") {
// POST /api/sessions create new session
if str_eq(clean, "/api/sessions") {
return session_create(body)
}
// MCP tool-bridge resume: POST /api/sessions/{id}/tool_result
// The client executed a tool the soul could not run in-process (an MCP
// connector/plugin) and posts the result back here so the agentic loop
// continues. {id} is the session_id from the prior tool_pending envelope.
if str_starts_with(clean, "/api/sessions/") && str_ends_with(clean, "/tool_result") {
let after: String = str_slice(clean, 14, str_len(clean))
let slash: Int = str_index_of(after, "/")
let session_id: String = if slash < 0 { after } else { str_slice(after, 0, slash) }
return handle_tool_result(session_id, body)
}
// POST /api/sessions/:id/approve user approval for a pending agentic tool call
if str_starts_with(clean, "/api/sessions/") {
let sess_after: String = str_slice(clean, 14, str_len(clean))
let sess_slash: Int = str_index_of(sess_after, "/")
let sess_id: String = if sess_slash < 0 { sess_after } else { str_slice(sess_after, 0, sess_slash) }
let sess_sub: String = if sess_slash < 0 { "" } else { str_slice(sess_after, sess_slash + 1, str_len(sess_after)) }
if !str_eq(sess_id, "") && str_eq(sess_sub, "approve") {
return handle_session_approve(sess_id, body)
}
}
if str_eq(clean, "/imprint/contextual") {
return route_imprint_contextual(body)
}
if str_eq(clean, "/imprint/user") {
return route_imprint_user(body)
}
if str_eq(clean, "/synthesize") {
return route_synthesize(body)
}
if str_eq(clean, "/api/elp/chat") {
return handle_elp_chat(body)
}
if str_eq(clean, "/api/chat") {
// NOTE: streaming (SSE / chunked transfer) is not implemented. All chat
// responses are buffered and returned as a single JSON object. Streaming
// would require runtime-level SSE support in el_runtime.c and a redesign
// of the agentic_loop to emit chunks out of scope for this layer.
let raw_msg: String = json_get(body, "message")
if str_eq(raw_msg, "") {
return "{\"error\":\"message is required\",\"code\":\"missing_param\"}"
}
let agentic_flag: Bool = json_get_bool(body, "agentic")
let reply: String = if agentic_flag {
handle_chat_agentic(body)
} else {
let screened_reply: String = layered_cycle(raw_msg)
screened_reply
}
auto_persist(body, reply)
return reply
}
if str_eq(clean, "/api/see") {
return handle_see(body)
}
if str_eq(clean, "/api/conversations") {
return handle_conversations(method)
}
if str_eq(clean, "/api/config") {
return handle_config(method, body)
}
if str_starts_with(clean, "/api/tools/") {
return handle_tool(clean, method, body)
}
if str_starts_with(clean, "/api/dharma") {
return handle_dharma(clean, method, body)
}
if str_starts_with(clean, "/api/nlg") {
return handle_nlg(clean, method, body)
}
if str_starts_with(clean, "/api/memories") {
return axon_post(clean, body)
}
if str_starts_with(clean, "/api/knowledge") {
return axon_post(clean, body)
}
if str_starts_with(clean, "/api/backlog") {
return axon_post(clean, body)
}
if str_starts_with(clean, "/api/artifacts") {
return axon_post(clean, body)
}
if str_starts_with(clean, "/api/projects") {
return axon_post(clean, body)
}
if str_starts_with(clean, "/api/imprints") {
return axon_post(clean, body)
}
// Neuron cognitive API POST endpoints
if str_eq(clean, "/api/neuron/session/begin") {
return handle_api_begin_session(body)
}
if str_eq(clean, "/api/neuron/ctx") {
return handle_api_compile_ctx(body)
}
if str_eq(clean, "/api/neuron/knowledge/search") {
