fix(summarization): summarize with the run model, fall back on summary-provider failure (#4361)

* fix(summarization): own the run model for compaction; bound failure

With summarization.model_name: null the summary model resolved to
config.models[0] while the executing model is selected per run; when they
differ and models[0]'s provider is broken (expired key, quota, outage)
compaction silently failed every triggered turn and context grew unbounded
until the main provider 400s the run (#3103's shape), even though the run's
own model was healthy.

Model ownership is now sourced from the builders, not re-derived at runtime:
- The lead, subagent, and manual /compact builders each pass the resolved run
  model into create_summarization_middleware(run_model_name=...). The middleware
  no longer reads runtime.context / get_config(), which do not carry a custom
  agent's or a subagent's resolved model, so a custom-agent lead run and a
  distinct-model subagent now summarize with their own model, not models[0] /
  the parent's. Runtime re-resolution and the per-name model cache are removed.
- model_name: null summarizes with the run's own model; an explicitly configured
  summary model generates and falls back to the run model on failure. The
  fallback is built lazily after the primary fails and its construction is
  guarded, so a broken fallback cannot skip a healthy primary or escape the
  automatic failure boundary.

Failure is bounded and side-effect-safe:
- An empty or whitespace-only response is treated as a generation failure, not a
  valid summary, so compaction never removes all history for an empty replacement.
- compact_state/acompact_state take raise_on_failure independent of force: the
  manual /compact path always surfaces a generation failure (even force=false)
  and routes it to the existing ContextCompactionFailed path (HTTP 500 ->
  frontend error toast) instead of an unconsumed response reason. The automatic
  path leaves compaction state unchanged.
- before_summarization hooks fire only after a replacement summary exists.

SummarizationConfig.model_name, config.example.yaml, and docs/summarization.md
document the final lead/subagent/manual ownership rules.

Part of RFC #4346 (section A). Evaluating fraction/triggers against the run
model's profile (profile ownership) is a separate follow-up.

* fix(summarization): manual /compact model ownership + fail-open construct/parse

Manual /compact carried only agent_name, so it derived the run model from the
custom-agent model or config.models[0] and missed the request-selected model the
run path uses (request -> custom-agent -> default). Carry model_name through
ThreadCompactRequest and the frontend compact call, resolve with the same
precedence, and move the custom-agent config read off the event loop (asyncio
.to_thread) with user_id so the strict blocking-IO gate is not bypassed by the
broad except.

Make one summary attempt own its full lifecycle so the fail-open boundary covers
construction and response parsing, not just invocation: build each candidate model
lazily and guarded (a raising constructor falls through to the healthy run model
instead of breaking agent construction), build the model_name:null primary from the
run model rather than config.models[0], and run response text extraction inside the
invocation try so a failing .text accessor falls back instead of escaping compaction.
Adds factory-level constructor-failure, response-extraction-failure (sync/async), and
route-path model-ownership tests.

backend/app/gateway/routers/threads.py

@@ -442,6 +442,7 @@ class ThreadCompactRequest(BaseModel):
     force: bool = Field(default=True, description="Run compaction even if automatic summarization thresholds are not met")
     keep: ContextSize | None = Field(default=None, description="Optional retention policy for this compaction only")
     agent_name: str | None = Field(default=None, max_length=128, description="Optional custom agent name for memory attribution")
+    model_name: str | None = Field(default=None, max_length=128, description="Optional model to summarize with; resolved request override -> custom-agent model -> default, mirroring run model selection")
 
 
 class ThreadCompactResponse(BaseModel):
@@ -1128,6 +1129,7 @@ async def compact_thread(thread_id: str, body: ThreadCompactRequest, request: Re
                 force=body.force,
                 user_id=get_effective_user_id(),
                 agent_name=body.agent_name,
+                model_name=body.model_name,
             )
     except ConflictError:
         raise HTTPException(status_code=409, detail="Thread has a run in flight. Compact after the run finishes.") from None

backend/docs/summarization.md

@@ -21,7 +21,7 @@ Summarization is configured in `config.yaml` under the `summarization` key:
 ```yaml
 summarization:
   enabled: true
-  model_name: null  # Use default model or specify a lightweight model
+  model_name: null  # null = summarize with the run's own model (see below); or name a lightweight model
 
   # Trigger conditions (OR logic - any condition triggers summarization)
   trigger:
@@ -61,8 +61,11 @@ summarization:
 
 #### `model_name`
 - **Type**: String or null
-- **Default**: `null` (uses default model)
-- **Description**: Model to use for generating summaries. Recommended to use a lightweight, cost-effective model like `gpt-4o-mini` or equivalent.
+- **Default**: `null`
+- **Description**: Model to use for generating summaries.
+  - **`null` (model ownership)**: summarize with the model the run actually executes with — the lead run's resolved model, a subagent's own model, or a thread's custom-agent model — **not** `config.models[0]`. This keeps compaction working on a run whose model is healthy even when `models[0]`'s provider is broken (expired key, quota, outage).
+  - **Set to a model name**: that model generates summaries. If its provider fails, compaction **falls back to the run's own model** so a broken summary provider cannot disable compaction while a working model is available. Recommended to use a lightweight, cost-effective model like `gpt-4o-mini` or equivalent.
+  - Ownership applies to all three paths — automatic lead compaction, subagent compaction, and manual `/compact`. Manual `/compact` resolves the run model with the same precedence as a normal run: the model selected for the request (`POST /api/threads/{id}/compact` body `model_name`, sent by the frontend from the composer's current model) → the thread's custom-agent model → the default. A whitespace-only summary response is treated as a generation failure (it is never committed as a valid empty summary).
 
 #### `trigger`
 - **Type**: Single `ContextSize` or list of `ContextSize` objects
@@ -223,9 +226,9 @@ The middleware intelligently preserves message context:
   - Summaries don't require the most powerful models
   - Significant cost savings on high-volume applications
 
-- **Default**: If `model_name` is `null`, uses the default model
-  - May be more expensive but ensures consistency
-  - Good for simple setups
+- **Default**: If `model_name` is `null`, summarizes with the run's own model (not `models[0]`)
+  - Keeps compaction working when `models[0]`'s provider is broken but the run's model is healthy
+  - Good for simple setups; no separate summary provider to keep credentialed
 
 ### Optimization Tips
 

backend/packages/harness/deerflow/agents/lead_agent/agent.py

@@ -133,9 +133,14 @@ def _resolve_model_name(requested_model_name: str | None = None, *, app_config:
     return default_model_name
 
 
-def _create_summarization_middleware(*, app_config: AppConfig | None = None) -> DeerFlowSummarizationMiddleware | None:
-    """Create and configure the summarization middleware from config."""
-    return create_summarization_middleware(app_config=app_config)
+def _create_summarization_middleware(*, app_config: AppConfig | None = None, run_model_name: str | None = None) -> DeerFlowSummarizationMiddleware | None:
+    """Create and configure the summarization middleware from config.
+
+    ``run_model_name`` is the resolved run model; it is the source of truth for
+    ``model_name: null`` summarization and the explicit-summary-model fallback, so a
+    custom agent's model is used instead of ``config.models[0]``.
+    """
+    return create_summarization_middleware(app_config=app_config, run_model_name=run_model_name)
 
 
 def _create_todo_list_middleware(is_plan_mode: bool) -> TodoMiddleware | None:
@@ -359,7 +364,7 @@ def build_middlewares(
     )
 
     # Add summarization middleware if enabled
-    summarization_middleware = _create_summarization_middleware(app_config=resolved_app_config)
+    summarization_middleware = _create_summarization_middleware(app_config=resolved_app_config, run_model_name=model_name)
     if summarization_middleware is not None:
         middlewares.append(summarization_middleware)
 

backend/packages/harness/deerflow/agents/middlewares/summarization_middleware.py

@@ -21,6 +21,25 @@ from deerflow.models import create_chat_model
 
 logger = logging.getLogger(__name__)
 _SUMMARY_TRIGGER_MESSAGE_NAME = "summary"
+_UNSET = object()
+# Valid non-generated summaries for the empty / too-long-to-summarize edges; these
+# short-circuit model invocation (and must not be treated as generation failures).
+_CANNED_SUMMARIES = frozenset(
+    {
+        "No previous conversation history.",
+        "Previous conversation was too long to summarize.",
+    }
+)
+
+
+class SummaryGenerationError(RuntimeError):
+    """Summary generation failed after exhausting the run-model fallback.
+
+    Raised only when a caller opts in via ``raise_on_failure`` (the manual
+    ``/compact`` path) so a real failure is reported distinctly from "nothing to
+    compact". The automatic path leaves ``raise_on_failure`` False and swallows the
+    failure, leaving compaction state unchanged for the turn.
