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# What does this PR do? As shown in #3421, we can scale stack to handle more RPS with k8s replicas. This PR enables multi process stack with uvicorn --workers so that we can achieve the same scaling without being in k8s. To achieve that we refactor main to split out the app construction logic. This method needs to be non-async. We created a new `Stack` class to house impls and have a `start()` method to be called in lifespan to start background tasks instead of starting them in the old `construct_stack`. This way we avoid having to manage an event loop manually. ## Test Plan CI > uv run --with llama-stack python -m llama_stack.core.server.server benchmarking/k8s-benchmark/stack_run_config.yaml works. > LLAMA_STACK_CONFIG=benchmarking/k8s-benchmark/stack_run_config.yaml uv run uvicorn llama_stack.core.server.server:create_app --port 8321 --workers 4 works.
517 lines
18 KiB
Python
517 lines
18 KiB
Python
# 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 inspect
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import json
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import logging # allow-direct-logging
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import os
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import sys
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from enum import Enum
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from io import BytesIO
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from pathlib import Path
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from typing import Any, TypeVar, Union, get_args, get_origin
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import httpx
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import yaml
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from fastapi import Response as FastAPIResponse
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from llama_stack_client import (
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NOT_GIVEN,
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APIResponse,
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AsyncAPIResponse,
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AsyncLlamaStackClient,
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AsyncStream,
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LlamaStackClient,
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)
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from pydantic import BaseModel, TypeAdapter
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from rich.console import Console
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from termcolor import cprint
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from llama_stack.core.build import print_pip_install_help
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from llama_stack.core.configure import parse_and_maybe_upgrade_config
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from llama_stack.core.datatypes import Api, BuildConfig, BuildProvider, DistributionSpec
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from llama_stack.core.request_headers import (
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PROVIDER_DATA_VAR,
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request_provider_data_context,
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)
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from llama_stack.core.resolver import ProviderRegistry
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from llama_stack.core.server.routes import RouteImpls, find_matching_route, initialize_route_impls
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from llama_stack.core.stack import (
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Stack,
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get_stack_run_config_from_distro,
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replace_env_vars,
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)
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from llama_stack.core.utils.config import redact_sensitive_fields
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from llama_stack.core.utils.context import preserve_contexts_async_generator
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from llama_stack.core.utils.exec import in_notebook
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from llama_stack.log import get_logger
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from llama_stack.providers.utils.telemetry.tracing import (
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CURRENT_TRACE_CONTEXT,
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end_trace,
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setup_logger,
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start_trace,
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)
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logger = get_logger(name=__name__, category="core")
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T = TypeVar("T")
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def convert_pydantic_to_json_value(value: Any) -> Any:
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if isinstance(value, Enum):
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return value.value
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elif isinstance(value, list):
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return [convert_pydantic_to_json_value(item) for item in value]
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elif isinstance(value, dict):
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return {k: convert_pydantic_to_json_value(v) for k, v in value.items()}
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elif isinstance(value, BaseModel):
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return json.loads(value.model_dump_json())
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else:
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return value
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def convert_to_pydantic(annotation: Any, value: Any) -> Any:
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if isinstance(annotation, type) and annotation in {str, int, float, bool}:
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return value
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origin = get_origin(annotation)
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if origin is list:
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item_type = get_args(annotation)[0]
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try:
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return [convert_to_pydantic(item_type, item) for item in value]
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except Exception:
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logger.error(f"Error converting list {value} into {item_type}")
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return value
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elif origin is dict:
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key_type, val_type = get_args(annotation)
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try:
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return {k: convert_to_pydantic(val_type, v) for k, v in value.items()}
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except Exception:
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logger.error(f"Error converting dict {value} into {val_type}")
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return value
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try:
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# Handle Pydantic models and discriminated unions
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return TypeAdapter(annotation).validate_python(value)
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except Exception as e:
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# TODO: this is workardound for having Union[str, AgentToolGroup] in API schema.
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# We should get rid of any non-discriminated unions in the API schema.
