build: Bump version to 0.2.18

.github/dependabot.yml

@@ -9,7 +9,6 @@ updates:
       day: "saturday"
     commit-message:
       prefix: chore(github-deps)
-
   - package-ecosystem: "uv"
     directory: "/"
     schedule:
@@ -20,14 +19,3 @@ updates:
       - python
     commit-message:
       prefix: chore(python-deps)
-
-  - package-ecosystem: npm
-    directory: "/llama_stack/ui"
-    schedule:
-      interval: "weekly"
-      day: "saturday"
-    labels:
-      - type/dependencies
-      - javascript
-    commit-message:
-      prefix: chore(ui-deps)

.github/workflows/changelog.yml

@@ -17,7 +17,7 @@ jobs:
       pull-requests: write  # for peter-evans/create-pull-request to create a PR
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
         with:
           ref: main
           fetch-depth: 0

.github/workflows/install-script-ci.yml

@@ -16,14 +16,14 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # 5.0.0
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # 4.2.2
       - name: Run ShellCheck on install.sh
         run: shellcheck scripts/install.sh
   smoke-test-on-dev:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/integration-auth-tests.yml

@@ -31,7 +31,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/integration-sql-store-tests.yml

@@ -44,7 +44,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/integration-tests.yml

@@ -65,7 +65,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Setup test environment
         uses: ./.github/actions/setup-test-environment

.github/workflows/integration-vector-io-tests.yml

@@ -33,7 +33,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/pre-commit.yml

@@ -20,7 +20,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
         with:
           # For dependabot PRs, we need to checkout with a token that can push changes
           token: ${{ github.actor == 'dependabot[bot]' && secrets.GITHUB_TOKEN || github.token }}
@@ -36,21 +36,6 @@ jobs:
             **/requirements*.txt
             .pre-commit-config.yaml
 
-      # npm ci may fail -
-      #   npm error `npm ci` can only install packages when your package.json and package-lock.json or npm-shrinkwrap.json are in sync. Please update your lock file with `npm install` before continuing.
-      #   npm error Invalid: lock file's llama-stack-client@0.2.17 does not satisfy llama-stack-client@0.2.18
-
-      # - name: Set up Node.js
-      #   uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4.1.0
-      #   with:
-      #     node-version: '20'
-      #     cache: 'npm'
-      #     cache-dependency-path: 'llama_stack/ui/'
-
-      # - name: Install npm dependencies
-      #   run: npm ci
-      #   working-directory: llama_stack/ui
-
       - uses: pre-commit/action@2c7b3805fd2a0fd8c1884dcaebf91fc102a13ecd # v3.0.1
         continue-on-error: true
         env:

.github/workflows/providers-build.yml

@@ -36,7 +36,7 @@ jobs:
       distros: ${{ steps.set-matrix.outputs.distros }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Generate Distribution List
         id: set-matrix
@@ -55,7 +55,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner
@@ -79,7 +79,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner
@@ -92,7 +92,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner
@@ -117,7 +117,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/python-build-test.yml

@@ -21,10 +21,10 @@ jobs:
 
     steps:
     - name: Checkout repository
-      uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+      uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
     - name: Install uv
-      uses: astral-sh/setup-uv@d9e0f98d3fc6adb07d1e3d37f3043649ddad06a1 # v6.5.0
+      uses: astral-sh/setup-uv@e92bafb6253dcd438e0484186d7669ea7a8ca1cc # v6.4.3
       with:
         python-version: ${{ matrix.python-version }}
         activate-environment: true

.github/workflows/record-integration-tests.yml

@@ -46,7 +46,7 @@ jobs:
           echo "::endgroup::"
 
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
         with:
           fetch-depth: 0
 

.github/workflows/semantic-pr.yml

@@ -22,6 +22,6 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Check PR Title's semantic conformance
-        uses: amannn/action-semantic-pull-request@7f33ba792281b034f64e96f4c0b5496782dd3b37 # v6.1.0
+        uses: amannn/action-semantic-pull-request@0723387faaf9b38adef4775cd42cfd5155ed6017 # v5.5.3
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/test-external-provider-module.yml

@@ -27,7 +27,7 @@ jobs:
         # container and point 'uv pip install' to the correct path...
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/test-external.yml

@@ -27,7 +27,7 @@ jobs:
         # container and point 'uv pip install' to the correct path...
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/ui-unit-tests.yml

@@ -26,10 +26,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Setup Node.js
-        uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4.1.0
         with:
           node-version: ${{ matrix.node-version }}
           cache: 'npm'

.github/workflows/unit-tests.yml

@@ -32,7 +32,7 @@ jobs:
           - "3.13"
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.github/workflows/update-readthedocs.yml

@@ -37,7 +37,7 @@ jobs:
       TOKEN: ${{ secrets.READTHEDOCS_TOKEN }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
 
       - name: Install dependencies
         uses: ./.github/actions/setup-runner

.pre-commit-config.yaml

@@ -146,50 +146,20 @@ repos:
         pass_filenames: false
         require_serial: true
         files: ^.github/workflows/.*$
-      # ui-prettier and ui-eslint are disabled until we can avoid `npm ci`, which is slow and may fail -
+      - id: ui-prettier
-      #   npm error `npm ci` can only install packages when your package.json and package-lock.json or npm-shrinkwrap.json are in sync. Please update your lock file with `npm install` before continuing.
+        name: Format UI code with Prettier
-      #   npm error Invalid: lock file's llama-stack-client@0.2.17 does not satisfy llama-stack-client@0.2.18
+        entry: bash -c 'cd llama_stack/ui && npm ci && npm run format'
-      # and until we have infra for installing prettier and next via npm -
-      #   Lint UI code with ESLint.....................................................Failed
-      #   - hook id: ui-eslint
-      #   - exit code: 127
-      #   > ui@0.1.0 lint
-      #   > next lint --fix --quiet
-      #   sh: line 1: next: command not found
-      #
-      # - id: ui-prettier
-      #   name: Format UI code with Prettier
-      #   entry: bash -c 'cd llama_stack/ui && npm ci && npm run format'
-      #   language: system
-      #   files: ^llama_stack/ui/.*\.(ts|tsx)$
-      #   pass_filenames: false
-      #   require_serial: true
-      # - id: ui-eslint
-      #   name: Lint UI code with ESLint
-      #   entry: bash -c 'cd llama_stack/ui && npm run lint -- --fix --quiet'
-      #   language: system
-      #   files: ^llama_stack/ui/.*\.(ts|tsx)$
-      #   pass_filenames: false
-      #   require_serial: true
-
-      - id: check-log-usage
-        name: Ensure 'llama_stack.log' usage for logging
-        entry: bash
         language: system
-        types: [python]
+        files: ^llama_stack/ui/.*\.(ts|tsx)$
-        pass_filenames: true
+        pass_filenames: false
-        args:
+        require_serial: true
-          - -c
+      - id: ui-eslint
-          - |
+        name: Lint UI code with ESLint
-            matches=$(grep -EnH '^[^#]*\b(import\s+logging|from\s+logging\b)' "$@" | grep -v -e '#\s*allow-direct-logging' || true)
+        entry: bash -c 'cd llama_stack/ui && npm ci && npm run lint -- --fix --quiet'
-            if [ -n "$matches" ]; then
+        language: system
-              # GitHub Actions annotation format
+        files: ^llama_stack/ui/.*\.(ts|tsx)$
-              while IFS=: read -r file line_num rest; do
+        pass_filenames: false
-                echo "::error file=$file,line=$line_num::Do not use 'import logging' or 'from logging import' in $file. Use the custom log instead: from llama_stack.log import get_logger; logger = get_logger(). If direct logging is truly needed, add: # allow-direct-logging"
+        require_serial: true
-              done <<< "$matches"
-              exit 1
-            fi
-            exit 0
 
 ci:
     autofix_commit_msg: 🎨 [pre-commit.ci] Auto format from pre-commit.com hooks

llama_stack/core/build.py

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import importlib.resources
+import logging
 import sys
 
 from pydantic import BaseModel
@@ -16,10 +17,9 @@ from llama_stack.core.external import load_external_apis
 from llama_stack.core.utils.exec import run_command
 from llama_stack.core.utils.image_types import LlamaStackImageType
 from llama_stack.distributions.template import DistributionTemplate
-from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api
 
