Tests pass with Ollama now

llama_stack/apis/agents/agents.py

@@ -29,11 +29,13 @@ from llama_stack.apis.common.deployment_types import *  # noqa: F403
 from llama_stack.apis.inference import *  # noqa: F403
 from llama_stack.apis.safety import *  # noqa: F403
 from llama_stack.apis.memory import *  # noqa: F403
+from llama_stack.apis.common.deployment_types import URL
+from llama_stack.apis.inference import InterleavedContent
 
 
 @json_schema_type
 class Attachment(BaseModel):
-    content: InterleavedTextMedia | URL
+    content: InterleavedContent | URL
     mime_type: str
 
 
@@ -102,20 +104,20 @@ class _MemoryBankConfigCommon(BaseModel):
 
 
 class AgentVectorMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal[MemoryBankType.vector.value] = MemoryBankType.vector.value
+    type: Literal["vector"] = "vector"
 
 
 class AgentKeyValueMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal[MemoryBankType.keyvalue.value] = MemoryBankType.keyvalue.value
+    type: Literal["keyvalue"] = "keyvalue"
     keys: List[str]  # what keys to focus on
 
 
 class AgentKeywordMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal[MemoryBankType.keyword.value] = MemoryBankType.keyword.value
+    type: Literal["keyword"] = "keyword"
 
 
 class AgentGraphMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal[MemoryBankType.graph.value] = MemoryBankType.graph.value
+    type: Literal["graph"] = "graph"
     entities: List[str]  # what entities to focus on
 
 
@@ -230,7 +232,7 @@ class MemoryRetrievalStep(StepCommon):
         StepType.memory_retrieval.value
     )
     memory_bank_ids: List[str]
-    inserted_context: InterleavedTextMedia
+    inserted_context: InterleavedContent
 
 
 Step = Annotated[

llama_stack/apis/batch_inference/batch_inference.py

@@ -17,7 +17,7 @@ from llama_stack.apis.inference import *  # noqa: F403
 @json_schema_type
 class BatchCompletionRequest(BaseModel):
     model: str
-    content_batch: List[InterleavedTextMedia]
+    content_batch: List[InterleavedContent]
     sampling_params: Optional[SamplingParams] = SamplingParams()
     logprobs: Optional[LogProbConfig] = None
 
@@ -53,7 +53,7 @@ class BatchInference(Protocol):
     async def batch_completion(
         self,
         model: str,
-        content_batch: List[InterleavedTextMedia],
+        content_batch: List[InterleavedContent],
         sampling_params: Optional[SamplingParams] = SamplingParams(),
         logprobs: Optional[LogProbConfig] = None,
     ) -> BatchCompletionResponse: ...

llama_stack/apis/common/training_types.py

@@ -10,6 +10,8 @@ from typing import Optional
 from llama_models.schema_utils import json_schema_type
 from pydantic import BaseModel
 
+from llama_stack.apis.common.deployment_types import URL
+
 
 @json_schema_type
 class PostTrainingMetric(BaseModel):

llama_stack/apis/datasets/datasets.py

@@ -6,12 +6,12 @@
 
 from typing import Any, Dict, List, Literal, Optional, Protocol
 
-from llama_models.llama3.api.datatypes import URL
-
 from llama_models.schema_utils import json_schema_type, webmethod
 
 from pydantic import BaseModel, Field
 
+from llama_stack.apis.common.deployment_types import URL
+
 from llama_stack.apis.common.type_system import ParamType
 from llama_stack.apis.resource import Resource, ResourceType
 

llama_stack/apis/eval/eval.py

@@ -15,6 +15,7 @@ from llama_stack.apis.agents import AgentConfig
 from llama_stack.apis.common.job_types import Job, JobStatus
 from llama_stack.apis.scoring import *  # noqa: F403
 from llama_stack.apis.eval_tasks import *  # noqa: F403
+from llama_stack.apis.inference import SamplingParams, SystemMessage
 
 
 @json_schema_type

llama_stack/apis/inference/inference.py

@@ -247,7 +247,7 @@ class CompletionResponseStreamChunk(BaseModel):
 @json_schema_type
 class BatchCompletionRequest(BaseModel):
     model: str
-    content_batch: List[InterleavedTextMedia]
+    content_batch: List[InterleavedContent]
     sampling_params: Optional[SamplingParams] = SamplingParams()
     response_format: Optional[ResponseFormat] = None
     logprobs: Optional[LogProbConfig] = None

