adding logo and favicon

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

chore: Enable keyword search for Milvus inline (#3073)

With https://github.com/milvus-io/milvus-lite/pull/294 - Milvus Lite
supports keyword search using BM25. While introducing keyword search we
had explicitly disabled it for inline milvus. This PR removes the need
for the check, and enables `inline::milvus` for tests.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

Run llama stack with `inline::milvus` enabled:

```
pytest tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes --stack-config=http://localhost:8321 --embedding-model=all-MiniLM-L6-v2 -v
```

```
INFO     2025-08-07 17:06:20,932 tests.integration.conftest:64 tests: Setting DISABLE_CODE_SANDBOX=1 for macOS
=========================================================================================== test session starts ============================================================================================
platform darwin -- Python 3.12.11, pytest-7.4.4, pluggy-1.5.0 -- /Users/vnarsing/miniconda3/envs/stack-client/bin/python
cachedir: .pytest_cache
metadata: {'Python': '3.12.11', 'Platform': 'macOS-14.7.6-arm64-arm-64bit', 'Packages': {'pytest': '7.4.4', 'pluggy': '1.5.0'}, 'Plugins': {'asyncio': '0.23.8', 'cov': '6.0.0', 'timeout': '2.2.0', 'socket': '0.7.0', 'html': '3.1.1', 'langsmith': '0.3.39', 'anyio': '4.8.0', 'metadata': '3.0.0'}}
rootdir: /Users/vnarsing/go/src/github/meta-llama/llama-stack
configfile: pyproject.toml
plugins: asyncio-0.23.8, cov-6.0.0, timeout-2.2.0, socket-0.7.0, html-3.1.1, langsmith-0.3.39, anyio-4.8.0, metadata-3.0.0
asyncio: mode=Mode.AUTO
collected 3 items

tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[None-None-all-MiniLM-L6-v2-None-384-vector] PASSED                                                   [ 33%]
tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[None-None-all-MiniLM-L6-v2-None-384-keyword] PASSED                                                  [ 66%]
tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[None-None-all-MiniLM-L6-v2-None-384-hybrid] PASSED                                                   [100%]

============================================================================================ 3 passed in 4.75s =============================================================================================
```

Signed-off-by: Varsha Prasad Narsing <varshaprasad96@gmail.com>
Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>

chore: Fixup main pre commit (#3204)

build: Bump version to 0.2.18

chore: Faster npm pre-commit (#3206)

Adds npm to pre-commit.yml installation and caches ui
Removes node installation during pre-commit.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

chiecking in for tonight, wip moving to agents api

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

remove log

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

updated

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

fix: disable ui-prettier & ui-eslint (#3207)

chore(pre-commit): add pre-commit hook to enforce llama_stack logger usage (#3061)

This PR adds a step in pre-commit to enforce using `llama_stack` logger.

Currently, various parts of the code base uses different loggers. As a
custom `llama_stack` logger exist and used in the codebase, it is better
to standardize its utilization.

Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>
Co-authored-by: Matthew Farrellee <matt@cs.wisc.edu>

fix: fix ```openai_embeddings``` for asymmetric embedding NIMs (#3205)

NVIDIA asymmetric embedding models (e.g.,
`nvidia/llama-3.2-nv-embedqa-1b-v2`) require an `input_type` parameter
not present in the standard OpenAI embeddings API. This PR adds the
`input_type="query"` as default and updates the documentation to suggest
using the `embedding` API for passage embeddings.