return handle_api_search_knowledge(method, path, body)
}
if str_eq(clean, "/api/neuron/knowledge/capture") {
return handle_api_capture_knowledge(body)
}
if str_eq(clean, "/api/neuron/knowledge/evolve") {
return handle_api_evolve_knowledge(body)
}
if str_eq(clean, "/api/neuron/knowledge/promote") {
return handle_api_promote_knowledge(body)
}
if str_eq(clean, "/api/neuron/processes") {
return handle_api_browse_processes(method, path, body)
}
if str_eq(clean, "/api/neuron/processes/define") {
return handle_api_define_process(body)
}
if str_eq(clean, "/api/neuron/state-events") {
return handle_api_log_state_event(body)
}
if str_eq(clean, "/api/neuron/config") {
return handle_api_inspect_config(path, body)
}
if str_eq(clean, "/api/neuron/config/tune") {
return handle_api_tune_config(body)
}
if str_eq(clean, "/api/neuron/graph") {
return handle_api_inspect_graph(method, path, body)
}
if str_eq(clean, "/api/neuron/graph/link") {
return handle_api_link_entities(body)
}
if str_eq(clean, "/api/neuron/memory") {
return handle_api_remember(body)
}
if str_eq(clean, "/api/safety-contact") {
return handle_safety_contact_post(body)
}
if str_eq(clean, "/api/neuron/node/create") {
return handle_api_node_create(body)
}
if str_eq(clean, "/api/neuron/node/update") {
return handle_api_node_update(body)
}
if str_eq(clean, "/api/neuron/node/delete") {
return handle_api_node_delete(body)
}
if str_eq(clean, "/api/neuron/memory/evolve") {
return handle_api_evolve_memory(body)
}
if str_eq(clean, "/api/neuron/memory/forget") {
return handle_api_forget(body)
}
if str_eq(clean, "/api/neuron/memory/delete") {
return handle_api_memory_delete(body)
}
if str_eq(clean, "/api/neuron/memory/update") {
return handle_api_memory_update(body)
}
if str_eq(clean, "/api/neuron/recall") {
return handle_api_recall(method, path, body)
}
if str_eq(clean, "/api/neuron/consolidate") {
return handle_api_consolidate(body)
}
if str_eq(clean, "/api/neuron/cultivate") {
return handle_api_cultivate(body)
}
if str_starts_with(clean, "/api/connectors") {
return handle_connectors(method, clean, body)
}
return err_404(clean)
}
if str_eq(method, "DELETE") {
// DELETE /api/sessions/:id delete a session and its history
if str_starts_with(clean, "/api/sessions/") {
let del_after: String = str_slice(clean, 14, str_len(clean))
let del_slash: Int = str_index_of(del_after, "/")
let del_id: String = if del_slash < 0 { del_after } else { str_slice(del_after, 0, del_slash) }
if !str_eq(del_id, "") {
return session_delete(del_id)
}
}
return err_404(clean)
}
if str_eq(method, "PATCH") {
// PATCH /api/sessions/:id update session title and/or folder
if str_starts_with(clean, "/api/sessions/") {
let patch_after: String = str_slice(clean, 14, str_len(clean))
let patch_slash: Int = str_index_of(patch_after, "/")
let patch_id: String = if patch_slash < 0 { patch_after } else { str_slice(patch_after, 0, patch_slash) }
if !str_eq(patch_id, "") {
return session_update_patch(patch_id, body)
}
}
return err_404(clean)
}
return err_405(method, clean)
}
+1 -1
View File
@@ -1,4 +1,5 @@
// auto-generated by elc --emit-header — do not edit
extern fn flag_true(body: String, key: String) -> Bool
extern fn rate_limit_check(ip: String, path: String) -> String
extern fn strip_query(path: String) -> String
extern fn err_404(path: String) -> String
@@ -11,5 +12,4 @@ extern fn route_synthesize(body: String) -> String
extern fn handle_dharma_recv(body: String) -> String
extern fn connectd_get(suffix: String) -> String
