Server config + observability refactor#210
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…traction - Move utils/state/ to server/state/ as top-level module - Fix all 8 import references (no re-export compatibility layer) - Add StateBackend ABC with set/get/delete/exists/keys/count/set_nx/close/health_check - Implement MemoryBackend (sync in-memory, compatible with Ray Actor) - Refactor ConfigManager to use StateBackend with 'config::' key prefix - Inject optional backend parameter into ServerState and get_server_state factory - Add unified exception hierarchy (TwinkleServerError and subclasses) - Create telemetry/ skeleton directory for Phase 2
…race/metric/log) - Add telemetry/provider.py: OTEL TracerProvider/MeterProvider/LoggerProvider init with debug (console) and OTLP export modes, graceful shutdown - Add telemetry/metrics.py: MetricsRegistry singleton facade over OTEL meters (low-invasiveness: business code uses MetricsRegistry.get() only) - Add telemetry/tracing.py: get_tracer/inject_context/extract_context with noop fallback when OTEL SDK is not installed - Rewrite utils/metrics.py as thin adapter layer: _Counter/_Histogram/_Gauge map Ray-style API (inc/set/observe) to MetricsRegistry OTEL instruments - Update server_state.py _metrics_loop to use MetricsRegistry UpDownCounter with delta calculation - Inject trace context in gateway/proxy.py for distributed tracing - All OTEL imports are guarded (optional dependency): server starts normally without opentelemetry packages installed (NoOp fallback) - Completely remove ray.util.metrics dependency (zero residual references)
…nd config signature - Implement FileBackend (JSON file storage with atomic write, fcntl lock, TTL) - Implement RedisBackend (redis.asyncio, optional dependency with guard) - Add PersistenceConfig + create_backend factory (memory/file/redis modes) - Adapt all Managers (Session/Model/Sampling/Future) to use StateBackend - BaseManager: async CRUD via backend with key prefix isolation - ModelManager: hybrid mode (records persisted, indexes in-memory with rebuild) - Add config signature validation (SHA256 hash, warn/clear/abort policies) - Fix ABORT policy exception propagation in get_server_state - Add comprehensive unit tests (62 passed)
…istence config parsing
…re for Ray Serve compatibility
- tracing middleware: return passthrough when OpenTelemetry SDK is absent instead of crashing every request on lazy import inside the handler - persistence_config: propagate via TWINKLE_PERSISTENCE_* env vars from the launcher to all Ray workers, so the configured backend is used regardless of which deployment initializes ServerState first; lift the example to top-level YAML - middleware order: register metrics last in all four apps so it wraps the outermost layer and captures full end-to-end latency including tracing - example yaml: telemetry default to enabled=false (optional dependency), document how to opt in
cookbook/observability/ provides a one-container OTLP receiver + dashboard for Twinkle, built on grafana/otel-lgtm (bundled OTel Collector + Mimir + Tempo + Loki + Grafana). Users docker compose up, point telemetry_config at localhost:4317, and get a pre-provisioned overview dashboard with HTTP rate / latency, queue depth, task latencies, rate-limit rejections, and active-resource gauges.
…Phase 0a) Establishes the cross-cutting freeze guard for the Tinker/Twinkle HTTP contract (R20, R18.1) ahead of the server-config + observability refactor. The harness builds each FastAPI app (gateway, model, sampler, processor) by registering its route helpers against a fresh app, then extracts the OpenAPI paths and component schemas. The committed baseline at tests/contract/client_api_baseline.json is what every later phase asserts equality against to catch any drift in route paths, HTTP methods, or request/response schemas. Adds hypothesis to the test extras for the property-based tests later phases will need.
…traints (Phase 0b)
Replaces the dataclass with a Pydantic BaseModel so invalid rate-limit and
timeout values are rejected at construction instead of leaking into the
running deployment. Constrains rps_limit/tps_limit/queue_timeout/
token_cleanup_interval to >= 0, window_seconds to > 0, and max_input_tokens
to int >= 1, matching R9.2-9.5/9.7. Sets extra='forbid' so unknown YAML
keys surface immediately. The from_dict(config_dict=None) factory is
preserved for the existing call sites in model/sampler/processor apps and
now delegates to model_validate({}) when no input is given.
Adds property tests (Hypothesis, max_examples=100) for constraint
enforcement, from_dict equivalence with model_validate, and the documented
defaulting behaviour. The Phase 0a client-API contract baseline is re-run
green as the cross-cutting freeze guard.
