apply change and fixed test cases

llama_stack/providers/remote/inference/sambanova/sambanova.py

@@ -8,16 +8,16 @@ import json
 from typing import AsyncGenerator
 
 from llama_models.datatypes import CoreModelId, SamplingStrategy
-
 from llama_models.llama3.api.chat_format import ChatFormat
-
-from llama_models.llama3.api.datatypes import Message
 from llama_models.llama3.api.tokenizer import Tokenizer
-
 from openai import OpenAI
 
+from llama_stack.apis.common.content_types import (
+    ImageContentItem,
+    InterleavedContent,
+    TextContentItem,
+)
 from llama_stack.apis.inference import *  # noqa: F403
-
 from llama_stack.providers.utils.inference.model_registry import (
     build_model_alias,
     ModelRegistryHelper,
@@ -25,9 +25,8 @@ from llama_stack.providers.utils.inference.model_registry import (
 from llama_stack.providers.utils.inference.openai_compat import (
     process_chat_completion_stream_response,
 )
-
 from llama_stack.providers.utils.inference.prompt_adapter import (
-    convert_image_media_to_url,
+    convert_image_content_to_url,
 )
 
 from .config import SambaNovaImplConfig
@@ -86,7 +85,7 @@ class SambaNovaInferenceAdapter(ModelRegistryHelper, Inference):
     async def completion(
         self,
         model_id: str,
-        content: InterleavedTextMedia,
+        content: InterleavedContent,
         sampling_params: Optional[SamplingParams] = SamplingParams(),
         response_format: Optional[ResponseFormat] = None,
         stream: Optional[bool] = False,
@@ -129,6 +128,7 @@ class SambaNovaInferenceAdapter(ModelRegistryHelper, Inference):
         self, request: ChatCompletionRequest
     ) -> ChatCompletionResponse:
         response = self._get_client().chat.completions.create(**request)
+
         choice = response.choices[0]
 
         result = ChatCompletionResponse(
@@ -163,7 +163,7 @@ class SambaNovaInferenceAdapter(ModelRegistryHelper, Inference):
     async def embeddings(
         self,
         model_id: str,
-        contents: List[InterleavedTextMedia],
+        contents: List[InterleavedContent],
     ) -> EmbeddingsResponse:
         raise NotImplementedError()
 
@@ -244,21 +244,19 @@ class SambaNovaInferenceAdapter(ModelRegistryHelper, Inference):
 
     async def convert_to_sambanova_content(self, message: Message) -> dict:
         async def _convert_content(content) -> dict:
-            if isinstance(content, ImageMedia):
-                download = False
-                if isinstance(content, ImageMedia) and isinstance(content.image, URL):
-                    download = content.image.uri.startswith("https://")
+            if isinstance(content, ImageContentItem):
+                url = await convert_image_content_to_url(content, download=True)
+                # A fix to make sure the call sucess.
+                components = url.split(";base64")
+                url = f"{components[0].lower()};base64{components[1]}"
                 return {
                     "type": "image_url",
-                    "image_url": {
-                        "url": await convert_image_media_to_url(
-                            content, download=download
-                        ),
-                    },
+                    "image_url": {"url": url},
                 }
             else:
-                assert isinstance(content, str)
-                return {"type": "text", "text": content}
+                text = content.text if isinstance(content, TextContentItem) else content
+                assert isinstance(text, str)
+                return {"type": "text", "text": text}
 
         if isinstance(message.content, list):
             # If it is a list, the text content should be wrapped in dict
@@ -320,11 +318,14 @@ class SambaNovaInferenceAdapter(ModelRegistryHelper, Inference):
         if not tool_calls:
             return []
 
+        for call in tool_calls:
+            call_function_arguments = json.loads(call.function.arguments)
+
         compitable_tool_calls = [
             ToolCall(
                 call_id=call.id,
                 tool_name=call.function.name,
-                arguments=call.function.arguments,
+                arguments=call_function_arguments,
             )
             for call in tool_calls
         ]