…th legacy)

Refactor experience production so heavy data (tokens/logprobs/routed_experts)
no longer rides runner->scheduler->coordinator as serialized bytes. The vLLM
recorder now captures it in-process into a MemoryStore keyed by task_id, and
the coordinator pulls it at finalize time via /records/consume_task. Runners
ship only a small reward map. Both paths coexist behind
`explorer.use_recorded_experience` (default off = legacy).

Recording module (trinity/common/models/vllm_patch/recording/):
- store: drop SqlStore; MemoryStore.update_reward_by_task_id stamps
  reward/run/task on a whole task-id group, pops and returns it (the
  in-memory replacement for the SQL HistoryRecorder join).
- recorder: track in-flight record tasks; add flush() (await pending +
  queue.join) so a consume sees a quiesced store; honor skip_recording_ctx.
- models: build_experience emits one Experience per completion (n>1) with
  info["sample_index"]; eid.suffix=request_id kept for traceability.
- context: add skip_recording_ctx; task_id already flows via api_key
  (RecordingIdentityMiddleware) and now also via VLLMModel.chat (Ray entry).
- query: POST /records/consume_task (flush -> update_reward_by_task_id ->
  serialize_many); drop the SqlStore 503 branch.
- config/server: remove RecordingConfig entirely; the logprob width is a
  recorder-internal constant (we store only the chosen token, which vLLM
  force-includes at logprobs=1). No static config threaded through launch.

task_id propagation (Ray entry, same contextvar as the HTTP middleware):
- vllm_model: chat/generate accept task_id_key, set task_id_ctx around
  _generate_internal; logprobs sets skip_recording_ctx (auxiliary forward).
- model: ModelWrapper.chat/chat_async forward task_id_key; SGLang.chat
  accepts-and-ignores it (recording is vLLM-only).

Coordinator + runner + workflow:
- rollout_coordinator: _resolve_rank_urls (ray.get_actor per engine) and a
  recording-mode finalize that fans out /records/consume_task per engine,
  deserializes, and feeds objects to the pipeline (no re-serialization).
- experience_pipeline: process_experiences(exps) public object entry.
- workflow_runner: recording mode returns a pickled reward map keyed by the
  per-sample task_id_key the workflow stamped; legacy path unchanged.
- workflow: SimpleWorkflow/AsyncSimpleWorkflow run a per-sample n=1 loop in
  recording mode (distinct task_id_key per sample == reward unit for GRPO),
  legacy n=repeat_times single-call path unchanged.
- config: ExplorerConfig.use_recorded_experience flag.

SQL path removal (MemoryStore only):
- delete proxy/recorder.py (HistoryRecorder) and proxy_test.py; proxy
  service/app drop /feedback, /commit, record_feedback, submit_experiences,
  ready_experiences (keep allocate_model + weight sync); allocator no longer
  fills record_db_url; drop InferenceModelConfig.record_db_url and the dead
  ExplorerConfig.db_url field; RecordingConfig deleted.

Serve-mode external reward reporting is intentionally left unimplemented this
version (proxy /feedback//commit removed); the affected serve integration
tests (TestServeWithTrainer, ServeTest) are skipped with a pointer to the
recording refactor plan. convert_messages_to_experience redirect (multi-turn)
is deferred with TODOs at its call sites.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

…-x-c/Trinity-RFT into feature/model_self_record_experience