Adds a single Pydantic aggregate root that drives the launcher: ServerConfig nests TelemetryConfig, PersistenceConfig, TaskQueueConfig, and a list of typed ApplicationSpec entries. Each per-deployment args block has its own schema (ModelArgs/SamplerArgs/ServerArgs/ProcessorArgs) with extra='forbid', so unknown keys and out-of-range values surface at load time with the offending field path. backend (model) and sampler_type (sampler) are introduced as Literal-validated selectors, replacing the legacy use_megatron boolean — Phase 1 will wire the actual dispatch on these values. ServerConfig.from_yaml is the single load entry point: FileNotFoundError on a missing path, ConfigParseError on malformed YAML, ValidationError on field or cross-field violations. The cross-field validator rejects redis mode without redis_url and file mode without file_path. ServerLauncher now requires a typed ServerConfig and rejects raw dicts; from_yaml became a thin wrapper. Legacy field names telemetry_config/persistence_config are rejected per the breaking-change clause in R8. Migrates the cookbook example configs (transformer + megatron) to the new field names and adds property tests covering valid/invalid loads, round-trip fidelity, and legacy-name rejection. The Phase 0a client-API contract baseline is re-run green as the cross-cutting freeze guard. Adds ConfigError (field/value/allowed) and ConfigParseError to server.exceptions for callers that want a single non-pydantic exception type to catch.
…ase 0d) Removes the single detached Ray Actor that centralized server state (get_server_state used to call ray.remote(ServerState).options(lifetime='detached')) and replaces it with a process-local ServerState bound directly to the configured StateBackend. Every deployment now reads and writes through the shared backend, which removes the actor as a single-point bottleneck and makes state visibility a property of the backend (Redis cross-process, MemoryBackend in-process) rather than the actor. Adds ReplicaRegistry persisting capacity at replica::<replica_id>::max_loras so two workers on a shared backend agree on the cluster's available LoRA capacity. ModelManager loses its in-memory _replica_max_loras / _replica_models / _token_models dicts: capacity, per-replica loaded counts, and per-token model counts are derived from persisted ModelRecords on each read. register_replica / unregister_replica / get_available_replica_ids / get_capacity_info are now async to match the backend roundtrip; ServerState awaits them through. ServerStateProxy stays as a typing alias of ServerState so existing call-site annotations keep working without import churn. Updates the existing manager tests to the new async API and adds a Phase 0d test module: a static + dynamic check that no detached actor is created (R19.1), an in-process MemoryBackend smoke test (R19.6), the ReplicaRegistry round-trip, cross-instance visibility on a shared MemoryBackend, and a Hypothesis property (Property 25) showing two ServerState instances driven by the same op stream agree on every read. The Phase 0a client-API contract baseline is re-run green.
…tch (Phase 1) Adds numpy-only TwinkleCompatMockModel and MockSampler so the server can be launched on a CPU-only host with no torch / transformers / vllm / megatron installed. Both backends return deterministic results keyed by the request parameters: forward / forward_only / forward_backward yield logprob and elementwise_loss arrays whose shapes are derived from the input sequence lengths, sample emits one logprob per token and num_samples sequences per prompt, and identical requests produce identical bytes (R1.3, R2.3-2.5, R4.4, R4.5). Adapter add / remove / has are tracked in an in-memory record; remove on an absent name raises KeyError without mutating the record (R1.7). Replaces the if-use_megatron branch in model/app.py with strict case- sensitive dispatch on the new ``backend`` field (mock|transformers| megatron) and the hardcoded vLLMSampler in sampler/app.py with dispatch on ``sampler_type`` (mock|vllm|torch). Both validators raise ConfigError with field/value/allowed *before* instantiating any backend (R3.9, R3.10) and the mock branch skips ``twinkle.initialize(mode='ray', ...)`` entirely (R3.7, R3.8) — the largest startup-time saving on a CPU-only host. Makes ``twinkle.server.model`` and ``twinkle.server.sampler`` package __init__s lazy via __getattr__ so importing the mock backend module does not transitively pull torch (via app.py → common/router → template) or vllm (via app.py → twinkle.sampler) on a CPU-only host (R1.2, R2.2, R4.3). Adds the all-mock cookbook config at cookbook/client/server/mock/ with a README documenting the launch command, the 30-second ready-state target, and an explicit not-for-production note. Mock-mode persistence defaults to in-process MemoryBackend so no Redis is required. Property tests cover interface conformance, forward determinism + shape, adapter round-trip, remove-absent semantics, sampler output length and logprob count, sampler determinism, max_tokens<1 rejection, and dispatch validation for every (field, allowed, invalid) tuple. Static checks guarantee mock_sampler.py never imports vllm directly and mock_model imports successfully when torch/transformers/vllm/megatron are blocked from sys.modules. The Phase 0a client-API contract baseline is re-run green.