<!-- If resolving an issue, uncomment and update the line below -->
Resolves #2892

```
pytest -s -v tests/integration/inference/test_openai_embeddings.py   --stack-config="inference=nvidia"   --embedding-model="nvidia/llama-3.2-nv-embedqa-1b-v2"   --env NVIDIA_API_KEY={nvidia_api_key}   --env NVIDIA_BASE_URL="https://integrate.api.nvidia.com"
```

cleaning up

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

updating session manager to cache messages locally

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

fix linter

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

more cleanup

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

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

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import uuid
 from collections.abc import AsyncGenerator
 from datetime import UTC, datetime
@@ -42,6 +41,7 @@ from llama_stack.apis.safety import Safety
 from llama_stack.apis.tools import ToolGroups, ToolRuntime
 from llama_stack.apis.vector_io import VectorIO
 from llama_stack.core.datatypes import AccessRule
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.kvstore import InmemoryKVStoreImpl, kvstore_impl
 from llama_stack.providers.utils.pagination import paginate_records
 from llama_stack.providers.utils.responses.responses_store import ResponsesStore
@@ -51,7 +51,7 @@ from .config import MetaReferenceAgentsImplConfig
 from .persistence import AgentInfo
 from .responses.openai_responses import OpenAIResponsesImpl
 
-logger = logging.getLogger()
+logger = get_logger(name=__name__, category="agents")
 
 
 class MetaReferenceAgentsImpl(Agents):

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

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import json
-import logging
 import uuid
 from datetime import UTC, datetime
 
@@ -15,9 +14,10 @@ from llama_stack.core.access_control.access_control import AccessDeniedError, is
 from llama_stack.core.access_control.datatypes import AccessRule
 from llama_stack.core.datatypes import User
 from llama_stack.core.request_headers import get_authenticated_user
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.kvstore import KVStore
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="agents")
 
 
 class AgentSessionInfo(Session):

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

@@ -5,13 +5,13 @@
 # the root directory of this source tree.
 
 import asyncio
-import logging
 
 from llama_stack.apis.inference import Message
 from llama_stack.apis.safety import Safety, SafetyViolation, ViolationLevel
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.telemetry import tracing
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="agents")
 
 
 class SafetyException(Exception):  # noqa: N818

llama_stack/providers/inline/inference/meta_reference/parallel_utils.py

@@ -12,7 +12,6 @@
 
 import copy
 import json
-import logging
 import multiprocessing
 import os
 import tempfile
@@ -32,13 +31,14 @@ from fairscale.nn.model_parallel.initialize import (
 from pydantic import BaseModel, Field
 from torch.distributed.launcher.api import LaunchConfig, elastic_launch
 
+from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import GenerationResult
 from llama_stack.providers.utils.inference.prompt_adapter import (
     ChatCompletionRequestWithRawContent,
     CompletionRequestWithRawContent,
 )
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="inference")
 
 
 class ProcessingMessageName(str, Enum):

llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 from collections.abc import AsyncGenerator
 
 from llama_stack.apis.inference import (
@@ -21,6 +20,7 @@ from llama_stack.apis.inference import (
     ToolPromptFormat,
 )
 from llama_stack.apis.models import ModelType
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
 from llama_stack.providers.utils.inference.embedding_mixin import (
     SentenceTransformerEmbeddingMixin,
@@ -32,7 +32,7 @@ from llama_stack.providers.utils.inference.openai_compat import (
 
 from .config import SentenceTransformersInferenceConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="inference")
 
 
 class SentenceTransformersInferenceImpl(

llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device.py

@@ -6,7 +6,6 @@
 
 import gc
 import json
-import logging
 import multiprocessing
 from pathlib import Path
 from typing import Any
@@ -28,6 +27,7 @@ from llama_stack.apis.post_training import (
     LoraFinetuningConfig,
     TrainingConfig,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.inline.post_training.common.utils import evacuate_model_from_device
 
 from ..config import HuggingFacePostTrainingConfig
@@ -44,7 +44,7 @@ from ..utils import (
     split_dataset,
 )
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="post_training")
 
 
 class HFFinetuningSingleDevice:

llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device_dpo.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import gc
-import logging
 import multiprocessing
 from pathlib import Path
 from typing import Any
@@ -24,6 +23,7 @@ from llama_stack.apis.post_training import (
     DPOAlignmentConfig,
     TrainingConfig,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.inline.post_training.common.utils import evacuate_model_from_device
 
 from ..config import HuggingFacePostTrainingConfig
@@ -40,7 +40,7 @@ from ..utils import (
     split_dataset,
 )
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="post_training")
 