-log = get_logger(name=__name__, category="core")
+log = logging.getLogger(__name__)
 
 # These are the dependencies needed by the distribution server.
 # `llama-stack` is automatically installed by the installation script.

llama_stack/core/configure.py

@@ -3,6 +3,7 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
+import logging
 import textwrap
 from typing import Any
 
@@ -20,10 +21,9 @@ from llama_stack.core.stack import cast_image_name_to_string, replace_env_vars
 from llama_stack.core.utils.config_dirs import EXTERNAL_PROVIDERS_DIR
 from llama_stack.core.utils.dynamic import instantiate_class_type
 from llama_stack.core.utils.prompt_for_config import prompt_for_config
-from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-logger = get_logger(name=__name__, category="core")
+logger = logging.getLogger(__name__)
 
 
 def configure_single_provider(registry: dict[str, ProviderSpec], provider: Provider) -> Provider:

llama_stack/core/library_client.py

@@ -7,7 +7,7 @@
 import asyncio
 import inspect
 import json
-import logging  # allow-direct-logging
+import logging
 import os
 import sys
 from concurrent.futures import ThreadPoolExecutor
@@ -48,7 +48,6 @@ from llama_stack.core.stack import (
 from llama_stack.core.utils.config import redact_sensitive_fields
 from llama_stack.core.utils.context import preserve_contexts_async_generator
 from llama_stack.core.utils.exec import in_notebook
-from llama_stack.log import get_logger
 from llama_stack.providers.utils.telemetry.tracing import (
     CURRENT_TRACE_CONTEXT,
     end_trace,
@@ -56,7 +55,7 @@ from llama_stack.providers.utils.telemetry.tracing import (
     start_trace,
 )
 
-logger = get_logger(name=__name__, category="core")
+logger = logging.getLogger(__name__)
 
 T = TypeVar("T")
 

llama_stack/core/request_headers.py

@@ -6,15 +6,15 @@
 
 import contextvars
 import json
+import logging
 from contextlib import AbstractContextManager
 from typing import Any
 
 from llama_stack.core.datatypes import User
-from llama_stack.log import get_logger
 
 from .utils.dynamic import instantiate_class_type
 
-log = get_logger(name=__name__, category="core")
+log = logging.getLogger(__name__)
 
 # Context variable for request provider data and auth attributes
 PROVIDER_DATA_VAR = contextvars.ContextVar("provider_data", default=None)

llama_stack/core/server/server.py

@@ -9,7 +9,7 @@ import asyncio
 import functools
 import inspect
 import json
-import logging  # allow-direct-logging
+import logging
 import os
 import ssl
 import sys

llama_stack/core/utils/exec.py

@@ -4,7 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import importlib
+import logging
 import os
 import signal
 import subprocess
@@ -12,9 +12,9 @@ import sys
 
 from termcolor import cprint
 
-from llama_stack.log import get_logger
+log = logging.getLogger(__name__)
 
-log = get_logger(name=__name__, category="core")
+import importlib
 
 
 def formulate_run_args(image_type: str, image_name: str) -> list:

llama_stack/core/utils/prompt_for_config.py

@@ -6,6 +6,7 @@
 
 import inspect
 import json
+import logging
 from enum import Enum
 from typing import Annotated, Any, Literal, Union, get_args, get_origin
 
@@ -13,9 +14,7 @@ from pydantic import BaseModel
 from pydantic.fields import FieldInfo
 from pydantic_core import PydanticUndefinedType
 
-from llama_stack.log import get_logger
+log = logging.getLogger(__name__)
-
-log = get_logger(name=__name__, category="core")
 
 
 def is_list_of_primitives(field_type):

llama_stack/log.py

@@ -4,10 +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  # allow-direct-logging
+import logging
 import os
 import re
-from logging.config import dictConfig  # allow-direct-logging
+from logging.config import dictConfig
 
 from rich.console import Console
 from rich.errors import MarkupError

llama_stack/models/llama/llama3/multimodal/encoder_utils.py

@@ -13,15 +13,14 @@
 
 # Copyright (c) Meta Platforms, Inc. and its affiliates.
 import math
+from logging import getLogger
 
 import torch
 import torch.nn.functional as F
 
-from llama_stack.log import get_logger
-
 from .utils import get_negative_inf_value, to_2tuple
 
-logger = get_logger(name=__name__, category="models::llama")
+logger = getLogger()
 
 
 def resize_local_position_embedding(orig_pos_embed, grid_size):

llama_stack/models/llama/llama3/multimodal/image_transform.py

@@ -13,6 +13,7 @@
 
 import math
 from collections import defaultdict
+from logging import getLogger
 from typing import Any
 
 import torch
@@ -20,11 +21,9 @@ import torchvision.transforms as tv
 from PIL import Image
 from torchvision.transforms import functional as F
 
-from llama_stack.log import get_logger
-
 IMAGE_RES = 224
 
-logger = get_logger(name=__name__, category="models::llama")
+logger = getLogger()
 
 
 class VariableSizeImageTransform:

llama_stack/models/llama/llama3/multimodal/model.py

@@ -3,6 +3,8 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
+
+import logging
 import math
 from collections.abc import Callable
 from functools import partial
@@ -20,8 +22,6 @@ from PIL import Image as PIL_Image
 from torch import Tensor, nn
 from torch.distributed import _functional_collectives as funcol
 
-from llama_stack.log import get_logger
-
 from ..model import ModelArgs, RMSNorm, apply_rotary_emb, precompute_freqs_cis
 from .encoder_utils import (
     build_encoder_attention_mask,
@@ -34,10 +34,9 @@ from .encoder_utils import (
 from .image_transform import VariableSizeImageTransform
 from .utils import get_negative_inf_value, to_2tuple
 
+logger = logging.getLogger(__name__)
 MP_SCALE = 8
 
-logger = get_logger(name=__name__, category="models")
-
 
 def reduce_from_tensor_model_parallel_region(input_):
     """All-reduce the input tensor across model parallel group."""
@@ -772,7 +771,7 @@ class TilePositionEmbedding(nn.Module):
         if embed is not None:
             # reshape the weights to the correct shape
             nt_old, nt_old, _, w = embed.shape
-            logger.info(f"Resizing tile embedding from {nt_old}x{nt_old} to {self.num_tiles}x{self.num_tiles}")
+            logging.info(f"Resizing tile embedding from {nt_old}x{nt_old} to {self.num_tiles}x{self.num_tiles}")
             embed_new = TilePositionEmbedding._dynamic_resize(embed, self.num_tiles)
             # assign the weights to the module
             state_dict[prefix + "embedding"] = embed_new

llama_stack/models/llama/llama3/tokenizer.py

@@ -4,8 +4,8 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-
 from collections.abc import Collection, Iterator, Sequence, Set
+from logging import getLogger
 from pathlib import Path
 from typing import (
     Literal,
@@ -14,9 +14,11 @@ from typing import (
 
 import tiktoken
 
-from llama_stack.log import get_logger
 from llama_stack.models.llama.tokenizer_utils import load_bpe_file
 
+logger = getLogger(__name__)
+
+
 # The tiktoken tokenizer can handle <=400k chars without
 # pyo3_runtime.PanicException.
 TIKTOKEN_MAX_ENCODE_CHARS = 400_000
@@ -29,8 +31,6 @@ MAX_NO_WHITESPACES_CHARS = 25_000
 
 _INSTANCE = None
 
-logger = get_logger(name=__name__, category="models::llama")
-
 
 class Tokenizer:
     """

llama_stack/models/llama/llama4/quantization/loader.py

@@ -4,6 +4,7 @@
 # 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
 from collections.abc import Callable
 