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.deployment_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: ...

llama_stack/apis/safety/safety.py

@@ -5,16 +5,16 @@
 # the root directory of this source tree.
 
 from enum import Enum
-from typing import Any, Dict, List, 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
+from pydantic import BaseModel, Field
+
+from llama_stack.apis.inference import Message
+from llama_stack.apis.shields import Shield
 
 from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
 
-from llama_models.llama3.api.datatypes import *  # noqa: F403
-from llama_stack.apis.shields import *  # noqa: F403
-
 
 @json_schema_type
 class ViolationLevel(Enum):

llama_stack/apis/synthetic_data_generation/synthetic_data_generation.py

@@ -13,6 +13,7 @@ from llama_models.schema_utils import json_schema_type, webmethod
 from pydantic import BaseModel
 
 from llama_models.llama3.api.datatypes import *  # noqa: F403
+from llama_stack.apis.inference import Message
 
 
 class FilteringFunction(Enum):

llama_stack/distribution/routers/routers.py

@@ -59,7 +59,7 @@ class MemoryRouter(Memory):
     async def query_documents(
         self,
         bank_id: str,
-        query: InterleavedTextMedia,
+        query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
     ) -> QueryDocumentsResponse:
         return await self.routing_table.get_provider_impl(bank_id).query_documents(
@@ -133,7 +133,7 @@ class InferenceRouter(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,
@@ -163,7 +163,7 @@ class InferenceRouter(Inference):
     async def embeddings(
         self,
         model_id: str,
-        contents: List[InterleavedTextMedia],
+        contents: List[InterleavedContent],
     ) -> EmbeddingsResponse:
         model = await self.routing_table.get_model(model_id)
         if model is None:

llama_stack/distribution/routers/routing_tables.py

@@ -16,8 +16,7 @@ from llama_stack.apis.memory_banks import *  # noqa: F403
 from llama_stack.apis.datasets import *  # noqa: F403
 from llama_stack.apis.eval_tasks import *  # noqa: F403
 
-
-from llama_models.llama3.api.datatypes import URL
+from llama_stack.apis.common.deployment_types import URL
 
 from llama_stack.apis.common.type_system import ParamType
 from llama_stack.distribution.store import DistributionRegistry
@@ -30,7 +29,6 @@ def get_impl_api(p: Any) -> Api:
 
 # TODO: this should return the registered object for all APIs
 async def register_object_with_provider(obj: RoutableObject, p: Any) -> RoutableObject:
-
     api = get_impl_api(p)
 
     assert obj.provider_id != "remote", "Remote provider should not be registered"
@@ -76,7 +74,6 @@ class CommonRoutingTableImpl(RoutingTable):
         self.dist_registry = dist_registry
 
     async def initialize(self) -> None:
-
         async def add_objects(
             objs: List[RoutableObjectWithProvider], provider_id: str, cls
         ) -> None:

llama_stack/providers/inline/agents/meta_reference/safety.py

@@ -9,8 +9,6 @@ import logging
 
 from typing import List
 
-from llama_models.llama3.api.datatypes import Message
-
 from llama_stack.apis.safety import *  # noqa: F403
 
 log = logging.getLogger(__name__)

llama_stack/providers/inline/safety/code_scanner/code_scanner.py

@@ -7,13 +7,17 @@
 import logging
 from typing import Any, Dict, List
 
-from llama_models.llama3.api.datatypes import interleaved_text_media_as_str, Message
+from llama_stack.apis.safety import *  # noqa: F403
+from llama_stack.apis.inference import Message
+from llama_stack.providers.utils.inference.prompt_adapter import (
+    interleaved_content_as_str,
+)
 
 from .config import CodeScannerConfig
 
-from llama_stack.apis.safety import *  # noqa: F403
 
 log = logging.getLogger(__name__)
+
 ALLOWED_CODE_SCANNER_MODEL_IDS = [
     "CodeScanner",
     "CodeShield",
@@ -48,7 +52,7 @@ class MetaReferenceCodeScannerSafetyImpl(Safety):
 
         from codeshield.cs import CodeShield
 
-        text = "\n".join([interleaved_text_media_as_str(m.content) for m in messages])
+        text = "\n".join([interleaved_content_as_str(m.content) for m in messages])
         log.info(f"Running CodeScannerShield on {text[50:]}")
         result = await CodeShield.scan_code(text)
 