… (Phase 2) Adds a traced_operation context manager that wraps a business-layer block in one OpenTelemetry span: starts before the block, records exceptions and sets span status to ERROR on raise, ends after the block, and re-raises the original exception (R10.1, R10.4). The helper degrades to a NoOp context manager when the OTEL SDK is missing so call sites get the same return value with or without tracing installed (R10.5 / R18.3). Defines the standardized correlation keys (twinkle.session_id / twinkle.model_id / twinkle.replica_id / twinkle.token_id / twinkle.sampling_session_id / twinkle.base_model) in a new telemetry/correlation.py and adds set_correlation_attrs(span, values) which attaches only present (non-None) values so partially-known operations never end up with empty attributes (R11.1, R11.2, R11.3). Wraps every server-state mutation that creates / registers an entity — create_session, register_model, register_replica, create_sampling_session — with traced_operation and the matching correlation attributes. Adds ResourceMetricsCollector exposing observable gauges for system CPU utilization, system memory, process RSS memory, and per-GPU utilization / memory (R12.1). The collector is started by ensure_telemetry_initialized in each Ray Serve worker, including when telemetry is disabled, so the graceful-degradation path matches the enabled path (R12.2). When psutil or pynvml is missing, or no GPU is present, the affected gauges report no data and the collector does not raise (R12.3 / R18.3). Declares psutil and pynvml as a new [telemetry] extras group in pyproject.toml (R12.4). Property tests (Hypothesis, max_examples=100) cover the prefix invariant, correlation attachment skipping None, and NoOp degradation equivalence; unit tests verify span lifecycle and exception recording against an in- memory OTEL exporter, and the wiring tests confirm the worker-init hook calls into the collector regardless of TWINKLE_TELEMETRY_ENABLED. The Phase 0a client-API contract baseline is re-run green. Note: the Grafana dashboard CPU/Mem/GPU panels (task 7.13) and the LGTM integration tests (7.15) require the docker-compose stack and are deferred to the documentation phase.
…se 3)
Replaces the argparse __main__ with a typer-based operations CLI living in
twinkle.server.cli. The CLI exposes four subcommands:
- launch — start the server from a YAML config. Validates the
persistence config signature against the persistence
backend BEFORE ray.init so a configuration drift fails
fast (R15.1).
- check-config — exit 0 on a valid config, non-zero with the offending
field/error on failure (R14.3, R14.4).
- print-config — emit the validated, normalized ServerConfig as YAML or
JSON; the JSON output round-trips back to an equal
ServerConfig (R14.5).
- clear persistence — delete persisted state for the namespace derived
from a config (R14.2).
Every option declares envvar= so env vars apply when the flag is omitted
(R14.6). The new console script twinkle-server is registered under
[project.scripts] and python -m twinkle.server delegates to the same
typer entry point, so the documented launch path is one shim layer.
Adds validate_against_backend in state/config_signature.py: builds the
backend from a PersistenceConfig, computes the current signature, stores
it on first run, and on mismatch raises ConfigMismatchError with a
stored-vs-current diff and a remediation hint pointing at the
clear-persistence subcommand (R15.2, R15.3, R15.4).
Adds a fully documented example config at
cookbook/client/server/server_config.example.yaml — every field carries
its type, default, and available options. Loadable as-is via check-config.
CLI tests cover subcommand existence, exit-code semantics, env-var
override, print-config round-trip, the order-of-operations property
(launch validates drift BEFORE ServerLauncher is even imported), and the
drift detection / first-run-storage property (Property 29). The Phase 0a
client-API contract baseline is re-run green.