@@ -12,13 +13,11 @@ from fairscale.nn.model_parallel.initialize import get_model_parallel_rank
 from torch import Tensor, nn
 from torch.nn import functional as F
 
-from llama_stack.log import get_logger
-
 from ...datatypes import QuantizationMode
 from ..model import Transformer, TransformerBlock
 from ..moe import MoE
 
-log = get_logger(name=__name__, category="models")
+log = logging.getLogger(__name__)
 
 
 def swiglu_wrapper_no_reduce(

llama_stack/models/llama/llama4/tokenizer.py

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 from collections.abc import Collection, Iterator, Sequence, Set
+from logging import getLogger
 from pathlib import Path
 from typing import (
     Literal,
@@ -13,9 +14,11 @@ from typing import (
 
 import tiktoken
 
-from llama_stack.log import get_logger
 from llama_stack.models.llama.tokenizer_utils import load_bpe_file
 
+logger = getLogger(__name__)
+
+
 # The tiktoken tokenizer can handle <=400k chars without
 # pyo3_runtime.PanicException.
 TIKTOKEN_MAX_ENCODE_CHARS = 400_000
@@ -98,8 +101,6 @@ BASIC_SPECIAL_TOKENS = [
     "<|fim_suffix|>",
 ]
 
-logger = get_logger(name=__name__, category="models::llama")
-
 
 class Tokenizer:
     """

llama_stack/models/llama/quantize_impls.py

@@ -6,10 +6,9 @@
 
 # type: ignore
 import collections
+import logging
 
-from llama_stack.log import get_logger
+log = logging.getLogger(__name__)
-
-log = get_logger(name=__name__, category="llama")
 
 try:
     import fbgemm_gpu.experimental.gen_ai  # noqa: F401

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

@@ -4,6 +4,7 @@
 # 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
@@ -41,7 +42,6 @@ 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 = get_logger(name=__name__, category="agents")
+logger = logging.getLogger()
 
 
 class MetaReferenceAgentsImpl(Agents):

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import json
+import logging
 import uuid
 from datetime import UTC, datetime
 
@@ -14,10 +15,9 @@ 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 = get_logger(name=__name__, category="agents")
+log = logging.getLogger(__name__)
 
 
 class AgentSessionInfo(Session):

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

@@ -17,8 +17,6 @@ from llama_stack.apis.agents.openai_responses import (
     OpenAIResponseOutputMessageContent,
     OpenAIResponseOutputMessageContentOutputText,
     OpenAIResponseOutputMessageFunctionToolCall,
-    OpenAIResponseOutputMessageMCPCall,
-    OpenAIResponseOutputMessageMCPListTools,
     OpenAIResponseText,
 )
 from llama_stack.apis.inference import (
@@ -119,25 +117,6 @@ async def convert_response_input_to_chat_messages(
                     ),
                 )
                 messages.append(OpenAIAssistantMessageParam(tool_calls=[tool_call]))
-            elif isinstance(input_item, OpenAIResponseOutputMessageMCPCall):
-                tool_call = OpenAIChatCompletionToolCall(
-                    index=0,
-                    id=input_item.id,
-                    function=OpenAIChatCompletionToolCallFunction(
-                        name=input_item.name,
-                        arguments=input_item.arguments,
-                    ),
-                )
-                messages.append(OpenAIAssistantMessageParam(tool_calls=[tool_call]))
-                messages.append(
-                    OpenAIToolMessageParam(
-                        content=input_item.output,
-                        tool_call_id=input_item.id,
-                    )
-                )
-            elif isinstance(input_item, OpenAIResponseOutputMessageMCPListTools):
-                # the tool list will be handled separately
-                pass
             else:
                 content = await convert_response_content_to_chat_content(input_item.content)
                 message_type = await get_message_type_by_role(input_item.role)

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 = get_logger(name=__name__, category="agents")
+log = logging.getLogger(__name__)
 
 
 class SafetyException(Exception):  # noqa: N818

llama_stack/providers/inline/files/localfs/files.py

@@ -11,7 +11,6 @@ from typing import Annotated
 
 from fastapi import File, Form, Response, UploadFile
 
-from llama_stack.apis.common.errors import ResourceNotFoundError
 from llama_stack.apis.common.responses import Order
 from llama_stack.apis.files import (
     Files,
@@ -21,15 +20,12 @@ from llama_stack.apis.files import (
     OpenAIFilePurpose,
 )
 from llama_stack.core.datatypes import AccessRule
-from llama_stack.log import get_logger
 from llama_stack.providers.utils.sqlstore.api import ColumnDefinition, ColumnType
 from llama_stack.providers.utils.sqlstore.authorized_sqlstore import AuthorizedSqlStore
 from llama_stack.providers.utils.sqlstore.sqlstore import sqlstore_impl
 
 from .config import LocalfsFilesImplConfig
 
-logger = get_logger(name=__name__, category="files")
-
 
 class LocalfsFilesImpl(Files):
     def __init__(self, config: LocalfsFilesImplConfig, policy: list[AccessRule]) -> None:
@@ -69,18 +65,6 @@ class LocalfsFilesImpl(Files):
         """Get the filesystem path for a file ID."""
         return Path(self.config.storage_dir) / file_id
 
-    async def _lookup_file_id(self, file_id: str) -> tuple[OpenAIFileObject, Path]:
-        """Look up a OpenAIFileObject and filesystem path from its ID."""
-        if not self.sql_store:
-            raise RuntimeError("Files provider not initialized")
-
-        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
-        if not row:
-            raise ResourceNotFoundError(file_id, "File", "client.files.list()")
-
-        file_path = Path(row.pop("file_path"))
-        return OpenAIFileObject(**row), file_path
-
     # OpenAI Files API Implementation
     async def openai_upload_file(
         self,
@@ -173,19 +157,37 @@ class LocalfsFilesImpl(Files):
 
     async def openai_retrieve_file(self, file_id: str) -> OpenAIFileObject:
         """Returns information about a specific file."""
-        file_obj, _ = await self._lookup_file_id(file_id)
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
 
-        return file_obj
+        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
+        if not row:
+            raise ValueError(f"File with id {file_id} not found")
+
+        return OpenAIFileObject(
+            id=row["id"],
+            filename=row["filename"],
+            purpose=OpenAIFilePurpose(row["purpose"]),
+            bytes=row["bytes"],
+            created_at=row["created_at"],
+            expires_at=row["expires_at"],
+        )
 
     async def openai_delete_file(self, file_id: str) -> OpenAIFileDeleteResponse:
         """Delete a file."""
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
+
+        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
+        if not row:
+            raise ValueError(f"File with id {file_id} not found")
+
         # Delete physical file
-        _, file_path = await self._lookup_file_id(file_id)
+        file_path = Path(row["file_path"])
         if file_path.exists():
             file_path.unlink()
 
         # Delete metadata from database
-        assert self.sql_store is not None, "Files provider not initialized"
         await self.sql_store.delete("openai_files", where={"id": file_id})
 
         return OpenAIFileDeleteResponse(
@@ -195,17 +197,25 @@ class LocalfsFilesImpl(Files):
 
     async def openai_retrieve_file_content(self, file_id: str) -> Response:
         """Returns the contents of the specified file."""
-        # Read file content
+        if not self.sql_store:
-        file_obj, file_path = await self._lookup_file_id(file_id)
+            raise RuntimeError("Files provider not initialized")
 
+        # Get file metadata
+        row = await self.sql_store.fetch_one("openai_files", policy=self.policy, where={"id": file_id})
+        if not row:
+            raise ValueError(f"File with id {file_id} not found")
+
+        # Read file content
+        file_path = Path(row["file_path"])
         if not file_path.exists():
-            logger.warning(f"File '{file_id}'s underlying '{file_path}' is missing, deleting metadata.")
+            raise ValueError(f"File content not found on disk: {file_path}")
-            await self.openai_delete_file(file_id)
+
-            raise ResourceNotFoundError(file_id, "File", "client.files.list()")
+        with open(file_path, "rb") as f:
+            content = f.read()
 
         # Return as binary response with appropriate content type
         return Response(
-            content=file_path.read_bytes(),
+            content=content,
             media_type="application/octet-stream",
-            headers={"Content-Disposition": f'attachment; filename="{file_obj.filename}"'},
+            headers={"Content-Disposition": f'attachment; filename="{row["filename"]}"'},
         )

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

@@ -12,6 +12,7 @@
 
 import copy
 import json
+import logging
 import multiprocessing
 import os
 import tempfile
@@ -31,14 +32,13 @@ 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 = get_logger(name=__name__, category="inference")
+log = logging.getLogger(__name__)
 
 
 class ProcessingMessageName(str, Enum):

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

@@ -4,6 +4,7 @@
 # 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 (
@@ -20,7 +21,6 @@ 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 = get_logger(name=__name__, category="inference")
+log = logging.getLogger(__name__)
 
 
 class SentenceTransformersInferenceImpl(

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

@@ -6,6 +6,7 @@
 
 import gc
 import json
+import logging
 import multiprocessing
 from pathlib import Path
 from typing import Any
@@ -27,7 +28,6 @@ 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 = get_logger(name=__name__, category="post_training")
+logger = logging.getLogger(__name__)
 
 
 class HFFinetuningSingleDevice:

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import gc
+import logging
 import multiprocessing
 from pathlib import Path
 from typing import Any
@@ -23,7 +24,6 @@ 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 = get_logger(name=__name__, category="post_training")
+logger = logging.getLogger(__name__)
 
 
 class HFDPOAlignmentSingleDevice:

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

@@ -4,6 +4,7 @@
 # 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
@@ -18,11 +19,10 @@ 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 = get_logger(name=__name__, category="post_training")
+logger = logging.getLogger(__name__)
 
 
 def setup_environment():

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

@@ -4,6 +4,7 @@
 # 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
@@ -18,7 +19,6 @@ 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,
@@ -45,7 +45,6 @@ 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
@@ -57,7 +56,9 @@ from llama_stack.providers.inline.post_training.torchtune.config import (
 )
 from llama_stack.providers.inline.post_training.torchtune.datasets.sft import SFTDataset
 
-log = get_logger(name=__name__, category="post_training")
+log = logging.getLogger(__name__)
+
+from torchtune.models.llama3._tokenizer import Llama3Tokenizer
 
 
 class LoraFinetuningSingleDevice:

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

@@ -4,6 +4,7 @@
 # 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
 
@@ -19,14 +20,13 @@ 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 = get_logger(name=__name__, category="safety")
+log = logging.getLogger(__name__)
 
 ALLOWED_CODE_SCANNER_MODEL_IDS = [
     "code-scanner",

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

@@ -4,6 +4,7 @@
 # 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
@@ -20,7 +21,6 @@ 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
@@ -132,8 +132,6 @@ 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:
@@ -409,7 +407,7 @@ 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:
-                logger.warning(f"Invalid safety codes returned: {invalid_codes}")
+                logging.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

@@ -4,6 +4,7 @@
 # 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
@@ -20,7 +21,6 @@ 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 = get_logger(name=__name__, category="safety")
+log = logging.getLogger(__name__)
 
 PROMPT_GUARD_MODEL = "Prompt-Guard-86M"
 

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

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

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

@@ -4,10 +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 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
@@ -37,7 +40,6 @@ 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,
 )
@@ -59,8 +61,6 @@ _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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import asyncio
+import logging
 import secrets
 import string
 from typing import Any
@@ -31,7 +32,6 @@ 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 = get_logger(name=__name__, category="tool_runtime")
+log = logging.getLogger(__name__)
 
 
 def make_random_string(length: int = 8):

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

@@ -8,6 +8,7 @@ import asyncio
 import base64
 import io
 import json
+import logging
 from typing import Any
 
 import faiss
@@ -23,7 +24,6 @@ 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 = get_logger(name=__name__, category="vector_io")
+logger = logging.getLogger(__name__)
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:{VERSION}::"

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import asyncio
+import logging
 import re
 import sqlite3
 import struct
@@ -23,7 +24,6 @@ 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 = get_logger(name=__name__, category="vector_io")
+logger = logging.getLogger(__name__)
 
 # Specifying search mode is dependent on the VectorIO provider.
 VECTOR_SEARCH = "vector"

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

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

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

@@ -77,10 +77,6 @@ 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

@@ -4,10 +4,11 @@
 # 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 NOT_GIVEN, APIConnectionError, BadRequestError
+from openai import APIConnectionError, BadRequestError
 
 from llama_stack.apis.common.content_types import (
     InterleavedContent,
@@ -26,16 +27,12 @@ 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,
@@ -57,7 +54,7 @@ from .openai_utils import (
 )
 from .utils import _is_nvidia_hosted
 
-logger = get_logger(name=__name__, category="inference")
+logger = logging.getLogger(__name__)
 
 
 class NVIDIAInferenceAdapter(OpenAIMixin, Inference, ModelRegistryHelper):
@@ -213,57 +210,6 @@ 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 httpx
+import logging
 
-from llama_stack.log import get_logger
+import httpx
 
 from . import NVIDIAConfig
 
-logger = get_logger(name=__name__, category="inference")
+logger = logging.getLogger(__name__)
 
 
 def _is_nvidia_hosted(config: NVIDIAConfig) -> bool:

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

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

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 
+import logging
 from collections.abc import AsyncGenerator
 
 from huggingface_hub import AsyncInferenceClient, HfApi
@@ -33,7 +34,6 @@ 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 = get_logger(name=__name__, category="inference")
+log = logging.getLogger(__name__)
 
 
 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 = get_logger(name=__name__, category="integration")
+logger = logging.getLogger(__name__)
 
 
 def warn_unsupported_params(config_dict: Any, supported_keys: set[str], config_name: str) -> None:

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import json
+import logging
 from typing import Any
 
 from llama_stack.apis.inference import Message
@@ -15,13 +16,12 @@ 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 = get_logger(name=__name__, category="safety")
+logger = logging.getLogger(__name__)
 
 
 class BedrockSafetyAdapter(Safety, ShieldsProtocolPrivate):

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

@@ -4,6 +4,7 @@
 # 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
@@ -11,13 +12,12 @@ 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 = get_logger(name=__name__, category="safety")
+logger = logging.getLogger(__name__)
 
 
 class NVIDIASafetyAdapter(Safety, ShieldsProtocolPrivate):

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import json
+import logging
 from typing import Any
 
 import litellm
@@ -19,13 +20,12 @@ 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 = get_logger(name=__name__, category="safety")
+logger = logging.getLogger(__name__)
 
 CANNED_RESPONSE_TEXT = "I can't answer that. Can I help with something else?"
 

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 import asyncio
 import json
+import logging
 from typing import Any
 from urllib.parse import urlparse
 
@@ -19,7 +20,6 @@ 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 = get_logger(name=__name__, category="vector_io")
+log = logging.getLogger(__name__)
 
 ChromaClientType = chromadb.api.AsyncClientAPI | chromadb.api.ClientAPI
 

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import asyncio
+import logging
 import os
 from typing import Any
 
@@ -20,7 +21,6 @@ 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 = get_logger(name=__name__, category="vector_io")
+logger = logging.getLogger(__name__)
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:milvus:{VERSION}::"

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

@@ -4,6 +4,7 @@
 # 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
@@ -21,7 +22,6 @@ 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 = get_logger(name=__name__, category="vector_io")
+log = logging.getLogger(__name__)
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:pgvector:{VERSION}::"

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

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 
 import asyncio
+import logging
 import uuid
 from typing import Any
 
@@ -23,7 +24,6 @@ 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 = get_logger(name=__name__, category="vector_io")
+log = logging.getLogger(__name__)
 CHUNK_ID_KEY = "_chunk_id"
 
 # KV store prefixes for vector databases

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

@@ -4,6 +4,7 @@
 # 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
@@ -18,7 +19,6 @@ 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 = get_logger(name=__name__, category="vector_io")
+log = logging.getLogger(__name__)
 
 VERSION = "v3"
 VECTOR_DBS_PREFIX = f"vector_dbs:weaviate:{VERSION}::"

llama_stack/providers/utils/inference/embedding_mixin.py

@@ -5,11 +5,10 @@
 # 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
 
@@ -28,7 +27,7 @@ from llama_stack.providers.utils.inference.prompt_adapter import interleaved_con
 EMBEDDING_MODELS = {}
 
 
-log = get_logger(name=__name__, category="inference")
+log = logging.getLogger(__name__)
 
 
 class SentenceTransformerEmbeddingMixin:

llama_stack/providers/utils/inference/openai_compat.py

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 import base64
 import json
+import logging
 import struct
 import time
 import uuid
@@ -121,7 +122,6 @@ 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 = get_logger(name=__name__, category="inference")
+logger = logging.getLogger(__name__)
 
 
 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 = get_logger(name=__name__, category="kvstore")
+log = logging.getLogger(__name__)
 
 
 class MongoDBKVStoreImpl(KVStore):

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

@@ -4,17 +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
 
 import psycopg2
 from psycopg2.extras import DictCursor
 
-from llama_stack.log import get_logger
-
 from ..api import KVStore
 from ..config import PostgresKVStoreConfig
 
-log = get_logger(name=__name__, category="kvstore")
+log = logging.getLogger(__name__)
 
 
 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=__name__, category="memory")
+logger = get_logger(__name__, category="vector_io")
 
 # Constants for OpenAI vector stores
 CHUNK_MULTIPLIER = 5

llama_stack/providers/utils/memory/vector_store.py

@@ -5,6 +5,7 @@
 # the root directory of this source tree.
 import base64
 import io
+import logging
 import re
 import time
 from abc import ABC, abstractmethod
@@ -25,7 +26,6 @@ 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 = get_logger(name=__name__, category="memory")
+log = logging.getLogger(__name__)
 
 
 class ChunkForDeletion(BaseModel):

llama_stack/providers/utils/sqlstore/sqlalchemy_sqlstore.py

@@ -22,7 +22,6 @@ from sqlalchemy import (
     text,
 )
 from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
-from sqlalchemy.ext.asyncio.engine import AsyncEngine
 
 from llama_stack.apis.common.responses import PaginatedResponse
 from llama_stack.log import get_logger
@@ -46,12 +45,9 @@ TYPE_MAPPING: dict[ColumnType, Any] = {
 class SqlAlchemySqlStoreImpl(SqlStore):
     def __init__(self, config: SqlAlchemySqlStoreConfig):
         self.config = config
-        self.async_session = async_sessionmaker(self.create_engine())
+        self.async_session = async_sessionmaker(create_async_engine(config.engine_str))
         self.metadata = MetaData()
 
-    def create_engine(self) -> AsyncEngine:
-        return create_async_engine(self.config.engine_str, pool_pre_ping=True)
-
     async def create_table(
         self,
         table: str,
@@ -87,7 +83,7 @@ class SqlAlchemySqlStoreImpl(SqlStore):
         else:
             sqlalchemy_table = self.metadata.tables[table]
 
-        engine = self.create_engine()
+        engine = create_async_engine(self.config.engine_str)
         async with engine.begin() as conn:
             await conn.run_sync(self.metadata.create_all, tables=[sqlalchemy_table], checkfirst=True)
 
@@ -245,7 +241,7 @@ class SqlAlchemySqlStoreImpl(SqlStore):
         nullable: bool = True,
     ) -> None:
         """Add a column to an existing table if the column doesn't already exist."""
-        engine = self.create_engine()
+        engine = create_async_engine(self.config.engine_str)
 
         try:
             async with engine.begin() as conn:

llama_stack/providers/utils/telemetry/tracing.py

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

llama_stack/ui/package-lock.json

@@ -8,17 +8,17 @@
       "name": "ui",
       "version": "0.1.0",
       "dependencies": {
-        "@radix-ui/react-collapsible": "^1.1.12",
+        "@radix-ui/react-collapsible": "^1.1.11",
         "@radix-ui/react-dialog": "^1.1.13",
         "@radix-ui/react-dropdown-menu": "^2.1.14",
         "@radix-ui/react-select": "^2.2.5",
-        "@radix-ui/react-separator": "^1.1.7",
+        "@radix-ui/react-separator": "^1.1.6",
         "@radix-ui/react-slot": "^1.2.3",
         "@radix-ui/react-tooltip": "^1.2.6",
         "class-variance-authority": "^0.7.1",
         "clsx": "^2.1.1",
         "framer-motion": "^11.18.2",
-        "llama-stack-client": "^0.2.18",
+        "llama-stack-client": "0.2.17",
         "lucide-react": "^0.510.0",
         "next": "15.3.3",
         "next-auth": "^4.24.11",
@@ -30,7 +30,7 @@
         "remeda": "^2.26.1",
         "shiki": "^1.29.2",
         "sonner": "^2.0.6",
-        "tailwind-merge": "^3.3.1"
+        "tailwind-merge": "^3.3.0"
       },
       "devDependencies": {
         "@eslint/eslintrc": "^3",
@@ -44,7 +44,7 @@
         "@types/react-dom": "^19",
         "eslint": "^9",
         "eslint-config-next": "15.3.2",
-        "eslint-config-prettier": "^10.1.8",
+        "eslint-config-prettier": "^10.1.5",
         "eslint-plugin-prettier": "^5.4.0",
         "jest": "^29.7.0",
         "jest-environment-jsdom": "^29.7.0",
@@ -2089,16 +2089,16 @@
       }
     },
     "node_modules/@radix-ui/react-collapsible": {
-      "version": "1.1.12",
+      "version": "1.1.11",
-      "resolved": "https://registry.npmjs.org/@radix-ui/react-collapsible/-/react-collapsible-1.1.12.tgz",
+      "resolved": "https://registry.npmjs.org/@radix-ui/react-collapsible/-/react-collapsible-1.1.11.tgz",
-      "integrity": "sha512-Uu+mSh4agx2ib1uIGPP4/CKNULyajb3p92LsVXmH2EHVMTfZWpll88XJ0j4W0z3f8NK1eYl1+Mf/szHPmcHzyA==",
+      "integrity": "sha512-2qrRsVGSCYasSz1RFOorXwl0H7g7J1frQtgpQgYrt+MOidtPAINHn9CPovQXb83r8ahapdx3Tu0fa/pdFFSdPg==",
       "license": "MIT",
       "dependencies": {
-        "@radix-ui/primitive": "1.1.3",
+        "@radix-ui/primitive": "1.1.2",
         "@radix-ui/react-compose-refs": "1.1.2",
         "@radix-ui/react-context": "1.1.2",
         "@radix-ui/react-id": "1.1.1",
-        "@radix-ui/react-presence": "1.1.5",
+        "@radix-ui/react-presence": "1.1.4",
         "@radix-ui/react-primitive": "2.1.3",
         "@radix-ui/react-use-controllable-state": "1.2.2",
         "@radix-ui/react-use-layout-effect": "1.1.1"
@@ -2118,36 +2118,6 @@
         }
       }
     },
-    "node_modules/@radix-ui/react-collapsible/node_modules/@radix-ui/primitive": {
-      "version": "1.1.3",
-      "resolved": "https://registry.npmjs.org/@radix-ui/primitive/-/primitive-1.1.3.tgz",
-      "integrity": "sha512-JTF99U/6XIjCBo0wqkU5sK10glYe27MRRsfwoiq5zzOEZLHU3A3KCMa5X/azekYRCJ0HlwI0crAXS/5dEHTzDg==",
-      "license": "MIT"
-    },
-    "node_modules/@radix-ui/react-collapsible/node_modules/@radix-ui/react-presence": {
-      "version": "1.1.5",
-      "resolved": "https://registry.npmjs.org/@radix-ui/react-presence/-/react-presence-1.1.5.tgz",
-      "integrity": "sha512-/jfEwNDdQVBCNvjkGit4h6pMOzq8bHkopq458dPt2lMjx+eBQUohZNG9A7DtO/O5ukSbxuaNGXMjHicgwy6rQQ==",
-      "license": "MIT",
-      "dependencies": {
-        "@radix-ui/react-compose-refs": "1.1.2",
-        "@radix-ui/react-use-layout-effect": "1.1.1"
-      },
-      "peerDependencies": {
-        "@types/react": "*",
-        "@types/react-dom": "*",
-        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc",
-        "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
-      },
-      "peerDependenciesMeta": {
-        "@types/react": {
-          "optional": true
-        },
-        "@types/react-dom": {
-          "optional": true
-        }
-      }
-    },
     "node_modules/@radix-ui/react-collapsible/node_modules/@radix-ui/react-primitive": {
       "version": "2.1.3",
       "resolved": "https://registry.npmjs.org/@radix-ui/react-primitive/-/react-primitive-2.1.3.tgz",
@@ -2885,35 +2855,12 @@
       }
     },
     "node_modules/@radix-ui/react-separator": {
-      "version": "1.1.7",
+      "version": "1.1.6",
-      "resolved": "https://registry.npmjs.org/@radix-ui/react-separator/-/react-separator-1.1.7.tgz",
+      "resolved": "https://registry.npmjs.org/@radix-ui/react-separator/-/react-separator-1.1.6.tgz",
-      "integrity": "sha512-0HEb8R9E8A+jZjvmFCy/J4xhbXy3TV+9XSnGJ3KvTtjlIUy/YQ/p6UYZvi7YbeoeXdyU9+Y3scizK6hkY37baA==",
+      "integrity": "sha512-Izof3lPpbCfTM7WDta+LRkz31jem890VjEvpVRoWQNKpDUMMVffuyq854XPGP1KYGWWmjmYvHvPFeocWhFCy1w==",
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llama_stack/ui/package.json