llama_stack/providers/remote/inference/cerebras/cerebras.py

@@ -10,7 +10,6 @@ from cerebras.cloud.sdk import AsyncCerebras
 
 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 llama_stack.apis.inference import *  # noqa: F403

llama_stack/providers/remote/inference/databricks/databricks.py

@@ -10,7 +10,6 @@ from llama_models.datatypes import CoreModelId
 
 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

llama_stack/providers/remote/inference/fireworks/fireworks.py

@@ -10,7 +10,6 @@ from fireworks.client import Fireworks
 from llama_models.datatypes import CoreModelId
 
 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 llama_stack.apis.inference import *  # noqa: F403
 from llama_stack.distribution.request_headers import NeedsRequestProviderData

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

@@ -11,7 +11,6 @@ import httpx
 from llama_models.datatypes import CoreModelId
 
 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 ollama import AsyncClient
 
@@ -90,7 +89,7 @@ model_aliases = [
         CoreModelId.llama3_2_11b_vision_instruct.value,
     ),
     build_model_alias_with_just_provider_model_id(
-        "llama3.2-vision",
+        "llama3.2-vision:latest",
         CoreModelId.llama3_2_11b_vision_instruct.value,
     ),
     build_model_alias(

llama_stack/providers/remote/inference/tgi/tgi.py

@@ -83,7 +83,7 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
     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,
@@ -267,7 +267,7 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
     async def embeddings(
         self,
         model_id: str,
-        contents: List[InterleavedTextMedia],
+        contents: List[InterleavedContent],
     ) -> EmbeddingsResponse:
         raise NotImplementedError()
 

llama_stack/providers/remote/inference/together/together.py

@@ -10,7 +10,6 @@ from llama_models.datatypes import CoreModelId
 
 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 together import Together

llama_stack/providers/remote/inference/vllm/vllm.py

@@ -8,7 +8,6 @@ import logging
 from typing import AsyncGenerator
 
 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 llama_models.sku_list import all_registered_models
 

llama_stack/providers/tests/inference/test_vision_inference.py

@@ -7,7 +7,6 @@
 from pathlib import Path
 
 import pytest
-from PIL import Image as PIL_Image
 
 
 from llama_models.llama3.api.datatypes import *  # noqa: F403
@@ -17,6 +16,9 @@ from .utils import group_chunks
 
 THIS_DIR = Path(__file__).parent
 
+with open(THIS_DIR / "pasta.jpeg", "rb") as f:
+    PASTA_IMAGE = f.read()
+
 
 class TestVisionModelInference:
     @pytest.mark.asyncio
@@ -24,12 +26,12 @@ class TestVisionModelInference:
         "image, expected_strings",
         [
             (
-                ImageMedia(image=PIL_Image.open(THIS_DIR / "pasta.jpeg")),
+                ImageContentItem(data=PASTA_IMAGE),
                 ["spaghetti"],
             ),
             (
-                ImageMedia(
-                    image=URL(
+                ImageContentItem(
+                    data=URL(
                         uri="https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
                     )
                 ),
@@ -58,7 +60,12 @@ class TestVisionModelInference:
             model_id=inference_model,
             messages=[
                 UserMessage(content="You are a helpful assistant."),
-                UserMessage(content=[image, "Describe this image in two sentences."]),
+                UserMessage(
+                    content=[
+                        image,
+                        TextContentItem(text="Describe this image in two sentences."),
+                    ]
+                ),
             ],
             stream=False,
             sampling_params=SamplingParams(max_tokens=100),
@@ -89,8 +96,8 @@ class TestVisionModelInference:
             )
 
         images = [
-            ImageMedia(
-                image=URL(
+            ImageContentItem(
+                data=URL(
                     uri="https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
                 )
             ),
@@ -106,7 +113,12 @@ class TestVisionModelInference:
                     messages=[
                         UserMessage(content="You are a helpful assistant."),
                         UserMessage(
-                            content=[image, "Describe this image in two sentences."]
+                            content=[
+                                image,
+                                TextContentItem(
+                                    text="Describe this image in two sentences."
+                                ),
+                            ]
                         ),
                     ],
                     stream=True,