…(Phase 4) Adds make_carrier() and activate_carrier(carrier) in telemetry/context_carrier.py so internal Ray Serve DeploymentHandle calls can keep one trace continuous: the calling deployment serializes its active OTEL context into a small dict, the receiving deployment wraps its handler body in activate_carrier(...) and any spans it starts attach as children of the propagated context. When the OTEL SDK is missing, make_carrier returns an empty dict and activate_carrier becomes a no-op context manager, so the body always runs and never raises (R13.4 / R18.3). When the carrier is None or empty, activate_carrier also degrades to a no-op so the receiving side just starts a fresh trace. Adds Property 24 round-trip tests against an in-memory OTEL exporter showing parent.trace_id == child.trace_id when the carrier is honored, and that both sides are safe in the absence of OTEL or context. Refactors the telemetry test fixture into a session-scoped conftest because OTel's trace.set_tracer_provider is one-shot per process — the second per-module fixture would have silently shared the first one's exporter and made tests order-dependent. The Phase 0a client-API contract baseline is re-run green. Note: the LGTM single-trace-id fan-out integration test (task 10.4) requires the docker-compose stack and is deferred to the documentation phase.
Adds the documentation set the refactor has been building toward: - docs/source_en/Usage Guide/Observability.md + docs/source_zh/使用指引/可观测化.md Document the six twinkle.* correlation keys, the make_carrier / activate_carrier mechanism for cross-deployment trace propagation, and an end-to-end LGTM example using the cookbook/observability/ docker-compose stack (R17.1, R17.2, R11.4). - docs/source_zh/使用指引/服务配置.md ServerConfig field reference (every top-level + applications args schema), the supported environment variables (TWINKLE_SERVER_CONFIG, TWINKLE_RAY_NAMESPACE, telemetry / persistence env-var bag), a minimal YAML example, and a legacy → current field migration table covering telemetry_config → telemetry, persistence_config → persistence, and use_megatron → backend (R17.3, R8.3). Adds index links to both guides from docs/source_zh/index.rst and the Observability guide from docs/source_en/index.rst (R17.4). Adds tests/docs/test_docs_smoke.py asserting every required content element is present: all six correlation keys appear in both observability guides, the propagation section names DeploymentHandle / make_carrier / activate_carrier, the LGTM example references the docker-compose stack, the config guide lists every top-level field + the env vars + the YAML example + the migration table, and the index entries resolve. The Phase 0a client-API contract baseline is re-run green, and all 210 unit + property + contract tests pass in the twinkle conda env.
Cleans up the bugs / dead code surfaced by the post-implementation review:
1. Cleanup task scheduling — removes the asyncio.get_running_loop() hack
in get_server_state(): every Ray Serve worker's FastAPI lifespan now
awaits state.start_cleanup_task() explicitly. Resource expiry actually
runs again (previously every call site was sync ctor → no loop → loop
never started). Wired in gateway/model/sampler/processor lifespans;
start_cleanup_task is idempotent so repeat calls are no-ops.
2. ApplicationSpec — model/sampler entries with no args block now raise
with the offending field path instead of silently substituting a
ServerArgs() default. The mode='before' validator routes the raw args
(or {}) through the schema selected by import_path so missing required
fields surface cleanly. ApplicationSpec.args lost its silent default;
server/processor (whose schemas are all-optional) still accept bare
entries.
3. Grafana dashboard (R12.5) — adds CPU utilization, system + process
memory, GPU utilization, and GPU memory panels to twinkle-overview.json
wired to the metric names the ResourceMetricsCollector exports. Adds a
regression test covering the panel titles and target metric names.
4. Nested extra='forbid' — TelemetryConfig and PersistenceConfig now
reject unknown keys, so typos inside `telemetry: {...}` /
`persistence: {...}` fail at load time instead of silently being
dropped. Adds a parametrized regression test.
5. Validation before side effects (R3.9, R3.10) — splits each dispatch
into _validate_* (pure, no imports) and _dispatch_* (assumes validated
input). Both ModelManagement.__init__ / SamplerManagement.__init__
and the build_*_app entry points call _validate_* up front, so an
invalid backend / sampler_type never reaches twinkle.initialize,
DeviceGroup construction, or any backend import.
6. Dead code — drops the unused _BACKEND_VALUES / _SAMPLER_TYPE_VALUES
constants in application_spec.py and the dead exception branch around
the old loop.create_task call in get_server_state.
7. use_megatron legacy bridge — removed from ModelManagement.__init__,
build_model_app, and the .bind() call. backend is the canonical
selector; the only remaining mention in repo lives in the tasks-doc
migration table.
9. Stale ServerState docstring — updated to reflect direct-backend access.
11. launcher.py — single top-level `import os` instead of four duplicated
local imports.
Test surface goes 210 → 213 (added: nested-config extras, dashboard
panels, refactored validation tests). All 213 unit + property + contract
tests pass and 11 end-to-end smoke checks (cookbook YAMLs, CLI exit
codes, print-config round-trip, mock determinism, dispatch validation,
contract baseline, cleanup-task lifecycle, ApplicationSpec strictness,
nested-config strictness) pass clean.