 
 class HFDPOAlignmentSingleDevice:

llama_stack/providers/inline/post_training/huggingface/utils.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import os
 import signal
 import sys
@@ -19,10 +18,11 @@ from transformers import AutoConfig, AutoModelForCausalLM
 
 from llama_stack.apis.datasetio import DatasetIO
 from llama_stack.apis.post_training import Checkpoint, TrainingConfig
+from llama_stack.log import get_logger
 
 from .config import HuggingFacePostTrainingConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="post_training")
 
 
 def setup_environment():

llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import os
 import time
 from datetime import UTC, datetime
@@ -19,6 +18,7 @@ from torch.utils.data import DataLoader, DistributedSampler
 from torchtune import modules, training
 from torchtune import utils as torchtune_utils
 from torchtune.data import padded_collate_sft
+from torchtune.models.llama3._tokenizer import Llama3Tokenizer
 from torchtune.modules.loss import CEWithChunkedOutputLoss
 from torchtune.modules.peft import (
     get_adapter_params,
@@ -45,6 +45,7 @@ from llama_stack.apis.post_training import (
 )
 from llama_stack.core.utils.config_dirs import DEFAULT_CHECKPOINT_DIR
 from llama_stack.core.utils.model_utils import model_local_dir
+from llama_stack.log import get_logger
 from llama_stack.models.llama.sku_list import resolve_model
 from llama_stack.providers.inline.post_training.common.utils import evacuate_model_from_device
 from llama_stack.providers.inline.post_training.torchtune.common import utils
@@ -56,9 +57,7 @@ from llama_stack.providers.inline.post_training.torchtune.config import (
 )
 from llama_stack.providers.inline.post_training.torchtune.datasets.sft import SFTDataset
 
-log = logging.getLogger(__name__)
-
-from torchtune.models.llama3._tokenizer import Llama3Tokenizer
+log = get_logger(name=__name__, category="post_training")
 
 
 class LoraFinetuningSingleDevice:

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

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import uuid
 from typing import TYPE_CHECKING, Any
 
@@ -20,13 +19,14 @@ from llama_stack.apis.safety import (
 )
 from llama_stack.apis.safety.safety import ModerationObject, ModerationObjectResults
 from llama_stack.apis.shields import Shield
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.inference.prompt_adapter import (
     interleaved_content_as_str,
 )
 
 from .config import CodeScannerConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="safety")
 
 ALLOWED_CODE_SCANNER_MODEL_IDS = [
     "code-scanner",

llama_stack/providers/inline/safety/llama_guard/llama_guard.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import re
 import uuid
 from string import Template
@@ -21,6 +20,7 @@ from llama_stack.apis.safety import (
 from llama_stack.apis.safety.safety import ModerationObject, ModerationObjectResults
 from llama_stack.apis.shields import Shield
 from llama_stack.core.datatypes import Api
+from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import Role
 from llama_stack.models.llama.sku_types import CoreModelId
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
@@ -132,6 +132,8 @@ Provide your safety assessment for ONLY THE LAST $agent_type message in the abov
 
 PROMPT_TEMPLATE = Template(f"{PROMPT_TASK}{SAFETY_CATEGORIES}{PROMPT_CONVERSATION}{PROMPT_INSTRUCTIONS}")
 
+logger = get_logger(name=__name__, category="safety")
+
 
 class LlamaGuardSafetyImpl(Safety, ShieldsProtocolPrivate):
     def __init__(self, config: LlamaGuardConfig, deps) -> None:
@@ -407,7 +409,7 @@ class LlamaGuardShield:
             unsafe_code_list = [code.strip() for code in unsafe_code.split(",")]
             invalid_codes = [code for code in unsafe_code_list if code not in SAFETY_CODE_TO_CATEGORIES_MAP]
             if invalid_codes:
-                logging.warning(f"Invalid safety codes returned: {invalid_codes}")
+                logger.warning(f"Invalid safety codes returned: {invalid_codes}")
                 # just returning safe object, as we don't know what the invalid codes can map to
                 return ModerationObject(
                     id=f"modr-{uuid.uuid4()}",