@@ -13,11 +13,11 @@
     "test:e2e": "playwright test"
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     "remeda": "^2.26.1",
     "shiki": "^1.29.2",
     "sonner": "^2.0.6",
-    "tailwind-merge": "^3.3.1"
+    "tailwind-merge": "^3.3.0"
   },
   "devDependencies": {
     "@eslint/eslintrc": "^3",
@@ -49,7 +49,7 @@
     "@types/react-dom": "^19",
     "eslint": "^9",
     "eslint-config-next": "15.3.2",
-    "eslint-config-prettier": "^10.1.8",
+    "eslint-config-prettier": "^10.1.5",
     "eslint-plugin-prettier": "^5.4.0",
     "jest": "^29.7.0",
     "jest-environment-jsdom": "^29.7.0",

tests/integration/files/test_files.py

@@ -8,27 +8,20 @@ from io import BytesIO
 from unittest.mock import patch
 
 import pytest
+from openai import OpenAI
 
 from llama_stack.core.datatypes import User
+from llama_stack.core.library_client import LlamaStackAsLibraryClient
 
 
-# a fixture to skip all these tests if a files provider is not available
+def test_openai_client_basic_operations(compat_client, client_with_models):
-@pytest.fixture(autouse=True)
-def skip_if_no_files_provider(llama_stack_client):
-    if not [provider for provider in llama_stack_client.providers.list() if provider.api == "files"]:
-        pytest.skip("No files providers found")
-
-
-def test_openai_client_basic_operations(openai_client):
     """Test basic file operations through OpenAI client."""
-    from openai import NotFoundError
+    if isinstance(client_with_models, LlamaStackAsLibraryClient) and isinstance(compat_client, OpenAI):
-
+        pytest.skip("OpenAI files are not supported when testing with LlamaStackAsLibraryClient")
-    client = openai_client
+    client = compat_client
 
     test_content = b"files test content"
 
-    uploaded_file = None
-
     try:
         # Upload file using OpenAI client
         with BytesIO(test_content) as file_buffer:
@@ -38,7 +31,6 @@ def test_openai_client_basic_operations(openai_client):
         # Verify basic response structure
         assert uploaded_file.id.startswith("file-")
         assert hasattr(uploaded_file, "filename")
-        assert uploaded_file.filename == "openai_test.txt"
 
         # List files
         files_list = client.files.list()
@@ -51,41 +43,37 @@ def test_openai_client_basic_operations(openai_client):
 
         # Retrieve file content - OpenAI client returns httpx Response object
         content_response = client.files.content(uploaded_file.id)
-        assert content_response.content == test_content
+        # The response is an httpx Response object with .content attribute containing bytes
+        if isinstance(content_response, str):
+            # Llama Stack Client returns a str
+            # TODO: fix Llama Stack Client
+            content = bytes(content_response, "utf-8")
+        else:
+            content = content_response.content
+        assert content == test_content
 
         # Delete file
         delete_response = client.files.delete(uploaded_file.id)
         assert delete_response.deleted is True
 
-        # Retrieve file should fail
+    except Exception as e:
-        with pytest.raises(NotFoundError, match="not found"):
-            client.files.retrieve(uploaded_file.id)
-
-        # File should not be found in listing
-        files_list = client.files.list()
-        file_ids = [f.id for f in files_list.data]
-        assert uploaded_file.id not in file_ids
-
-        # Double delete should fail
-        with pytest.raises(NotFoundError, match="not found"):
-            client.files.delete(uploaded_file.id)
-
-    finally:
         # Cleanup in case of failure
-        if uploaded_file is not None:
+        try:
-            try:
+            client.files.delete(uploaded_file.id)
-                client.files.delete(uploaded_file.id)
+        except Exception:
-            except NotFoundError:
+            pass
-                pass  # ignore 404
+        raise e
 
 
-@pytest.mark.xfail(message="User isolation broken for current providers, must be fixed.")
 @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user")
-def test_files_authentication_isolation(mock_get_authenticated_user, llama_stack_client):
+def test_files_authentication_isolation(mock_get_authenticated_user, compat_client, client_with_models):
     """Test that users can only access their own files."""
-    from llama_stack_client import NotFoundError
+    if isinstance(client_with_models, LlamaStackAsLibraryClient) and isinstance(compat_client, OpenAI):
+        pytest.skip("OpenAI files are not supported when testing with LlamaStackAsLibraryClient")
+    if not isinstance(client_with_models, LlamaStackAsLibraryClient):
+        pytest.skip("Authentication tests require LlamaStackAsLibraryClient (library mode)")
 
-    client = llama_stack_client
+    client = compat_client
 
     # Create two test users
     user1 = User("user1", {"roles": ["user"], "teams": ["team-a"]})
@@ -129,7 +117,7 @@ def test_files_authentication_isolation(mock_get_authenticated_user, llama_stack
 
         # User 1 cannot retrieve user2's file
         mock_get_authenticated_user.return_value = user1
-        with pytest.raises(NotFoundError, match="not found"):
+        with pytest.raises(ValueError, match="not found"):
             client.files.retrieve(user2_file.id)
 
         # User 1 can access their file content
@@ -143,7 +131,7 @@ def test_files_authentication_isolation(mock_get_authenticated_user, llama_stack
 
         # User 1 cannot access user2's file content
         mock_get_authenticated_user.return_value = user1
-        with pytest.raises(NotFoundError, match="not found"):
+        with pytest.raises(ValueError, match="not found"):
             client.files.content(user2_file.id)
 
         # User 1 can delete their own file
@@ -153,7 +141,7 @@ def test_files_authentication_isolation(mock_get_authenticated_user, llama_stack
 