llama_stack/providers/tests/post_training/fixtures.py

@@ -7,8 +7,8 @@
 import pytest
 import pytest_asyncio
 
-from llama_models.llama3.api.datatypes import URL
 from llama_stack.apis.common.type_system import *  # noqa: F403
+from llama_stack.apis.common.deployment_types import URL
 from llama_stack.apis.datasets import DatasetInput
 from llama_stack.apis.models import ModelInput
 

llama_stack/providers/utils/datasetio/url_utils.py

@@ -10,7 +10,7 @@ from urllib.parse import unquote
 
 import pandas
 
-from llama_models.llama3.api.datatypes import URL
+from llama_stack.apis.common.deployment_types import URL
 
 from llama_stack.providers.utils.memory.vector_store import parse_data_url
 

llama_stack/providers/utils/inference/embedding_mixin.py

@@ -7,9 +7,11 @@
 import logging
 from typing import List
 
-from llama_models.llama3.api.datatypes import InterleavedTextMedia
-
-from llama_stack.apis.inference.inference import EmbeddingsResponse, ModelStore
+from llama_stack.apis.inference import (
+    EmbeddingsResponse,
+    InterleavedContent,
+    ModelStore,
+)
 
 EMBEDDING_MODELS = {}
 
@@ -23,7 +25,7 @@ class SentenceTransformerEmbeddingMixin:
     async def embeddings(
         self,
         model_id: str,
-        contents: List[InterleavedTextMedia],
+        contents: List[InterleavedContent],
     ) -> EmbeddingsResponse:
         model = await self.model_store.get_model(model_id)
         embedding_model = self._load_sentence_transformer_model(

llama_stack/providers/utils/inference/openai_compat.py

@@ -93,11 +93,15 @@ def process_chat_completion_response(
 ) -> ChatCompletionResponse:
     choice = response.choices[0]
 
-    completion_message = formatter.decode_assistant_message_from_content(
+    raw_message = formatter.decode_assistant_message_from_content(
         text_from_choice(choice), get_stop_reason(choice.finish_reason)
     )
     return ChatCompletionResponse(
-        completion_message=completion_message,
+        completion_message=CompletionMessage(
+            content=raw_message.content,
+            stop_reason=raw_message.stop_reason,
+            tool_calls=raw_message.tool_calls,
+        ),
         logprobs=None,
     )
 

llama_stack/providers/utils/inference/prompt_adapter.py

@@ -6,6 +6,7 @@
 
 import asyncio
 import base64
+import io
 import json
 import logging
 import re
@@ -21,7 +22,6 @@ from llama_models.llama3.api.datatypes import (
     RawMediaItem,
     RawTextItem,
     Role,
-    ToolChoice,
     ToolPromptFormat,
 )
 from llama_models.llama3.prompt_templates import (
@@ -47,6 +47,7 @@ from llama_stack.apis.inference import (
     ResponseFormatType,
     SystemMessage,
     TextContentItem,
+    ToolChoice,
     UserMessage,
 )
 
@@ -136,7 +137,7 @@ def request_has_media(request: Union[ChatCompletionRequest, CompletionRequest]):
 async def localize_image_content(media: ImageContentItem) -> Tuple[bytes, str]:
     if isinstance(media.data, URL) and media.data.uri.startswith("http"):
         async with httpx.AsyncClient() as client:
-            r = await client.get(media.image.uri)
+            r = await client.get(media.data.uri)
             content = r.content
             content_type = r.headers.get("content-type")
             if content_type:
@@ -145,7 +146,7 @@ async def localize_image_content(media: ImageContentItem) -> Tuple[bytes, str]:
                 format = "png"
         return content, format
     else:
-        image = PIL_Image.open(media.data)
+        image = PIL_Image.open(io.BytesIO(media.data))
         return media.data, image.format
 
 
@@ -153,7 +154,7 @@ async def convert_image_content_to_url(
     media: ImageContentItem, download: bool = False, include_format: bool = True
 ) -> str:
     if isinstance(media.data, URL) and not download:
-        return media.image.uri
+        return media.data.uri
 
     content, format = await localize_image_content(media)
     if include_format:

llama_stack/providers/utils/memory/file_utils.py

@@ -8,7 +8,7 @@ import base64
 import mimetypes
 import os
 
-from llama_models.llama3.api.datatypes import URL
+from llama_stack.apis.common.deployment_types import URL
 
 
 def data_url_from_file(file_path: str) -> URL: