7 Commits

Author SHA1 Message Date
Zheng Feng
dcb2e687d5
feat(channels): add GitHub as a webhook-driven channel (#3754)
* feat(channels): add GitHub event-driven agents (#3754)

Add a webhook-driven GitHub channel with fail-closed webhook routing, deterministic per-agent PR/issue threads, mention-gated trigger fan-out, GitHub App token injection for sandboxed gh/git commands, and backend/AGENTS.md documentation.

* fix(llm-middleware): classify bare IndexError as transient

Upstream chat providers occasionally return 200 OK with an empty
generations list (observed against Volces "coding" on
ark.cn-beijing.volces.com). When that happens,
langchain_core.language_models.chat_models.ainvoke raises
``IndexError: list index out of range`` at
``llm_result.generations[0][0].message`` and kills the run.

Treat a bare IndexError reaching the middleware as a transient
upstream-payload glitch and route it through the existing
retry/backoff path instead of failing the whole agent run. The
retry budget and backoff schedule are unchanged.

Adds three regression tests covering the classifier and both the
recover-on-retry and exhausted-retries paths.

* fix(runtime): ignore stale LLM fallback markers from prior runs

When a run on a thread ends with the LLM-error-handling middleware emitting
a `deerflow_error_fallback`-marked AIMessage (e.g. after the IndexError
empty-generations classification fix lands), that message is persisted to
the thread's checkpoint as part of the messages channel. LangGraph replays
the full message history in `stream_mode="values"` chunks, so every
subsequent run on the same thread re-streams the stale fallback marker —
and the worker's chunk scanner faithfully picks it up, flipping
`RunStatus.success` to `RunStatus.error` for runs that themselves had
no LLM failure at all.

Snapshot the set of pre-existing message ids from the pre-run checkpoint
and thread it through `_extract_llm_error_fallback_message` /
`_try_extract_from_message` as a filter. Markers on history messages are
ignored; markers on fresh messages produced during this run still trip
the error path. Falls back to an empty set when the checkpointer is
absent or the snapshot can't be captured, preserving the prior behavior
on first-run / no-state paths.

Adds unit tests for the new filter (helper-level and `_collect_pre_existing_message_ids`)
plus an integration test exercising the full `run_agent` path with a stale
history checkpointer.

* fix(channels): make github channel fire-and-forget to avoid httpx.ReadTimeout on long runs

GitHub agent runs (clone -> edit -> test -> push -> PR) routinely exceed
the langgraph_sdk default 300s read deadline. The manager's runs.wait
call kept an HTTP stream open for the entire run lifetime, so the long
run blew up with httpx.ReadTimeout and the outer except branch then
released the dedupe key and emitted a false 'internal error' outbound.

The GitHub channel's outbound send is log-only by design: agents post to
the issue/PR via the gh CLI in the sandbox when they choose to comment
or create a PR. There is nothing for the manager to ferry back, so the
long-poll was pure overhead.

This change adds ChannelRunPolicy.fire_and_forget (default False) and
sets it True for the github channel. When fire_and_forget is True,
_handle_chat dispatches via client.runs.create (short POST, returns
once the run is pending) instead of client.runs.wait, and skips the
response-extraction + outbound-publish block. ConflictError on a busy
thread still trips the standard THREAD_BUSY_MESSAGE path so behavior on
the busy case is preserved for any future non-github fire-and-forget
channel.

Other (non-github) channels are unchanged: their policy defaults
fire_and_forget=False and they continue to dispatch via runs.wait.

Adds 6 regression tests in tests/test_channels.py::TestGithubFireAndForget:
- Default ChannelRunPolicy.fire_and_forget is False.
- The github policy registers fire_and_forget=True.
- github inbound calls runs.create, not runs.wait, with the right kwargs.
- github inbound publishes no outbound on success.
- ConflictError from runs.create still emits THREAD_BUSY_MESSAGE.
- Non-github channels (slack) still dispatch via runs.wait.

* test(lead-agent): accept user_id kwarg in skill-policy test stubs

The two GitHub-channel tests added in #3754 stubbed
_load_enabled_skills_for_tool_policy with a lambda that only accepted
`available_skills` and `app_config`, but the real function (and its call
site in agent.py) also passes `user_id`. This raised TypeError on every
run, failing backend-unit-tests.

Add `user_id=None` to match the three sibling stubs in the same file.

* refactor(gateway): disambiguate context-key set names

The two frozensets _INTERNAL_ONLY_CONTEXT_KEYS and _CONTEXT_ONLY_KEYS
shared a confusable "CONTEXT_ONLY" token in different orders, and the
first broke the _CONTEXT_<X>_KEYS pattern of its sibling
_CONTEXT_CONFIGURABLE_KEYS. Rename to make the distinct axes explicit:

  _CONTEXT_INTERNAL_CALLER_KEYS  - WHO: internal callers (scheduler) only
  _CONTEXT_RUNTIME_ONLY_KEYS     - WHERE: runtime context only, never configurable

Pure rename, no behavior change.
2026-07-04 22:56:24 +08:00
Huixin615
88e36d9686
fix(#3189): prevent write_file streaming timeout on long reports (#3195)
* fix(#3189): prevent write_file streaming timeout on long reports

Adds a layered defense against StreamChunkTimeoutError caused by oversized
single-shot write_file tool calls:

- factory: default stream_chunk_timeout to 240s for OpenAI-compatible
  clients (overridable via ModelConfig.stream_chunk_timeout in config.yaml)
- sandbox/tools: server-side 80 KB length guard on non-append write_file
  calls (configurable via DEERFLOW_WRITE_FILE_MAX_BYTES env var, 0 disables);
  rejects oversized payloads with a structured error pointing the model at
  str_replace or append=True
- middleware: classify StreamChunkTimeoutError as transient but cap retries
  at 1 via per-exception _RETRY_BUDGET_OVERRIDES (same-payload retry on a
  chunk-gap timeout buffers the same way upstream; full 3-attempt loop
  would stack 6-12 min of dead air)
- middleware: surface an actionable user-facing message for stream-drop
  exceptions instead of leaking the raw langchain stack
- prompts: add a routing-style File Editing Workflow hint to both lead_agent
  and general_purpose subagent prompts, pointing the model at str_replace
  for incremental edits (mirrors Claude Code's Edit / Codex's apply_patch)
- tests: behavioural coverage for size guard, retry budget override,
  stream-drop user message, factory default injection

Refs #3189

* fix(#3189): drop stream_chunk_timeout for non-OpenAI providers

Address CR feedback on PR #3195:

- factory: pop `stream_chunk_timeout` from kwargs for any model_use_path other than `langchain_openai:ChatOpenAI` instead of returning early. `ModelConfig.stream_chunk_timeout` is part of the shared schema, so a user-supplied value on a non-OpenAI provider would otherwise be forwarded to its constructor and raise `TypeError: unexpected keyword argument`.

- factory: rewrite docstring to describe the actual `exclude_none=True` behaviour (explicit null is excluded and falls back to the default) instead of the misleading "None falling out via exclude_none=True keeps its value".

- tests: add regression coverage asserting the kwarg is stripped before reaching a non-OpenAI provider's constructor.

Refs: bytedance#3189

* fix(#3189): restrict stream-drop user copy to StreamChunkTimeoutError only

Per CR on #3195: narrow _STREAM_DROP_EXCEPTIONS to StreamChunkTimeoutError. Generic httpx RemoteProtocolError / ReadError fall back to the standard 'temporarily unavailable' copy, since they routinely fire on transient network blips where the 'split the output' guidance is misleading. Retry/backoff classification is unchanged — both remain transient/retriable. Tests updated to reflect new copy, plus a symmetric regression test for ReadError.

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-06-07 17:47:11 +08:00
Nan Gao
79cc227917
fix(middleware): fix LLM fallback run status (#3321)
* Fix LLM fallback run status

* optimize LLM fallback maker extraction in streaming path
2026-05-31 22:42:13 +08:00
greatmengqi
38714b6ceb
refactor: thread app_config through middleware factories (#2652)
* refactor: thread app_config through middleware factories

Continues the incremental config-refactor sequence (#2611 root, #2612 lead
path) one layer deeper into the middleware factories. Two ambient lookups
inside _build_runtime_middlewares are eliminated and the LLMErrorHandling
band-aid removed:

- _build_runtime_middlewares / build_lead_runtime_middlewares /
  build_subagent_runtime_middlewares now require app_config: AppConfig.
- get_guardrails_config() inside the factory is replaced with
  app_config.guardrails (semantically identical — same default-factory
  GuardrailsConfig — verified by direct equality check).
- LLMErrorHandlingMiddleware.__init__ now requires app_config and reads
  circuit_breaker fields directly. The class-level
  circuit_failure_threshold / circuit_recovery_timeout_sec defaults are
  removed along with the try/except (FileNotFoundError, RuntimeError):
  pass band-aid — the let-it-crash invariant the rest of the refactor
  enforces.

Caller chain (already-resolved app_config sources):
- _build_middlewares in lead_agent/agent.py: reorder so
  resolved_app_config = app_config or get_app_config() is computed BEFORE
  build_lead_runtime_middlewares is called, then passed as kwarg.
- SubagentExecutor: optional app_config parameter (mirrors the lead-agent
  pattern); _create_agent does the same `or get_app_config()` fallback at
  agent-build time, so task_tool callers don't need to plumb app_config
  through yet (typed-context plumbing for tool runtimes is a separate
  refactor).

Tests:
- test_llm_error_handling_middleware: _make_app_config helper using
  AppConfig(sandbox=SandboxConfig(use="test")) — same minimal-config
  pattern conftest already uses. Three direct LLMErrorHandlingMiddleware()
  calls each followed by post-construction circuit_breaker mutation fold
  cleanly into _build_middleware(circuit_failure_threshold=...,
  circuit_recovery_timeout_sec=...).

Verification:
- tests/test_llm_error_handling_middleware.py — 14 passed
- tests/test_subagent_executor.py — 28 passed
- tests/test_tool_error_handling_middleware.py — 6 passed
- tests/test_task_tool_core_logic.py — 18 passed (verifies task_tool
  unchanged behavior)
- Full suite: 2697 passed, 3 skipped. The single intermittent failure in
  tests/test_client_e2e.py::test_tool_call_produces_events is pre-existing
  LLM flakiness (the test asserts the model decided to call a tool;
  reproduces 1/3 on unchanged main as well).

* fix: address middleware app config review comments

* fix: satisfy app config annotation lint

* test: cover explicit app config middleware wiring

---------

Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>
2026-04-30 12:41:09 +08:00
Xun
a62ca5dd47
fix: Catch httpx.ReadError in the error handling (#2309)
* fix: Catch httpx.ReadError in the error handling

* fix
2026-04-19 22:30:22 +08:00
Jin
4d4ddb3d3f
feat(llm): introduce lightweight circuit breaker to prevent rate-limit bans and resource exhaustion (#2095) 2026-04-12 17:48:40 +08:00
3a672b39c7
Fix/1681 llm call retry handling (#1683)
* fix(runtime): handle llm call errors gracefully

* fix(runtime): preserve graph control flow in llm retry middleware

---------

Co-authored-by: luoxiao6645 <luoxiao6645@gmail.com>
2026-04-02 10:12:17 +08:00