+    """
 
 
 @dataclass(frozen=True)
@@ -82,22 +101,115 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
         self,
         *args,
         before_summarization: list[BeforeSummarizationHook] | None = None,
+        app_config: Any | None = None,
+        configured_model_name: str | None = None,
+        run_model_name: str | None = None,
+        anchor_model_name: str | None = _UNSET,  # type: ignore[assignment]
         **kwargs,
     ) -> None:
         super().__init__(*args, **kwargs)
         self._before_summarization_hooks = before_summarization or []
+        # Model-ownership state. The model that actually executes the run is selected
+        # per run and is the authoritative source of truth, so the caller (lead /
+        # subagent / manual builders) supplies it directly as ``run_model_name``
+        # instead of the middleware re-deriving it from ``runtime.context`` /
+        # ``get_config()`` — those fields do not carry a custom agent's or a subagent's
+        # resolved model.
+        #
+        # ``configured_model_name`` is the explicitly configured summary model
+        # (``None`` => summarize with the run's own model). ``run_model_name`` is the
+        # model the run executes with; when they differ and the summary provider is
+        # broken (expired key, quota, outage) the run's own working model can still
+        # compact.
+        self._app_config = app_config
+        self._configured_summary_model_name = configured_model_name
+        self._run_model_name = run_model_name
         # The summary LLM call runs inside a LangGraph middleware hook, so its token
         # stream would otherwise be captured by the messages-tuple stream callback and
         # broadcast to the frontend as a phantom AI message. Tag a dedicated model copy
         # with TAG_NOSTREAM so the streaming handler skips it.
         # Keep self.model untagged so the parent's profile / ls_params inspection still works.
-        #
-        # Preserve any tags already bound on the model (e.g. "middleware:summarize" set in
-        # lead_agent/agent.py for RunJournal attribution): RunnableBinding.with_config does a
-        # shallow merge that would otherwise overwrite the existing tags list entirely.
-        existing_tags = list((getattr(self.model, "config", None) or {}).get("tags") or [])
+        self._summary_model = self._tag_nostream(self.model)
+        # ``self.model`` is the pre-built *anchor* model: it drives the parent's token
+        # counter / profile inspection and is reused verbatim by generation when a
+        # candidate matches its name. The factory builds it guarded and passes its name
+        # explicitly; direct construction (tests) mirrors the old factory choice
+        # (configured model, else default) so the passed ``model`` is the primary.
+        if anchor_model_name is _UNSET:
+            self._anchor_model_name = configured_model_name or self._default_model_name()
+        else:
+            self._anchor_model_name = anchor_model_name
+        # Nostream generation models built lazily by name and cached (None = a build
+        # that failed, so a broken candidate config is not retried every turn and does
+        # not escape the fail-open boundary).
+        self._model_cache: dict[str | None, Any] = {}
+
+    def _tag_nostream(self, model: Any) -> Any:
+        """Return a copy of ``model`` carrying TAG_NOSTREAM without clobbering tags.
+
+        lead_agent/agent.py binds "middleware:summarize" for RunJournal attribution;
+        RunnableBinding.with_config shallow-merges config, so existing tags must be
+        preserved explicitly instead of being overwritten with just [TAG_NOSTREAM].
+        """
+        existing_tags = list((getattr(model, "config", None) or {}).get("tags") or [])
         merged_tags = [*existing_tags, TAG_NOSTREAM] if TAG_NOSTREAM not in existing_tags else existing_tags
-        self._summary_model = self.model.with_config(tags=merged_tags)
+        return model.with_config(tags=merged_tags)
+
+    def _default_model_name(self) -> str | None:
+        if self._app_config is None:
+            return None
+        models = getattr(self._app_config, "models", None)
+        return models[0].name if models else None
+
+    def _generation_candidate_names(self) -> list[str | None]:
+        """Ordered summary-generation candidates by name (deduplicated).
+
+        Explicit summary model: the configured model first, then the run's own model
+        as a distinct fallback. ``model_name: null``: the run's own model only — its
+        construction is the primary, so there is no eager dependency on
+        ``config.models[0]`` (a bare default is used only when no run model was
+        resolved). A ``None`` entry means "let ``create_chat_model`` pick the default",
+        which only occurs when nothing resolves a name.
+        """
+        default = self._default_model_name()
+        if self._configured_summary_model_name is not None:
+            names = [self._configured_summary_model_name, self._run_model_name or default]
+        else:
+            names = [self._run_model_name or default]
+        deduped: list[str | None] = []
+        seen: set[str | None] = set()
+        for name in names:
+            if name in seen:
+                continue
+            seen.add(name)
+            deduped.append(name)
+        return deduped
+
+    def _model_for(self, name: str | None) -> Any | None:
+        """The nostream summary model for ``name``, built lazily and guarded.
+
+        Returns the pre-built anchor when ``name`` matches it (no rebuild), otherwise
+        constructs and caches. A construction failure is caught and cached as ``None``
+        so a broken candidate config never escapes the fail-open boundary, is never
+        retried this turn, and still lets the next candidate run.
+        """
+        if name == self._anchor_model_name:
+            return self._summary_model
+        if name in self._model_cache:
+            return self._model_cache[name]
+        try:
+            model = create_chat_model(
+                name=name,
+                thinking_enabled=False,
+                app_config=self._app_config,
+                attach_tracing=False,
+            )
+            built = self._tag_nostream(model.with_config(tags=["middleware:summarize"]))
+        except Exception:
+            logger.exception("Failed to build summary model %r; trying the next candidate", name)
+            built = None
+        self._model_cache[name] = built
+        return built
 
     @override
     def _create_summary(self, messages_to_summarize: list[AnyMessage]) -> str | None:
@@ -107,6 +219,31 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
     async def _acreate_summary(self, messages_to_summarize: list[AnyMessage]) -> str | None:
         return await self._asummarize_with(messages_to_summarize)
 
+    def _prepare_summary_prompt(self, messages_to_summarize: list[AnyMessage], previous_summary: str | None) -> str | None:
+        """Return the formatted prompt, or a canned string for the empty/too-long edges.
+
+        A non-``None`` return that is not a real prompt (the two canned strings) is a
+        valid summary and short-circuits generation; ``None`` means "build a prompt".
+        """
+        if not messages_to_summarize:
+            return "No previous conversation history."
+        prompt = self._build_summary_prompt(messages_to_summarize, previous_summary=previous_summary)
+        if prompt is None:
+            return "Previous conversation was too long to summarize."
+        return prompt
+
+    @staticmethod
+    def _nonempty_summary(text: Any) -> str | None:
+        """Normalize a model response's text; a blank/whitespace-only body is a failure.
+
+        Committing ``""`` as a summary would fire the before_summarization hooks and
+        remove all prior history for an empty replacement, so an empty body is treated
+        as generation failure (try the fallback, or leave state unchanged) rather than
+        a valid summary.
+        """
+        stripped = text.strip() if isinstance(text, str) else ""
+        return stripped or None
+
     def _summarize_with(self, messages_to_summarize: list[AnyMessage], previous_summary: str | None = None) -> str | None:
         """Mirror the parent ``_create_summary`` but invoke the nostream-tagged model.
 
@@ -114,38 +251,84 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
         cached and reused across concurrent runs, so a temporary swap would leak the
         ``RunnableBinding`` to other coroutines during ``await`` and break parent logic
         that inspects the raw model (``profile`` / ``_get_ls_params``).
+
+        Generation uses the run's own model (``model_name: null``) or the explicitly
+        configured summary model, falling back to the run model on failure so a broken
+        summary provider cannot disable compaction while a working model is available.
         """
-        if not messages_to_summarize:
-            return "No previous conversation history."
-        prompt = self._build_summary_prompt(messages_to_summarize, previous_summary=previous_summary)
-        if prompt is None:
-            return "Previous conversation was too long to summarize."
-        try:
-            response = self._summary_model.invoke(
-                prompt,
-                config={"metadata": {"lc_source": "summarization"}},
-            )
-            return response.text.strip()
-        except Exception:
-            logger.exception("Summary generation failed; skipping compaction this turn")
-            return None
+        prompt = self._prepare_summary_prompt(messages_to_summarize, previous_summary)
+        if prompt is None or prompt in _CANNED_SUMMARIES:
+            return prompt
+        # Walk the ordered candidates; each attempt owns its full lifecycle (lazy
+        # guarded construction -> invoke -> text extraction -> non-empty validation),
+        # and any failure at any stage falls through to the next candidate. When all
+        # candidates fail the caller leaves compaction state unchanged.
+        names = self._generation_candidate_names()
+        for index, name in enumerate(names):
+            text = self._invoke_summary(self._model_for(name), prompt, last=index == len(names) - 1)
+            if text is not None:
+                return text
+        return None
 
     async def _asummarize_with(self, messages_to_summarize: list[AnyMessage], previous_summary: str | None = None) -> str | None:
         """Async counterpart of :meth:`_summarize_with` using the nostream model."""
-        if not messages_to_summarize:
-            return "No previous conversation history."
