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remove legacy tracing

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This commit is contained in:
Emilio Garcia 2025-10-07 14:32:32 -04:00
parent 5f827fd4ed
commit 0c843ec87f
16 changed files with 15 additions and 211 deletions
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2
llama_stack/apis/conversations/conversations.py
View file

@ -20,7 +20,6 @@ from llama_stack.apis.agents.openai_responses import (
OpenAIResponseOutputMessageWebSearchToolCall,
)
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
Metadata = dict[str, str]
@ -163,7 +162,6 @@ class ConversationItemDeletedResource(BaseModel):
@runtime_checkable
@trace_protocol
class Conversations(Protocol):
"""Protocol for conversation management operations."""

2
llama_stack/apis/files/files.py
View file

@ -12,7 +12,6 @@ from pydantic import BaseModel, Field
from llama_stack.apis.common.responses import Order
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, webmethod
@ -102,7 +101,6 @@ class OpenAIFileDeleteResponse(BaseModel):
@runtime_checkable
@trace_protocol
class Files(Protocol):
"""Files

2
llama_stack/apis/inference/inference.py
View file

@ -29,7 +29,6 @@ from llama_stack.models.llama.datatypes import (
ToolDefinition,
ToolPromptFormat,
)
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
register_schema(ToolCall)
@ -996,7 +995,6 @@ class ListOpenAIChatCompletionResponse(BaseModel):
@runtime_checkable
@trace_protocol
class InferenceProvider(Protocol):
"""
This protocol defines the interface that should be implemented by all inference providers.

2
llama_stack/apis/models/models.py
View file

@ -11,7 +11,6 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator
from llama_stack.apis.resource import Resource, ResourceType
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, webmethod
@ -101,7 +100,6 @@ class OpenAIListModelsResponse(BaseModel):
@runtime_checkable
@trace_protocol
class Models(Protocol):
@webmethod(route="/models", method="GET", level=LLAMA_STACK_API_V1)
async def list_models(self) -> ListModelsResponse:

3
llama_stack/apis/prompts/prompts.py
View file

@ -11,7 +11,7 @@ from typing import Protocol, runtime_checkable
from pydantic import BaseModel, Field, field_validator, model_validator
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, webmethod
@ -92,7 +92,6 @@ class ListPromptsResponse(BaseModel):
@runtime_checkable
@trace_protocol
class Prompts(Protocol):
"""Prompts

3
llama_stack/apis/safety/safety.py
View file

@ -12,7 +12,7 @@ from pydantic import BaseModel, Field
from llama_stack.apis.inference import Message
from llama_stack.apis.shields import Shield
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, webmethod
@ -94,7 +94,6 @@ class ShieldStore(Protocol):
@runtime_checkable
@trace_protocol
class Safety(Protocol):
"""Safety

3
llama_stack/apis/shields/shields.py
View file

@ -10,7 +10,7 @@ from pydantic import BaseModel
from llama_stack.apis.resource import Resource, ResourceType
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, webmethod
@ -48,7 +48,6 @@ class ListShieldsResponse(BaseModel):
@runtime_checkable
@trace_protocol
class Shields(Protocol):
@webmethod(route="/shields", method="GET", level=LLAMA_STACK_API_V1)
async def list_shields(self) -> ListShieldsResponse:

3
llama_stack/apis/tools/rag_tool.py
View file

@ -12,7 +12,7 @@ from typing_extensions import runtime_checkable
from llama_stack.apis.common.content_types import URL, InterleavedContent
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
@ -184,7 +184,6 @@ class RAGQueryConfig(BaseModel):
@runtime_checkable
@trace_protocol
class RAGToolRuntime(Protocol):
@webmethod(route="/tool-runtime/rag-tool/insert", method="POST", level=LLAMA_STACK_API_V1)
async def insert(

4
llama_stack/apis/tools/tools.py
View file

@ -13,7 +13,7 @@ from typing_extensions import runtime_checkable
from llama_stack.apis.common.content_types import URL, InterleavedContent
from llama_stack.apis.resource import Resource, ResourceType
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, webmethod
from .rag_tool import RAGToolRuntime
@ -109,7 +109,6 @@ class ListToolDefsResponse(BaseModel):
@runtime_checkable
@trace_protocol
class ToolGroups(Protocol):
@webmethod(route="/toolgroups", method="POST", level=LLAMA_STACK_API_V1)
async def register_tool_group(
@ -191,7 +190,6 @@ class SpecialToolGroup(Enum):
@runtime_checkable
@trace_protocol
class ToolRuntime(Protocol):
tool_store: ToolStore | None = None

3
llama_stack/apis/vector_dbs/vector_dbs.py
View file

@ -10,7 +10,7 @@ from pydantic import BaseModel
from llama_stack.apis.resource import Resource, ResourceType
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.schema_utils import json_schema_type, webmethod
@ -64,7 +64,6 @@ class ListVectorDBsResponse(BaseModel):
@runtime_checkable
@trace_protocol
class VectorDBs(Protocol):
@webmethod(route="/vector-dbs", method="GET", level=LLAMA_STACK_API_V1)
async def list_vector_dbs(self) -> ListVectorDBsResponse:

3
llama_stack/apis/vector_io/vector_io.py
View file

@ -16,7 +16,7 @@ from pydantic import BaseModel, Field
from llama_stack.apis.inference import InterleavedContent
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.apis.version import LLAMA_STACK_API_V1
from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
from llama_stack.providers.utils.vector_io.vector_utils import generate_chunk_id
from llama_stack.schema_utils import json_schema_type, webmethod
from llama_stack.strong_typing.schema import register_schema
@ -471,7 +471,6 @@ class VectorDBStore(Protocol):
@runtime_checkable
@trace_protocol
class VectorIO(Protocol):
vector_db_store: VectorDBStore | None = None

35
llama_stack/core/library_client.py
View file

@ -48,12 +48,7 @@ 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,
setup_logger,
start_trace,
)
logger = get_logger(name=__name__, category="core")
@ -206,8 +201,6 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
super().__init__()
# when using the library client, we should not log to console since many
# of our logs are intended for server-side usage
current_sinks = os.environ.get("TELEMETRY_SINKS", "sqlite").split(",")
os.environ["TELEMETRY_SINKS"] = ",".join(sink for sink in current_sinks if sink != "console")
if in_notebook():
import nest_asyncio
@ -293,8 +286,6 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
raise _e
assert self.impls is not None
if Api.telemetry in self.impls:
setup_logger(self.impls[Api.telemetry])
if not os.environ.get("PYTEST_CURRENT_TEST"):
console = Console()
@ -384,13 +375,7 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
body, field_names = self._handle_file_uploads(options, body)
body = self._convert_body(path, options.method, body, exclude_params=set(field_names))
trace_path = webmethod.descriptive_name or route_path
await start_trace(trace_path, {"__location__": "library_client"})
try:
result = await matched_func(**body)
finally:
await end_trace()
result = await matched_func(**body)
# Handle FastAPI Response objects (e.g., from file content retrieval)
if isinstance(result, FastAPIResponse):
@ -448,19 +433,13 @@ class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
body = self._convert_body(path, options.method, body)
trace_path = webmethod.descriptive_name or route_path
await start_trace(trace_path, {"__location__": "library_client"})
async def gen():
try:
async for chunk in await func(**body):
data = json.dumps(convert_pydantic_to_json_value(chunk))
sse_event = f"data: {data}\n\n"
yield sse_event.encode("utf-8")
finally:
await end_trace()
async for chunk in await func(**body):
data = json.dumps(convert_pydantic_to_json_value(chunk))
sse_event = f"data: {data}\n\n"
yield sse_event.encode("utf-8")
wrapped_gen = preserve_contexts_async_generator(gen(), [CURRENT_TRACE_CONTEXT, PROVIDER_DATA_VAR])
wrapped_gen = preserve_contexts_async_generator(gen(), [PROVIDER_DATA_VAR])
mock_response = httpx.Response(
status_code=httpx.codes.OK,

17
llama_stack/core/server/server.py
View file

@ -58,14 +58,6 @@ from llama_stack.core.utils.config_resolution import Mode, resolve_config_or_dis
from llama_stack.core.utils.context import preserve_contexts_async_generator
from llama_stack.log import get_logger
from llama_stack.providers.datatypes import Api
from llama_stack.providers.inline.telemetry.meta_reference.config import TelemetryConfig
from llama_stack.providers.inline.telemetry.meta_reference.telemetry import (
TelemetryAdapter,
)
from llama_stack.providers.utils.telemetry.tracing import (
CURRENT_TRACE_CONTEXT,
setup_logger,
)
from .auth import AuthenticationMiddleware
from .quota import QuotaMiddleware
@ -237,9 +229,7 @@ def create_dynamic_typed_route(func: Any, method: str, route: str) -> Callable:
try:
if is_streaming:
gen = preserve_contexts_async_generator(
sse_generator(func(**kwargs)), [CURRENT_TRACE_CONTEXT, PROVIDER_DATA_VAR]
)
gen = preserve_contexts_async_generator(sse_generator(func(**kwargs)), [PROVIDER_DATA_VAR])
return StreamingResponse(gen, media_type="text/event-stream")
else:
value = func(**kwargs)
@ -408,11 +398,6 @@ def create_app() -> StackApp:
if cors_config:
app.add_middleware(CORSMiddleware, **cors_config.model_dump())
if Api.telemetry in impls:
setup_logger(impls[Api.telemetry])
else:
setup_logger(TelemetryAdapter(TelemetryConfig(), {}))
# Load external APIs if configured
external_apis = load_external_apis(config)
all_routes = get_all_api_routes(external_apis)

