feat(loop-detection): defer warning injection (#2752)

* fix(loop-detection): defer warn injection to wrap_model_call

The warn branch in LoopDetectionMiddleware injected a HumanMessage
into state from after_model. The tools node had not yet produced
ToolMessage responses to the previous AIMessage(tool_calls=...), so
the new HumanMessage landed *between* the assistant's tool_calls and
their responses. OpenAI/Moonshot reject the next request with
"tool_call_ids did not have response messages" because their
validators require tool_calls to be followed immediately by tool
messages.

Detection now runs in after_model as before, but only enqueues the
warning into a per-thread list. Injection happens in wrap_model_call,
where every prior ToolMessage is already present in request.messages.
The warning is appended at the end as HumanMessage(name="loop_warning")
— pairing intact, AIMessage semantics untouched, no SystemMessage
issues for Anthropic.

Closes #2029, addresses #2255 #2293 #2304 #2511.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* fix(channels): remove loop warning display filter

* feat(loop-detection): scope pending warnings by run

* docs(loop-detection): update docs

* test(loop-detection): assert deferred warnings are queued

* fix(loop-detection): cap transient warning state

* docs: update docs

* add async awrap_model_call test coverage

* docs(loop-detection): document transient warnings

---------

Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Nan Gao
2026-05-21 08:36:07 +02:00
committed by GitHub
parent 7ec8d3a6e7
commit dcc6f1e678
7 changed files with 696 additions and 221 deletions
@@ -50,6 +50,8 @@ Intercepts clarification tool calls and converts them into proper user-facing re
Detects when the agent is making the same tool call repeatedly without making progress. When a loop is detected, the middleware intervenes to break the cycle and prevents the agent from burning turns indefinitely.
Warning interventions are queued per thread and run, then drained on the next model call as a single hidden `HumanMessage(name="loop_warning")` appended after existing tool results. This keeps provider tool-call pairing valid. Run start/end hooks clear stale or undelivered warnings, and hard stops still strip tool calls before forcing a final text response.
**Configuration**: built-in, no user configuration.
---