-        prompt = self._build_summary_prompt(messages_to_summarize, previous_summary=previous_summary)
-        if prompt is None:
-            return "Previous conversation was too long to summarize."
-        try:
-            response = await self._summary_model.ainvoke(
-                prompt,
-                config={"metadata": {"lc_source": "summarization"}},
-            )
-            return response.text.strip()
-        except Exception:
-            logger.exception("Summary generation failed; skipping compaction this turn")
+        prompt = self._prepare_summary_prompt(messages_to_summarize, previous_summary)
+        if prompt is None or prompt in _CANNED_SUMMARIES:
+            return prompt
+        names = self._generation_candidate_names()
+        for index, name in enumerate(names):
+            text = await self._ainvoke_summary(self._model_for(name), prompt, last=index == len(names) - 1)
+            if text is not None:
+                return text
+        return None
+
+    def _invoke_summary(self, model: Any | None, prompt: str, *, last: bool = False) -> str | None:
+        """Invoke ``model`` for a summary; ``None`` on error or a blank response.
+
+        Text extraction / non-empty validation runs *inside* the try: reading the
+        response's ``.text`` is part of consuming the provider result, so a failing
+        accessor must convert to a candidate failure (fall through) rather than escape
+        the fail-open boundary.
+        """
+        if model is None:
             return None
+        try:
+            response = model.invoke(prompt, config={"metadata": {"lc_source": "summarization"}})
+            return self._checked_summary(response, last)
+        except Exception:
+            self._log_summary_error(last)
+            return None
+
+    async def _ainvoke_summary(self, model: Any | None, prompt: str, *, last: bool = False) -> str | None:
+        """Async counterpart of :meth:`_invoke_summary`."""
+        if model is None:
+            return None
+        try:
+            response = await model.ainvoke(prompt, config={"metadata": {"lc_source": "summarization"}})
+            return self._checked_summary(response, last)
+        except Exception:
+            self._log_summary_error(last)
+            return None
+
+    def _checked_summary(self, response: Any, last: bool) -> str | None:
+        summary = self._nonempty_summary(getattr(response, "text", None))
+        if summary is None:
+            self._log_summary_empty(last)
+        return summary
+
+    @staticmethod
+    def _log_summary_error(last: bool) -> None:
+        if last:
+            logger.exception("Summary generation failed; skipping compaction this turn")
+        else:
+            logger.warning("Summary generation failed; falling back to the run model", exc_info=True)
+
+    @staticmethod
+    def _log_summary_empty(last: bool) -> None:
+        if last:
+            logger.warning("Summary model returned empty text; skipping compaction this turn")
+        else:
+            logger.warning("Summary model returned empty text; falling back to the run model")
 
     @staticmethod
     def _summary_count_message(summary_text: str) -> HumanMessage:
@@ -303,15 +486,30 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
         runtime: Runtime,
         *,
         force: bool = False,
+        raise_on_failure: bool = False,
     ) -> ContextCompactionResult | None:
+        """Summarize old context and retain the active tail.
+
+        ``force`` bypasses the automatic trigger threshold (a manual caller always
+        wants to compact). ``raise_on_failure`` is a *separate* concern: when set (the
+        manual ``/compact`` path), a generation failure raises ``SummaryGenerationError``
+        so it can be reported distinctly from "nothing to compact"; the automatic path
+        leaves it False and swallows the failure, retrying on a later triggered turn.
+        """
         prepared = self._prepare_compaction(state, force=force)
         if prepared is None:
             return None
         messages_to_summarize, preserved_messages, previous_summary, total_tokens = prepared
-        self._fire_hooks(messages_to_summarize, preserved_messages, runtime)
         summary = self._summarize_with(messages_to_summarize, previous_summary=previous_summary)
         if summary is None:
+            if raise_on_failure:
+                raise SummaryGenerationError("summary generation failed")
             return None
+        # Fire hooks only once a replacement summary exists — flushing pre-compaction
+        # messages into durable memory for a summary that never materializes would
+        # duplicate that work on the next attempt. Messages are still removed after
+        # this returns (in _maybe_summarize), so hooks run before they are gone.
+        self._fire_hooks(messages_to_summarize, preserved_messages, runtime)
         return ContextCompactionResult(
             summary_text=summary,
             messages_to_summarize=tuple(messages_to_summarize),
@@ -325,15 +523,20 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
         runtime: Runtime,
         *,
         force: bool = False,
+        raise_on_failure: bool = False,
     ) -> ContextCompactionResult | None:
+        """Async counterpart of :meth:`compact_state` (see it for ``raise_on_failure``)."""
         prepared = self._prepare_compaction(state, force=force)
         if prepared is None:
             return None
         messages_to_summarize, preserved_messages, previous_summary, total_tokens = prepared
-        self._fire_hooks(messages_to_summarize, preserved_messages, runtime)
         summary = await self._asummarize_with(messages_to_summarize, previous_summary=previous_summary)
         if summary is None:
+            if raise_on_failure:
+                raise SummaryGenerationError("summary generation failed")
             return None
+        # Fire hooks only once a replacement summary exists (see compact_state).
+        self._fire_hooks(messages_to_summarize, preserved_messages, runtime)
         return ContextCompactionResult(
             summary_text=summary,
             messages_to_summarize=tuple(messages_to_summarize),
@@ -444,11 +647,37 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
                 logger.exception("before_summarization hook %s failed", hook_name)
 
 
+def _build_summary_anchor(candidate_names: list[str | None], app_config: Any) -> tuple[Any | None, str | None]:
+    """Build the first constructible model among ``candidate_names`` (guarded).
+
+    The returned model is tagged for RunJournal attribution but *not* TAG_NOSTREAM (the
+    middleware wraps a nostream copy). It becomes the parent's token-counter / profile
+    anchor and is reused for generation when a candidate matches its name. A per-name
+    construction failure is swallowed and the next candidate tried, so a broken primary
+    constructor neither breaks agent construction nor skips the healthy run model; a
+    trailing ``None`` name asks ``create_chat_model`` for its own default. Returns
+    ``(None, None)`` when nothing can be constructed.
+    """
+    tried: set[str | None] = set()
+    for name in candidate_names:
+        if name in tried:
+            continue
+        tried.add(name)
+        try:
+            model = create_chat_model(name=name, thinking_enabled=False, app_config=app_config, attach_tracing=False)
+        except Exception:
+            logger.exception("Failed to build summary anchor model %r; trying the next candidate", name)
+            continue
+        return model.with_config(tags=["middleware:summarize"]), name
+    return None, None
+
+
 def create_summarization_middleware(
     *,
     app_config: Any | None = None,
     keep: tuple[str, int | float] | None = None,
     skip_memory_flush: bool = False,
+    run_model_name: str | None = None,
 ) -> DeerFlowSummarizationMiddleware | None:
     """Create the configured summarization middleware.
 
@@ -456,6 +685,13 @@ def create_summarization_middleware(
     use this factory so model resolution, hooks, prompt config, and retention
     defaults cannot drift.
 
+    ``run_model_name`` is the model the run actually executes with, resolved by the
+    caller (the lead / subagent / manual builders each already resolve it) and passed
+    in as the authoritative source of truth for ``model_name: null`` summarization and
+    the explicit-summary-model fallback. The middleware does not re-derive it from
+    ``runtime.context`` / ``get_config()``, which do not carry a custom agent's or a
+    subagent's resolved model.
+
     ``skip_memory_flush`` omits the ``memory_flush_hook`` that otherwise
     flushes pre-compaction messages into the durable memory queue. The lead
     chain keeps it (research should persist); the subagent chain sets it so a
@@ -477,23 +713,25 @@ def create_summarization_middleware(
         else:
             trigger = config.trigger.to_tuple()
 
-    if config.model_name:
-        model = create_chat_model(
-            name=config.model_name,
-            thinking_enabled=False,
-            app_config=resolved_app_config,
-            attach_tracing=False,
-        )
-    else:
-        model = create_chat_model(
-            thinking_enabled=False,
-            app_config=resolved_app_config,
-            attach_tracing=False,
-        )
-    model = model.with_config(tags=["middleware:summarize"])
+    default_name = resolved_app_config.models[0].name if getattr(resolved_app_config, "models", None) else None
+    # Build the anchor (token-counter / profile model, reused for generation) guarded,
+    # rather than eagerly building the configured/default model and letting a broken
+    # constructor escape. Candidates in order: the primary generation model (configured
+    # summary model, else the run's own model), then the run model, then the default,
+    # then ``None`` (create_chat_model's default) as a last resort. So the null case
+    # builds from ``run_model_name`` — not ``config.models[0]`` — and a broken primary
+    # falls through to the healthy run model instead of failing agent construction.
+    primary_name = config.model_name or run_model_name or default_name
+    anchor_model, anchor_name = _build_summary_anchor(
+        [primary_name, run_model_name or default_name, default_name, None],
+        resolved_app_config,
+    )
+    if anchor_model is None:
+        logger.warning("Summarization is enabled but no summary model could be constructed; compaction is unavailable for this build")
+        return None
 
     kwargs: dict[str, Any] = {
-        "model": model,
+        "model": anchor_model,
         "trigger": trigger,
         "keep": keep or config.keep.to_tuple(),
     }
@@ -511,4 +749,8 @@ def create_summarization_middleware(
     return DeerFlowSummarizationMiddleware(
         **kwargs,
         before_summarization=hooks,
+        app_config=resolved_app_config,
+        configured_model_name=config.model_name,
+        run_model_name=run_model_name,
+        anchor_model_name=anchor_name,
     )

backend/packages/harness/deerflow/agents/middlewares/tool_error_handling_middleware.py

@@ -475,6 +475,11 @@ def build_subagent_runtime_middlewares(
     summarization_middleware = create_summarization_middleware(
         app_config=app_config,
         skip_memory_flush=True,
+        # The subagent's resolved model is the source of truth for null-model
+        # summarization: the subagent context/configurable does not carry the child
+        # model (it inherits the parent's), so passing it directly is what makes a
+        # distinct-model subagent summarize with its own model, not the parent's.
+        run_model_name=model_name,
     )
     if summarization_middleware is not None:
         middlewares.append(summarization_middleware)

backend/packages/harness/deerflow/config/summarization_config.py

@@ -28,7 +28,10 @@ class SummarizationConfig(BaseModel):
     )
     model_name: str | None = Field(
         default=None,
-        description="Model name to use for summarization (None = use a lightweight model)",
+        description="Model name to use for summarization. None = summarize with the model the run "
+        "actually executes with (the lead run's model, a subagent's own model, or a thread's "
+        "custom-agent model), not config.models[0]. When set, that model generates and the run's "
+        "own model is used as a fallback if the configured summary provider fails.",
     )
     trigger: ContextSize | list[ContextSize] | None = Field(
         default=None,

backend/packages/harness/deerflow/runtime/context_compaction.py

@@ -2,15 +2,19 @@
 
 from __future__ import annotations
 
+import asyncio
+import logging
 from dataclasses import dataclass
 from types import SimpleNamespace
 
 from langgraph.types import Overwrite
 
-from deerflow.agents.middlewares.summarization_middleware import DeerFlowSummarizationMiddleware, create_summarization_middleware
+from deerflow.agents.middlewares.summarization_middleware import DeerFlowSummarizationMiddleware, SummaryGenerationError, create_summarization_middleware
 from deerflow.config.app_config import AppConfig, get_app_config
 from deerflow.runtime.checkpoint_state import CheckpointStateAccessor
 
+logger = logging.getLogger(__name__)
+
 
 class ContextCompactionDisabled(RuntimeError):
     """Raised when manual compaction is requested while summarization is disabled."""
@@ -38,13 +42,60 @@ def _create_compaction_middleware(
     *,
     app_config: AppConfig,
     keep: tuple[str, int | float] | None,
+    run_model_name: str | None = None,
 ) -> DeerFlowSummarizationMiddleware:
-    middleware = create_summarization_middleware(app_config=app_config, keep=keep)
+    middleware = create_summarization_middleware(app_config=app_config, keep=keep, run_model_name=run_model_name)
     if middleware is None:
         raise ContextCompactionDisabled("Context compaction is disabled.")
     return middleware
 
 
+def _safe_load_agent_config(agent_name: str, user_id: str | None):
+    """Load a custom agent's config, returning ``None`` on any failure.
+
+    A missing / unparseable agent config must not fail compaction; the run model is a
+    best-effort optimization and the default is a safe fallback. The caller runs this
+    off the event loop via ``asyncio.to_thread``, so the strict blocking-IO detector
+    does not flag the filesystem read and the broad ``except`` here cannot mask a
+    ``BlockingError`` raised on the loop.
+    """
+    from deerflow.config.agents_config import load_agent_config
+
+    try:
+        return load_agent_config(agent_name, user_id=user_id)
+    except Exception:
+        logger.warning("Could not load agent config for %r; using the default model for summarization", agent_name, exc_info=True)
+        return None
+
+
+async def _aresolve_thread_model_name(
+    model_name: str | None,
+    agent_name: str | None,
+    user_id: str | None,
+    app_config: AppConfig,
+) -> str | None:
+    """Resolve the model a thread should summarize with, mirroring lead resolution.
+
+    Precedence matches ``lead_agent._resolve_model_name``: an explicit request model
+    override (validated against configured models) wins, else the thread's custom-agent
+    configured model, else ``config.models[0]``. Manual ``/compact`` does not execute
+    the agent, so there is no live runtime carrying the selected model — the caller
+    (route / client) supplies it as ``model_name`` the same way a normal run submits
+    ``context.model_name``. The custom-agent config read happens only when no request
+    model was supplied, runs off the event loop, and passes the owning ``user_id`` so
+    the per-user agent directory resolves.
+    """
+    default = app_config.models[0].name if getattr(app_config, "models", None) else None
+    candidate = model_name
+    if not candidate and agent_name:
+        agent_config = await asyncio.to_thread(_safe_load_agent_config, agent_name, user_id)
+        if agent_config and agent_config.model:
+            candidate = agent_config.model
+    if candidate and app_config.get_model_config(candidate):
+        return candidate
+    return default
+
+
 async def compact_thread_context(
     accessor: CheckpointStateAccessor,
     thread_id: str,
@@ -53,11 +104,13 @@ async def compact_thread_context(
     force: bool = True,
     user_id: str | None = None,
     agent_name: str | None = None,
+    model_name: str | None = None,
     app_config: AppConfig | None = None,
 ) -> ThreadCompactionResult:
     """Summarize old messages in a thread and write a compacted checkpoint."""
     resolved_app_config = app_config or get_app_config()
-    middleware = _create_compaction_middleware(app_config=resolved_app_config, keep=keep)
+    run_model_name = await _aresolve_thread_model_name(model_name, agent_name, user_id, resolved_app_config)
+    middleware = _create_compaction_middleware(app_config=resolved_app_config, keep=keep, run_model_name=run_model_name)
 
     read_config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
     snapshot = await accessor.aget(read_config)
@@ -80,7 +133,18 @@ async def compact_thread_context(
     if agent_name:
         runtime_context["agent_name"] = agent_name
     runtime = SimpleNamespace(context=runtime_context)
-    result = await middleware.acompact_state(state, runtime, force=force)  # type: ignore[arg-type]
+    try:
+        # ``raise_on_failure`` is independent of ``force``: a manual caller always wants
+        # a generation failure surfaced (even a force=False call that met the threshold),
+        # so it must not collapse into the force=False "nothing to compact" branch below.
+        result = await middleware.acompact_state(state, runtime, force=force, raise_on_failure=True)  # type: ignore[arg-type]
+    except SummaryGenerationError as exc:
+        # A compressible thread whose summary LLM failed (after the run-model fallback)
+        # is a real failure, distinct from "nothing to compact". Route it to the
+        # already-consumed ContextCompactionFailed path (HTTP 500 -> frontend error
+        # toast) instead of a compacted=False result that reads as "does not need
+        # compaction".
+        raise ContextCompactionFailed("summary generation failed") from exc
     if result is None:
         return ThreadCompactionResult(thread_id=thread_id, compacted=False, reason="not_enough_messages")
 

backend/tests/test_context_compaction.py

@@ -10,9 +10,10 @@ from langgraph.graph.message import add_messages
 from langgraph.types import Overwrite
 
 from app.gateway import services as gateway_services
+from deerflow.agents.middlewares.summarization_middleware import SummaryGenerationError
 from deerflow.runtime import context_compaction
 from deerflow.runtime.checkpoint_state import CheckpointStateAccessor
-from deerflow.runtime.context_compaction import compact_thread_context
+from deerflow.runtime.context_compaction import ContextCompactionFailed, compact_thread_context
 
 
 class _FakeAccessor:
@@ -56,7 +57,7 @@ class _FakeCompactionMiddleware:
             return None
         return (state["messages"][:-1], state["messages"][-1:], state.get("summary_text"), 123)
 
-    async def acompact_state(self, state, runtime, *, force=False):
+    async def acompact_state(self, state, runtime, *, force=False, raise_on_failure=False):
         self.runtime_contexts.append(dict(runtime.context))
         prepared = self._prepare_compaction(state, force=force)
         if prepared is None:
@@ -90,6 +91,9 @@ async def test_compact_thread_context_reads_materialized_state_and_overwrites_me
         "_create_compaction_middleware",
         lambda **_kwargs: middleware,
     )
+    import deerflow.config.agents_config as agents_config
+
+    monkeypatch.setattr(agents_config, "load_agent_config", lambda name, **_kw: None)
 
     result = await compact_thread_context(
         accessor,
@@ -255,3 +259,180 @@ async def test_compact_thread_context_returns_noop_without_writing(monkeypatch):
     assert result.reason == "not_enough_messages"
     assert accessor.update_args is None
     assert middleware.prepare_calls == 1
+
+
+@pytest.mark.asyncio
+async def test_compact_thread_context_raises_on_summary_generation_failure(monkeypatch):
+    """A compressible thread whose summary LLM fails (after the run-model fallback) is
+    a real failure: it must surface via the already-consumed ``ContextCompactionFailed``
+    path (HTTP 500 -> frontend error toast), not a ``compacted=False`` result that the
+    frontend renders as the benign "does not need compaction" toast."""
+    accessor = _FakeAccessor(
+        {
+            "messages": [
+                HumanMessage(content="old question"),
+                AIMessage(content="old answer"),
+                HumanMessage(content="latest question"),
+            ],
+        }
+    )
+
+    captured: dict[str, object] = {}
+
+    class _FailingMiddleware:
+        async def acompact_state(self, state, runtime, *, force=False, raise_on_failure=False):
+            # The manual path must opt into raise_on_failure regardless of force.
+            captured["raise_on_failure"] = raise_on_failure
+            raise SummaryGenerationError("summary generation failed")
+
+    monkeypatch.setattr(
+        context_compaction,
+        "_create_compaction_middleware",
+        lambda **_kwargs: _FailingMiddleware(),
+    )
+
+    with pytest.raises(ContextCompactionFailed):
+        await compact_thread_context(accessor, "thread-1", app_config=SimpleNamespace())
+
+    assert captured["raise_on_failure"] is True
+    assert accessor.update_args is None
+
+
+def _model_app_config(*names):
+    models = [SimpleNamespace(name=n) for n in names]
+    return SimpleNamespace(
+        models=models,
+        get_model_config=lambda n: next((m for m in models if m.name == n), None),
+    )
+
+
+@pytest.mark.asyncio
+async def test_resolve_request_model_overrides_agent_and_default(monkeypatch):
+    """The selected request model wins over both the custom-agent model and the default,
+    mirroring lead resolution (request -> agent -> default). A supplied request model
+    also short-circuits the agent-config filesystem read entirely."""
+    import deerflow.config.agents_config as agents_config
+
+    def _fail(name, **_kw):
+        raise AssertionError("agent config must not be loaded when a request model is supplied")
+
+    monkeypatch.setattr(agents_config, "load_agent_config", _fail)
+    app_config = _model_app_config("default-model", "agent-model", "selected-model")
+
+    got = await context_compaction._aresolve_thread_model_name("selected-model", "research-agent", "user-1", app_config)
+    assert got == "selected-model"
+
+
+@pytest.mark.asyncio
+async def test_resolve_invalid_request_model_falls_to_default_not_agent(monkeypatch):
+    """A request model that is not a configured model falls straight to the default —
+    the agent model is only consulted when no request model was supplied, matching
+    ``lead_agent._resolve_model_name(requested or agent)``."""
+    import deerflow.config.agents_config as agents_config
+
+    monkeypatch.setattr(agents_config, "load_agent_config", lambda name, **_kw: SimpleNamespace(model="agent-model"))
+    app_config = _model_app_config("default-model", "agent-model")
+
+    got = await context_compaction._aresolve_thread_model_name("ghost-model", "research-agent", "user-1", app_config)
+    assert got == "default-model"
+
+
+@pytest.mark.asyncio
+async def test_resolve_agent_model_when_no_request_model(monkeypatch):
+    """With no request model, a custom-agent thread summarizes with its own model, and
+    the agent config is loaded with the owning ``user_id`` (per-user agent directory)."""
+    import deerflow.config.agents_config as agents_config
+
+    seen: dict[str, object] = {}
+
+    def _load(name, *, user_id=None):
+        seen["name"] = name
+        seen["user_id"] = user_id
+        return SimpleNamespace(model="agent-model")
+
+    monkeypatch.setattr(agents_config, "load_agent_config", _load)
+    app_config = _model_app_config("default-model", "agent-model")
+
+    got = await context_compaction._aresolve_thread_model_name(None, "research-agent", "user-1", app_config)
+    assert got == "agent-model"
+    assert seen == {"name": "research-agent", "user_id": "user-1"}
+
+
+@pytest.mark.asyncio
+async def test_resolve_falls_back_to_default(monkeypatch):
+    """No agent, an unloadable agent config, or an agent whose model is not configured all
+    resolve to the default model rather than failing compaction."""
+    import deerflow.config.agents_config as agents_config
+
+    app_config = _model_app_config("default-model")
+
+    # No request model and no agent → default.
+    assert await context_compaction._aresolve_thread_model_name(None, None, "user-1", app_config) == "default-model"
+
+    # Agent config cannot be loaded (missing/unparseable) → default, not a crash.
+    def _raise(name, **_kw):
+        raise FileNotFoundError("agent directory not found")
+
+    monkeypatch.setattr(agents_config, "load_agent_config", _raise)
+    assert await context_compaction._aresolve_thread_model_name(None, "ghost-agent", "user-1", app_config) == "default-model"
+
+    # Agent's model is not a configured model → default.
+    monkeypatch.setattr(agents_config, "load_agent_config", lambda name, **_kw: SimpleNamespace(model="unconfigured"))
+    assert await context_compaction._aresolve_thread_model_name(None, "x-agent", "user-1", app_config) == "default-model"
+
+
+@pytest.mark.asyncio
+async def test_resolve_agent_config_load_runs_off_the_event_loop(monkeypatch):
+    """The blocking agent-config read must run off the event loop (``asyncio.to_thread``),
+    not synchronously before the first await where the strict blocking-IO gate would flag
+    it and the broad except would then mask the ``BlockingError`` as a default fallback."""
+    import threading
+
+    import deerflow.config.agents_config as agents_config
+
+    main_thread = threading.get_ident()
+    seen: dict[str, object] = {}
+
+    def _load(name, *, user_id=None):
+        seen["thread"] = threading.get_ident()
+        return SimpleNamespace(model="agent-model")
+
+    monkeypatch.setattr(agents_config, "load_agent_config", _load)
+    app_config = _model_app_config("default-model", "agent-model")
+
+    got = await context_compaction._aresolve_thread_model_name(None, "research-agent", "user-1", app_config)
+    assert got == "agent-model"
+    assert seen["thread"] != main_thread
+
+
+@pytest.mark.asyncio
+async def test_compact_thread_context_threads_selected_model_to_factory(monkeypatch):
+    """Route/client path: the model selected for the thread request reaches the
+    summarization factory as ``run_model_name`` — covering the real call, not only the
+    resolver in isolation (request override -> agent -> default)."""
+    import deerflow.config.agents_config as agents_config
+
+    monkeypatch.setattr(agents_config, "load_agent_config", lambda name, **_kw: SimpleNamespace(model="agent-model"))
+    app_config = _model_app_config("default-model", "agent-model", "selected-model")
+
+    captured: dict[str, object] = {}
+
+    def _capture(**kwargs):
+        captured["run_model_name"] = kwargs.get("run_model_name")
+        return _FakeCompactionMiddleware()
+
+    monkeypatch.setattr(context_compaction, "_create_compaction_middleware", _capture)
+
+    messages = [HumanMessage(content="old"), AIMessage(content="a"), HumanMessage(content="new")]
+
+    # 1. Explicit request model wins.
+    await compact_thread_context(_FakeAccessor({"messages": messages}), "thread-1", app_config=app_config, user_id="user-1", agent_name="research-agent", model_name="selected-model")
+    assert captured["run_model_name"] == "selected-model"
+
+    # 2. No request model → the custom agent's model.
+    await compact_thread_context(_FakeAccessor({"messages": messages}), "thread-1", app_config=app_config, user_id="user-1", agent_name="research-agent")
+    assert captured["run_model_name"] == "agent-model"
+
+    # 3. No request model, no agent → default.
+    await compact_thread_context(_FakeAccessor({"messages": messages}), "thread-1", app_config=app_config, user_id="user-1")
+    assert captured["run_model_name"] == "default-model"

backend/tests/test_durable_context_middleware.py

@@ -503,7 +503,7 @@ class TestMiddlewareRegistration:
         summary_sentinel = object()
 
         monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-        monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: summary_sentinel)
+        monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: summary_sentinel)
         monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
         middlewares = lead_agent_module.build_middlewares(

backend/tests/test_lead_agent_model_resolution.py

@@ -609,6 +609,38 @@ def test_build_middlewares_passes_explicit_app_config_to_shared_factory(monkeypa
     assert middlewares[0] == "base-middleware"
 
 
+def test_build_middlewares_passes_run_model_name_to_summarization(monkeypatch):
+    """The resolved run model (e.g. a custom agent's model, distinct from models[0])
+    is threaded into the summarization factory, so null-model compaction summarizes
+    with it rather than config.models[0]. Production-shaped: the model reaches the
+    factory as an argument, not via runtime.context."""