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if origin is Union:
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for union_type in get_args(annotation):
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try:
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return convert_to_pydantic(union_type, value)
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except Exception:
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continue
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logger.warning(
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f"Warning: direct client failed to convert parameter {value} into {annotation}: {e}",
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)
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raise ValueError(f"Failed to convert parameter {value} into {annotation}: {e}") from e
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class LibraryClientUploadFile:
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"""LibraryClient UploadFile object that mimics FastAPI's UploadFile interface."""
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def __init__(self, filename: str, content: bytes):
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self.filename = filename
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self.content = content
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self.content_type = "application/octet-stream"
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async def read(self) -> bytes:
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return self.content
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class LibraryClientHttpxResponse:
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"""LibraryClient httpx Response object for FastAPI Response conversion."""
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def __init__(self, response):
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self.content = response.body if isinstance(response.body, bytes) else response.body.encode()
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self.status_code = response.status_code
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self.headers = response.headers
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class LlamaStackAsLibraryClient(LlamaStackClient):
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def __init__(
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self,
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config_path_or_distro_name: str,
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skip_logger_removal: bool = False,
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custom_provider_registry: ProviderRegistry | None = None,
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provider_data: dict[str, Any] | None = None,
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):
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super().__init__()
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self.async_client = AsyncLlamaStackAsLibraryClient(
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config_path_or_distro_name, custom_provider_registry, provider_data, skip_logger_removal
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)
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self.provider_data = provider_data
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self.loop = asyncio.new_event_loop()
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# use a new event loop to avoid interfering with the main event loop
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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try:
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loop.run_until_complete(self.async_client.initialize())
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finally:
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asyncio.set_event_loop(None)
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def initialize(self):
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"""
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Deprecated method for backward compatibility.
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"""
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pass
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def request(self, *args, **kwargs):
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loop = self.loop
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asyncio.set_event_loop(loop)
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if kwargs.get("stream"):
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def sync_generator():
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try:
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async_stream = loop.run_until_complete(self.async_client.request(*args, **kwargs))
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while True:
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chunk = loop.run_until_complete(async_stream.__anext__())
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yield chunk
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except StopAsyncIteration:
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pass
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finally:
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pending = asyncio.all_tasks(loop)
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if pending:
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loop.run_until_complete(asyncio.gather(*pending, return_exceptions=True))
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return sync_generator()
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else:
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try:
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result = loop.run_until_complete(self.async_client.request(*args, **kwargs))
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finally:
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pending = asyncio.all_tasks(loop)
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if pending:
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loop.run_until_complete(asyncio.gather(*pending, return_exceptions=True))
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return result
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class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
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def __init__(
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self,
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config_path_or_distro_name: str,
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custom_provider_registry: ProviderRegistry | None = None,
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provider_data: dict[str, Any] | None = None,
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skip_logger_removal: bool = False,
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):
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super().__init__()
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# when using the library client, we should not log to console since many
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# of our logs are intended for server-side usage
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current_sinks = os.environ.get("TELEMETRY_SINKS", "sqlite").split(",")
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os.environ["TELEMETRY_SINKS"] = ",".join(sink for sink in current_sinks if sink != "console")
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if in_notebook():
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import nest_asyncio
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nest_asyncio.apply()
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if not skip_logger_removal:
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self._remove_root_logger_handlers()
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if config_path_or_distro_name.endswith(".yaml"):
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config_path = Path(config_path_or_distro_name)
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if not config_path.exists():
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raise ValueError(f"Config file {config_path} does not exist")
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config_dict = replace_env_vars(yaml.safe_load(config_path.read_text()))
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config = parse_and_maybe_upgrade_config(config_dict)
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else:
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# distribution
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config = get_stack_run_config_from_distro(config_path_or_distro_name)
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self.config_path_or_distro_name = config_path_or_distro_name
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self.config = config
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self.custom_provider_registry = custom_provider_registry
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self.provider_data = provider_data
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self.route_impls: RouteImpls | None = None # Initialize to None to prevent AttributeError
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def _remove_root_logger_handlers(self):
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"""
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Remove all handlers from the root logger. Needed to avoid polluting the console with logs.
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"""
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root_logger = logging.getLogger()
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for handler in root_logger.handlers[:]:
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root_logger.removeHandler(handler)
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logger.info(f"Removed handler {handler.__class__.__name__} from root logger")
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async def initialize(self) -> bool:
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"""
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Initialize the async client.
