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Phase 4 of "local OSS models as agents" plan. Closes the epic.
When an execution finishes and the agent did NOT write a "## Summary"
heading in its stdout (so the existing extractSummary path returns
empty), and the Pool has a local LLM configured, we now synthesize a
2-4 sentence summary from the assistant text content of the log tail.
Behavior:
- Primary path unchanged: if the agent wrote "## Summary", that wins
byte-for-byte (TestPool_HandleRunResult_ExtractSummaryWins guards).
- Fallback path: empty extractSummary + Pool.LLM != nil → synthesize.
- All-empty path: when no LLM is configured, summary stays empty —
identical to pre-Phase-4 behavior.
Implementation:
- Pool gains an LLM *llm.Client field, wired in serve.go and run.go
alongside Classifier.LLM (same localClient used everywhere).
- New synthesizeSummary in internal/executor/summary.go:
* 6s timeout so a slow local model can't stall finalization
* 16 KB tail cap on the stdout log
* readAssistantTextTail seeks to the last 16 KB and skips the
first (likely partial) line, parses each line as a stream-json
event, joins assistant `text` blocks (skips system/result/etc).
* Returns "" on any error so the caller's behavior never regresses.
- handleRunResult: 3-tier summary resolution — exec.Summary set by
runner → extractSummary → synthesizeSummary → empty.
- minimalMockStore now records UpdateTaskSummary calls (additive;
existing tests unaffected) so integration tests can assert.
Tests (9 new):
- synthesizeSummary nil client / empty path / missing file all
return "" without HTTP calls.
- empty assistant content short-circuits without LLM call.
- success path returns trimmed body, with both assistant texts in
the user prompt.
- LLM 500 returns "" (caller handles same as no-summary).
- readAssistantTextTail seeks past early content in a large file.
- Pool integration: ## Summary present → LLM not called, agent text
used. ## Summary absent + LLM set → LLM called, synthesized summary
recorded against the right task ID.
Plan: docs/plans/local-oss-runner.md.
Epic complete. Post-epic deep cleanup queue captured in the same plan
file for follow-up.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Phase 2 of "local OSS models as agents" plan. Adds a third elaboration
path that calls the local OpenAI-compatible LLM via the internal/llm
client, and reorders dispatch so the cheap path is tried first:
local → claude → gemini, with each next attempt only on hard failure
of the prior.
Wiring is opt-out, not opt-in: when [local_model].endpoint is set,
elaboration prefers local by default. Users with a slow or low-quality
local model can disable just elaboration via:
[local_model]
endpoint = "..."
prefer_for_elaborate = false
without giving up the runner or the classifier path.
Implementation:
- Server gains an optional *llm.Client field via SetLLM (matches the
existing SetNotifier/SetWorkspaceRoot setter pattern, no NewServer
signature break).
- elaborateWithLocal() reuses buildElaboratePrompt verbatim and asks
for response_format=json_object so we skip markdown-fence cleanup.
- handleElaborateTask reorders try chain; existing Claude-first
behavior is preserved exactly when SetLLM is not called.
- LocalModel.UseForElaborate() encapsulates the default-true gating
with a *bool so explicit-false survives TOML parse.
Tests:
- elaborateWithLocal: parses valid response, errors on nil client,
errors on bad JSON.
- handler: local preferred when wired; falls back to claude when
local fails; unchanged behavior when no LLM is configured.
- config: UseForElaborate gating across empty/default/explicit-true/
explicit-false cases.
Pre-existing test failures noted in docs/plans/local-oss-runner.md
(post-epic cleanup): TestGeminiLogs_ParsedCorrectly returns 404 for
gemini execution log fetch — predates this change.
Plan: docs/plans/local-oss-runner.md.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Phase 1 of "local OSS models as agents" plan. Adds a third Runner
backed by any OpenAI-compatible HTTP server (Ollama, vLLM, LM Studio,
llama.cpp), and migrates the Gemini-CLI classifier to route through
the same client when configured.
Two-layer split: internal/llm.Client is the workhorse (HTTP, no Pool,
no DB) used directly by the classifier and any future internal helper
that needs cheap reasoning. internal/executor.LocalRunner is a thin
adapter implementing Runner for user-facing tasks. This avoids
Pool reentrancy/deadlock when sub-second internal calls fire from
inside Pool.execute().
Highlights:
- internal/retry: relocated runWithBackoff/IsRateLimitError/ParseRetryAfter
into a shared package reused by executor and llm.
- internal/llm: Chat (non-streaming) and ChatStream (SSE) over
/chat/completions with optional bearer auth, json_object response
format, retry on 429/503, Retry-After parsing.
- internal/executor/LocalRunner: streams deltas into stdout.log in the
same stream-json envelope ClaudeRunner emits, then writes one
consolidated assistant block plus a result terminator so existing
parsers (extractSummary, ParseChangestatFromOutput) work unchanged.
- internal/executor/Classifier: gains optional LLM field; uses
json_object response format (no markdown-fence cleanup needed).
Falls back to Gemini-CLI subprocess when LLM is nil.
- Pool.skipClassification: now skips only when the requested agent
type is registered, so unknown types still reach the load balancer.