+    app_config = _make_app_config(
+        [
+            _make_model("default-model", supports_thinking=False),
+            _make_model("custom-agent-model", supports_thinking=False),
+        ]
+    )
+    captured: dict[str, object] = {}
+
+    monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init: ["base-middleware"])
+    monkeypatch.setattr(
+        lead_agent_module,
+        "_create_summarization_middleware",
+        lambda **kwargs: captured.update(kwargs) or None,
+    )
+    monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
+    monkeypatch.setattr(lead_agent_module, "TitleMiddleware", lambda *, app_config: "title-middleware")
+    monkeypatch.setattr(lead_agent_module, "MemoryMiddleware", lambda agent_name=None, *, memory_config: "memory-middleware")
+
+    lead_agent_module.build_middlewares(
+        {"configurable": {"is_plan_mode": False, "subagent_enabled": False}},
+        model_name="custom-agent-model",
+        app_config=app_config,
+    )
+
+    assert captured["run_model_name"] == "custom-agent-model"
+
+
 def test_build_middlewares_orders_skill_activation_before_policy_and_durable_context(monkeypatch):
     from deerflow.agents.middlewares.durable_context_middleware import DurableContextMiddleware
     from deerflow.agents.middlewares.skill_activation_middleware import SkillActivationMiddleware
@@ -616,7 +648,7 @@ def test_build_middlewares_orders_skill_activation_before_policy_and_durable_con
 
     app_config = _make_app_config([_make_model("safe-model", supports_thinking=False)])
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -644,7 +676,7 @@ def test_compiled_skill_policy_chain_filters_schema_and_blocks_execution(monkeyp
         loop_detection=LoopDetectionConfig(enabled=False),
     )
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -715,7 +747,7 @@ def test_build_middlewares_places_mcp_routing_before_deferred_filter(monkeypatch
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -746,7 +778,7 @@ def test_build_middlewares_uses_loop_detection_config(monkeypatch):
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -772,7 +804,7 @@ def test_build_middlewares_omits_loop_detection_when_disabled(monkeypatch):
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -799,7 +831,7 @@ def test_build_middlewares_injects_configured_extension_middlewares(monkeypatch)
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -829,7 +861,7 @@ def test_build_middlewares_passes_subagent_total_limit_from_app_config(monkeypat
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -852,7 +884,7 @@ def test_build_middlewares_allows_runtime_subagent_total_limit_override(monkeypa
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     middlewares = lead_agent_module.build_middlewares(
@@ -881,7 +913,7 @@ def test_build_middlewares_rejects_invalid_configured_extension_middleware(monke
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     with pytest.raises(ValueError, match="not an instance of type"):
@@ -901,7 +933,7 @@ def test_build_middlewares_rejects_configured_extension_class_with_wrong_base(mo
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     with pytest.raises(ValueError, match="is not a subclass of AgentMiddleware"):
@@ -921,7 +953,7 @@ def test_build_middlewares_reraises_configured_extension_instantiation_failure(m
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     with pytest.raises(RuntimeError, match="configured middleware init failed"):
@@ -941,7 +973,7 @@ def test_build_middlewares_rejects_missing_configured_extension_module(monkeypat
 
     monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
     monkeypatch.setattr(lead_agent_module, "build_lead_runtime_middlewares", lambda *, app_config, lazy_init=True: [])
-    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
+    monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **_kwargs: None)
     monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
 
     with pytest.raises(ImportError, match="Could not import module definitely_missing_pkg.middlewares_typo"):
@@ -986,7 +1018,10 @@ def test_create_summarization_middleware_uses_configured_model_alias(monkeypatch
     fake_model.with_config.assert_called_once_with(tags=["middleware:summarize"])
 
 
-def test_create_summarization_middleware_omits_model_name_when_unconfigured(monkeypatch):
+def test_create_summarization_middleware_uses_default_when_unconfigured(monkeypatch):
+    """Null summary config with no supplied run model builds the anchor from the default
+    model — now with an explicit name rather than relying on create_chat_model's internal
+    default, so the factory has no implicit models[0] dependency. Same resulting model."""
     app_config = _make_app_config([_make_model("default-model", supports_thinking=False)])
     app_config.summarization = SummarizationConfig(enabled=True, model_name=None)
     app_config.memory = MemoryConfig(enabled=False)
@@ -1004,10 +1039,35 @@ def test_create_summarization_middleware_omits_model_name_when_unconfigured(monk
 
     middleware = lead_agent_module._create_summarization_middleware(app_config=app_config)
 
-    assert "name" not in captured
+    assert captured["name"] == "default-model"
     assert captured["thinking_enabled"] is False
     assert captured["app_config"] is app_config
     assert middleware["model"] is fake_model
+    assert middleware["anchor_model_name"] == "default-model"
+
+
+def test_create_summarization_middleware_threads_run_model_name(monkeypatch):
+    """A custom agent's resolved model reaches the middleware as run_model_name (the
+    model-ownership source of truth), while configured_model_name stays None for a
+    null summarization config."""
+    app_config = _make_app_config(
+        [
+            _make_model("default-model", supports_thinking=False),
+            _make_model("custom-agent-model", supports_thinking=False),
+        ]
+    )
+    app_config.summarization = SummarizationConfig(enabled=True, model_name=None)
+    app_config.memory = MemoryConfig(enabled=False)
+
+    fake_model = MagicMock()
+    fake_model.with_config.return_value = fake_model
+    monkeypatch.setattr(summarization_middleware_module, "create_chat_model", lambda **kwargs: fake_model)
+    monkeypatch.setattr(summarization_middleware_module, "DeerFlowSummarizationMiddleware", lambda **kwargs: kwargs)
+
+    middleware = lead_agent_module._create_summarization_middleware(app_config=app_config, run_model_name="custom-agent-model")
+
+    assert middleware["run_model_name"] == "custom-agent-model"
+    assert middleware["configured_model_name"] is None
 
 
 def test_create_summarization_middleware_uses_frontend_supported_update_key(monkeypatch):

backend/tests/test_summarization_middleware.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from types import SimpleNamespace
 from unittest import mock
-from unittest.mock import MagicMock
+from unittest.mock import AsyncMock, MagicMock
 
 import pytest
 from langchain.agents import create_agent
@@ -13,7 +13,7 @@ from langgraph.constants import TAG_NOSTREAM
 
 from deerflow.agents.memory.summarization_hook import memory_flush_hook
 from deerflow.agents.middlewares.dynamic_context_middleware import _DYNAMIC_CONTEXT_REMINDER_KEY, DynamicContextMiddleware, is_dynamic_context_reminder
-from deerflow.agents.middlewares.summarization_middleware import DeerFlowSummarizationMiddleware, SummarizationEvent, create_summarization_middleware
+from deerflow.agents.middlewares.summarization_middleware import DeerFlowSummarizationMiddleware, SummarizationEvent, SummaryGenerationError, create_summarization_middleware
 from deerflow.agents.thread_state import ThreadState
 from deerflow.config.memory_config import MemoryConfig
 from deerflow.config.summarization_config import SummarizationConfig
@@ -78,6 +78,7 @@ def _middleware(
 ) -> DeerFlowSummarizationMiddleware:
     model = MagicMock()
     model.invoke.return_value = SimpleNamespace(text="compressed summary")
+    model.ainvoke = AsyncMock(return_value=SimpleNamespace(text="compressed summary"))
     model.with_config.return_value = model
     return DeerFlowSummarizationMiddleware(
         model=model,
@@ -727,3 +728,481 @@ def test_benign_summary_input_text_preserved() -> None:
     assert out is not None
     assert "User: what is the plan" in out
     assert "prior recap text" in out
+
+
+def _app_config(model_names=("default-model",)):
+    """Minimal AppConfig-shaped stub: ordered ``models`` + ``get_model_config``."""
+    models = [SimpleNamespace(name=name) for name in model_names]
+
+    def get_model_config(name):
+        return next((model for model in models if model.name == name), None)
+
+    return SimpleNamespace(models=models, get_model_config=get_model_config)
+
+
+def _tracking_create_chat_model(built: list, *, fail: bool = False):
+    """Patch target for ``create_chat_model``: records built names, returns a mock
+    whose summary text is ``from-<name>`` (or fails on invoke when ``fail``)."""
+
+    def _factory(*, name=None, thinking_enabled=False, app_config=None, attach_tracing=True, **kwargs):
+        model = MagicMock()
+        model.with_config.return_value = model
+        if fail:
+            model.invoke.side_effect = RuntimeError("provider down")
+            model.ainvoke = AsyncMock(side_effect=RuntimeError("provider down"))
+        else:
+            model.invoke.return_value = SimpleNamespace(text=f"from-{name}")
+            model.ainvoke = AsyncMock(return_value=SimpleNamespace(text=f"from-{name}"))
+        built.append(name)
+        return model
+
+    return _factory
+
+
+def _blank_model(*, text: str = "   \n\t ") -> MagicMock:
+    """A model whose response body is whitespace-only (a generation failure)."""