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Returns:
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bool: True if initialization was successful
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"""
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try:
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self.route_impls = None
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stack = Stack(self.config, self.custom_provider_registry)
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await stack.initialize()
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self.impls = stack.impls
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except ModuleNotFoundError as _e:
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cprint(_e.msg, color="red", file=sys.stderr)
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cprint(
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"Using llama-stack as a library requires installing dependencies depending on the distribution (providers) you choose.\n",
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color="yellow",
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file=sys.stderr,
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)
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if self.config_path_or_distro_name.endswith(".yaml"):
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providers: dict[str, list[BuildProvider]] = {}
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for api, run_providers in self.config.providers.items():
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for provider in run_providers:
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providers.setdefault(api, []).append(
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BuildProvider(provider_type=provider.provider_type, module=provider.module)
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)
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providers = dict(providers)
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build_config = BuildConfig(
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distribution_spec=DistributionSpec(
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providers=providers,
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),
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external_providers_dir=self.config.external_providers_dir,
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)
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print_pip_install_help(build_config)
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else:
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prefix = "!" if in_notebook() else ""
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cprint(
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f"Please run:\n\n{prefix}llama stack build --distro {self.config_path_or_distro_name} --image-type venv\n\n",
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"yellow",
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file=sys.stderr,
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)
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cprint(
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"Please check your internet connection and try again.",
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"red",
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file=sys.stderr,
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)
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raise _e
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assert self.impls is not None
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if Api.telemetry in self.impls:
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setup_logger(self.impls[Api.telemetry])
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if not os.environ.get("PYTEST_CURRENT_TEST"):
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console = Console()
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console.print(f"Using config [blue]{self.config_path_or_distro_name}[/blue]:")
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safe_config = redact_sensitive_fields(self.config.model_dump())
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console.print(yaml.dump(safe_config, indent=2))
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self.route_impls = initialize_route_impls(self.impls)
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return True
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async def request(
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self,
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cast_to: Any,
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options: Any,
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*,
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stream=False,
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stream_cls=None,
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):
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if self.route_impls is None:
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raise ValueError("Client not initialized. Please call initialize() first.")
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# Create headers with provider data if available
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headers = options.headers or {}
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if self.provider_data:
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keys = ["X-LlamaStack-Provider-Data", "x-llamastack-provider-data"]
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if all(key not in headers for key in keys):
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headers["X-LlamaStack-Provider-Data"] = json.dumps(self.provider_data)
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# Use context manager for provider data
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with request_provider_data_context(headers):
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if stream:
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response = await self._call_streaming(
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cast_to=cast_to,
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options=options,
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stream_cls=stream_cls,
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)
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else:
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response = await self._call_non_streaming(
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cast_to=cast_to,
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options=options,
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)
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return response
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def _handle_file_uploads(self, options: Any, body: dict) -> tuple[dict, list[str]]:
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"""Handle file uploads from OpenAI client and add them to the request body."""
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if not (hasattr(options, "files") and options.files):
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return body, []
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if not isinstance(options.files, list):
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return body, []
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field_names = []
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for file_tuple in options.files:
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if not (isinstance(file_tuple, tuple) and len(file_tuple) >= 2):
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continue
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field_name = file_tuple[0]
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file_object = file_tuple[1]
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if isinstance(file_object, BytesIO):
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file_object.seek(0)
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file_content = file_object.read()
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filename = getattr(file_object, "name", "uploaded_file")
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field_names.append(field_name)
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body[field_name] = LibraryClientUploadFile(filename, file_content)
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return body, field_names
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async def _call_non_streaming(
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self,
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*,
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cast_to: Any,
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options: Any,
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):
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assert self.route_impls is not None # Should be guaranteed by request() method, assertion for mypy