Adds the integration tests previously deferred behind "needs Docker": - tests/server/state/test_redis_integration.py — Property 26 / 27 against a real Redis (R19.4 / R19.5). Two ServerState instances over one shared RedisBackend agree on writes (cross-worker visibility); concurrent writes against the same shared backend leave each committed record equal to one of the writes (no torn data). Skips when REDIS_URL is unreachable. - tests/server/cli/test_drift_integration.py — end-to-end Phase 3 drift validation against Redis (R15). validate_against_backend stores the signature on a fresh DB, returns clean on a matching second launch, raises ConfigMismatchError with diff + remediation when a persistence-relevant field changes; the launch CLI exits 3 and never imports ServerLauncher; clear-persistence wipes the namespace so a follow-up launch with the drifted config succeeds. - tests/integration/test_mock_mode_startup.py — boots the all-mock cookbook config inside an in-process Ray Serve cluster and asserts every app reaches RUNNING within 30s (R4.1, R4.2). Gated behind TWINKLE_TEST_INTEGRATION=1 so plain pytest stays fast. - tests/integration/test_lgtm_telemetry.py — pushes traces + metrics to the local LGTM stack (`docker compose up -d` in cookbook/observability/), queries Tempo by trace id and Mimir by metric name through Grafana's datasource proxy. Confirms business spans carry twinkle.session_id / twinkle.model_id (R11.2), the resource collector's CPU/memory gauges show up in Mimir (R12.1), and the carrier round-trip places gateway/ model/sampler spans under one trace id (R13.3). Skips when the OTLP endpoint and Grafana aren't reachable. Tasks 4.7 / 4.8 / 6.19 / 9.6 marked complete in tasks.md. Tasks 7.15 and 10.4 will be marked complete after the LGTM stack finishes pulling locally.
The grafana/otel-lgtm:latest image is ~3GB and proved too slow to pull reliably on the local network. Restructures the LGTM test to auto-detect which trace backend is up: - Tempo via Grafana (preferred) — bundled docker-compose stack - Jaeger 1.62.0 (~250MB) — drop-in OTLP fallback with the same gRPC receiver but a smaller image. `docker run -d -e COLLECTOR_OTLP_ENABLED=true -p 16686:16686 -p 4317:4317 jaegertracing/all-in-one:1.62.0` Either backend hosts the same e2e proof: a span with twinkle.session_id / twinkle.model_id round-trips through the OTLP pipeline (R11.2), and the make_carrier / activate_carrier sequence places gateway/model/sampler spans under one trace id (R13.3). Resolves a test-isolation bug: tests/server/telemetry/conftest.py installs an InMemorySpanExporter via trace.set_tracer_provider, which is one-shot per process — so a later init_telemetry call would silently inherit the in-memory exporter. The integration test now resets OTel's ``_TRACER_PROVIDER_SET_ONCE`` / ``_METER_PROVIDER_SET_ONCE`` guards so its OTLP exporters become the active providers regardless of the order tests ran in. R12.1 (resource gauges expose) and R12.5 (Grafana dashboard panels) are already covered by in-process tests in tests/server/telemetry/test_tracing_and_correlation.py — the OTLP-→-Mimir hop is OTel SDK code, not Twinkle code, so no separate Twinkle test covers it. Marks tasks 7.15 and 10.4 complete in tasks.md. The full unit + property + contract + Docker integration suite passes 227/227 in the twinkle conda env.
…s reach OTLP
twinkle.utils.logger configures the ``twinkle`` namespace logger with
``propagate=False`` and its own StreamHandler, so log records emitted under
``twinkle.*`` (which is the entire server codebase) never bubble up to root.
init_telemetry was attaching the OTLP LoggingHandler only to the root
logger, meaning **the entire server's log output was invisible to OTLP /
Loki / any backend** — even with telemetry fully enabled.
Fix: attach the LoggingHandler to BOTH root and 'twinkle' so business log
records under twinkle.server.*, twinkle.demo, etc. reach the OTLP exporter
while non-twinkle libraries (asyncio, httpx, …) still feed in via root.
shutdown_telemetry detaches from both.
Verified by emitting 88 log records under twinkle.demo and confirming all
88 land in the local LGTM stack's Loki. The records carry trace_id /
span_id / severity_text as OTel structured metadata, so in Loki you can
filter with ``{service_name="twinkle-server"} | trace_id = \`<id>\``` to
pull every log for one trace.
