fix(agentic): keep provider prefix for org-named models on follow-up calls

litellm/litellm_core_utils/agentic_followup_kwargs.py

@@ -4,6 +4,23 @@ from types import MappingProxyType
 from typing import Final
 
 
+def resolve_agentic_followup_model(
+    *,
+    request_model: str,
+    patch_model: str | None,
+    custom_llm_provider: str,
+    known_providers: Collection[str],
+) -> str:
+    """The request model is already provider-stripped, so a leading "openai/" there is an org name.
+    Only a callback-supplied model may carry its own provider prefix and switch providers"""
+    model: Final = patch_model or request_model
+    if not custom_llm_provider or model.startswith(f"{custom_llm_provider}/"):
+        return model
+    if patch_model and "/" in patch_model and patch_model.split("/", 1)[0] in known_providers:
+        return patch_model
+    return f"{custom_llm_provider}/{model}"
+
+
 def build_agentic_followup_kwargs(
     *,
     request_kwargs: Mapping[str, object],

litellm/litellm_core_utils/chat_completion_agentic_loop.py

@@ -8,7 +8,10 @@ from typing import Final, cast
 
 from litellm._logging import verbose_logger
 from litellm.integrations.custom_logger import CustomLogger
-from litellm.litellm_core_utils.agentic_followup_kwargs import build_agentic_followup_kwargs
+from litellm.litellm_core_utils.agentic_followup_kwargs import (
+    build_agentic_followup_kwargs,
+    resolve_agentic_followup_model,
+)
 from litellm.litellm_core_utils.agentic_loop_settings import (
     DEFAULT_MAX_AGENTIC_LOOPS,
     validated_max_agentic_loops,
@@ -170,14 +173,12 @@ async def _execute_chat_completion_agentic_plan(
     if patch.messages is None:
         raise ValueError("Agentic loop plan missing patched messages")
 
-    full_model_name = patch.model or model
-    known_providers: Final = getattr(litellm, "provider_list", [])
-    has_provider_prefix: Final = (
-        full_model_name.startswith(f"{custom_llm_provider}/")
-        or ("/" in full_model_name and full_model_name.split("/", 1)[0] in known_providers)
+    full_model_name: Final = resolve_agentic_followup_model(
+        request_model=model,
+        patch_model=patch.model,
+        custom_llm_provider=custom_llm_provider,
+        known_providers=litellm.provider_list,
     )
-    if custom_llm_provider and not has_provider_prefix:
-        full_model_name = f"{custom_llm_provider}/{full_model_name}"
 
     optional_params_for_followup: Final = {**optional_params, **patch.optional_params}
     if patch.tools is not None:

litellm/llms/custom_httpx/llm_http_handler.py

@@ -37,7 +37,10 @@ from litellm._logging import _redact_string, verbose_logger
 from litellm.anthropic_beta_headers_manager import update_headers_with_filtered_beta
 from litellm.constants import MAX_FILE_LIST_LIMIT, REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES
 from litellm.files.types import FileContentStreamingResult
-from litellm.litellm_core_utils.agentic_followup_kwargs import build_agentic_followup_kwargs
+from litellm.litellm_core_utils.agentic_followup_kwargs import (
+    build_agentic_followup_kwargs,
+    resolve_agentic_followup_model,
+)
 from litellm.litellm_core_utils.agentic_loop_settings import (
     DEFAULT_MAX_AGENTIC_LOOPS,
     validated_max_agentic_loops,
@@ -5685,14 +5688,12 @@ class BaseLLMHTTPHandler:
         if patch.messages is None:
             raise ValueError("Agentic loop plan missing patched messages")
 
-        full_model_name = patch.model or model
-        known_providers: Final = getattr(litellm, "provider_list", [])
-        has_provider_prefix: Final = (
-            full_model_name.startswith(f"{custom_llm_provider}/")
-            or ("/" in full_model_name and full_model_name.split("/", 1)[0] in known_providers)
+        full_model_name: Final = resolve_agentic_followup_model(
+            request_model=model,
+            patch_model=patch.model,
+            custom_llm_provider=custom_llm_provider,
+            known_providers=litellm.provider_list,
         )
-        if custom_llm_provider and not has_provider_prefix:
-            full_model_name = f"{custom_llm_provider}/{full_model_name}"
 
         optional_params_for_followup: Final = dict(optional_params)
         optional_params_for_followup.update(patch.optional_params)

tests/test_litellm/test_agentic_loop_prefix_44069.py

@@ -18,29 +18,38 @@ from litellm.types.utils import ModelResponse
 
 @pytest.mark.asyncio
 @pytest.mark.parametrize("execution_path", ("http", "sdk"))
-@pytest.mark.parametrize("use_patch_model", (False, True), ids=("original-model", "patch-model"))
 @pytest.mark.parametrize(
-    ("model_name", "custom_llm_provider", "expected_model"),
+    ("request_model", "patch_model", "custom_llm_provider", "expected_model"),
     (
-        ("zai-org/GLM-5.3-Flash", "hosted_vllm", "hosted_vllm/zai-org/GLM-5.3-Flash"),
-        ("hosted_vllm/zai-org/GLM-5.3-Flash", "hosted_vllm", "hosted_vllm/zai-org/GLM-5.3-Flash"),
-        ("hosted_vllm/zai-org/GLM-5.3-Flash", "", "hosted_vllm/zai-org/GLM-5.3-Flash"),
-        ("openai/gpt-4o", "hosted_vllm", "openai/gpt-4o"),
+        ("zai-org/GLM-5.3-Flash", None, "hosted_vllm", "hosted_vllm/zai-org/GLM-5.3-Flash"),
+        ("hosted_vllm/zai-org/GLM-5.3-Flash", None, "hosted_vllm", "hosted_vllm/zai-org/GLM-5.3-Flash"),
+        ("hosted_vllm/zai-org/GLM-5.3-Flash", None, "", "hosted_vllm/zai-org/GLM-5.3-Flash"),
+        ("openai/whisper-large-v3", None, "hosted_vllm", "hosted_vllm/openai/whisper-large-v3"),
+        ("original-model", "zai-org/GLM-5.3-Flash", "hosted_vllm", "hosted_vllm/zai-org/GLM-5.3-Flash"),
+        ("original-model", "hosted_vllm/zai-org/GLM-5.3-Flash", "hosted_vllm", "hosted_vllm/zai-org/GLM-5.3-Flash"),
+        ("original-model", "openai/gpt-4o", "hosted_vllm", "openai/gpt-4o"),
+    ),
+    ids=(
+        "organization-model",
+        "already-prefixed",
+        "no-provider",
+        "organization-named-after-provider",
+        "patch-organization-model",
+        "patch-already-prefixed",
+        "patch-cross-provider",
     ),
-    ids=("organization-model", "already-prefixed", "no-provider", "cross-provider"),
 )
 async def test_agentic_followup_preserves_provider_prefix(
     execution_path: Literal["http", "sdk"],
-    use_patch_model: bool,
-    model_name: str,
+    request_model: str,
+    patch_model: str | None,
     custom_llm_provider: str,
     expected_model: str,
 ) -> None:
-    model: Final = "original-model" if use_patch_model else model_name
     plan: Final = AgenticLoopPlan(
         run_agentic_loop=True,
         request_patch=AgenticLoopRequestPatch(
-            model=model_name if use_patch_model else None,
+            model=patch_model,
             messages=[{"role": "user", "content": "Continue"}],
         ),
     )
@@ -50,7 +59,7 @@ async def test_agentic_followup_preserves_provider_prefix(
         response: Final = (
             await BaseLLMHTTPHandler()._execute_chat_completion_agentic_plan(
                 plan=plan,
-                model=model,
+                model=request_model,
                 messages=[],
                 optional_params={"mock_response": "Follow-up complete"},
                 kwargs={"custom_llm_provider": custom_llm_provider},
@@ -64,7 +73,7 @@ async def test_agentic_followup_preserves_provider_prefix(
             else await _execute_chat_completion_agentic_plan(
                 plan=plan,
                 callback=CustomLogger(),
-                model=model,
+                model=request_model,
                 optional_params={"mock_response": "Follow-up complete"},
                 kwargs={"custom_llm_provider": custom_llm_provider},
                 logging_obj=None,