extern fn connectd_post(suffix: String, body: String) -> String
extern fn handle_connectors(method: String, clean: String, body: String) -> String
extern fn handle_request(method: String, path: String, body: String) -> String
+1 -1
View File
@@ -244,7 +244,7 @@ fn safety_general_hard_phrases() -> String {
}
fn safety_soft_phrases() -> String {
return "[\"stressed\",\"overwhelmed\",\"can't cope\",\"cannot cope\",\"struggling\",\"anxious\",\"anxiety\",\"depressed\",\"depression\",\"lonely\",\"isolated\",\"hopeless\",\"hopelessness\",\"exhausted\",\"burnt out\",\"burned out\",\"burnout\",\"panic\",\"panicking\",\"falling apart\",\"breaking down\",\"can't handle\",\"cannot handle\",\"losing it\",\"nothing matters\",\"don't care anymore\",\"given up\",\"giving up\",\"helpless\",\"worthless\",\"useless\",\"hate myself\",\"no one cares\",\"nobody cares\",\"no one understands\",\"nobody understands\",\"empty inside\",\"can't stop crying\",\"breaking point\",\"at my limit\",\"having a breakdown\""]"
return "[\"stressed\",\"overwhelmed\",\"can't cope\",\"cannot cope\",\"struggling\",\"anxious\",\"anxiety\",\"depressed\",\"depression\",\"lonely\",\"isolated\",\"hopeless\",\"hopelessness\",\"exhausted\",\"burnt out\",\"burned out\",\"burnout\",\"panic\",\"panicking\",\"falling apart\",\"breaking down\",\"can't handle\",\"cannot handle\",\"losing it\",\"nothing matters\",\"don't care anymore\",\"given up\",\"giving up\",\"helpless\",\"worthless\",\"useless\",\"hate myself\",\"no one cares\",\"nobody cares\",\"no one understands\",\"nobody understands\",\"empty inside\",\"can't stop crying\",\"breaking point\",\"at my limit\",\"having a breakdown\"]"
}
// ISSUE 5 TODO: phrase lists are rebuilt from JSON literals on every call.
+29 -18
View File
@@ -373,6 +373,32 @@ fn session_update_patch(session_id: String, body: String) -> String {
+ ",\"updated_at\":" + int_to_str(ts) + "}"
}
// session_search_entry extract one search-result entry from a raw node JSON.
// Returns a JSON object string or "" if the node is not a valid session:meta node.
//
// Extracted from session_search's while loop body to reduce the loop's lexical
// complexity. The ELC compiler runs out of memory processing while loops with
// many `let` bindings extracting the body into a separate function gives the
// compiler a clean scope boundary at each call. Each function compiles in O(N)
// rather than the exponential growth caused by rebinding accumulation inside loops.
// (2026-07-01 self-review: root cause of sessions.c OOM/truncation since June 30)
fn session_search_entry(node: String) -> String {
let label: String = json_get(node, "label")
if !str_eq(label, "session:meta") { return "" }
let content: String = json_get(node, "content")
let sess_id: String = json_get(content, "id")
if str_eq(sess_id, "") { return "" }
let title: String = json_get(content, "title")
let created_raw: String = json_get(content, "created_at")
let updated_raw: String = json_get(content, "updated_at")
let eff_created: String = if str_eq(created_raw, "") { "0" } else { created_raw }
let eff_updated: String = if str_eq(updated_raw, "") { eff_created } else { updated_raw }
let e_id: String = "{\"id\":\"" + json_safe(sess_id) + "\""
let e_title: String = ",\"title\":\"" + json_safe(title) + "\""
let e_ts: String = ",\"created_at\":" + eff_created + ",\"updated_at\":" + eff_updated + "}"
return e_id + e_title + e_ts
}
// session_search search session:meta nodes whose content matches query.
