fix(oci): translate response_format json_schema to OCI's accepted shape

litellm/llms/oci/chat/transformation.py

@@ -199,19 +199,49 @@ def _normalize_response_format(selected_params: Dict, vendor: OCIVendors) -> Non
     rf = selected_params.get("responseFormat")
     if not isinstance(rf, dict) or "type" not in rf:
         return
-    rf_payload = dict(rf)
-    selected_params["responseFormat"] = rf_payload
-    response_type = rf_payload["type"]
-    if "json_schema" in rf_payload:
-        raw_schema = rf_payload.pop("json_schema")
-        rf_payload["jsonSchema"] = (
-            dict(raw_schema) if isinstance(raw_schema, dict) else raw_schema
-        )
+
+    rf_type = str(rf["type"]).lower()
+    raw_schema = rf.get("json_schema")
+    json_schema = raw_schema if isinstance(raw_schema, dict) else None
+
+    if rf_type == "text":
+        selected_params["responseFormat"] = {"type": "TEXT"}
+        return
+
     if vendor == OCIVendors.COHERE:
-        rf_payload["type"] = response_type
-    else:
-        fmt = response_type.upper()
-        rf_payload["type"] = "JSON_OBJECT" if fmt == "JSON" else fmt
+        # OCI Cohere has no JSON_SCHEMA type; a schema rides on JSON_OBJECT.
+        payload: Dict[str, Any] = {"type": "JSON_OBJECT"}
+        if json_schema is not None and json_schema.get("schema") is not None:
+            payload["schema"] = json_schema["schema"]
+        selected_params["responseFormat"] = payload
+        return
+
+    if rf_type == "json_schema":
+        if json_schema is None:
+            raise OCIError(
+                status_code=400,
+                message="response_format type 'json_schema' requires a 'json_schema' object",
+            )
+        # OCI's ResponseJsonSchema accepts only name/description/schema/isStrict.
+        # OpenAI sends `strict` instead of `isStrict`; forwarding it (or any
+        # other extra key) makes OCI reject the whole request with HTTP 400.
+        oci_schema: Dict[str, Any] = {"name": json_schema.get("name") or "response"}
+        if json_schema.get("description") is not None:
+            oci_schema["description"] = json_schema["description"]
+        if json_schema.get("schema") is not None:
+            oci_schema["schema"] = json_schema["schema"]
+        if json_schema.get("strict") is not None:
+            oci_schema["isStrict"] = json_schema["strict"]
+        selected_params["responseFormat"] = {
+            "type": "JSON_SCHEMA",
+            "jsonSchema": oci_schema,
+        }
+        return
+
+    fmt = rf_type.upper()
+    selected_params["responseFormat"] = {
+        "type": "JSON_OBJECT" if fmt == "JSON" else fmt
+    }
 
 
 def get_vendor_from_model(model: str) -> OCIVendors:

litellm/types/llms/oci.py

@@ -291,25 +291,6 @@ class CohereToolResult(BaseModel):
     outputs: List[Dict[str, Any]]
 
 
-class CohereResponseFormat(BaseModel):
-    """Response format for Cohere."""
-
-    type: str
-
-
-class CohereResponseTextFormat(CohereResponseFormat):
-    """Text response format for Cohere."""
-
-    type: Literal["text"] = "text"
-
-
-class CohereResponseJSONSchemaFormat(CohereResponseFormat):
-    """JSON schema response format for Cohere."""
-
-    type: Literal["json_schema"] = "json_schema"
-    jsonSchema: Dict[str, Any]
-
-
 class CohereChatRequest(BaseModel):
     """Cohere chat request model."""
 
@@ -336,13 +317,10 @@ class CohereChatRequest(BaseModel):
     # ``OCIChatConfig.openai_to_oci_cohere_param_map`` which marks
     # ``tool_choice`` as unsupported. The field is intentionally absent here
     # so it isn't silently dropped or surfaced as a supported feature.
-    responseFormat: Optional[
-        Union[
-            CohereResponseTextFormat,
-            CohereResponseJSONSchemaFormat,
-            CohereResponseFormat,
-        ]
-    ] = None
+    # OCI Cohere responseFormat is {"type": "TEXT" | "JSON_OBJECT", "schema"?: ...};
+    # there is no JSON_SCHEMA type. The shape is built in
+    # OCIChatConfig._normalize_response_format.
+    responseFormat: Optional[Dict[str, Any]] = None
     preambleOverride: Optional[str] = None
     documents: Optional[List[Dict[str, Any]]] = None
     searchQueriesOnly: Optional[bool] = None

tests/integration/test_oci_proxy_integration.py

@@ -30,6 +30,7 @@
 
 from __future__ import annotations
 
+import json
 import os
 import socket
 import subprocess
@@ -41,7 +42,6 @@
 import httpx
 import pytest
 