+    model = MagicMock()
+    model.with_config.return_value = model
+    model.invoke.return_value = SimpleNamespace(text=text)
+    model.ainvoke = AsyncMock(return_value=SimpleNamespace(text=text))
+    return model
+
+
+def test_null_model_summarizes_with_the_run_model(monkeypatch: pytest.MonkeyPatch) -> None:
+    """model_name: null must summarize with the model the run actually uses, not
+    config.models[0]. This is the model-ownership fix: a run on a non-default model
+    while models[0]'s provider is broken must still compact.
+
+    Production-shaped: the run model is supplied at build time (``run_model_name``),
+    and the runtime carries NO ``model_name`` in its context — the previous fixture
+    injected ``runtime.context['model_name']``, which the production custom-agent /
+    subagent contexts never populate."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built))
+
+    default_model = MagicMock()
+    default_model.with_config.return_value = default_model
+    default_model.invoke.return_value = SimpleNamespace(text="from-default")
+    middleware = DeerFlowSummarizationMiddleware(
+        model=default_model,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name=None,
+        run_model_name="run-model",
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    # The run model was built + used; the default (models[0]) never generated a summary.
+    assert built == ["run-model"]
+    default_model.invoke.assert_not_called()
+    assert result is not None
+    assert result["summary_text"] == "from-run-model"
+
+
+def test_explicit_summary_model_failure_falls_back_to_run_model(monkeypatch: pytest.MonkeyPatch) -> None:
+    """An explicitly configured summary model generates; if its provider is broken,
+    compaction falls back to the run's own (working) model instead of no-op'ing.
+    The fallback is built lazily only after the primary fails."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built))
+
+    explicit = MagicMock()
+    explicit.with_config.return_value = explicit
+    explicit.invoke.side_effect = RuntimeError("summary provider down")
+    middleware = DeerFlowSummarizationMiddleware(
+        model=explicit,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name="summary-model",
+        run_model_name="run-model",
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    explicit.invoke.assert_called_once()  # primary tried
+    assert built == ["run-model"]  # fallback built (lazily, after primary failed) + used
+    assert result is not None
+    assert result["summary_text"] == "from-run-model"
+
+
+@pytest.mark.anyio
+async def test_async_explicit_failure_falls_back_to_run_model(monkeypatch: pytest.MonkeyPatch) -> None:
+    """The async path applies the same run-model fallback as the sync path."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built))
+
+    explicit = MagicMock()
+    explicit.with_config.return_value = explicit
+    explicit.ainvoke = AsyncMock(side_effect=RuntimeError("summary provider down"))
+    middleware = DeerFlowSummarizationMiddleware(
+        model=explicit,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name="summary-model",
+        run_model_name="run-model",
+    )
+
+    result = await middleware.abefore_model({"messages": _messages()}, _runtime())
+
+    explicit.ainvoke.assert_awaited_once()
+    assert built == ["run-model"]
+    assert result is not None
+    assert result["summary_text"] == "from-run-model"
+
+
+def test_both_summary_models_failing_returns_none_on_automatic_path(monkeypatch: pytest.MonkeyPatch) -> None:
+    """When the explicit model and the run-model fallback both fail, the automatic
+    path leaves compaction state unchanged (returns None) rather than raising."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built, fail=True))
+
+    explicit = MagicMock()
+    explicit.with_config.return_value = explicit
+    explicit.invoke.side_effect = RuntimeError("provider down")
+    middleware = DeerFlowSummarizationMiddleware(
+        model=explicit,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name="summary-model",
+        run_model_name="run-model",
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    assert result is None
+    explicit.invoke.assert_called_once()  # primary tried
+    assert built == ["run-model"]  # fallback tried too
+
+
+def test_explicit_summary_model_equal_to_run_model_is_not_retried(monkeypatch: pytest.MonkeyPatch) -> None:
+    """When the configured summary model IS the run model, there is no distinct
+    fallback: the failed model must not be re-invoked (that would just burn another
+    call against a provider we already know is down) and no second model is built."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built, fail=True))
+
+    explicit = MagicMock()
+    explicit.with_config.return_value = explicit
+    explicit.invoke.side_effect = RuntimeError("provider down")
+    middleware = DeerFlowSummarizationMiddleware(
+        model=explicit,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("summary-model",)),
+        configured_model_name="summary-model",
+        run_model_name="summary-model",  # run model == configured summary model
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    assert result is None
+    explicit.invoke.assert_called_once()  # tried exactly once, not twice
+    assert built == []  # no distinct fallback model was built
+
+
+def test_fallback_construction_error_does_not_escape_automatic_path(monkeypatch: pytest.MonkeyPatch) -> None:
+    """A broken run-model config must not skip the healthy primary or escape the
+    automatic failure boundary: the primary is tried first, and a fallback that
+    fails to *construct* is swallowed (returns None), not raised."""
+
+    def _failing_build(*, name=None, **kwargs):
+        raise RuntimeError("cannot build run model")
+
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _failing_build)
+
+    explicit = MagicMock()
+    explicit.with_config.return_value = explicit
+    explicit.invoke.side_effect = RuntimeError("summary provider down")
+    middleware = DeerFlowSummarizationMiddleware(
+        model=explicit,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name="summary-model",
+        run_model_name="run-model",
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    assert result is None
+    explicit.invoke.assert_called_once()  # healthy-or-not, the primary was still tried first
+
+
+def test_blank_summary_response_is_not_committed_null_case(monkeypatch: pytest.MonkeyPatch) -> None:
+    """A whitespace-only model response is a generation failure, not a valid empty
+    summary: the automatic path returns None (history preserved, no RemoveMessage)
+    instead of removing all history for an empty replacement."""
+    run_model = _blank_model()
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", lambda **kwargs: run_model)
+
+    default_model = MagicMock()
+    default_model.with_config.return_value = default_model
+    middleware = DeerFlowSummarizationMiddleware(
+        model=default_model,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name=None,
+        run_model_name="run-model",
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    assert result is None
+    run_model.invoke.assert_called_once()
+
+
+@pytest.mark.anyio
+async def test_blank_summary_response_is_not_committed_async(monkeypatch: pytest.MonkeyPatch) -> None:
+    """Async counterpart: a whitespace-only response leaves compaction state unchanged."""
+    run_model = _blank_model()
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", lambda **kwargs: run_model)
+
+    default_model = MagicMock()
+    default_model.with_config.return_value = default_model
+    middleware = DeerFlowSummarizationMiddleware(
+        model=default_model,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name=None,
+        run_model_name="run-model",
+    )
+
+    result = await middleware.abefore_model({"messages": _messages()}, _runtime())
+
+    assert result is None
+    run_model.ainvoke.assert_awaited_once()
+
+
+def test_blank_primary_summary_falls_back_to_run_model(monkeypatch: pytest.MonkeyPatch) -> None:
+    """A blank primary response is treated as failure and triggers the run-model
+    fallback, exactly as a raised exception would."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built))
+
+    explicit = _blank_model()  # primary returns whitespace
+    middleware = DeerFlowSummarizationMiddleware(
+        model=explicit,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name="summary-model",
+        run_model_name="run-model",
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    explicit.invoke.assert_called_once()  # blank primary counted as a failure
+    assert built == ["run-model"]  # fallback built + used
+    assert result is not None
+    assert result["summary_text"] == "from-run-model"
+
+
+def test_manual_compaction_failure_raises_summary_generation_error(monkeypatch: pytest.MonkeyPatch) -> None:
+    """A manual /compact opts into ``raise_on_failure`` so a generation failure raises,
+    letting the caller report it distinctly from "nothing to compact". This is now
+    decoupled from ``force`` (which only bypasses the trigger threshold)."""
+    default_model = MagicMock()
+    default_model.with_config.return_value = default_model
+    default_model.invoke.side_effect = RuntimeError("provider down")
+    middleware = DeerFlowSummarizationMiddleware(
+        model=default_model,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model",)),
+        configured_model_name=None,
+        run_model_name="default-model",
+    )
+
+    with pytest.raises(SummaryGenerationError):
+        middleware.compact_state({"messages": _messages()}, _runtime(), force=True, raise_on_failure=True)
+
+
+def test_force_alone_does_not_raise_on_failure(monkeypatch: pytest.MonkeyPatch) -> None:
+    """``force`` bypasses the threshold but must NOT, on its own, raise on a generation
+    failure — only ``raise_on_failure`` does. The automatic path (force + no
+    raise_on_failure) leaves state unchanged."""
+    default_model = MagicMock()
+    default_model.with_config.return_value = default_model
+    default_model.invoke.side_effect = RuntimeError("provider down")
+    middleware = DeerFlowSummarizationMiddleware(
+        model=default_model,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model",)),
+        configured_model_name=None,
+        run_model_name="default-model",
+    )
+
+    assert middleware.compact_state({"messages": _messages()}, _runtime(), force=True) is None
+
+
+def test_before_summarization_hook_not_fired_when_summary_fails(monkeypatch: pytest.MonkeyPatch) -> None:
+    """Hooks must not enqueue durable-memory work for a summary that never
+    materializes; on failure the automatic path returns None without firing hooks."""