fn session_search(query: String) -> String {
if str_eq(query, "") { return "[]" }
@@ -383,22 +409,7 @@ fn session_search(query: String) -> String {
let out: String = ""
let i: Int = 0
while i < total {
let node: String = json_array_get(results, i)
let label: String = json_get(node, "label")
let content: String = json_get(node, "content")
let is_session: Bool = str_eq(label, "session:meta")
let sess_id: String = json_get(content, "id")
let title: String = json_get(content, "title")
let created_raw: String = json_get(content, "created_at")
let updated_raw: String = json_get(content, "updated_at")
let eff_created: String = if str_eq(created_raw, "") { "0" } else { created_raw }
let eff_updated: String = if str_eq(updated_raw, "") { eff_created } else { updated_raw }
let entry: String = if is_session && !str_eq(sess_id, "") {
"{\"id\":\"" + json_safe(sess_id) + "\""
+ ",\"title\":\"" + json_safe(title) + "\""
+ ",\"created_at\":" + eff_created
+ ",\"updated_at\":" + eff_updated + "}"
} else { "" }
let entry: String = session_search_entry(json_array_get(results, i))
let out = if !str_eq(entry, "") {
if str_eq(out, "") { entry } else { out + "," + entry }
} else { out }
@@ -503,10 +514,10 @@ fn session_hist_save(session_id: String, hist: String) -> Void {
let last_role: String = json_get(last_entry, "role")
let last_content: String = json_get(last_entry, "content")
let topic_snip: String = if str_len(last_content) > 200 { str_slice(last_content, 0, 200) } else { last_content }
let safe_topic: String = str_replace(topic_snip, """, "'")
let safe_topic: String = str_replace(topic_snip, "\"", "'")
let ts_now: String = int_to_str(time_now())
let topic_content: String = "last-session-topic | ts:" + ts_now + " | session:" + session_id + " | topic:" + safe_topic
let topic_tags: String = "["last-session-topic","conv:history","Conversation","session:topic"]"
let topic_tags: String = "[\"last-session-topic\",\"conv:history\",\"Conversation\",\"session:topic\"]"
let topic_label: String = "last-session-topic:" + session_id
// Delete old last-session-topic node for this session before writing fresh
let old_topic: String = engram_search_json("last-session-topic:" + session_id, 2)
+1
View File
@@ -8,6 +8,7 @@ extern fn session_list() -> String
extern fn session_get(session_id: String) -> String
extern fn session_delete(session_id: String) -> String
extern fn session_update_patch(session_id: String, body: String) -> String
extern fn session_search_entry(node: String) -> String
extern fn session_search(query: String) -> String
extern fn session_hist_load(session_id: String) -> String
extern fn session_hist_save(session_id: String, hist: String) -> Void
+21
View File
@@ -346,6 +346,27 @@ fn emit_session_start_event() -> Void {
el_from_float(0.9), el_from_float(0.9), el_from_float(1.0),
"Episodic", tags
)
// Prune accumulated session-start events keep the 10 most recent.
// engram_search_json returns results in insertion order (oldest first), so
// results[0..count-11] are the oldest; forgetting them leaves the newest 10.
let keep_n: Int = 10
let old_events: String = engram_search_json("session-start InternalStateEvent", 200)
if !str_eq(old_events, "") && !str_eq(old_events, "[]") {
let ev_count: Int = json_array_len(old_events)
if ev_count > keep_n {
let prune_to: Int = ev_count - keep_n
let ei: Int = 0
while ei < prune_to {
let old_ev: String = json_array_get(old_events, ei)
let old_ev_id: String = json_get(old_ev, "id")
if !str_eq(old_ev_id, "") {
engram_forget(old_ev_id)
}
let ei = ei + 1
}
println("[soul] pruned " + int_to_str(prune_to) + " old session-start events (kept " + int_to_str(keep_n) + ")")
}
}
println("[soul] session-start event logged (boot=" + boot_num + " nodes=" + int_to_str(node_ct) + " edges=" + int_to_str(edge_ct) + " prev_summary=" + has_prev_sum + ")")
}
+2 -6
View File
@@ -1,15 +1,11 @@
// stewardship.elh — Layer 2 public surface
// auto-generated by elc --emit-header — do not edit
extern fn steward_log_event(kind: String, detail: String) -> Void
extern fn steward_get_mission() -> String
extern fn steward_align(input: String, imprint_id: String) -> String
extern fn steward_validate_imprint(imprint_id: String, tool_name: String) -> String
extern fn steward_cgi_check(action: String) -> String
// steward_log_event is an internal helper exported here because El has no access modifiers.
// External callers have no business invoking this directly — use steward_align,
// steward_validate_imprint, or steward_cgi_check, which call it at the correct points.
extern fn steward_log_event(kind: String, detail: String) -> Void
// Behavioral profiling and continuity detection (Layer 2 — session fingerprinting).
extern fn steward_fingerprint_session(input: String, session_id: String) -> String
extern fn extract_dim(content: String, key: String) -> String
extern fn steward_build_baseline() -> String
extern fn steward_check_continuity(current_fingerprint: String, session_id: String) -> String
extern fn steward_session_check(input: String, session_id: String) -> String
+3 -1
View File
@@ -46,7 +46,9 @@ fn handle_config(method: String, body: String) -> String {
}
}
let current_model: String = state_get("soul_model")
let display: String = if str_eq(current_model, "") { "claude-sonnet-4-5" } else { current_model }
// Display fallback aligned with the intended product default (was claude-sonnet-4-5,
// which silently became the app's picker default on fresh profiles 2026-07-13).
let display: String = if str_eq(current_model, "") { "claude-opus-4-8" } else { current_model }
return "{\"model\":\"" + display + "\",\"ok\":true}"
}
+1 -1
View File
@@ -1,4 +1,4 @@
// auto-generated by elc --emit-header - do not edit
// auto-generated by elc --emit-header do not edit
extern fn auth_headers(tok: String) -> Map
extern fn axon_get(path: String) -> String
extern fn axon_post(path: String, body: String) -> String
+191
View File
@@ -0,0 +1,191 @@
#!/bin/bash
# Neuron Telegram Gateway
# Polls Telegram for new messages, forwards to the soul at localhost:7770, sends responses back.
# Supports plain text chat + commands: /memory, /remember, /status
#
# Token resolution order:
# 1. $TELEGRAM_BOT_TOKEN env var
# 2. macOS Keychain: security find-generic-password -s neuron-telegram-bot -a neuron -w
set -euo pipefail
TOKEN="${TELEGRAM_BOT_TOKEN:-$(security find-generic-password -s neuron-telegram-bot -a neuron -w 2>/dev/null || true)}"
SOUL_URL="http://localhost:7770"
OFFSET=0
POLL_TIMEOUT=30
if [[ -z "$TOKEN" ]]; then
echo "ERROR: No Telegram bot token. Set TELEGRAM_BOT_TOKEN or store in keychain." >&2
echo "See: ~/Development/neuron-technologies/neuron/docs/telegram-bot-setup.md" >&2
exit 1
fi
TG="https://api.telegram.org/bot${TOKEN}"
log() { echo "[$(date '+%Y-%m-%d %H:%M:%S')] $*"; }
# Send a Telegram message back to a chat
send_message() {
local chat_id="$1"
local text="$2"
curl -s -X POST "${TG}/sendMessage" \
-H "Content-Type: application/json" \
-d "$(jq -n --argjson cid "$chat_id" --arg t "$text" \
'{chat_id: $cid, text: $t, parse_mode: "Markdown"}')" \
> /dev/null
}
# Store a memory in the soul
store_memory() {
local content="$1"
local label="${2:-telegram:conversation}"
curl -s -X POST "${SOUL_URL}/api/neuron/memory" \
-H "Content-Type: application/json" \
-d "$(jq -n --arg c "$content" --arg l "$label" \
'{content: $c, label: $l}')" \
> /dev/null
}
# Chat with the soul; echoes the response text
soul_chat() {
local message="$1"
local from="${2:-unknown}"
local response
response=$(curl -s -X POST "${SOUL_URL}/api/chat" \
-H "Content-Type: application/json" \
-d "$(jq -n --arg m "$message" --arg f "$from" \
'{message: $m, from: $f}')" 2>/dev/null)
# Extract .response — fall back to raw body on parse failure
jq -r '.response // empty' <<< "$response" 2>/dev/null || echo "$response"
}
# Search soul memories; echoes formatted results
soul_recall() {
local query="$1"
local limit="${2:-3}"
local raw
raw=$(curl -s -X POST "${SOUL_URL}/api/neuron/recall" \
-H "Content-Type: application/json" \
-d "$(jq -n --arg q "$query" --argjson l "$limit" \
'{query: $q, limit: $l}')" 2>/dev/null)
# Format top results as a numbered list (truncate long nodes to 300 chars)
jq -r 'if type == "array" then
to_entries | .[:3] | map(
(.index + 1 | tostring) + ". " + (.value.content | .[0:300] | gsub("\n";" "))
) | join("\n\n")
else
"No results found."
end' <<< "$raw" 2>/dev/null || echo "No results found."
