feat(databricks/chat): support structured outputs on databricks

Closes https://github.com/BerriAI/litellm/pull/6978

- handles content as list for dbrx, - handles streaming+response_format for dbrx

litellm/llms/databricks/common_utils.py

@@ -0,0 +1,82 @@
+from typing import Literal, Optional, Tuple
+
+from .exceptions import DatabricksError
+
+
+class DatabricksBase:
+    def _get_databricks_credentials(
+        self, api_key: Optional[str], api_base: Optional[str], headers: Optional[dict]
+    ) -> Tuple[str, dict]:
+        headers = headers or {"Content-Type": "application/json"}
+        try:
+            from databricks.sdk import WorkspaceClient
+
+            databricks_client = WorkspaceClient()
+
+            api_base = api_base or f"{databricks_client.config.host}/serving-endpoints"
+
+            if api_key is None:
+                databricks_auth_headers: dict[str, str] = (
+                    databricks_client.config.authenticate()
+                )
+                headers = {**databricks_auth_headers, **headers}
+
+            return api_base, headers
+        except ImportError:
+            raise DatabricksError(
+                status_code=400,
+                message=(
+                    "If the Databricks base URL and API key are not set, the databricks-sdk "
+                    "Python library must be installed. Please install the databricks-sdk, set "
+                    "{LLM_PROVIDER}_API_BASE and {LLM_PROVIDER}_API_KEY environment variables, "
+                    "or provide the base URL and API key as arguments."
+                ),
+            )
+
+    def databricks_validate_environment(
+        self,
+        api_key: Optional[str],
+        api_base: Optional[str],
+        endpoint_type: Literal["chat_completions", "embeddings"],
+        custom_endpoint: Optional[bool],
+        headers: Optional[dict],
+    ) -> Tuple[str, dict]:
+        if api_key is None and headers is None:
+            if custom_endpoint is not None:
+                raise DatabricksError(
+                    status_code=400,
+                    message="Missing API Key - A call is being made to LLM Provider but no key is set either in the environment variables ({LLM_PROVIDER}_API_KEY) or via params",
+                )
+            else:
+                api_base, headers = self._get_databricks_credentials(
+                    api_base=api_base, api_key=api_key, headers=headers
+                )
+
+        if api_base is None:
+            if custom_endpoint:
+                raise DatabricksError(
+                    status_code=400,
+                    message="Missing API Base - A call is being made to LLM Provider but no api base is set either in the environment variables ({LLM_PROVIDER}_API_KEY) or via params",
+                )
+            else:
+                api_base, headers = self._get_databricks_credentials(
+                    api_base=api_base, api_key=api_key, headers=headers
+                )
+
+        if headers is None:
+            headers = {
+                "Authorization": "Bearer {}".format(api_key),
+                "Content-Type": "application/json",
+            }
+        else:
+            if api_key is not None:
+                headers.update({"Authorization": "Bearer {}".format(api_key)})
+
+        if api_key is not None:
+            headers["Authorization"] = f"Bearer {api_key}"
+
+        if endpoint_type == "chat_completions" and custom_endpoint is not True:
+            api_base = "{}/chat/completions".format(api_base)
+        elif endpoint_type == "embeddings" and custom_endpoint is not True:
+            api_base = "{}/embeddings".format(api_base)
+        return api_base, headers