         # User 1 cannot delete user2's file
         mock_get_authenticated_user.return_value = user1
-        with pytest.raises(NotFoundError, match="not found"):
+        with pytest.raises(ValueError, match="not found"):
             client.files.delete(user2_file.id)
 
         # User 2 can still access their file after user1's file is deleted
@@ -181,9 +169,14 @@ def test_files_authentication_isolation(mock_get_authenticated_user, llama_stack
 
 
 @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user")
-def test_files_authentication_shared_attributes(mock_get_authenticated_user, llama_stack_client):
+def test_files_authentication_shared_attributes(mock_get_authenticated_user, compat_client, client_with_models):
     """Test access control with users having identical attributes."""
-    client = llama_stack_client
+    if isinstance(client_with_models, LlamaStackAsLibraryClient) and isinstance(compat_client, OpenAI):
+        pytest.skip("OpenAI files are not supported when testing with LlamaStackAsLibraryClient")
+    if not isinstance(client_with_models, LlamaStackAsLibraryClient):
+        pytest.skip("Authentication tests require LlamaStackAsLibraryClient (library mode)")
+
+    client = compat_client
 
     # Create users with identical attributes (required for default policy)
     user_a = User("user-a", {"roles": ["user"], "teams": ["shared-team"]})
@@ -238,8 +231,14 @@ def test_files_authentication_shared_attributes(mock_get_authenticated_user, lla
 
 
 @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user")
-def test_files_authentication_anonymous_access(mock_get_authenticated_user, llama_stack_client):
+def test_files_authentication_anonymous_access(mock_get_authenticated_user, compat_client, client_with_models):
-    client = llama_stack_client
+    """Test anonymous user behavior when no authentication is present."""
+    if isinstance(client_with_models, LlamaStackAsLibraryClient) and isinstance(compat_client, OpenAI):
+        pytest.skip("OpenAI files are not supported when testing with LlamaStackAsLibraryClient")
+    if not isinstance(client_with_models, LlamaStackAsLibraryClient):
+        pytest.skip("Authentication tests require LlamaStackAsLibraryClient (library mode)")
+
+    client = compat_client
 
     # Simulate anonymous user (no authentication)
     mock_get_authenticated_user.return_value = None

tests/integration/fixtures/common.py

@@ -263,21 +263,8 @@ def instantiate_llama_stack_client(session):
 
 
 @pytest.fixture(scope="session")
-def require_server(llama_stack_client):
+def openai_client(client_with_models):
-    """
+    base_url = f"{client_with_models.base_url}/v1/openai/v1"
-    Skip test if no server is running.
-
-    We use the llama_stack_client to tell if a server was started or not.
-
-    We use this with openai_client because it relies on a running server.
-    """
-    if isinstance(llama_stack_client, LlamaStackAsLibraryClient):
-        pytest.skip("No server running")
-
-
-@pytest.fixture(scope="session")
-def openai_client(llama_stack_client, require_server):
-    base_url = f"{llama_stack_client.base_url}/v1/openai/v1"
     return OpenAI(base_url=base_url, api_key="fake")
 
 

tests/integration/non_ci/responses/test_basic_responses.py

@@ -7,9 +7,8 @@
 import time
 
 import pytest
-
+from fixtures.test_cases import basic_test_cases, image_test_cases, multi_turn_image_test_cases, multi_turn_test_cases
-from .fixtures.test_cases import basic_test_cases, image_test_cases, multi_turn_image_test_cases, multi_turn_test_cases
+from streaming_assertions import StreamingValidator
-from .streaming_assertions import StreamingValidator
 
 
 @pytest.mark.parametrize("case", basic_test_cases)

tests/integration/non_ci/responses/test_tool_responses.py

@@ -10,12 +10,7 @@ import os
 import httpx
 import openai
 import pytest
-
+from fixtures.test_cases import (
-from llama_stack import LlamaStackAsLibraryClient
-from llama_stack.core.datatypes import AuthenticationRequiredError
-from tests.common.mcp import dependency_tools, make_mcp_server
-
-from .fixtures.test_cases import (
     custom_tool_test_cases,
     file_search_test_cases,
     mcp_tool_test_cases,
@@ -23,8 +18,12 @@ from .fixtures.test_cases import (
     multi_turn_tool_execution_test_cases,
     web_search_test_cases,
 )
-from .helpers import new_vector_store, setup_mcp_tools, upload_file, wait_for_file_attachment
+from helpers import new_vector_store, setup_mcp_tools, upload_file, wait_for_file_attachment
-from .streaming_assertions import StreamingValidator
+from streaming_assertions import StreamingValidator
+
+from llama_stack import LlamaStackAsLibraryClient
+from llama_stack.core.datatypes import AuthenticationRequiredError
+from tests.common.mcp import dependency_tools, make_mcp_server
 
 
 @pytest.mark.parametrize("case", web_search_test_cases)
@@ -196,56 +195,6 @@ def test_response_non_streaming_mcp_tool(compat_client, text_model_id, case):
         assert len(response.output) >= 3
 
 
-@pytest.mark.parametrize("case", mcp_tool_test_cases)
-def test_response_sequential_mcp_tool(compat_client, text_model_id, case):
-    if not isinstance(compat_client, LlamaStackAsLibraryClient):
-        pytest.skip("in-process MCP server is only supported in library client")
-
-    with make_mcp_server() as mcp_server_info:
-        tools = setup_mcp_tools(case.tools, mcp_server_info)
-
-        response = compat_client.responses.create(
-            model=text_model_id,
-            input=case.input,
-            tools=tools,
-            stream=False,
-        )
-
-        assert len(response.output) >= 3
-        list_tools = response.output[0]
-        assert list_tools.type == "mcp_list_tools"
-        assert list_tools.server_label == "localmcp"
-        assert len(list_tools.tools) == 2
-        assert {t.name for t in list_tools.tools} == {
-            "get_boiling_point",
-            "greet_everyone",
-        }
-
-        call = response.output[1]
-        assert call.type == "mcp_call"
-        assert call.name == "get_boiling_point"
-        assert json.loads(call.arguments) == {
-            "liquid_name": "myawesomeliquid",
-            "celsius": True,
-        }
-        assert call.error is None
-        assert "-100" in call.output
-
-        # sometimes the model will call the tool again, so we need to get the last message
-        message = response.output[-1]
-        text_content = message.content[0].text
-        assert "boiling point" in text_content.lower()
-
-        response2 = compat_client.responses.create(
-            model=text_model_id, input=case.input, tools=tools, stream=False, previous_response_id=response.id
-        )
-
-        assert len(response2.output) >= 1
-        message = response2.output[-1]
-        text_content = message.content[0].text
-        assert "boiling point" in text_content.lower()
-
-
 @pytest.mark.parametrize("case", custom_tool_test_cases)
 def test_response_non_streaming_custom_tool(compat_client, text_model_id, case):
     response = compat_client.responses.create(

tests/integration/post_training/test_post_training.py

@@ -4,6 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import logging
 import sys
 import time
 import uuid
@@ -18,10 +19,10 @@ from llama_stack.apis.post_training import (
     LoraFinetuningConfig,
     TrainingConfig,
 )
-from llama_stack.log import get_logger
 
 # Configure logging
-logger = get_logger(name=__name__, category="post_training")
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", force=True)
+logger = logging.getLogger(__name__)
 
 
 skip_because_resource_intensive = pytest.mark.skip(

tests/integration/vector_io/test_openai_vector_stores.py

@@ -4,6 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import logging
 import time
 from io import BytesIO
 
@@ -13,9 +14,8 @@ from openai import BadRequestError as OpenAIBadRequestError
 
 from llama_stack.apis.vector_io import Chunk
 from llama_stack.core.library_client import LlamaStackAsLibraryClient
-from llama_stack.log import get_logger
 
