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>

backend/app/channels/manager.py

@@ -146,13 +146,6 @@ def _normalize_custom_agent_name(raw_value: str) -> str:
     return normalized
 
 
-def _strip_loop_warning_text(text: str) -> str:
-    """Remove middleware-authored loop warning lines from display text."""
-    if "[LOOP DETECTED]" not in text:
-        return text
-    return "\n".join(line for line in text.splitlines() if "[LOOP DETECTED]" not in line).strip()
-
-
 def _extract_response_text(result: dict | list) -> str:
     """Extract the last AI message text from a LangGraph runs.wait result.
 
@@ -162,7 +155,6 @@ def _extract_response_text(result: dict | list) -> str:
     Handles special cases:
     - Regular AI text responses
     - Clarification interrupts (``ask_clarification`` tool messages)
-    - Strips loop-detection warnings attached to tool-call AI messages
     """
     if isinstance(result, list):
         messages = result
@@ -192,12 +184,7 @@ def _extract_response_text(result: dict | list) -> str:
         # Regular AI message with text content
         if msg_type == "ai":
             content = msg.get("content", "")
-            has_tool_calls = bool(msg.get("tool_calls"))
             if isinstance(content, str) and content:
-                if has_tool_calls:
-                    content = _strip_loop_warning_text(content)
-                    if not content:
-                        continue
                 return content
             # content can be a list of content blocks
             if isinstance(content, list):
@@ -208,8 +195,6 @@ def _extract_response_text(result: dict | list) -> str:
                     elif isinstance(block, str):
                         parts.append(block)
                 text = "".join(parts)
-                if has_tool_calls:
-                    text = _strip_loop_warning_text(text)
                 if text:
                     return text
     return ""