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path = options.url
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body = options.params or {}
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body |= options.json_data or {}
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matched_func, path_params, route_path, webmethod = find_matching_route(options.method, path, self.route_impls)
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body |= path_params
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body, field_names = self._handle_file_uploads(options, body)
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body = self._convert_body(path, options.method, body, exclude_params=set(field_names))
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trace_path = webmethod.descriptive_name or route_path
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await start_trace(trace_path, {"__location__": "library_client"})
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try:
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result = await matched_func(**body)
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finally:
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await end_trace()
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# Handle FastAPI Response objects (e.g., from file content retrieval)
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if isinstance(result, FastAPIResponse):
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return LibraryClientHttpxResponse(result)
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json_content = json.dumps(convert_pydantic_to_json_value(result))
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filtered_body = {k: v for k, v in body.items() if not isinstance(v, LibraryClientUploadFile)}
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status_code = httpx.codes.OK
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if options.method.upper() == "DELETE" and result is None:
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status_code = httpx.codes.NO_CONTENT
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if status_code == httpx.codes.NO_CONTENT:
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json_content = ""
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mock_response = httpx.Response(
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status_code=status_code,
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content=json_content.encode("utf-8"),
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headers={
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"Content-Type": "application/json",
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},
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request=httpx.Request(
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method=options.method,
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url=options.url,
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params=options.params,
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headers=options.headers or {},
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json=convert_pydantic_to_json_value(filtered_body),
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),
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)
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response = APIResponse(
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raw=mock_response,
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client=self,
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cast_to=cast_to,
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options=options,
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stream=False,
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stream_cls=None,
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)
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return response.parse()
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async def _call_streaming(
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self,
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*,
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cast_to: Any,
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options: Any,
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stream_cls: Any,
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):
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assert self.route_impls is not None # Should be guaranteed by request() method, assertion for mypy
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path = options.url
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body = options.params or {}
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body |= options.json_data or {}
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func, path_params, route_path, webmethod = find_matching_route(options.method, path, self.route_impls)
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body |= path_params
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body = self._convert_body(path, options.method, body)
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trace_path = webmethod.descriptive_name or route_path
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await start_trace(trace_path, {"__location__": "library_client"})
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async def gen():
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try:
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async for chunk in await func(**body):
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data = json.dumps(convert_pydantic_to_json_value(chunk))
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sse_event = f"data: {data}\n\n"
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yield sse_event.encode("utf-8")
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finally:
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await end_trace()
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wrapped_gen = preserve_contexts_async_generator(gen(), [CURRENT_TRACE_CONTEXT, PROVIDER_DATA_VAR])
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mock_response = httpx.Response(
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status_code=httpx.codes.OK,
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content=wrapped_gen,
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headers={
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"Content-Type": "application/json",
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},
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request=httpx.Request(
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method=options.method,
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url=options.url,
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params=options.params,
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headers=options.headers or {},
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json=convert_pydantic_to_json_value(body),
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),
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)
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# we use asynchronous impl always internally and channel all requests to AsyncLlamaStackClient
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# however, the top-level caller may be a SyncAPIClient -- so its stream_cls might be a Stream (SyncStream)
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# so we need to convert it to AsyncStream
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# mypy can't track runtime variables inside the [...] of a generic, so ignore that check
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args = get_args(stream_cls)
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|
stream_cls = AsyncStream[args[0]] # type: ignore[valid-type]
|
|
response = AsyncAPIResponse(
|
|
raw=mock_response,
|
|
client=self,
|
|
cast_to=cast_to,
|
|
options=options,
|
|
stream=True,
|
|
stream_cls=stream_cls,
|
|
)
|
|
return await response.parse()
|
|
|
|
def _convert_body(
|
|
self, path: str, method: str, body: dict | None = None, exclude_params: set[str] | None = None
|
|
) -> dict:
|
|
if not body:
|
|
return {}
|
|
|
|
assert self.route_impls is not None # Should be guaranteed by request() method, assertion for mypy
|
|
exclude_params = exclude_params or set()
|
|
|
|
func, _, _, _ = find_matching_route(method, path, self.route_impls)
|
|
sig = inspect.signature(func)
|
|
|
|
# Strip NOT_GIVENs to use the defaults in signature
|
|
body = {k: v for k, v in body.items() if v is not NOT_GIVEN}
|
|
|
|
# Convert parameters to Pydantic models where needed
|
|
converted_body = {}
|
|
for param_name, param in sig.parameters.items():
|
|
if param_name in body:
|
|
value = body.get(param_name)
|
|
if param_name in exclude_params:
|
|
converted_body[param_name] = value
|
|
else:
|
|
converted_body[param_name] = convert_to_pydantic(param.annotation, value)
|
|
|
|
return converted_body
|