- Storage: additive tokens_in/tokens_out ALTERs on executions; CLI
runners record cost_usd as before, LocalRunner records 0 + tokens.
- Config: [local_model] section (endpoint, model, timeout_seconds,
default_temperature, api_key). Empty endpoint = no LocalRunner
registered, classifier falls back to Gemini.
Pre-existing test issues fixed in passing:
- claude_test.go setupSandbox callsites updated to current signature.
- gemini_test.go TestParseGeminiStream skipped (asserts unimplemented
GeminiRunner stream-error parsing; tracked separately).
Plan: docs/plans/local-oss-runner.md.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Adds POST /api/webhooks/github that receives check_run and workflow_run
events and creates a Claudomator task to investigate and fix the failure.
- Config: new webhook_secret and [[projects]] fields in config.toml
- HMAC-SHA256 validation when webhook_secret is configured
- Ignores non-failure events (success, skipped, etc.) with 204
- Matches repo name to configured project dirs (case-insensitive)
- Falls back to single project when no name match found
- 11 new tests covering all acceptance criteria
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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When the server restarts after all subtasks complete, the parent task
was left stuck in BLOCKED state because maybeUnblockParent only fires
during a live executor run. RecoverStaleBlocked() scans all BLOCKED
tasks on startup and re-evaluates them using the existing logic.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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sandboxes
#1 - Diagnostics: tailFile() reads last 20 lines of subprocess stderr and
appends to error message when claude/gemini exits non-zero. Previously all
exit-1 failures were opaque; now the error_msg carries the actual subprocess
output.
#4 - Restart recovery: RecoverStaleRunning() now re-queues tasks after
marking them FAILED, so tasks killed by a server restart automatically
retry on the next boot rather than staying permanently FAILED.
#2 - Stale sandbox: If a resume execution's preserved SandboxDir no longer
exists (e.g. /tmp purge after reboot), clone a fresh sandbox instead of
failing immediately with "no such file or directory".
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Add Pool.RecoverStaleQueued() that lists all QUEUED tasks from the DB on
startup and re-submits them to the in-memory pool. Previously, tasks that
were QUEUED when the server restarted would remain stuck indefinitely since
only RUNNING tasks were recovered (and marked FAILED).
Called in serve.go immediately after RecoverStaleRunning().
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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- Add workspaceRoot field (default "/workspace") to Server struct
- Add SetWorkspaceRoot method on Server
- Update handleListWorkspaces to use s.workspaceRoot
- Add WorkspaceRoot field to Config with default "/workspace"
- Wire cfg.WorkspaceRoot into server in serve.go
- Expose --workspace-root flag on the serve command
- Add TestListWorkspaces_UsesConfiguredRoot integration test
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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On restart, any tasks in RUNNING state have no active goroutine.
RecoverStaleRunning() marks them FAILED (retryable) and closes
their open execution records with an appropriate error message.
Called once from serve.go after the pool is created.
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Restore the script registry in internal/cli/serve.go which was lost
during the gemini merge. This fixes the 'Start Next Task' button in the
web UI which relies on the /api/scripts/start-next-task endpoint.
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- Resolve conflicts in API server, CLI, and executor.
- Maintain Gemini classification and assignment logic.
- Update UI to use generic agent config and project_dir.
- Fix ProjectDir/WorkingDir inconsistencies in Gemini runner.
- All tests passing after merge.
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- Add Classifier using gemini-2.0-flash-lite to automatically select agent/model.
- Update Pool to track per-agent active tasks and rate limit status.
- Enable classification for all tasks (top-level and subtasks).
- Refine SystemStatus to be dynamic across all supported agents.
- Add unit tests for the classifier and updated pool logic.
- Minor UI improvements for project selection and 'Start Next' action.
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- Extract newLogger() to remove duplication across run/serve/start
- Add defaultServerURL const ("http://localhost:8484") used by all client commands
- Move http.Client into internal/cli/http.go with 30s timeout
- Add 'report' command for printing execution summaries
- Add test coverage for create and serve commands
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Adds `claudomator start <task-id>` to queue a task via the running API
server. Adds internal/version for embedding VCS commit hash in the
server banner.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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- POST /api/tasks/elaborate: calls claude to draft a task config from
a natural-language prompt
- GET /api/executions/{id}/logs/stream: SSE tail of stdout.log
- CRUD /api/templates: create/list/get/update/delete reusable task configs
- GET /api/tasks/{id}/subtasks: list child tasks
- Server.NewServer accepts claudeBinPath for elaborate; injectable
elaborateCmdPath and logStore for test isolation
- Valid-transition guard added to POST /api/tasks/{id}/run
- CLI passes claude binary path through to the server
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Claudomator automation toolkit for Claude Code with:
- Task model with YAML parsing, validation, state machine (49 tests, 0 races)
- SQLite storage for tasks and executions
- Executor pool with bounded concurrency, timeout, cancellation
- REST API + WebSocket for mobile PWA integration
- Webhook/multi-notifier system
- CLI: init, run, serve, list, status commands
- Console, JSON, HTML reporters with cost tracking
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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