llama_stack/providers/inline/safety/prompt_guard/prompt_guard.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 from typing import Any
 
 import torch
@@ -21,6 +20,7 @@ from llama_stack.apis.safety import (
 from llama_stack.apis.safety.safety import ModerationObject
 from llama_stack.apis.shields import Shield
 from llama_stack.core.utils.model_utils import model_local_dir
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
 from llama_stack.providers.utils.inference.prompt_adapter import (
     interleaved_content_as_str,
@@ -28,7 +28,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
 
 from .config import PromptGuardConfig, PromptGuardType
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="safety")
 
 PROMPT_GUARD_MODEL = "Prompt-Guard-86M"
 

llama_stack/providers/inline/scoring/basic/utils/ifeval_utils.py

@@ -7,7 +7,6 @@
 import collections
 import functools
 import json
-import logging
 import random
 import re
 import string
@@ -20,7 +19,9 @@ import nltk
 from pythainlp.tokenize import sent_tokenize as sent_tokenize_thai
 from pythainlp.tokenize import word_tokenize as word_tokenize_thai
 
-logger = logging.getLogger()
+from llama_stack.log import get_logger
+
+logger = get_logger(name=__name__, category="scoring")
 
 WORD_LIST = [
     "western",

llama_stack/providers/inline/telemetry/meta_reference/telemetry.py

@@ -4,13 +4,10 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import threading
 from typing import Any
 
 from opentelemetry import metrics, trace
-
-logger = logging.getLogger(__name__)
 from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter
 from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
 from opentelemetry.sdk.metrics import MeterProvider
@@ -40,6 +37,7 @@ from llama_stack.apis.telemetry import (
     UnstructuredLogEvent,
 )
 from llama_stack.core.datatypes import Api
+from llama_stack.log import get_logger
 from llama_stack.providers.inline.telemetry.meta_reference.console_span_processor import (
     ConsoleSpanProcessor,
 )
@@ -61,6 +59,8 @@ _GLOBAL_STORAGE: dict[str, dict[str | int, Any]] = {
 _global_lock = threading.Lock()
 _TRACER_PROVIDER = None
 
+logger = get_logger(name=__name__, category="telemetry")
+
 
 def is_tracing_enabled(tracer):
     with tracer.start_as_current_span("check_tracing") as span:

llama_stack/providers/inline/tool_runtime/rag/memory.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import asyncio
-import logging
 import secrets
 import string
 from typing import Any
@@ -32,6 +31,7 @@ from llama_stack.apis.tools import (
     ToolRuntime,
 )
 from llama_stack.apis.vector_io import QueryChunksResponse, VectorIO
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import ToolGroupsProtocolPrivate
 from llama_stack.providers.utils.inference.prompt_adapter import interleaved_content_as_str
 from llama_stack.providers.utils.memory.vector_store import (
@@ -42,7 +42,7 @@ from llama_stack.providers.utils.memory.vector_store import (
 from .config import RagToolRuntimeConfig
 from .context_retriever import generate_rag_query
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="tool_runtime")
 
 
 def make_random_string(length: int = 8):

llama_stack/providers/inline/vector_io/faiss/faiss.py

@@ -8,7 +8,6 @@ import asyncio
 import base64
 import io
 import json
-import logging
 from typing import Any
 
 import faiss
@@ -24,6 +23,7 @@ from llama_stack.apis.vector_io import (
     QueryChunksResponse,
     VectorIO,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import (
     HealthResponse,
     HealthStatus,
@@ -40,7 +40,7 @@ from llama_stack.providers.utils.memory.vector_store import (
 
 from .config import FaissVectorIOConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="vector_io")
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:{VERSION}::"

llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import asyncio
-import logging
 import re
 import sqlite3
 import struct
@@ -24,6 +23,7 @@ from llama_stack.apis.vector_io import (
     QueryChunksResponse,
     VectorIO,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import VectorDBsProtocolPrivate
 from llama_stack.providers.utils.kvstore import kvstore_impl
 from llama_stack.providers.utils.kvstore.api import KVStore
@@ -36,7 +36,7 @@ from llama_stack.providers.utils.memory.vector_store import (
     VectorDBWithIndex,
 )
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="vector_io")
 
 # Specifying search mode is dependent on the VectorIO provider.
 VECTOR_SEARCH = "vector"

llama_stack/providers/remote/inference/llama_openai_compat/llama.py

@@ -3,15 +3,14 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
-import logging
-
+from llama_stack.log import get_logger
 from llama_stack.providers.remote.inference.llama_openai_compat.config import LlamaCompatConfig
 from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
 from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
 
 from .models import MODEL_ENTRIES
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="inference")
 
 
 class LlamaCompatInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):

llama_stack/providers/remote/inference/nvidia/NVIDIA.md

@@ -77,6 +77,10 @@ print(f"Response: {response.completion_message.content}")
 ```
 
 ### Create Embeddings
+> Note on OpenAI embeddings compatibility
+>
+> NVIDIA asymmetric embedding models (e.g., `nvidia/llama-3.2-nv-embedqa-1b-v2`) require an `input_type` parameter not present in the standard OpenAI embeddings API. The NVIDIA Inference Adapter automatically sets `input_type="query"` when using the OpenAI-compatible embeddings endpoint for NVIDIA. For passage embeddings, use the `embeddings` API with `task_type="document"`.
+
 ```python
 response = client.inference.embeddings(
     model_id="nvidia/llama-3.2-nv-embedqa-1b-v2",

llama_stack/providers/remote/inference/nvidia/nvidia.py

@@ -4,11 +4,10 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import warnings
 from collections.abc import AsyncIterator
 
-from openai import APIConnectionError, BadRequestError
+from openai import NOT_GIVEN, APIConnectionError, BadRequestError
 
 from llama_stack.apis.common.content_types import (
     InterleavedContent,
@@ -27,12 +26,16 @@ from llama_stack.apis.inference import (
     Inference,
     LogProbConfig,
     Message,
+    OpenAIEmbeddingData,
+    OpenAIEmbeddingsResponse,
+    OpenAIEmbeddingUsage,
     ResponseFormat,
     SamplingParams,
     TextTruncation,
     ToolChoice,
     ToolConfig,
 )
+from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import ToolDefinition, ToolPromptFormat
 from llama_stack.providers.utils.inference.model_registry import (
     ModelRegistryHelper,
@@ -54,7 +57,7 @@ from .openai_utils import (
 )
 from .utils import _is_nvidia_hosted
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="inference")
 
 
 class NVIDIAInferenceAdapter(OpenAIMixin, Inference, ModelRegistryHelper):
@@ -210,6 +213,57 @@ class NVIDIAInferenceAdapter(OpenAIMixin, Inference, ModelRegistryHelper):
         #
         return EmbeddingsResponse(embeddings=[embedding.embedding for embedding in response.data])
 
+    async def openai_embeddings(
+        self,
+        model: str,
+        input: str | list[str],
+        encoding_format: str | None = "float",
+        dimensions: int | None = None,
+        user: str | None = None,
+    ) -> OpenAIEmbeddingsResponse:
+        """
+        OpenAI-compatible embeddings for NVIDIA NIM.
+
+        Note: NVIDIA NIM asymmetric embedding models require an "input_type" field not present in the standard OpenAI embeddings API.
+        We default this to "query" to ensure requests succeed when using the
+        OpenAI-compatible endpoint. For passage embeddings, use the embeddings API with
+        `task_type='document'`.
+        """
+        extra_body: dict[str, object] = {"input_type": "query"}
+        logger.warning(
+            "NVIDIA OpenAI-compatible embeddings: defaulting to input_type='query'. "
+            "For passage embeddings, use the embeddings API with task_type='document'."
+        )
+
+        response = await self.client.embeddings.create(
+            model=await self._get_provider_model_id(model),
+            input=input,
+            encoding_format=encoding_format if encoding_format is not None else NOT_GIVEN,
+            dimensions=dimensions if dimensions is not None else NOT_GIVEN,
+            user=user if user is not None else NOT_GIVEN,
+            extra_body=extra_body,
+        )
+
+        data = []
+        for i, embedding_data in enumerate(response.data):
+            data.append(
+                OpenAIEmbeddingData(
+                    embedding=embedding_data.embedding,
+                    index=i,
+                )
+            )
+
+        usage = OpenAIEmbeddingUsage(
+            prompt_tokens=response.usage.prompt_tokens,
+            total_tokens=response.usage.total_tokens,
+        )
+
+        return OpenAIEmbeddingsResponse(
+            data=data,
+            model=response.model,
+            usage=usage,
+        )
+
     async def chat_completion(
         self,
         model_id: str,

