llama-stack/llama_stack/distribution/library_client.py
raghotham 5a422e236c
chore: make cprint write to stderr (#2250)
Also do sys.exit(1) in case of errors
2025-05-24 23:39:57 -07:00

413 lines
15 KiB
Python

# 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
import logging
import os
import sys
from concurrent.futures import ThreadPoolExecutor
from enum import Enum
from pathlib import Path
from typing import Any, TypeVar, Union, get_args, get_origin
import httpx
import yaml
from llama_stack_client import (
NOT_GIVEN,
APIResponse,
AsyncAPIResponse,
AsyncLlamaStackClient,
AsyncStream,
LlamaStackClient,
)
from pydantic import BaseModel, TypeAdapter
from rich.console import Console
from termcolor import cprint
from llama_stack.distribution.build import print_pip_install_help
from llama_stack.distribution.configure import parse_and_maybe_upgrade_config
from llama_stack.distribution.datatypes import Api, BuildConfig, DistributionSpec
from llama_stack.distribution.request_headers import (
PROVIDER_DATA_VAR,
request_provider_data_context,
)
from llama_stack.distribution.resolver import ProviderRegistry
from llama_stack.distribution.server.endpoints import (
find_matching_endpoint,
initialize_endpoint_impls,
)
from llama_stack.distribution.stack import (
construct_stack,
get_stack_run_config_from_template,
replace_env_vars,
)
from llama_stack.distribution.utils.config import redact_sensitive_fields
from llama_stack.distribution.utils.context import preserve_contexts_async_generator
from llama_stack.distribution.utils.exec import in_notebook
from llama_stack.providers.utils.telemetry.tracing import (
CURRENT_TRACE_CONTEXT,
end_trace,
setup_logger,
start_trace,
)
logger = logging.getLogger(__name__)
T = TypeVar("T")
def convert_pydantic_to_json_value(value: Any) -> Any:
if isinstance(value, Enum):
return value.value
elif isinstance(value, list):
return [convert_pydantic_to_json_value(item) for item in value]
elif isinstance(value, dict):
return {k: convert_pydantic_to_json_value(v) for k, v in value.items()}
elif isinstance(value, BaseModel):
return json.loads(value.model_dump_json())
else:
return value
def convert_to_pydantic(annotation: Any, value: Any) -> Any:
if isinstance(annotation, type) and annotation in {str, int, float, bool}:
return value
origin = get_origin(annotation)
if origin is list:
item_type = get_args(annotation)[0]
try:
return [convert_to_pydantic(item_type, item) for item in value]
except Exception:
logger.error(f"Error converting list {value} into {item_type}")
return value
elif origin is dict:
key_type, val_type = get_args(annotation)
try:
return {k: convert_to_pydantic(val_type, v) for k, v in value.items()}
except Exception:
logger.error(f"Error converting dict {value} into {val_type}")
return value
try:
# Handle Pydantic models and discriminated unions
return TypeAdapter(annotation).validate_python(value)
except Exception as e:
# TODO: this is workardound for having Union[str, AgentToolGroup] in API schema.
# We should get rid of any non-discriminated unions in the API schema.
if origin is Union:
for union_type in get_args(annotation):
try:
return convert_to_pydantic(union_type, value)
except Exception:
continue
logger.warning(
f"Warning: direct client failed to convert parameter {value} into {annotation}: {e}",
)
raise ValueError(f"Failed to convert parameter {value} into {annotation}: {e}") from e
class LlamaStackAsLibraryClient(LlamaStackClient):
def __init__(
self,
config_path_or_template_name: str,
skip_logger_removal: bool = False,
custom_provider_registry: ProviderRegistry | None = None,
provider_data: dict[str, Any] | None = None,
):
super().__init__()
self.async_client = AsyncLlamaStackAsLibraryClient(
config_path_or_template_name, custom_provider_registry, provider_data
)
self.pool_executor = ThreadPoolExecutor(max_workers=4)
self.skip_logger_removal = skip_logger_removal
self.provider_data = provider_data
def initialize(self):
if in_notebook():
import nest_asyncio
nest_asyncio.apply()
if not self.skip_logger_removal:
self._remove_root_logger_handlers()
return asyncio.run(self.async_client.initialize())
def _remove_root_logger_handlers(self):
"""
Remove all handlers from the root logger. Needed to avoid polluting the console with logs.