+    default_model = MagicMock()
+    default_model.with_config.return_value = default_model
+    default_model.invoke.side_effect = RuntimeError("provider down")
+    captured: list[SummarizationEvent] = []
+    middleware = DeerFlowSummarizationMiddleware(
+        model=default_model,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model",)),
+        configured_model_name=None,
+        run_model_name="default-model",
+        before_summarization=[captured.append],
+    )
+
+    # The run uses the default model, which fails; no distinct fallback in the null case.
+    assert middleware.before_model({"messages": _messages()}, _runtime()) is None
+    assert captured == []
+
+
+def _factory_app_config(model_names, *, summary_model_name=None):
+    """AppConfig-shaped stub for the factory: summarization enabled + ordered models."""
+    models = [SimpleNamespace(name=name) for name in model_names]
+    return SimpleNamespace(
+        summarization=SummarizationConfig(enabled=True, model_name=summary_model_name),
+        memory=MemoryConfig(enabled=False),
+        models=models,
+        get_model_config=lambda name: next((model for model in models if model.name == name), None),
+    )
+
+
+def test_factory_null_case_anchor_is_run_model_not_models0(monkeypatch):
+    """model_name: null builds the summary model from ``run_model_name``, never
+    config.models[0]. A run on a non-default model whose models[0] provider is broken
+    still gets a working summarization middleware — the factory has no eager models[0]
+    dependency."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built))
+
+    middleware = create_summarization_middleware(
+        app_config=_factory_app_config(("models0", "run-model")),
+        keep=("messages", 2),
+        run_model_name="run-model",
+    )
+
+    assert middleware is not None
+    assert built == ["run-model"]  # anchor built from the run model, not models0 / None
+    result = middleware.compact_state({"messages": _messages()}, _runtime(), force=True)
+    assert result is not None
+    assert result.summary_text == "from-run-model"
+
+
+def test_factory_configured_constructor_failure_falls_back_to_run_model(monkeypatch):
+    """A configured summary model whose *constructor* raises must not break middleware
+    creation or skip the healthy run model. The anchor falls through the broken
+    constructor to the run model, and generation summarizes with it (the reviewer's
+    ``configured='broken-summary'`` reproduction)."""
+    built: list = []
+
+    def _factory(*, name=None, thinking_enabled=False, app_config=None, attach_tracing=True, **kwargs):
+        if name == "broken-summary":
+            raise RuntimeError("cannot construct summary provider")
+        model = MagicMock()
+        model.with_config.return_value = model
+        model.invoke.return_value = SimpleNamespace(text=f"from-{name}")
+        model.ainvoke = AsyncMock(return_value=SimpleNamespace(text=f"from-{name}"))
+        built.append(name)
+        return model
+
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _factory)
+
+    middleware = create_summarization_middleware(
+        app_config=_factory_app_config(("models0", "run-model"), summary_model_name="broken-summary"),
+        keep=("messages", 2),
+        run_model_name="run-model",
+    )
+
+    assert middleware is not None  # a broken configured constructor did not break creation
+    assert "run-model" in built  # the healthy run model was constructed as the anchor
+    result = middleware.compact_state({"messages": _messages()}, _runtime(), force=True)
+    assert result is not None
+    assert result.summary_text == "from-run-model"
+
+
+class _RaisingTextResponse:
+    """A provider response whose ``.text`` accessor fails — a realistic malformed result."""
+
+    @property
+    def text(self):
+        raise ValueError("malformed content blocks")
+
+
+def _text_raises_model() -> MagicMock:
+    model = MagicMock()
+    model.with_config.return_value = model
+    model.invoke.return_value = _RaisingTextResponse()
+    model.ainvoke = AsyncMock(return_value=_RaisingTextResponse())
+    return model
+
+
+def test_text_extraction_failure_falls_back_to_run_model(monkeypatch):
+    """A response whose ``.text`` accessor raises is part of consuming the provider
+    result, so it must be a candidate failure that falls back to the run model — not an
+    exception that escapes automatic compaction."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built))
+
+    primary = _text_raises_model()
+    middleware = DeerFlowSummarizationMiddleware(
+        model=primary,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name="summary-model",
+        run_model_name="run-model",
+    )
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    primary.invoke.assert_called_once()  # primary invoked; its .text raised
+    assert built == ["run-model"]  # fell back to the run model
+    assert result is not None
+    assert result["summary_text"] == "from-run-model"
+
+
+@pytest.mark.anyio
+async def test_text_extraction_failure_falls_back_to_run_model_async(monkeypatch):
+    """Async counterpart: a ``.text`` accessor failure falls back to the run model."""
+    built: list = []
+    monkeypatch.setattr("deerflow.agents.middlewares.summarization_middleware.create_chat_model", _tracking_create_chat_model(built))
+
+    primary = _text_raises_model()
+    middleware = DeerFlowSummarizationMiddleware(
+        model=primary,
+        trigger=("messages", 4),
+        keep=("messages", 2),
+        token_counter=len,
+        app_config=_app_config(("default-model", "run-model")),
+        configured_model_name="summary-model",
+        run_model_name="run-model",
+    )
+
+    result = await middleware.abefore_model({"messages": _messages()}, _runtime())
+
+    primary.ainvoke.assert_awaited_once()
+    assert built == ["run-model"]
+    assert result is not None
+    assert result["summary_text"] == "from-run-model"

backend/tests/test_tool_error_handling_middleware.py

@@ -681,10 +681,11 @@ def test_subagent_runtime_middlewares_attach_durable_context_before_summarizatio
     sentinel = object()
     captured: dict[str, object] = {}
 
-    def fake_create_summarization_middleware(*, app_config=None, keep=None, skip_memory_flush=False):
+    def fake_create_summarization_middleware(*, app_config=None, keep=None, skip_memory_flush=False, run_model_name=None):
         captured["app_config"] = app_config
         captured["keep"] = keep
         captured["skip_memory_flush"] = skip_memory_flush
+        captured["run_model_name"] = run_model_name
         return sentinel
 
     # summarization is enabled by default False; flip it on so the factory path
@@ -703,6 +704,10 @@ def test_subagent_runtime_middlewares_attach_durable_context_before_summarizatio
     # skip_memory_flush=True so subagent-internal turns are not flushed into the
     # PARENT thread's durable memory (#3875 Phase 3 review).
     assert captured["skip_memory_flush"] is True
+    # Model ownership: the subagent's own resolved model is threaded into the factory
+    # so a distinct-model subagent summarizes with its model, not the parent's — the
+    # subagent context/configurable never carries the child model.
+    assert captured["run_model_name"] == "test-model"
     durable = [middleware for middleware in middlewares if isinstance(middleware, DurableContextMiddleware)]
     assert len(durable) == 1
     # ``_skills_root`` is ``posixpath.normpath(container_path)``, so compare against

config.example.yaml

@@ -1522,7 +1522,11 @@ title:
 summarization:
   enabled: true
 
-  # Model to use for summarization (null = use default model)
+  # Model to use for summarization.
+  #   null = summarize with the model the run actually uses (the lead run's model, a
+  #          subagent's own model, or a thread's custom-agent model), NOT models[0].
+  #   set  = that model generates; if its provider fails, compaction falls back to the
+  #          run's own model so a broken summary provider cannot disable compaction.
   # Recommended: Use a lightweight, cost-effective model like "gpt-4o-mini" or similar
   model_name: null
 

frontend/src/components/workspace/input-box.tsx

@@ -1001,6 +1001,8 @@ export function InputBox({
         signal,
         agentName:
           typeof context.agent_name === "string" ? context.agent_name : null,
+        modelName:
+          typeof context.model_name === "string" ? context.model_name : null,
       });
       if (
         !isCurrentGoalRequest(compactRequestStateRef.current, request, threadId)
@@ -1039,6 +1041,7 @@ export function InputBox({
     }
   }, [
     context.agent_name,
+    context.model_name,
     queryClient,
     t.inputBox.compactFailed,
     t.inputBox.compactSkipped,

frontend/src/core/threads/api.ts

@@ -17,6 +17,7 @@ export type ThreadCompactResponse = {
 export type CompactThreadContextOptions = {
   signal?: AbortSignal;
   agentName?: string | null;
+  modelName?: string | null;
 };
 
 export type ThreadBranchResponse = {
@@ -110,6 +111,7 @@ export async function compactThreadContext(
       body: JSON.stringify({
         force: true,
         ...(options.agentName ? { agent_name: options.agentName } : {}),
+        ...(options.modelName ? { model_name: options.modelName } : {}),
       }),
       signal: options.signal,
     },