fix(ollama): Download remote image URLs for Ollama

llama_stack/providers/remote/inference/ollama/ollama.py

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 
+import base64
 import uuid
 from collections.abc import AsyncGenerator, AsyncIterator
 from typing import Any
@@ -77,6 +78,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
     content_has_media,
     convert_image_content_to_url,
     interleaved_content_as_str,
+    localize_image_content,
     request_has_media,
 )
 
@@ -496,6 +498,21 @@ class OllamaInferenceAdapter(
         user: str | None = None,
     ) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
         model_obj = await self._get_model(model)
+
+        # Ollama does not support image urls, so we need to download the image and convert it to base64
+        async def _convert_message(m: OpenAIMessageParam) -> OpenAIMessageParam:
+            if isinstance(m.content, list):
+                for c in m.content:
+                    if c.type == "image_url" and c.image_url.url:
+                        localize_result = await localize_image_content(c.image_url.url)
+                        if localize_result is None:
+                            raise ValueError(f"Failed to localize image content from {c.image_url.url}")
+
+                        content, format = localize_result
+                        c.image_url.url = f"data:image/{format};base64,{base64.b64encode(content).decode('utf-8')}"
+            return m
+
+        messages = [await _convert_message(m) for m in messages]
         params = await prepare_openai_completion_params(
             model=model_obj.provider_resource_id,
             messages=messages,

llama_stack/providers/utils/inference/prompt_adapter.py

@@ -180,11 +180,10 @@ def request_has_media(request: ChatCompletionRequest | CompletionRequest):
         return content_has_media(request.content)
 
 
-async def localize_image_content(media: ImageContentItem) -> tuple[bytes, str]:
+async def localize_image_content(uri: str) -> tuple[bytes, str] | None:
-    image = media.image
+    if uri.startswith("http"):
-    if image.url and image.url.uri.startswith("http"):
         async with httpx.AsyncClient() as client:
-            r = await client.get(image.url.uri)
+            r = await client.get(uri)
             content = r.content
             content_type = r.headers.get("content-type")
             if content_type:
@@ -194,11 +193,7 @@ async def localize_image_content(media: ImageContentItem) -> tuple[bytes, str]:
 
         return content, format
     else:
-        # data is a base64 encoded string, decode it to bytes first
+        return None
-        # TODO(mf): do this more efficiently, decode less
-        data_bytes = base64.b64decode(image.data)
-        pil_image = PIL_Image.open(io.BytesIO(data_bytes))
-        return data_bytes, pil_image.format
 
 
 async def convert_image_content_to_url(
@@ -208,7 +203,18 @@ async def convert_image_content_to_url(
     if image.url and (not download or image.url.uri.startswith("data")):
         return image.url.uri
 
-    content, format = await localize_image_content(media)
+    if image.data:
+        # data is a base64 encoded string, decode it to bytes first
+        # TODO(mf): do this more efficiently, decode less
+        content = base64.b64decode(image.data)
+        pil_image = PIL_Image.open(io.BytesIO(content))
+        format = pil_image.format
+    else:
+        localize_result = await localize_image_content(image.url.uri)
+        if localize_result is None:
+            raise ValueError(f"Failed to localize image content from {image.url.uri}")
+        content, format = localize_result
+
     if include_format:
         return f"data:image/{format};base64," + base64.b64encode(content).decode("utf-8")
     else:

tests/verifications/openai_api/fixtures/test_cases/responses.yaml

@@ -8,6 +8,17 @@ test_response_basic:
     - case_id: "saturn"
       input: "Which planet has rings around it with a name starting with letter S?"
       output: "saturn"
+    - case_id: "image_input"
+      input:
+      - role: user
+        content:
+        - type: input_text
+          text: "what teams are playing in this image?"
+      - role: user
+        content:
+        - type: input_image
+          image_url: "https://upload.wikimedia.org/wikipedia/commons/3/3b/LeBron_James_Layup_%28Cleveland_vs_Brooklyn_2018%29.jpg"
+      output: "brooklyn nets"
 
 test_response_multi_turn:
   test_name: test_response_multi_turn