Merge 58d0dc37d6 into e1d16f51d1

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,
@@ -170,9 +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
-    if "/" not in full_model_name:
-        full_model_name = f"{custom_llm_provider}/{full_model_name}"
+    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,
+    )
 
     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,
@@ -5685,9 +5688,12 @@ class BaseLLMHTTPHandler:
         if patch.messages is None:
             raise ValueError("Agentic loop plan missing patched messages")
 
-        full_model_name = patch.model or model
-        if "/" not in full_model_name:
-            full_model_name = f"{custom_llm_provider}/{full_model_name}"
+        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,
+        )
 
         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

@@ -0,0 +1,92 @@
+from typing import Final, Literal
+from unittest.mock import AsyncMock, patch
+
+import pytest
+
+import litellm
+from litellm.integrations.custom_logger import CustomLogger
+from litellm.litellm_core_utils.chat_completion_agentic_loop import (
+    _execute_chat_completion_agentic_plan,
+)
+from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler
+from litellm.types.integrations.custom_logger import (
+    AgenticLoopPlan,
+    AgenticLoopRequestPatch,
+)
+from litellm.types.utils import ModelResponse
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("execution_path", ("http", "sdk"))
+@pytest.mark.parametrize(
+    ("request_model", "patch_model", "custom_llm_provider", "expected_model"),
+    (
+        ("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",
+    ),
+)
+async def test_agentic_followup_preserves_provider_prefix(
+    execution_path: Literal["http", "sdk"],
+    request_model: str,
+    patch_model: str | None,
+    custom_llm_provider: str,
+    expected_model: str,
+) -> None:
+    plan: Final = AgenticLoopPlan(
+        run_agentic_loop=True,
+        request_patch=AgenticLoopRequestPatch(
+            model=patch_model,
+            messages=[{"role": "user", "content": "Continue"}],
+        ),
+    )
+    followup: Final = AsyncMock(wraps=litellm.acompletion)
+
+    with patch("litellm.acompletion", new=followup):
+        response: Final = (
+            await BaseLLMHTTPHandler()._execute_chat_completion_agentic_plan(
+                plan=plan,
+                model=request_model,
+                messages=[],
+                optional_params={"mock_response": "Follow-up complete"},
+                kwargs={"custom_llm_provider": custom_llm_provider},
+                custom_llm_provider=custom_llm_provider,
+                depth=0,
+                max_loops=3,
+                fingerprints=[],
+                fingerprint="followup",
+            )
+            if execution_path == "http"
+            else await _execute_chat_completion_agentic_plan(
+                plan=plan,
+                callback=CustomLogger(),
+                model=request_model,
+                optional_params={"mock_response": "Follow-up complete"},
+                kwargs={"custom_llm_provider": custom_llm_provider},
+                logging_obj=None,
+                custom_llm_provider=custom_llm_provider,
+                depth=0,
+                max_loops=3,
+                fingerprints=[],
+                fingerprint="followup",
+            )
+        )
+
+    followup.assert_awaited_once()
+    assert followup.await_args is not None
+    assert followup.await_args.kwargs["model"] == expected_model
+    assert isinstance(response, ModelResponse)
+    assert response.model == expected_model.split("/", 1)[1]