Litellm dev 01 25 2025 p2 (#8003)

* fix(base_utils.py): supported nested json schema passed in for anthropic calls

* refactor(base_utils.py): refactor ref parsing to prevent infinite loop

* test(test_openai_endpoints.py): refactor anthropic test to use bedrock

* fix(langfuse_prompt_management.py): add unit test for sync langfuse calls

Resolves https://github.com/BerriAI/litellm/issues/7938#issuecomment-2613293757

litellm/llms/base_llm/base_utils.py

@@ -1,3 +1,4 @@
+import copy
 from abc import ABC, abstractmethod
 from typing import List, Optional, Type, Union
 
@@ -31,6 +32,47 @@ class BaseLLMModelInfo(ABC):
         pass
 
 
+def _dict_to_response_format_helper(
+    response_format: dict, ref_template: Optional[str] = None
+) -> dict:
+    if ref_template is not None and response_format.get("type") == "json_schema":
+        # Deep copy to avoid modifying original
+        modified_format = copy.deepcopy(response_format)
+        schema = modified_format["json_schema"]["schema"]
+
+        # Update all $ref values in the schema
+        def update_refs(schema):
+            stack = [(schema, [])]
+            visited = set()
+
+            while stack:
+                obj, path = stack.pop()
+                obj_id = id(obj)
+
+                if obj_id in visited:
+                    continue
+                visited.add(obj_id)
+
+                if isinstance(obj, dict):
+                    if "$ref" in obj:
+                        ref_path = obj["$ref"]
+                        model_name = ref_path.split("/")[-1]
+                        obj["$ref"] = ref_template.format(model=model_name)
+
+                    for k, v in obj.items():
+                        if isinstance(v, (dict, list)):
+                            stack.append((v, path + [k]))
+
+                elif isinstance(obj, list):
+                    for i, item in enumerate(obj):
+                        if isinstance(item, (dict, list)):
+                            stack.append((item, path + [i]))
+
+        update_refs(schema)
+        return modified_format
+    return response_format
+
+
 def type_to_response_format_param(
     response_format: Optional[Union[Type[BaseModel], dict]],
     ref_template: Optional[str] = None,
@@ -44,7 +86,7 @@ def type_to_response_format_param(
         return None
 
     if isinstance(response_format, dict):
-        return response_format
+        return _dict_to_response_format_helper(response_format, ref_template)
 
     # type checkers don't narrow the negation of a `TypeGuard` as it isn't
     # a safe default behaviour but we know that at this point the `response_format`