-logger = get_logger(name=__name__, category="vector_io")
+logger = logging.getLogger(__name__)
 
 
 def skip_if_provider_doesnt_support_openai_vector_stores(client_with_models):

tests/unit/files/test_files.py

@@ -7,7 +7,6 @@
 
 import pytest
 
-from llama_stack.apis.common.errors import ResourceNotFoundError
 from llama_stack.apis.common.responses import Order
 from llama_stack.apis.files import OpenAIFilePurpose
 from llama_stack.core.access_control.access_control import default_policy
@@ -191,7 +190,7 @@ class TestOpenAIFilesAPI:
 
     async def test_retrieve_file_not_found(self, files_provider):
         """Test retrieving a non-existent file."""
-        with pytest.raises(ResourceNotFoundError, match="not found"):
+        with pytest.raises(ValueError, match="File with id file-nonexistent not found"):
             await files_provider.openai_retrieve_file("file-nonexistent")
 
     async def test_retrieve_file_content_success(self, files_provider, sample_text_file):
@@ -209,7 +208,7 @@ class TestOpenAIFilesAPI:
 
     async def test_retrieve_file_content_not_found(self, files_provider):
         """Test retrieving content of a non-existent file."""
-        with pytest.raises(ResourceNotFoundError, match="not found"):
+        with pytest.raises(ValueError, match="File with id file-nonexistent not found"):
             await files_provider.openai_retrieve_file_content("file-nonexistent")
 
     async def test_delete_file_success(self, files_provider, sample_text_file):
@@ -230,12 +229,12 @@ class TestOpenAIFilesAPI:
         assert delete_response.deleted is True
 
         # Verify file no longer exists
-        with pytest.raises(ResourceNotFoundError, match="not found"):
+        with pytest.raises(ValueError, match=f"File with id {uploaded_file.id} not found"):
             await files_provider.openai_retrieve_file(uploaded_file.id)
 
     async def test_delete_file_not_found(self, files_provider):
         """Test deleting a non-existent file."""
-        with pytest.raises(ResourceNotFoundError, match="not found"):
+        with pytest.raises(ValueError, match="File with id file-nonexistent not found"):
             await files_provider.openai_delete_file("file-nonexistent")
 
     async def test_file_persistence_across_operations(self, files_provider, sample_text_file):

tests/unit/providers/agents/meta_reference/test_openai_responses.py

@@ -24,7 +24,6 @@ from llama_stack.apis.agents.openai_responses import (
     OpenAIResponseMessage,
     OpenAIResponseObjectWithInput,
     OpenAIResponseOutputMessageContentOutputText,
-    OpenAIResponseOutputMessageMCPCall,
     OpenAIResponseOutputMessageWebSearchToolCall,
     OpenAIResponseText,
     OpenAIResponseTextFormat,
@@ -462,53 +461,6 @@ async def test_prepend_previous_response_web_search(openai_responses_impl, mock_
     assert input[3].content == "fake_input"
 
 
-async def test_prepend_previous_response_mcp_tool_call(openai_responses_impl, mock_responses_store):
-    """Test prepending a previous response which included an mcp tool call to a new response."""
-    input_item_message = OpenAIResponseMessage(
-        id="123",
-        content=[OpenAIResponseInputMessageContentText(text="fake_previous_input")],
-        role="user",
-    )
-    output_tool_call = OpenAIResponseOutputMessageMCPCall(
-        id="ws_123",
-        name="fake-tool",
-        arguments="fake-arguments",
-        server_label="fake-label",
-    )
-    output_message = OpenAIResponseMessage(
-        id="123",
-        content=[OpenAIResponseOutputMessageContentOutputText(text="fake_tool_call_response")],
-        status="completed",
-        role="assistant",
-    )
-    response = OpenAIResponseObjectWithInput(
-        created_at=1,
-        id="resp_123",
-        model="fake_model",
-        output=[output_tool_call, output_message],
-        status="completed",
-        text=OpenAIResponseText(format=OpenAIResponseTextFormat(type="text")),
-        input=[input_item_message],
-    )
-    mock_responses_store.get_response_object.return_value = response
-
-    input_messages = [OpenAIResponseMessage(content="fake_input", role="user")]
-    input = await openai_responses_impl._prepend_previous_response(input_messages, "resp_123")
-
-    assert len(input) == 4
-    # Check for previous input
-    assert isinstance(input[0], OpenAIResponseMessage)
-    assert input[0].content[0].text == "fake_previous_input"
-    # Check for previous output MCP tool call
-    assert isinstance(input[1], OpenAIResponseOutputMessageMCPCall)
-    # Check for previous output web search response
-    assert isinstance(input[2], OpenAIResponseMessage)
-    assert input[2].content[0].text == "fake_tool_call_response"
-    # Check for new input
-    assert isinstance(input[3], OpenAIResponseMessage)
-    assert input[3].content == "fake_input"
-
-
 async def test_create_openai_response_with_instructions(openai_responses_impl, mock_inference_api):
     # Setup
     input_text = "What is the capital of Ireland?"

tests/unit/providers/inference/test_remote_vllm.py

@@ -6,7 +6,7 @@
 
 import asyncio
 import json
-import logging  # allow-direct-logging
+import logging
 import threading
 import time
 from http.server import BaseHTTPRequestHandler, HTTPServer

uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.12"
 resolution-markers = [
     "(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
@@ -523,7 +523,7 @@ wheels = [
 
 [[package]]
 name = "chromadb"
-version = "1.0.20"
+version = "1.0.16"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "bcrypt" },
@@ -554,13 +554,13 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uvicorn", extra = ["standard"] },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/e0/5d/430c4780738ed8385afb2031c619c71e4d354b435f1523fd628562d42377/chromadb-1.0.20.tar.gz", hash = "sha256:9ca88516f1eefa26e4c308ec9bdae9d209c0ba5fe1fae3f16b250e52246944db", size = 1244999, upload-time = "2025-08-18T17:03:31.195Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/15/2a/5b7e793d2a27c425e9f1813e9cb965b70e9bda08b69ee15a10e07dc3e59a/chromadb-1.0.16.tar.gz", hash = "sha256:3c864b5beb5e131bdc1f83c0b63a01ec481c6ee52028f088563ffba8478478e1", size = 1241545, upload-time = "2025-08-08T00:25:41.414Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/59/2f/d40a4aedd9298a012fb9f455a1e334fc875e12c9c667aab8a956a9dff559/chromadb-1.0.20-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:0955b9cbd0dfe23ecfd8d911254ff9e57750acbe9c5ff723e2975290092d9d29", size = 19069234, upload-time = "2025-08-18T17:03:28.714Z" },
+    { url = "https://files.pythonhosted.org/packages/a3/9d/bffcc814272c9b7982551803b2d45b77f39eeea1b9e965c00c05ee81c649/chromadb-1.0.16-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:144163ce7ca4f4448684d5d0c13ebb37c4d68490ecb60967a95d05cea30e0d2d", size = 18942157, upload-time = "2025-08-08T00:25:38.459Z" },
-    { url = "https://files.pythonhosted.org/packages/6a/2e/fcc80bb635719d3cf0705be89e2510bd191d5f544d1c5e9e4392ba95cff4/chromadb-1.0.20-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:52819408a48f0209a0ce4e6655eaaa683cce03f8081f297f88699f00bc8281aa", size = 18264273, upload-time = "2025-08-18T17:03:25.614Z" },
+    { url = "https://files.pythonhosted.org/packages/58/4e/de0086f3cbcfd667d75d112bb546386803ab5335599bf7099272a675e98b/chromadb-1.0.16-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:4ebcc5894e6fbb6b576452bbf4659746bfe58d9daf99a18363364e9497434bd2", size = 18147831, upload-time = "2025-08-08T00:25:35.546Z" },
-    { url = "https://files.pythonhosted.org/packages/4f/de/e93edfcebf863d652bb0c03c23ae5a4e9e448b6e01fdac8a8624aa7dd2a4/chromadb-1.0.20-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:68dbe15270e743077d47360695e0af918d17b225011e00d491afefbee017097f", size = 18835560, upload-time = "2025-08-18T17:03:18.783Z" },
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