-
 # ---------------------------------------------------------------------------
 # Skip gate
 # ---------------------------------------------------------------------------
@@ -79,7 +79,9 @@ def _wait_for_health(base_url: str, proc: subprocess.Popen, deadline: float) ->
         except httpx.HTTPError:
             pass
         time.sleep(0.5)
-    raise RuntimeError(f"litellm proxy did not become ready within {STARTUP_TIMEOUT_S}s")
+    raise RuntimeError(
+        f"litellm proxy did not become ready within {STARTUP_TIMEOUT_S}s"
+    )
 
 
 def _oci_env_from_profile() -> dict[str, str]:
@@ -206,9 +208,7 @@ def test_chat_completion_via_proxy(proxy_url: str, model: str) -> None:
     # Reasoning models may return empty content if their budget covers only
     # the thinking turn — accept either text or a non-empty reasoning field.
     has_content = bool(msg.get("content"))
-    has_reasoning = bool(msg.get("reasoning_content")) or bool(
-        msg.get("reasoning")
-    )
+    has_reasoning = bool(msg.get("reasoning_content")) or bool(msg.get("reasoning"))
     assert has_content or has_reasoning, f"empty assistant message for {model}: {msg}"
     usage = body.get("usage") or {}
     assert usage.get("total_tokens", 0) > 0
@@ -232,7 +232,7 @@ def test_chat_completion_streaming_via_proxy(proxy_url: str, model: str) -> None
                 continue
             if not line.startswith("data:"):
                 continue
-            payload = line[len("data:"):].strip()
+            payload = line[len("data:") :].strip()
             if payload == "[DONE]":
                 saw_done = True
                 break
@@ -274,9 +274,54 @@ def test_model_list_advertises_oci_models(proxy_url: str) -> None:
         assert expected in advertised, f"{expected} missing from /v1/models: {advertised}"
 
 
+@pytest.mark.parametrize("model", ["oci-cohere-command", "oci-llama"])
+def test_response_format_json_schema_via_proxy(proxy_url: str, model: str) -> None:
+    """A response_format json_schema succeeds through the gateway for both a
+    Cohere and a generic OCI model.
+    Regression for the HTTP 400 ``Please pass in correct format of request``
+    that rejected every json_schema request (which MLflow LLM judges always
+    send): generic models choke on OpenAI's ``strict`` key, and Cohere has no
+    JSON_SCHEMA type.
+    """
+    r = httpx.post(
+        f"{proxy_url}/v1/chat/completions",
+        headers=_auth_headers(),
+        json={
+            "model": model,
+            "messages": [
+                {
+                    "role": "user",
+                    "content": "Rate the answer 4 to 2+2. Give an integer score and a short rationale.",
+                }
+            ],
+            "max_tokens": 200,
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "judgment",
+                    "strict": True,
+                    "schema": {
+                        "type": "object",
+                        "properties": {
+                            "score": {"type": "integer"},
+                            "rationale": {"type": "string"},
+                        },
+                        "required": ["score", "rationale"],
+                        "additionalProperties": False,
+                    },
+                },
+            },
+        },
+        timeout=REQUEST_TIMEOUT_S,
+    )
+    assert r.status_code == 200, f"{model} json_schema -> {r.status_code}: {r.text}"
+    content = r.json()["choices"][0]["message"]["content"]
+    assert content is not None
+    assert "score" in json.loads(content)
+
+
 def test_omitted_max_tokens_not_truncated(proxy_url: str) -> None:
     """A request that omits max_tokens completes instead of being cut off.
-
     Regression for OCI's tiny server-side maxTokens default (~20 tokens): without
     an injected default, a request that doesn't set max_tokens came back with
     finish_reason "length" after ~19 tokens, so structured outputs (e.g. MLflow
@@ -308,4 +353,4 @@ def test_omitted_max_tokens_not_truncated(proxy_url: str) -> None:
     assert content.strip(), f"empty content: {choice}"
     # The ~20-token server default truncated well before this; a complete
     # four-to-five sentence answer comfortably exceeds it.
-    assert body["usage"]["completion_tokens"] > 50, body["usage"]
+    assert body["usage"]["completion_tokens"] > 50, body["usage"]

tests/test_litellm/llms/oci/chat/test_oci_chat_transformation.py

@@ -364,6 +364,137 @@ def test_transform_request_response_format_json_shorthand(self):
         rf = transformed_request["chatRequest"]["responseFormat"]
         assert rf["type"] == "JSON_OBJECT"
 