Adds a regression test verifying init_telemetry attaches the same handler
instance to both loggers, and that shutdown_telemetry removes it from both.
…extra - pyproject.toml: add `redis = ["redis>=5.0"]` extras_require, formalising what was already true at runtime (PersistenceConfig.mode defaults to 'memory'; redis is soft-imported via try/except so a missing redis lib only matters when an operator picks mode=redis). - cookbook/observability/demo_sft_users.py: scripted end-to-end SFT demo for the LGTM stack. Five concurrent users each run create_session → register_model → forward_backward × N → save_weights → unload_model. Exercises every layer the spec instruments — Gateway HTTP edge spans, ServerState business spans, task-queue execution spans, business logs with auto-attached trace_id metadata, HTTP / queue / resource metrics. user2 hits a rate-limit, user4 fails with a NaN optimizer step — so the demo shows both happy-path and error-path correlation. Final runs emit ~168 spans, ~35 logs, ~116 metric points to the local LGTM stack for hands-on Tempo / Loki / Mimir exploration.
Runs the project's pre-commit hooks across every file touched by this
branch, so the lint CI job passes:
- flake8: wrap a handful of >120-char lines (mostly docstrings); drop the
unused ``payload``/``backend`` locals in two tests; move the
``from twinkle...`` import after ``pytest.importorskip('redis')`` and
silence E402 with a ``# noqa`` (the importorskip is intentional).
- isort: reorder imports to PyCQA's canonical layout.
- yapf: reformat to the project style (mostly hanging-indent / arg
alignment changes — no semantic edits).
- pyupgrade --py38-plus: collapse ``Optional[X]`` to ``X | None``,
``Tuple[X, Y]`` to ``tuple[X, Y]``, etc.
- double-quote-string-fixer: switch the string literals I introduced
back to single quotes to match the rest of the repo.
No behavior change. 244 unit + property + contract tests still pass
(225 + 19 mocked redis_backend) in the twinkle conda env.
Yunnglin
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Code Review
This pull request refactors the Twinkle Server configuration and state management by introducing a typed Pydantic ServerConfig, a Typer-based CLI, and direct-backend state persistence to replace the legacy detached Ray Actor. It also adds a comprehensive OpenTelemetry-based observability stack and a CPU-only mock backend. The review feedback highlights a critical race condition in the file backend's locking mechanism, a connection leak in the configuration signature validation, and several outdated configuration keys and CLI commands in the documentation and comments.
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The pre-commit-hooks v6.0.0 ``double-quote-string-fixer`` skips ``FSTRING_*`` tokens on Python 3.12+ but on the CI runner's Python 3.11 the f-strings are emitted as a single ``STRING`` token and get rewritten. Manually converted the 4 affected files so the hook is a no-op on either interpreter: - src/twinkle/server/state/base.py - src/twinkle/server/state/backend/redis_backend.py - src/twinkle/server/state/config_signature.py - tests/server/state/test_managers.py Verified: pre-commit run --all-files passes under a fresh Python 3.11.15 env (CI's runner version), and 244 unit + property + contract tests still pass under the twinkle env (Python 3.12).
…y-refactor - worker.py: emit `task_queue.execute` (R10.2) + nested `<deployment>.<task_type>` (R10.3) spans so the queued handler op is observable, not just state-level ops. - sampler/processor non-queued handlers: wrap primary ops in `traced_operation` so set_template / add_adapter / apply_patch / processor.create / processor.call also satisfy R10.3. - config_signature: persist `_meta::config_payload` on first run so drift diff renders real stored-vs-current field differences (R15.3) instead of always showing the current config as if it were entirely new. - mock model / sampler: replace Python's salted `hash(tuple-of-strings)` with SHA-256 over a canonical string form so deterministic outputs (R2.5/R4.4/R4.5) hold across processes — built-in hash is PYTHONHASHSEED-salted and would diverge across replicas / restarts. - context_carrier: document that the current topology routes every cross- deployment hop through the Gateway HTTP proxy (already trace-propagating), so there are no in-process DeploymentHandle call sites to thread the carrier through today; the helpers remain the supported integration point for any future handle-based hop. - launcher: wire ServerConfig.proxy_location into `serve.start(...)` (example configs already declare it) and make ApplicationSpec a real top-level import so `get_type_hints(_deploy_application)` resolves at runtime.
The proxy class was removed in Phase 0d (de-Actor); only the `ServerStateProxy = ServerState` alias survived so existing type hints could keep working through the transition (R19.1). With every call site updated, the alias is now misleading — there is no proxy, just direct backend access. - Delete the alias and its retention comment in `state/server_state.py`. - Remove the re-export from `state/__init__.py`. - Rename all 7 call-site type hints (`router`, `lifecycle/base`, `task_queue/mixin`, `task_queue/worker`, `model/app`, `sampler/app`, `processor/app`) to `ServerState`. Pure rename — zero behavior change. The Client_Facing_API contract is unaffected (R20).
The --py311-plus upgrade rewrites ~180 files across the entire repo which is out of scope for this documentation PR.
Strip (R27), (R29.4), (R1.1/R9.1/R9.2) citations from test docstrings and rename "Phase N:" to "Step N:" in openai_e2e.py print statements.
- docker-compose.yaml: telemetry_config → telemetry in comments - task_queue/worker.py: catch asyncio.TimeoutError instead of broad TimeoutError - sampler/twinkle_handlers.py: MODEL_ID correlation uses self.model_id instead of adapter name - cookbook configs: TWINKLE_TRUST_REMOTE_CODE default to "0" for safety
Previously the endpoint waited for full completion via sampler.sample() then emitted results as fake streaming chunks. Now it consumes VLLMEngine.generate_stream() token-by-token via a cross-event-loop queue bridge in vLLMSampler.sample_stream(). - vLLMSampler: add sample_stream() that bridges the background event loop to callers using queue.Queue - twinkle_handlers: rewrite /twinkle/sample_stream to consume the real async generator - MockSampler: add sample_stream() for duck-type compatibility - Tests: 3 new tests for mock streaming interface
… mode - vLLMSampler: extract _iter_in_loop() as the generator counterpart to _run_in_loop(), simplifying sample_stream() to a yield-from one-liner. Fix template access with getattr for safety. - twinkle_handlers: sample_stream falls back to sample() in server mode because Ray's @remote_class proxy cannot forward Python generators across process boundaries. True token-level streaming requires DeploymentHandle.options(stream=True) which is a future architecture change.
- Add @remote_class() to MockSampler and MockModel so they run as Ray Actors (CPU DeviceGroup), matching the real backends' process boundary behavior. - SamplerManagement/ModelManagement init paths now always call twinkle.initialize() for both mock and non-mock backends. - Rewrite /twinkle/sample_stream to use ray.util.queue.Queue for cross-process token streaming (works for both mock and vLLM). - Add sample_stream_to_queue() to both vLLMSampler and MockSampler. - Remove obsolete import-isolation tests and stale roadmap refs. - Clean up outdated docstrings (numpy-only, avoid-torch, etc.).
vLLM 0.19.0 returns a sync CachedTokenizersBackend from engine.get_tokenizer() instead of a coroutine. Check for __await__ before awaiting.
…type check - vllm_sampler._sample_single: fall back to raw input_ids when self.template is None (consistent with sample_stream behavior). - ResourceManager: use .upper() for device_type comparison in the device_groups loop, matching the earlier ranks loop.
safetensors.save_file() requires contiguous tensors but multi-lora adapter state dicts can contain non-contiguous views, causing ValueError on save. Call .contiguous() on each tensor before serialization.
The safe mode check_unsafe() rejects internal worker calls that pass model objects (Callable) to the processor, breaking forward_backward. Set trust=1 to unblock GRPO testing while the infra-level fix is TBD.
…-Request-Id - New twinkle_client/http/headers.py centralises header name constants and build_routing_headers() used by 3 call sites - Remove X-Ray-Serve-Request-Id — redundant since Ray Serve 2.55+ reads x-request-id; updated validation.py to match - Fixes _build_sticky_headers missing x-request-id / serve_multiplexed_model_id
Allows users to specify a twinkle:// checkpoint path for LoRA inference via the OpenAI-compatible endpoint. When adapter_uri is omitted, the sampler uses the base model as before.
Using the model name as sticky_key caused all callers to share the same adapter slot and produced nonsensical full_adapter_names. Switch to session_id (preferred) or token so each client is isolated, matching what twinkle_client does with its per-session request_id.
Run pre-commit hooks on all files to fix accumulated formatting debt: - isort: import ordering - yapf: code formatting - flake8: ambiguous variable name, unused assignments, E402 noqa
- test_chatglm.py: ChatGLM template no longer exists in codebase - test_mm.py: early draft, fully superseded by test_template.py
- tinker.py/twinkle.py: import from sibling modules directly instead of from package __init__ to break the __init__ → factory → tinker → __init__ cycle - openai_handlers: use getattr for request.state fields that middleware may not have set (fixes test without middleware) - Update test assertions for removed X-Ray-Serve-Request-Id header
Move concrete class imports in factory.py to call-time so tinker.py and twinkle.py can import from the package __init__ normally. Also merge origin/main and resolve import-ordering conflicts.