llama_stack/providers/remote/inference/nvidia/utils.py

@@ -4,13 +4,13 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
-
 import httpx
 
+from llama_stack.log import get_logger
+
 from . import NVIDIAConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="inference")
 
 
 def _is_nvidia_hosted(config: NVIDIAConfig) -> bool:

llama_stack/providers/remote/inference/openai/openai.py

@@ -4,15 +4,14 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
-
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
 from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
 
 from .config import OpenAIConfig
 from .models import MODEL_ENTRIES
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="inference")
 
 
 #

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

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 
-import logging
 from collections.abc import AsyncGenerator
 
 from huggingface_hub import AsyncInferenceClient, HfApi
@@ -34,6 +33,7 @@ from llama_stack.apis.inference import (
     ToolPromptFormat,
 )
 from llama_stack.apis.models import Model
+from llama_stack.log import get_logger
 from llama_stack.models.llama.sku_list import all_registered_models
 from llama_stack.providers.datatypes import ModelsProtocolPrivate
 from llama_stack.providers.utils.inference.model_registry import (
@@ -58,7 +58,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
 
 from .config import InferenceAPIImplConfig, InferenceEndpointImplConfig, TGIImplConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="inference")
 
 
 def build_hf_repo_model_entries():

llama_stack/providers/remote/post_training/nvidia/utils.py

@@ -4,18 +4,18 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 import warnings
 from typing import Any
 
 from pydantic import BaseModel
 
 from llama_stack.apis.post_training import TrainingConfig
+from llama_stack.log import get_logger
 from llama_stack.providers.remote.post_training.nvidia.config import SFTLoRADefaultConfig
 
 from .config import NvidiaPostTrainingConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="integration")
 
 
 def warn_unsupported_params(config_dict: Any, supported_keys: set[str], config_name: str) -> None:

llama_stack/providers/remote/safety/bedrock/bedrock.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import json
-import logging
 from typing import Any
 
 from llama_stack.apis.inference import Message
@@ -16,12 +15,13 @@ from llama_stack.apis.safety import (
     ViolationLevel,
 )
 from llama_stack.apis.shields import Shield
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
 from llama_stack.providers.utils.bedrock.client import create_bedrock_client
 
 from .config import BedrockSafetyConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="safety")
 
 
 class BedrockSafetyAdapter(Safety, ShieldsProtocolPrivate):

llama_stack/providers/remote/safety/nvidia/nvidia.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 from typing import Any
 
 import requests
@@ -12,12 +11,13 @@ import requests
 from llama_stack.apis.inference import Message
 from llama_stack.apis.safety import RunShieldResponse, Safety, SafetyViolation, ViolationLevel
 from llama_stack.apis.shields import Shield
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
 from llama_stack.providers.utils.inference.openai_compat import convert_message_to_openai_dict_new
 
 from .config import NVIDIASafetyConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="safety")
 
 
 class NVIDIASafetyAdapter(Safety, ShieldsProtocolPrivate):

llama_stack/providers/remote/safety/sambanova/sambanova.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import json
-import logging
 from typing import Any
 
 import litellm
@@ -20,12 +19,13 @@ from llama_stack.apis.safety import (
 )
 from llama_stack.apis.shields import Shield
 from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
 from llama_stack.providers.utils.inference.openai_compat import convert_message_to_openai_dict_new
 
 from .config import SambaNovaSafetyConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="safety")
 
