ModelConfig.params was loaded from config but never consumed — the spawn
command in DefaultModelManager was hardcoded. Thread it through: params (a
flag->value map) flattens to token order on ModelDescriptor.extraArgs and
appends to the llama-server argv. This engages Multi-Token Prediction
speculative decoding purely from config:
[[models]]
params = { "-md" = "/path/draft.gguf", "-ngld" = "99", "--spec-type" = "draft-mtp", "--spec-draft-n-max" = "4" }
Each entry stays a distinct argv token (no shell), so paths with spaces are safe.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Vikunja #167/#168/#169.
#167 PlanGrounder (infrastructure/workflow): build-prereq + touches-scope
existence grounding, emits PlanGroundingEvaluatedEvent. Deterministic fold
over recorded workspace/plan events (invariants #8/#9).
#168 positive-pattern mining (SessionOrchestratorPlanPatterns): mine
SuccessfulPlanShape from cross-session log — a locked plan whose own
workflow later completed — and inject the closest-resembling plan shape as
L0/SYSTEM advisory context for the planning stage. Keyword-Jaccard
resemblance, no LLM/embedder, replays identically. Advisory only (#3).
#169 stage-prompt audit + CORREX_STAGE_GUIDANCE ON/OFF toggle in
SessionOrchestratorExecution. RunCommand gains --intent to seed a
freestyle session over REST.
Also: workspace verification events + concept-compiler wiring. ./gradlew
check green.
GenerationConfig only carried temperature/top_p/max_tokens/stop/seed. Added nullable
topK/minP/repeatPenalty, serialized to the llama.cpp and OpenAI-compat request bodies
via @EncodeDefault(NEVER) so an unset knob is omitted (the model keeps its own default)
and behavior is unchanged unless the operator opts in.
Surfaced as a new [sampling] config section feeding the default stage GenerationConfig
(the main agentic loop) through TomlWorkflowLoader + ExecutionPlanCompiler; the former
hardcoded temperature=0.7/topP=1.0 stage defaults now come from config. Talkie
chat/narration keep their own generation settings.
Vikunja #46 (task 76) — sampling half.
The 'router' name was misleading — it's the always-on conversational front-end
(CHAT triage + STEERING into a running workflow), not a routing layer, and it's
distinct from InferenceRouter. Rename core:router -> core:talkie, package
com.correx.core.router -> com.correx.core.talkie, and RouterFacade/Config/State/
Repository/ContextBuilder/Projector/Reducer/Response -> Talkie*. Config section
[router] -> [talkie] (legacy [router] still read as fallback).
Persisted wire formats are preserved: ChatTurnRole.ROUTER and the
RouterNarrationEvent @SerialName("RouterNarration") stay, so existing event
logs still replay. RouterNarrationEvent the class is now TalkieNarrationEvent.
Enable autonomous QA through a remote OpenAI-compatible provider (NVIDIA NIM)
and harden the tool/approval path so unattended multi-stage runs complete.
- inference: add openai_compat provider (Bearer chat-completions for NIM/OpenAI),
dispatched by provider type "nim"/"openai"; key via api_key/api_key_env.
- server: bind configured [server] host/port instead of a hardcoded 8080;
POST /sessions accepts an optional `intent` (WS parity) for intent-driven workflows.
- kernel: thread the bound operator profile's approval_mode into per-tool gating so
auto/yolo enable unattended approval (engine still consulted; policy/plane-2 BLOCK
stays terminal); on a recoverable tool failure feed the tool's arg-schema back into
context so the model self-corrects instead of repeating a malformed call.
- tools: split deletion out of file_write into a separate, explicitly-named file_delete
tool — a model can no longer delete a file by getting a write-mode parameter wrong.
- server: add GET /metrics/tool-reliability — per-model tool-call validity from the
event log (measurement groundwork for capability-aware routing).