"""
root_logger = logging.getLogger()
for handler in root_logger.handlers[:]:
root_logger.removeHandler(handler)
logger.info(f"Removed handler {handler.__class__.__name__} from root logger")
def request(self, *args, **kwargs):
if kwargs.get("stream"):
# NOTE: We are using AsyncLlamaStackClient under the hood
# A new event loop is needed to convert the AsyncStream
# from async client into SyncStream return type for streaming
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
def sync_generator():
try:
async_stream = loop.run_until_complete(self.async_client.request(*args, **kwargs))
while True:
chunk = loop.run_until_complete(async_stream.__anext__())
yield chunk
except StopAsyncIteration:
pass
finally:
pending = asyncio.all_tasks(loop)
if pending:
loop.run_until_complete(asyncio.gather(*pending, return_exceptions=True))
loop.close()
return sync_generator()
else:
return asyncio.run(self.async_client.request(*args, **kwargs))
class AsyncLlamaStackAsLibraryClient(AsyncLlamaStackClient):
def __init__(
self,
config_path_or_template_name: str,
custom_provider_registry: ProviderRegistry | None = None,
provider_data: dict[str, Any] | None = None,
):
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 config_path_or_template_name.endswith(".yaml"):
config_path = Path(config_path_or_template_name)
if not config_path.exists():
raise ValueError(f"Config file {config_path} does not exist")
config_dict = replace_env_vars(yaml.safe_load(config_path.read_text()))
config = parse_and_maybe_upgrade_config(config_dict)
else:
# template
config = get_stack_run_config_from_template(config_path_or_template_name)
self.config_path_or_template_name = config_path_or_template_name
self.config = config
self.custom_provider_registry = custom_provider_registry
self.provider_data = provider_data
async def initialize(self) -> bool:
try:
self.endpoint_impls = None
self.impls = await construct_stack(self.config, self.custom_provider_registry)
except ModuleNotFoundError as _e:
cprint(_e.msg, color="red", file=sys.stderr)
cprint(
"Using llama-stack as a library requires installing dependencies depending on the template (providers) you choose.\n",
color="yellow",
file=sys.stderr,
)
if self.config_path_or_template_name.endswith(".yaml"):
# Convert Provider objects to their types
provider_types: dict[str, str | list[str]] = {}
for api, providers in self.config.providers.items():
types = [p.provider_type for p in providers]
# Convert single-item lists to strings
provider_types[api] = types[0] if len(types) == 1 else types
build_config = BuildConfig(
distribution_spec=DistributionSpec(
providers=provider_types,
),
external_providers_dir=self.config.external_providers_dir,
)
print_pip_install_help(build_config)
else:
prefix = "!" if in_notebook() else ""
cprint(
f"Please run:\n\n{prefix}llama stack build --template {self.config_path_or_template_name} --image-type venv\n\n",
"yellow",
file=sys.stderr,
)
cprint(
"Please check your internet connection and try again.",
"red",
file=sys.stderr,
)
raise _e
if Api.telemetry in self.impls:
setup_logger(self.impls[Api.telemetry])
if not os.environ.get("PYTEST_CURRENT_TEST"):
console = Console()
console.print(f"Using config [blue]{self.config_path_or_template_name}[/blue]:")
safe_config = redact_sensitive_fields(self.config.model_dump())
console.print(yaml.dump(safe_config, indent=2))
self.endpoint_impls = initialize_endpoint_impls(self.impls)
return True
async def request(
self,
cast_to: Any,
options: Any,
*,
stream=False,
stream_cls=None,
):
if not self.endpoint_impls:
raise ValueError("Client not initialized")
# Create headers with provider data if available
headers = options.headers or {}
if self.provider_data:
keys = ["X-LlamaStack-Provider-Data", "x-llamastack-provider-data"]
if all(key not in headers for key in keys):
headers["X-LlamaStack-Provider-Data"] = json.dumps(self.provider_data)
# Use context manager for provider data
with request_provider_data_context(headers):
if stream:
response = await self._call_streaming(
cast_to=cast_to,
options=options,
stream_cls=stream_cls,
)
else:
response = await self._call_non_streaming(
cast_to=cast_to,
options=options,
)
return response
async def _call_non_streaming(
self,
*,
cast_to: Any,
options: Any,
):
path = options.url
body = options.params or {}
body |= options.json_data or {}
matched_func, path_params, route = find_matching_endpoint(options.method, path, self.endpoint_impls)
body |= path_params
body = self._convert_body(path, options.method, body)
await start_trace(route, {"__location__": "library_client"})
try:
result = await matched_func(**body)
finally:
await end_trace()
json_content = json.dumps(convert_pydantic_to_json_value(result))
mock_response = httpx.Response(
status_code=httpx.codes.OK,
content=json_content.encode("utf-8"),
headers={
"Content-Type": "application/json",
},
request=httpx.Request(
method=options.method,
url=options.url,
params=options.params,
headers=options.headers or {},
json=convert_pydantic_to_json_value(body),
),
)
response = APIResponse(
raw=mock_response,
client=self,
cast_to=cast_to,
options=options,
stream=False,
stream_cls=None,
)
return response.parse()
async def _call_streaming(
self,
*,
cast_to: Any,
options: Any,
stream_cls: Any,
):
path = options.url
body = options.params or {}
body |= options.json_data or {}
func, path_params, route = find_matching_endpoint(options.method, path, self.endpoint_impls)
body |= path_params
body = self._convert_body(path, options.method, body)
await start_trace(route, {"__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()
wrapped_gen = preserve_contexts_async_generator(gen(), [CURRENT_TRACE_CONTEXT, PROVIDER_DATA_VAR])
mock_response = httpx.Response(
status_code=httpx.codes.OK,
content=wrapped_gen,
headers={
"Content-Type": "application/json",
},
request=httpx.Request(
method=options.method,
url=options.url,
params=options.params,
headers=options.headers or {},
json=convert_pydantic_to_json_value(body),
),
)
# we use asynchronous impl always internally and channel all requests to AsyncLlamaStackClient
# however, the top-level caller may be a SyncAPIClient -- so its stream_cls might be a Stream (SyncStream)
# so we need to convert it to AsyncStream
args = get_args(stream_cls)
stream_cls = AsyncStream[args[0]]
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) -> dict:
if not body:
return {}
func, _, _ = find_matching_endpoint(method, path, self.endpoint_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)
converted_body[param_name] = convert_to_pydantic(param.annotation, value)
return converted_body