 CANNED_RESPONSE_TEXT = "I can't answer that. Can I help with something else?"
 

llama_stack/providers/remote/vector_io/chroma/chroma.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 import asyncio
 import json
-import logging
 from typing import Any
 from urllib.parse import urlparse
 
@@ -20,6 +19,7 @@ from llama_stack.apis.vector_io import (
     QueryChunksResponse,
     VectorIO,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 from llama_stack.providers.inline.vector_io.chroma import ChromaVectorIOConfig as InlineChromaVectorIOConfig
 from llama_stack.providers.utils.kvstore import kvstore_impl
@@ -33,7 +33,7 @@ from llama_stack.providers.utils.memory.vector_store import (
 
 from .config import ChromaVectorIOConfig as RemoteChromaVectorIOConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="vector_io")
 
 ChromaClientType = chromadb.api.AsyncClientAPI | chromadb.api.ClientAPI
 

llama_stack/providers/remote/vector_io/milvus/milvus.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import asyncio
-import logging
 import os
 from typing import Any
 
@@ -21,6 +20,7 @@ from llama_stack.apis.vector_io import (
     QueryChunksResponse,
     VectorIO,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import VectorDBsProtocolPrivate
 from llama_stack.providers.inline.vector_io.milvus import MilvusVectorIOConfig as InlineMilvusVectorIOConfig
 from llama_stack.providers.utils.kvstore import kvstore_impl
@@ -36,7 +36,7 @@ from llama_stack.providers.utils.vector_io.vector_utils import sanitize_collecti
 
 from .config import MilvusVectorIOConfig as RemoteMilvusVectorIOConfig
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="vector_io")
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:milvus:{VERSION}::"
@@ -413,15 +413,6 @@ class MilvusVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP
         index = await self._get_and_cache_vector_db_index(vector_db_id)
         if not index:
             raise VectorStoreNotFoundError(vector_db_id)
-
-        if params and params.get("mode") == "keyword":
-            # Check if this is inline Milvus (Milvus-Lite)
-            if hasattr(self.config, "db_path"):
-                raise NotImplementedError(
-                    "Keyword search is not supported in Milvus-Lite. "
-                    "Please use a remote Milvus server for keyword search functionality."
-                )
-
         return await index.query_chunks(query, params)
 
     async def delete_chunks(self, store_id: str, chunks_for_deletion: list[ChunkForDeletion]) -> None:

llama_stack/providers/remote/vector_io/pgvector/pgvector.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 from typing import Any
 
 import psycopg2
@@ -22,6 +21,7 @@ from llama_stack.apis.vector_io import (
     QueryChunksResponse,
     VectorIO,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 from llama_stack.providers.utils.kvstore import kvstore_impl
 from llama_stack.providers.utils.kvstore.api import KVStore
@@ -34,7 +34,7 @@ from llama_stack.providers.utils.memory.vector_store import (
 
 from .config import PGVectorVectorIOConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="vector_io")
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:pgvector:{VERSION}::"

llama_stack/providers/remote/vector_io/qdrant/qdrant.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import asyncio
-import logging
 import uuid
 from typing import Any
 
@@ -24,6 +23,7 @@ from llama_stack.apis.vector_io import (
     VectorStoreChunkingStrategy,
     VectorStoreFileObject,
 )
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 from llama_stack.providers.inline.vector_io.qdrant import QdrantVectorIOConfig as InlineQdrantVectorIOConfig
 from llama_stack.providers.utils.kvstore import KVStore, kvstore_impl
@@ -36,7 +36,7 @@ from llama_stack.providers.utils.memory.vector_store import (
 
 from .config import QdrantVectorIOConfig as RemoteQdrantVectorIOConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="vector_io")
 CHUNK_ID_KEY = "_chunk_id"
 
