mirror of
https://github.com/meta-llama/llama-stack.git
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API Updates (#73)
* API Keys passed from Client instead of distro configuration * delete distribution registry * Rename the "package" word away * Introduce a "Router" layer for providers Some providers need to be factorized and considered as thin routing layers on top of other providers. Consider two examples: - The inference API should be a routing layer over inference providers, routed using the "model" key - The memory banks API is another instance where various memory bank types will be provided by independent providers (e.g., a vector store is served by Chroma while a keyvalue memory can be served by Redis or PGVector) This commit introduces a generalized routing layer for this purpose. * update `apis_to_serve` * llama_toolchain -> llama_stack * Codemod from llama_toolchain -> llama_stack - added providers/registry - cleaned up api/ subdirectories and moved impls away - restructured api/api.py - from llama_stack.apis.<api> import foo should work now - update imports to do llama_stack.apis.<api> - update many other imports - added __init__, fixed some registry imports - updated registry imports - create_agentic_system -> create_agent - AgenticSystem -> Agent * Moved some stuff out of common/; re-generated OpenAPI spec * llama-toolchain -> llama-stack (hyphens) * add control plane API * add redis adapter + sqlite provider * move core -> distribution * Some more toolchain -> stack changes * small naming shenanigans * Removing custom tool and agent utilities and moving them client side * Move control plane to distribution server for now * Remove control plane from API list * no codeshield dependency randomly plzzzzz * Add "fire" as a dependency * add back event loggers * stack configure fixes * use brave instead of bing in the example client * add init file so it gets packaged * add init files so it gets packaged * Update MANIFEST * bug fix --------- Co-authored-by: Hardik Shah <hjshah@fb.com> Co-authored-by: Xi Yan <xiyan@meta.com> Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
This commit is contained in:
Ashwin Bharambe
GitHub
parent
f294eac5f5
commit
9487ad8294
213 changed files with 1725 additions and 1204 deletions
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import asyncio
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import base64
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import logging
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import queue
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import threading
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import uuid
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from datetime import datetime
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from functools import wraps
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from typing import Any, Dict, List
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from llama_toolchain.telemetry.api import * # noqa: F403
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def generate_short_uuid(len: int = 12):
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full_uuid = uuid.uuid4()
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uuid_bytes = full_uuid.bytes
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encoded = base64.urlsafe_b64encode(uuid_bytes)
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return encoded.rstrip(b"=").decode("ascii")[:len]
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CURRENT_TRACE_CONTEXT = None
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BACKGROUND_LOGGER = None
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class BackgroundLogger:
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def __init__(self, api: Telemetry, capacity: int = 1000):
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self.api = api
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self.log_queue = queue.Queue(maxsize=capacity)
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self.worker_thread = threading.Thread(target=self._process_logs, daemon=True)
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self.worker_thread.start()
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def log_event(self, event):
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try:
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self.log_queue.put_nowait(event)
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except queue.Full:
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print("Log queue is full, dropping event")
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def _process_logs(self):
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while True:
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try:
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event = self.log_queue.get()
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# figure out how to use a thread's native loop
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asyncio.run(self.api.log_event(event))
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except Exception:
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import traceback
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traceback.print_exc()
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print("Error processing log event")
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finally:
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self.log_queue.task_done()
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def __del__(self):
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self.log_queue.join()
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class TraceContext:
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spans: List[Span] = []
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def __init__(self, logger: BackgroundLogger, trace_id: str):
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self.logger = logger
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self.trace_id = trace_id
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def push_span(self, name: str, attributes: Dict[str, Any] = None):
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current_span = self.get_current_span()
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span = Span(
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span_id=generate_short_uuid(),
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trace_id=self.trace_id,
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name=name,
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start_time=datetime.now(),
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parent_span_id=current_span.span_id if current_span else None,
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attributes=attributes,
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)
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self.logger.log_event(
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StructuredLogEvent(
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trace_id=span.trace_id,
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span_id=span.span_id,
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timestamp=span.start_time,
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attributes=span.attributes,
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payload=SpanStartPayload(
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name=span.name,
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parent_span_id=span.parent_span_id,
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),
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)
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)
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self.spans.append(span)
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def pop_span(self, status: SpanStatus = SpanStatus.OK):
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span = self.spans.pop()
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if span is not None:
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self.logger.log_event(
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StructuredLogEvent(
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trace_id=span.trace_id,
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span_id=span.span_id,
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timestamp=span.start_time,
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attributes=span.attributes,
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payload=SpanEndPayload(
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status=status,
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),
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)
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)
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def get_current_span(self):
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return self.spans[-1] if self.spans else None
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def setup_logger(api: Telemetry, level: int = logging.INFO):
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global BACKGROUND_LOGGER
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BACKGROUND_LOGGER = BackgroundLogger(api)
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logger = logging.getLogger()
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logger.setLevel(level)
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logger.addHandler(TelemetryHandler())
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async def start_trace(name: str, attributes: Dict[str, Any] = None):
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global CURRENT_TRACE_CONTEXT, BACKGROUND_LOGGER
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if BACKGROUND_LOGGER is None:
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print("No Telemetry implementation set. Skipping trace initialization...")
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return
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trace_id = generate_short_uuid()
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context = TraceContext(BACKGROUND_LOGGER, trace_id)
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context.push_span(name, {"__root__": True, **(attributes or {})})
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CURRENT_TRACE_CONTEXT = context
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async def end_trace(status: SpanStatus = SpanStatus.OK):
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global CURRENT_TRACE_CONTEXT
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context = CURRENT_TRACE_CONTEXT
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if context is None:
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return
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context.pop_span(status)
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CURRENT_TRACE_CONTEXT = None
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def severity(levelname: str) -> LogSeverity:
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if levelname == "DEBUG":
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return LogSeverity.DEBUG
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elif levelname == "INFO":
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return LogSeverity.INFO
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elif levelname == "WARNING":
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return LogSeverity.WARNING
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elif levelname == "ERROR":
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return LogSeverity.ERROR
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elif levelname == "CRITICAL":
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return LogSeverity.CRITICAL
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else:
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raise ValueError(f"Unknown log level: {levelname}")
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# TODO: ideally, the actual emitting should be done inside a separate daemon
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# process completely isolated from the server
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class TelemetryHandler(logging.Handler):
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def emit(self, record: logging.LogRecord):
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# horrendous hack to avoid logging from asyncio and getting into an infinite loop
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if record.module in ("asyncio", "selector_events"):
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return
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global CURRENT_TRACE_CONTEXT, BACKGROUND_LOGGER
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if BACKGROUND_LOGGER is None:
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raise RuntimeError("Telemetry API not initialized")
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context = CURRENT_TRACE_CONTEXT
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if context is None:
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return
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span = context.get_current_span()
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if span is None:
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return
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BACKGROUND_LOGGER.log_event(
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UnstructuredLogEvent(
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trace_id=span.trace_id,
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span_id=span.span_id,
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timestamp=datetime.now(),
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message=self.format(record),
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severity=severity(record.levelname),
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)
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)
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def close(self):
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pass
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def span(name: str, attributes: Dict[str, Any] = None):
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def decorator(func):
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@wraps(func)
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def sync_wrapper(*args, **kwargs):
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try:
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global CURRENT_TRACE_CONTEXT
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context = CURRENT_TRACE_CONTEXT
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if context:
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context.push_span(name, attributes)
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result = func(*args, **kwargs)
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finally:
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context.pop_span()
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return result
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@wraps(func)
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async def async_wrapper(*args, **kwargs):
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try:
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global CURRENT_TRACE_CONTEXT
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context = CURRENT_TRACE_CONTEXT
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if context:
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context.push_span(name, attributes)
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result = await func(*args, **kwargs)
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finally:
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context.pop_span()
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return result
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@wraps(func)
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def wrapper(*args, **kwargs):
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if asyncio.iscoroutinefunction(func):
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return async_wrapper(*args, **kwargs)
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else:
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return sync_wrapper(*args, **kwargs)
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return wrapper
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return decorator
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