}
# Check if soul is reachable
soul_health() {
curl -s --max-time 3 "${SOUL_URL}/" > /dev/null 2>&1 && echo "up" || echo "down"
}
handle_update() {
local update="$1"
local chat_id msg_text from_name update_id
update_id=$(jq -r '.update_id' <<< "$update")
chat_id=$(jq -r '.message.chat.id // empty' <<< "$update")
msg_text=$(jq -r '.message.text // empty' <<< "$update")
from_name=$(jq -r '.message.from.first_name // "stranger"' <<< "$update")
# Skip non-message updates (inline queries, etc.)
if [[ -z "$chat_id" || -z "$msg_text" ]]; then
OFFSET=$((update_id + 1))
return
fi
log "[$update_id] from=$from_name chat=$chat_id text=${msg_text:0:60}"
# Route by command prefix
if [[ "$msg_text" == /status* ]]; then
local health
health=$(soul_health)
if [[ "$health" == "up" ]]; then
send_message "$chat_id" "Soul is *online* at ${SOUL_URL}"
else
send_message "$chat_id" "Soul appears to be *offline* (${SOUL_URL} unreachable)."
fi
elif [[ "$msg_text" == /memory* ]]; then
local query="${msg_text#/memory}"
query="${query# }"
if [[ -z "$query" ]]; then
send_message "$chat_id" "Usage: /memory <query>"
else
local results
results=$(soul_recall "$query" 3)
if [[ -n "$results" ]]; then
send_message "$chat_id" "*Memories matching \"${query}\":*
${results}"
else
send_message "$chat_id" "No memories found for \"${query}\"."
fi
fi
elif [[ "$msg_text" == /remember* ]]; then
local content="${msg_text#/remember}"
content="${content# }"
if [[ -z "$content" ]]; then
send_message "$chat_id" "Usage: /remember <text to store>"
else
store_memory "Telegram (${from_name}): ${content}" "telegram:explicit"
send_message "$chat_id" "Stored: _${content}_"
fi
else
# Plain text — forward to soul chat
local soul_response
soul_response=$(soul_chat "$msg_text" "$from_name" 2>/dev/null || true)
if [[ -z "$soul_response" ]]; then
soul_response="Neuron is resting — try again in a moment."
fi
send_message "$chat_id" "$soul_response"
# Capture conversation as a memory (fire-and-forget)
store_memory "Telegram conversation with ${from_name}: [user] ${msg_text} [soul] ${soul_response}" \
"telegram:conversation" &
fi
OFFSET=$((update_id + 1))
}
log "Neuron Telegram gateway starting (soul=${SOUL_URL}, poll_timeout=${POLL_TIMEOUT}s)"
while true; do
# Long-poll for updates
UPDATES=$(curl -s --max-time $((POLL_TIMEOUT + 5)) \
"${TG}/getUpdates?offset=${OFFSET}&timeout=${POLL_TIMEOUT}" 2>/dev/null || true)
if [[ -z "$UPDATES" ]]; then
log "WARN: Empty response from Telegram; retrying in 5s"
sleep 5
continue
fi
OK=$(jq -r '.ok // false' <<< "$UPDATES" 2>/dev/null)
if [[ "$OK" != "true" ]]; then
DESC=$(jq -r '.description // "unknown error"' <<< "$UPDATES" 2>/dev/null)
log "WARN: Telegram API error: ${DESC}; retrying in 10s"
sleep 10
continue
fi
# Iterate over each update
COUNT=$(jq '.result | length' <<< "$UPDATES" 2>/dev/null || echo 0)
if [[ "$COUNT" -gt 0 ]]; then
for i in $(seq 0 $((COUNT - 1))); do
update=$(jq ".result[$i]" <<< "$UPDATES")
handle_update "$update"
done
fi
# Avoid hammering the API if something is very wrong
sleep 1
done