 # KV store prefixes for vector databases

llama_stack/providers/remote/vector_io/weaviate/weaviate.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 import json
-import logging
 from typing import Any
 
 import weaviate
@@ -19,6 +18,7 @@ from llama_stack.apis.files.files import Files
 from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
 from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 from llama_stack.providers.utils.kvstore import kvstore_impl
 from llama_stack.providers.utils.kvstore.api import KVStore
@@ -34,7 +34,7 @@ from llama_stack.providers.utils.vector_io.vector_utils import sanitize_collecti
 
 from .config import WeaviateVectorIOConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="vector_io")
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:weaviate:{VERSION}::"

llama_stack/providers/utils/inference/embedding_mixin.py

@@ -5,10 +5,11 @@
 # the root directory of this source tree.
 
 import base64
-import logging
 import struct
 from typing import TYPE_CHECKING
 
+from llama_stack.log import get_logger
+
 if TYPE_CHECKING:
     from sentence_transformers import SentenceTransformer
 
@@ -27,7 +28,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import interleaved_con
 EMBEDDING_MODELS = {}
 
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="inference")
 
 
 class SentenceTransformerEmbeddingMixin:

llama_stack/providers/utils/inference/openai_compat.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 import base64
 import json
-import logging
 import struct
 import time
 import uuid
@@ -122,6 +121,7 @@ from llama_stack.apis.inference import (
 from llama_stack.apis.inference import (
     OpenAIChoice as OpenAIChatCompletionChoice,
 )
+from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import (
     BuiltinTool,
     StopReason,
@@ -134,7 +134,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
     decode_assistant_message,
 )
 
-logger = logging.getLogger(__name__)
+logger = get_logger(name=__name__, category="inference")
 
 
 class OpenAICompatCompletionChoiceDelta(BaseModel):

llama_stack/providers/utils/kvstore/mongodb/mongodb.py

@@ -4,16 +4,16 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 from datetime import datetime
 
 from pymongo import AsyncMongoClient
 
+from llama_stack.log import get_logger
 from llama_stack.providers.utils.kvstore import KVStore
 
 from ..config import MongoDBKVStoreConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="kvstore")
 
 
 class MongoDBKVStoreImpl(KVStore):

llama_stack/providers/utils/kvstore/postgres/postgres.py

@@ -4,16 +4,17 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 from datetime import datetime
 
 import psycopg2
 from psycopg2.extras import DictCursor
 
+from llama_stack.log import get_logger
+
 from ..api import KVStore
 from ..config import PostgresKVStoreConfig
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="kvstore")
 
 
 class PostgresKVStoreImpl(KVStore):

llama_stack/providers/utils/memory/openai_vector_store_mixin.py

@@ -44,7 +44,7 @@ from llama_stack.providers.utils.memory.vector_store import (
     make_overlapped_chunks,
 )
 
-logger = get_logger(__name__, category="vector_io")
+logger = get_logger(name=__name__, category="memory")
 
 # Constants for OpenAI vector stores
 CHUNK_MULTIPLIER = 5

llama_stack/providers/utils/memory/vector_store.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 import base64
 import io
-import logging
 import re
 import time
 from abc import ABC, abstractmethod
@@ -26,6 +25,7 @@ from llama_stack.apis.common.content_types import (
 from llama_stack.apis.tools import RAGDocument
 from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import Chunk, ChunkMetadata, QueryChunksResponse
+from llama_stack.log import get_logger
 from llama_stack.models.llama.llama3.tokenizer import Tokenizer
 from llama_stack.providers.datatypes import Api
 from llama_stack.providers.utils.inference.prompt_adapter import (
@@ -33,7 +33,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
 )
 from llama_stack.providers.utils.vector_io.vector_utils import generate_chunk_id
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="memory")
 
 
 class ChunkForDeletion(BaseModel):

llama_stack/providers/utils/telemetry/tracing.py

@@ -6,7 +6,7 @@
 
 import asyncio
 import contextvars
-import logging
+import logging  # allow-direct-logging
 import queue
 import random
 import sys