- docs: update AGENTS.md across kernel, tools, server, inference.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Adds task tracking as a first-class event-sourced aggregate (ADR-0012). The
event log stays the only source of truth; the board is a projection, and all of
a project's task events live in one stream (tasks:<projectId>).
core:
- new core:tasks module mirroring core:sessions: TaskStatus/State/Reducer/
BoardProjector/CounterProjection/Repository + TaskService write path that
appends events via the existing EventStore (no new storage)
- task events in core:events (sealed marker TaskEvent), registered in
Serialization.kt; status is derived by the reducer from lifecycle facts
- work-graph edges: TaskLinkType + typed TaskTargetKind on the link, so bundle
resolution dispatches on the recorded kind instead of guessing from the id
- delete is a soft tombstone (TaskDeletedEvent); cancel stays a visible outcome
surfaces:
- agent tools (Tier T2 mutators, T1 read): task_create / task_update /
task_delete / task_context, registered in both the main and per-workspace
tool registries
- REST GET /tasks/{id}/context for external agents
context bundle (TaskContextAssembler):
- task fields + acceptance criteria + relevant files + resolved dependency
tasks (live status) + raw related links + notes, with a compact render()
- semantic enrichment via a TaskKnowledgeRetriever port bridged to the existing
L3 retriever (late-bound holder for composition-root ordering)
- ADR/doc resolution via a TaskDocumentResolver port + filesystem adapter
(docs/decisions/adr-*.md, padding-agnostic; *.md paths)
Unit-verified across core:tasks / infrastructure:tools / apps:server; full
gradlew check green. Not yet live-QA'd end-to-end against a running server.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The rubber-duck path emits a fenced {"ideas":[…]} block; Ideas.parse strips it
from the chat turn and onUserInput records an IdeaCapturedEvent each (CHAT only).
IdeaReader folds eventStore.allEvents() into the active cross-session board, and
DefaultRouterContextBuilder injects a capped "## Ideas" entry — router-only, so
workflow stages never see it. Extended SYSTEM_PROMPT option (d) to capture ideas.
Users declare artifact kinds in [[artifacts]] (id + schema_path to a JSON-schema file + llm_emitted); ConfigArtifactKind registers them at startup via createWorkflowLoader(extraKinds). New JsonSchemaValidator validates any non-built-in kind generically against its declared deriveJsonSchema(), so an LLM-emitted custom kind is checked against its shape, never trusted. Removed the dead payloadSerializer from the ArtifactKind contract. Schema source is path-to-file (not inline TOML — the hand-rolled parser can't nest).
[[models]] config (ModelConfig/ModelsSettings) parsed by ConfigLoader;
InfrastructureModule.createModelManager + modelConfigToDescriptor; Main.kt
managed boot path spawns the default llama-server when [[models]] is present
(static [[providers]] path preserved when absent) and kills it on shutdown.
Plan: docs/plans/2026-05-31-model-lifecycle-management.md (slice 1 of 5).
When a user sends input, embed it, query L3 across all sessions, dedup
against in-session turns, and record the retrieval as an event so replay
is deterministic (invariant #9). Hits land in RouterState; context
injection follows in a later slice.
- Add L3MemoryRetrievedEvent + L3RetrievedHit (registered in eventModule)
- RouterState.lastRetrievedMemory + reducer case; RouterTurn carries turnId
- RouterConfig.retrievalK (default 5)
- Harden L3 write path: runCatching + visible logging, cancellation
re-thrown; event append stays ahead of the L3 write
- Warn prominently when the non-durable in_memory L3 backend is selected
Adds [router.embedder] and [router.l3] sections to CorrexConfig with
backend selectors. Ships LlamaCppEmbedder that hits llama.cpp's
/embedding endpoint (handles OpenAI-compatible, simple, and array
response shapes; validates dimension). InfrastructureModule gains
createEmbedderFromConfig and createL3MemoryStoreFromConfig that
dispatch on backend value.
Defaults preserve current behavior (noop embedder + in-memory L3).
Switching to "llamacpp" / "turbovec" is a config-only change — no code
edits required. For turbovec backend, the bundled python sidecar
script is extracted from classpath to ~/.cache/correx/ on first use.
Introduces Embedder contract in core:inference with a NoopEmbedder
default (zero vector) and wires both Embedder and L3MemoryStore into
DefaultRouterFacade. Each ChatTurnEvent emission now embeds the turn
content and writes a corresponding L3MemoryEntry, so cross-session
memory is captured at the source of truth (the event emission point).
InfrastructureModule defaults to NoopEmbedder + InMemoryL3MemoryStore
so the system runs without an external embedding model or vector store
wired. The TurboVec adapter stays unwired for now; switching to it is
a configuration concern (Epic 12 config layer).
Also gitignores apps/tui/logs/ (Kotlin TUI runtime logs, pre-Go rewrite).
LlamaCppInferenceProvider was created with empty capabilities, causing
NoEligibleProviderException when the router requested ModelCapability.General.
FirstAvailableRoutingStrategy requires declared capabilities to cover all
requested ones — empty set satisfied nothing.
Add a DEFAULT_LLAMA_CAPABILITIES constant with General, Coding, Reasoning,
Summarization, and ToolCalling scores, and pass it through createLlamaCppProvider()
to ModelDescriptor. Existing callers get sensible defaults automatically.
This is the root cause of the 'router not connected — epic 14' placeholder:
the server-side error (capability mismatch) sent a ProtocolError instead of a
RouterResponseMessage, so the TUI never set routerConnected=true.
- GlobalStreamHandler.handleCreateGrant validates scope (SESSION/STAGE)
and sends ProtocolError to client on validation failure instead of
silent log.warn + drop.
- Derive event stageId directly from GrantScope type, removing
redundant stageIdForEvent tuple.
- SessionOrchestrator integrates ApprovalEngine to check active grants
before requesting user approval for T2+ tool calls.
- ContextEntry gains EntryRole (SYSTEM/USER/ASSISTANT/TOOL) field for
proper chat message role mapping.
- RouterContextBuilder.build is now suspend; uses Tokenizer for
accurate token estimation with fallback to character-based estimate.
- LlamaCppInferenceProvider maps EntryRole to ChatMessage role instead
of heuristic layer-based inference.
- fixed the tool overlay in tui.
- fixed tool calling - added schemas.
- getting all sessionIds via event store.
- instead of sending all events on the replay - there's a new way for replaying.
- session snapshot is now a thing getting sent for previously created sessions.
- added logging to important parts.
- revert workflowId from WorkflowCompletedEvent.
fixed detekt issues where possible.
fixed disttar failing build because tools is added twice in the server module.
added workflowId where required.
fixed some tests not being recognized because of runBlocking without explicit return type.
formatting + imports.
Implements the full conversational router facade: RouterState, RouterReducer,
RouterProjector, RouterRepository, RouterContextBuilder, RouterFacade, protocol
types, WebSocket wiring, infrastructure factory, and deterministic test suite.
Also fixes spec divergences found in post-implementation review:
- Add SteeringNote domain object to core:context (epic prerequisite)
- Rename RouterFacade.handleChat → onUserInput per spec interface contract
- Add in-memory ConcurrentHashMap conversation history to DefaultRouterFacade
- Make RouterRepository.getRouterState suspend
- Rename RouterConfig.keepLast → conversationKeepLast, fix defaults (6, 4096)
- Refactor InfrastructureModule.createRouterFacade to self-assemble internally
- Fix FileReadTool: allowedPaths was dead constructor param (@SuppressUnusedParameter);
now stored as private val and enforced in validateRequest
- Disable koverVerify on modules tested via testing/ submodules or with
hardware/integration dependencies (24 modules); build gate now passes clean
- SessionOrchestrator: wire T2/T3/T4 approval gate before tool execution;
emit OrchestrationPausedEvent/ApprovalRequestedEvent, await decision,
return rejection as ERROR context entry so LLM sees the denial;
propagate tool ERROR entries as StageExecutionResult.Failure
- SandboxedToolExecutor: remove dead code and simplify
- InfrastructureModule: minor wiring cleanup
- LlamaCppInferenceProvider / build.gradle: related build fixes
New core:artifacts-store interface + infrastructure/artifacts-cas
implementation: segment files + SQLite index, Blake3 hashing,
group-commit fsync via flushBefore, recovery tail-scan, manual
compactor, and oldest-first disk-cap evictor.
Inference events now carry promptArtifactId / responseArtifactId;
orchestrators put bytes before emitting. SqliteEventStore wraps
its txn in artifactStore.flushBefore so segment data is fsynced
before the event commit, making the crash window non-corrupting
(TailScanner re-indexes orphan tail records on reopen).
Compactor and evictor are mutually exclusive via maintenanceMutex.
Step 9 (cloud sync) deferred to a later epic.
See docs/reviews/2026-05-18-cas-steps-1-8-review.md for the final
review.
kami