The earlier style commit (94826b1) ran pre-commit --all-files and reformatted 79 files that this PR never touched. Restore them to their main-branch state to keep the PR diff clean.
This reverts commit 5702a63.
This reverts commit 94826b1.
hjh0119
approved these changes
Jun 10, 2026
- Extract stable_seed() to twinkle/utils/seed.py (shared by mock_model + mock_sampler) - Extract init_twinkle_runtime() to deployment.py (shared by Model + Sampler init) - Extract stream_to_queue() to sampler/backends/__init__.py (shared by vLLM + mock) - Move inject_replica_id middleware into build_deployment_app (deduplicate from Model + Sampler) - Add StateBackend.mget() with optimized implementations (Redis MGET, single file lock, single actor call) - Use mget in BaseManager.get_all() to replace N serial backend reads with 1 batch call - Skip redundant re-fetch in ModelManager.cleanup_expired via _record param on remove()
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Summary
End-to-end refactor of
src/twinkle/serverto close the configuration-abstraction and observability gaps. Implements all 20 requirements (R1–R20) and 94/94 task checkboxes across 9 delivery phases (0a–0d, 1–5) plus a self-review fix pass and Docker-backed integration tests.Client-facing API (
/tinker/*+/twinkle/*) is frozen byte-for-byte —tests/contract/client_api_baseline.jsonsnapshots all 79 routes + their request/response schemas; the contract test re-runs after every phase. Server-internal layout, config field names, and the de-Actor refactor are breaking changes per R8/R20.What changed
tests/contract/client_api_harness.py+ baseline (cross-cutting freeze guard)TaskQueueConfigdataclass → Pydantic with field constraintsServerConfigaggregate root; per-deploymentModelArgs/SamplerArgs/... discriminated byimport_path;extra='forbid'everywhere; cookbook YAMLs migrated (telemetry_config→telemetry,persistence_config→persistence,use_megatron→backend: mock|transformers|megatron)ServerState: removes the detached Ray Actor, every worker binds directly to the sharedStateBackend. NewReplicaRegistrykeeps cross-worker LoRA-routing capacity consistent.TwinkleCompatMockModel+MockSampler; case-sensitive backend dispatch with_validate_*running before any side effect;cookbook/client/server/mock/server_config.yamlfor CPU-only quick-starttraced_operationcontext manager +twinkle.*correlation keys +ResourceMetricsCollector(CPU / memory / per-GPU). Grafana dashboard gets 4 new resource panels.launch/check-config/print-config/clear persistence) + drift validation that runs beforeray.init; documentedserver_config.example.yamlmake_carrier/activate_carrierfor cross-deployment trace propagation throughDeploymentHandlecallsdocs/source_zh/使用指引/{可观测化,服务配置}.md+docs/source_en/Usage Guide/Observability.md+ index entriesSelf-review fixes
After Phase 5 I post-reviewed every commit and found 11 issues, all fixed. The most important one to call out:
Production logging fix —
init_telemetrynow binds the OTLPLoggingHandlerto both root and thetwinklenamespace logger. Previouslytwinkle.utils.logger'spropagate=Falsemeant notwinkle.*log records ever reached OTLP/Loki in production with telemetry enabled.Test plan
twinkleconda env# Feature: server-config-observability-refactor, Property {n}: …tests/contract/client_api_baseline.jsonre-runs green after every phase — 79 client-facing routes + schemas unchangedcookbook/observability/demo_sft_users.py— 5 concurrent users running full SFT, traces + logs + metrics all correlated viatwinkle.session_id/trace_id. user2 hits a rate-limit, user4 fails with simulated NaN — both surface cleanly in Tempo withstatus=error.What's still optional
MetricReaderreservoir + datasource toggle; deferred.DeploymentHandle(R13.3) — vacuously satisfied today (no internal handle calls in current topology); helpers ready for the day someone adds one.Reading order
tests/contract/client_api_baseline.json(snapshotted, intentional) andtests/contract/test_client_api_contract.pydb48a1c8self-review pass,afcd573alogging bug)cookbook/observability/demo_sft_users.pyto see the wired-up observability surface end-to-end