142
llama_stack/providers/utils/telemetry/trace_protocol.py
View file

@ -1,142 +0,0 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import asyncio
import inspect
import json
from collections.abc import AsyncGenerator, Callable
from functools import wraps
from typing import Any
from pydantic import BaseModel
from llama_stack.models.llama.datatypes import Primitive
def serialize_value(value: Any) -> Primitive:
return str(_prepare_for_json(value))
def _prepare_for_json(value: Any) -> str:
"""Serialize a single value into JSON-compatible format."""
if value is None:
return ""
elif isinstance(value, str | int | float | bool):
return value
elif hasattr(value, "_name_"):
return value._name_
elif isinstance(value, BaseModel):
return json.loads(value.model_dump_json())
elif isinstance(value, list | tuple | set):
return [_prepare_for_json(item) for item in value]
elif isinstance(value, dict):
return {str(k): _prepare_for_json(v) for k, v in value.items()}
else:
try:
json.dumps(value)
return value
except Exception:
return str(value)
def trace_protocol[T](cls: type[T]) -> type[T]:
"""
A class decorator that automatically traces all methods in a protocol/base class
and its inheriting classes.
"""
def trace_method(method: Callable) -> Callable:
is_async = asyncio.iscoroutinefunction(method)
is_async_gen = inspect.isasyncgenfunction(method)
def create_span_context(self: Any, *args: Any, **kwargs: Any) -> tuple:
class_name = self.__class__.__name__
method_name = method.__name__
span_type = "async_generator" if is_async_gen else "async" if is_async else "sync"
sig = inspect.signature(method)
param_names = list(sig.parameters.keys())[1:] # Skip 'self'
combined_args = {}
for i, arg in enumerate(args):
param_name = param_names[i] if i < len(param_names) else f"position_{i + 1}"
combined_args[param_name] = serialize_value(arg)
for k, v in kwargs.items():
combined_args[str(k)] = serialize_value(v)
span_attributes = {
"__autotraced__": True,
"__class__": class_name,
"__method__": method_name,
"__type__": span_type,
"__args__": str(combined_args),
}
return class_name, method_name, span_attributes
@wraps(method)
async def async_gen_wrapper(self: Any, *args: Any, **kwargs: Any) -> AsyncGenerator:
from llama_stack.providers.utils.telemetry import tracing
class_name, method_name, span_attributes = create_span_context(self, *args, **kwargs)
with tracing.span(f"{class_name}.{method_name}", span_attributes) as span:
try:
count = 0
async for item in method(self, *args, **kwargs):
yield item
count += 1
finally:
span.set_attribute("chunk_count", count)
@wraps(method)
async def async_wrapper(self: Any, *args: Any, **kwargs: Any) -> Any:
from llama_stack.providers.utils.telemetry import tracing
class_name, method_name, span_attributes = create_span_context(self, *args, **kwargs)
with tracing.span(f"{class_name}.{method_name}", span_attributes) as span:
try:
result = await method(self, *args, **kwargs)
span.set_attribute("output", serialize_value(result))
return result
except Exception as e:
span.set_attribute("error", str(e))
raise
@wraps(method)
def sync_wrapper(self: Any, *args: Any, **kwargs: Any) -> Any:
from llama_stack.providers.utils.telemetry import tracing
class_name, method_name, span_attributes = create_span_context(self, *args, **kwargs)
with tracing.span(f"{class_name}.{method_name}", span_attributes) as span:
try:
result = method(self, *args, **kwargs)
span.set_attribute("output", serialize_value(result))
return result
except Exception as e:
span.set_attribute("error", str(e))
raise
if is_async_gen:
return async_gen_wrapper
elif is_async:
return async_wrapper
else:
return sync_wrapper
original_init_subclass = getattr(cls, "__init_subclass__", None)
def __init_subclass__(cls_child, **kwargs): # noqa: N807
if original_init_subclass:
original_init_subclass(**kwargs)
for name, method in vars(cls_child).items():
if inspect.isfunction(method) and not name.startswith("_"):
setattr(cls_child, name, trace_method(method)) # noqa: B010
cls.__init_subclass__ = classmethod(__init_subclass__)
return cls

1
llama_stack/providers/utils/telemetry/tracing.py
View file

@ -29,7 +29,6 @@ from llama_stack.apis.telemetry import (
UnstructuredLogEvent,
)
from llama_stack.log import get_logger
from llama_stack.providers.utils.telemetry.trace_protocol import serialize_value
logger = get_logger(__name__, category="core")

1
tests/unit/providers/vector_io/test_qdrant.py
View file

@ -122,7 +122,6 @@ def _prepare_for_json(value: Any) -> str:
return str(value)
@patch("llama_stack.providers.utils.telemetry.trace_protocol._prepare_for_json", new=_prepare_for_json)
async def test_qdrant_register_and_unregister_vector_db(
qdrant_adapter: QdrantVectorIOAdapter,
mock_vector_db,