+    def test_transform_request_response_format_json_schema_generic(self):
+        """A GENERIC json_schema must become OCI's JSON_SCHEMA shape with the
+        OpenAI ``strict`` key renamed to ``isStrict``.
+
+        OCI's ResponseJsonSchema rejects ``strict`` (and any other extra key)
+        with HTTP 400 "Please pass in correct format of request", so the raw
+        OpenAI body must not be forwarded.
+        """
+        config = OCIChatConfig()
+        optional_params = {
+            "oci_compartment_id": TEST_COMPARTMENT_ID,
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "judgment",
+                    "description": "a score and rationale",
+                    "strict": True,
+                    "schema": {
+                        "type": "object",
+                        "properties": {"score": {"type": "integer"}},
+                        "required": ["score"],
+                    },
+                },
+            },
+        }
+        transformed_request = config.transform_request(
+            model=TEST_MODEL_NAME,  # xai.grok-4 -> GENERIC
+            messages=TEST_MESSAGES,  # type: ignore
+            optional_params=optional_params,
+            litellm_params={},
+            headers={},
+        )
+        rf = transformed_request["chatRequest"]["responseFormat"]
+        assert rf["type"] == "JSON_SCHEMA"
+        assert "strict" not in rf["jsonSchema"]
+        assert rf["jsonSchema"]["isStrict"] is True
+        assert rf["jsonSchema"]["name"] == "judgment"
+        assert rf["jsonSchema"]["description"] == "a score and rationale"
+        assert rf["jsonSchema"]["schema"]["properties"]["score"]["type"] == "integer"
+
+    def test_transform_request_response_format_json_schema_generic_no_strict(self):
+        """A GENERIC json_schema without ``strict`` must omit ``isStrict``."""
+        config = OCIChatConfig()
+        optional_params = {
+            "oci_compartment_id": TEST_COMPARTMENT_ID,
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {"name": "j", "schema": {"type": "object"}},
+            },
+        }
+        transformed_request = config.transform_request(
+            model=TEST_MODEL_NAME,
+            messages=TEST_MESSAGES,  # type: ignore
+            optional_params=optional_params,
+            litellm_params={},
+            headers={},
+        )
+        rf = transformed_request["chatRequest"]["responseFormat"]
+        assert rf["type"] == "JSON_SCHEMA"
+        assert "isStrict" not in rf["jsonSchema"]
+
+    def test_transform_request_response_format_json_schema_cohere(self):
+        """A Cohere json_schema must fold the schema onto JSON_OBJECT.
+
+        OCI Cohere has no JSON_SCHEMA type; sending one yields HTTP 400.
+        """
+        config = OCIChatConfig()
+        optional_params = {
+            "oci_compartment_id": TEST_COMPARTMENT_ID,
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "judgment",
+                    "strict": True,
+                    "schema": {
+                        "type": "object",
+                        "properties": {"score": {"type": "integer"}},
+                    },
+                },
+            },
+        }
+        transformed_request = config.transform_request(
+            model="cohere.command-latest",
+            messages=TEST_MESSAGES,  # type: ignore
+            optional_params=optional_params,
+            litellm_params={},
+            headers={},
+        )
+        rf = transformed_request["chatRequest"]["responseFormat"]
+        assert rf["type"] == "JSON_OBJECT"
+        assert "jsonSchema" not in rf
+        assert rf["schema"]["properties"]["score"]["type"] == "integer"
+
+    def test_transform_request_response_format_cohere_json_object(self):
+        """Cohere json_object without a schema stays a bare JSON_OBJECT."""
+        config = OCIChatConfig()
+        optional_params = {
+            "oci_compartment_id": TEST_COMPARTMENT_ID,
+            "response_format": {"type": "json_object"},
+        }
+        transformed_request = config.transform_request(
+            model="cohere.command-latest",
+            messages=TEST_MESSAGES,  # type: ignore
+            optional_params=optional_params,
+            litellm_params={},
+            headers={},
+        )
+        rf = transformed_request["chatRequest"]["responseFormat"]
+        assert rf == {"type": "JSON_OBJECT"}
+
+    def test_transform_request_json_schema_without_body_raises_generic(self):
+        """A GENERIC json_schema with no ``json_schema`` body must raise an early
+        400, not silently emit {"type": "JSON_SCHEMA"} (which OCI rejects)."""
+        from litellm.llms.oci.common_utils import OCIError
+
+        config = OCIChatConfig()
+        optional_params = {
+            "oci_compartment_id": TEST_COMPARTMENT_ID,
+            "response_format": {"type": "json_schema"},
+        }
+        with pytest.raises(OCIError) as exc_info:
+            config.transform_request(
+                model=TEST_MODEL_NAME,  # GENERIC
+                messages=TEST_MESSAGES,  # type: ignore
+                optional_params=optional_params,
+                litellm_params={},
+                headers={},
+            )
+        assert exc_info.value.status_code == 400
+        assert "json_schema" in str(exc_info.value)
+
     def test_transform_response_without_token_details(self):
         """
         Tests that responses missing completionTokensDetails and promptTokensDetails