Update the "InterleavedTextMedia" type (#635)

## What does this PR do?

This is a long-pending change and particularly important to get done
now.

Specifically:
- we cannot "localize" (aka download) any URLs from media attachments
anywhere near our modeling code. it must be done within llama-stack.
- `PIL.Image` is infesting all our APIs via `ImageMedia ->
InterleavedTextMedia` and that cannot be right at all. Anything in the
API surface must be "naturally serializable". We need a standard `{
type: "image", image_url: "<...>" }` which is more extensible
- `UserMessage`, `SystemMessage`, etc. are moved completely to
llama-stack from the llama-models repository.

See https://github.com/meta-llama/llama-models/pull/244 for the
corresponding PR in llama-models.

## Test Plan

```bash
cd llama_stack/providers/tests

pytest -s -v -k "fireworks or ollama or together" inference/test_vision_inference.py
pytest -s -v -k "(fireworks or ollama or together) and llama_3b" inference/test_text_inference.py
pytest -s -v -k chroma memory/test_memory.py \
  --env EMBEDDING_DIMENSION=384 --env CHROMA_DB_PATH=/tmp/foobar

pytest -s -v -k fireworks agents/test_agents.py  \
   --safety-shield=meta-llama/Llama-Guard-3-8B \
   --inference-model=meta-llama/Llama-3.1-8B-Instruct
```

Updated the client sdk (see PR ...), installed the SDK in the same
environment and then ran the SDK tests:

```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=together pytest -s -v agents/test_agents.py
LLAMA_STACK_CONFIG=ollama pytest -s -v memory/test_memory.py

# this one needed a bit of hacking in the run.yaml to ensure I could register the vision model correctly
INFERENCE_MODEL=llama3.2-vision:latest LLAMA_STACK_CONFIG=ollama pytest -s -v inference/test_inference.py
```

llama_stack/apis/memory/memory.py

@@ -8,27 +8,27 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
-from typing import List, Optional, Protocol, runtime_checkable
+from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
 
 from llama_models.schema_utils import json_schema_type, webmethod
-
 from pydantic import BaseModel, Field
 
-from llama_models.llama3.api.datatypes import *  # noqa: F403
-from llama_stack.apis.memory_banks import *  # noqa: F403
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.inference import InterleavedContent
+from llama_stack.apis.memory_banks import MemoryBank
 from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
 
 
 @json_schema_type
 class MemoryBankDocument(BaseModel):
     document_id: str
-    content: InterleavedTextMedia | URL
+    content: InterleavedContent | URL
     mime_type: str | None = None
     metadata: Dict[str, Any] = Field(default_factory=dict)
 
 
 class Chunk(BaseModel):
-    content: InterleavedTextMedia
+    content: InterleavedContent
     token_count: int
     document_id: str
 
@@ -62,6 +62,6 @@ class Memory(Protocol):
     async def query_documents(
         self,
         bank_id: str,
-        query: InterleavedTextMedia,
+        query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
     ) -> QueryDocumentsResponse: ...