forked from phoenix-oss/llama-stack-mirror
# What does this PR do? This commit enhances the signal handling mechanism in the server by improving the `handle_signal` (previously handle_sigint) function. It now properly retrieves the signal name, ensuring clearer logging when a termination signal is received. Additionally, it cancels all running tasks and waits for their completion before stopping the event loop, allowing for a more graceful shutdown. Support for handling SIGTERM has also been added alongside SIGINT. Before the changes, handle_sigint used asyncio.run(run_shutdown()). However, asyncio.run() is meant to start a new event loop, and calling it inside an existing one (like when running Uvicorn) raises an error. The fix replaces asyncio.run(run_shutdown()) with an async function scheduled on the existing loop using loop.create_task(shutdown()). This ensures that the shutdown coroutine runs within the current event loop instead of trying to create a new one. Furthermore, this commit updates the project dependencies. `fastapi` and `uvicorn` have been added to the development dependencies in `pyproject.toml` and `uv.lock`, ensuring that the necessary packages are available for development and execution. Closes: https://github.com/meta-llama/llama-stack/issues/1043 Signed-off-by: Sébastien Han <seb@redhat.com> [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan Run a server and send SIGINT: ``` INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" python -m llama_stack.distribution.server.server --yaml-config ./llama_stack/templates/ollama/run.yaml Using config file: llama_stack/templates/ollama/run.yaml Run configuration: apis: - agents - datasetio - eval - inference - safety - scoring - telemetry - tool_runtime - vector_io container_image: null datasets: [] eval_tasks: [] image_name: ollama metadata_store: db_path: /Users/leseb/.llama/distributions/ollama/registry.db namespace: null type: sqlite models: - metadata: {} model_id: meta-llama/Llama-3.2-3B-Instruct model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType - llm provider_id: ollama provider_model_id: null - metadata: embedding_dimension: 384 model_id: all-MiniLM-L6-v2 model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType - embedding provider_id: sentence-transformers provider_model_id: null providers: agents: - config: persistence_store: db_path: /Users/leseb/.llama/distributions/ollama/agents_store.db namespace: null type: sqlite provider_id: meta-reference provider_type: inline::meta-reference datasetio: - config: {} provider_id: huggingface provider_type: remote::huggingface - config: {} provider_id: localfs provider_type: inline::localfs eval: - config: {} provider_id: meta-reference provider_type: inline::meta-reference inference: - config: url: http://localhost:11434 provider_id: ollama provider_type: remote::ollama - config: {} provider_id: sentence-transformers provider_type: inline::sentence-transformers safety: - config: {} provider_id: llama-guard provider_type: inline::llama-guard scoring: - config: {} provider_id: basic provider_type: inline::basic - config: {} provider_id: llm-as-judge provider_type: inline::llm-as-judge - config: openai_api_key: '********' provider_id: braintrust provider_type: inline::braintrust telemetry: - config: service_name: llama-stack sinks: console,sqlite sqlite_db_path: /Users/leseb/.llama/distributions/ollama/trace_store.db provider_id: meta-reference provider_type: inline::meta-reference tool_runtime: - config: api_key: '********' max_results: 3 provider_id: brave-search provider_type: remote::brave-search - config: api_key: '********' max_results: 3 provider_id: tavily-search provider_type: remote::tavily-search - config: {} provider_id: code-interpreter provider_type: inline::code-interpreter - config: {} provider_id: rag-runtime provider_type: inline::rag-runtime vector_io: - config: kvstore: db_path: /Users/leseb/.llama/distributions/ollama/faiss_store.db namespace: null type: sqlite provider_id: faiss provider_type: inline::faiss scoring_fns: [] server: port: 8321 tls_certfile: null tls_keyfile: null shields: [] tool_groups: - args: null mcp_endpoint: null provider_id: tavily-search toolgroup_id: builtin::websearch - args: null mcp_endpoint: null provider_id: rag-runtime toolgroup_id: builtin::rag - args: null mcp_endpoint: null provider_id: code-interpreter toolgroup_id: builtin::code_interpreter vector_dbs: [] version: '2' INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:213: Resolved 31 providers INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-inference => ollama INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-inference => sentence-transformers INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: models => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inference => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-vector_io => faiss INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-safety => llama-guard INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: shields => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: safety => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: vector_dbs => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: vector_io => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => brave-search INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => tavily-search INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => code-interpreter INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => rag-runtime INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: tool_groups => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: tool_runtime => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: agents => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-datasetio => huggingface INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-datasetio => localfs INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: datasets => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: datasetio => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: telemetry => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => basic INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => llm-as-judge INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => braintrust INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: scoring_functions => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: scoring => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-eval => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: eval_tasks => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: eval => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inspect => __builtin__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:216: INFO 2025-02-12 10:21:03,723 llama_stack.providers.remote.inference.ollama.ollama:148: checking connectivity to Ollama at `http://localhost:11434`... INFO 2025-02-12 10:21:03,734 httpx:1740: HTTP Request: GET http://localhost:11434/api/ps "HTTP/1.1 200 OK" INFO 2025-02-12 10:21:03,843 faiss.loader:148: Loading faiss. INFO 2025-02-12 10:21:03,865 faiss.loader:150: Successfully loaded faiss. INFO 2025-02-12 10:21:03,868 faiss:173: Failed to load GPU Faiss: name 'GpuIndexIVFFlat' is not defined. Will not load constructor refs for GPU indexes. Warning: `bwrap` is not available. Code interpreter tool will not work correctly. INFO 2025-02-12 10:21:04,315 datasets:54: PyTorch version 2.6.0 available. INFO 2025-02-12 10:21:04,556 httpx:1740: HTTP Request: GET http://localhost:11434/api/ps "HTTP/1.1 200 OK" INFO 2025-02-12 10:21:04,557 llama_stack.providers.utils.inference.embedding_mixin:42: Loading sentence transformer for all-MiniLM-L6-v2... INFO 2025-02-12 10:21:07,202 sentence_transformers.SentenceTransformer:210: Use pytorch device_name: mps INFO 2025-02-12 10:21:07,202 sentence_transformers.SentenceTransformer:218: Load pretrained SentenceTransformer: all-MiniLM-L6-v2 INFO 2025-02-12 10:21:09,500 llama_stack.distribution.stack:102: Models: all-MiniLM-L6-v2 served by sentence-transformers INFO 2025-02-12 10:21:09,500 llama_stack.distribution.stack:102: Models: meta-llama/Llama-3.2-3B-Instruct served by ollama INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::equality served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::regex_parser_multiple_choice_answer served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::subset_of served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-correctness served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-relevancy served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-similarity served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-entity-recall served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-precision served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-recall served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-relevancy served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::factuality served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::faithfulness served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: llm-as-judge::405b-simpleqa served by llm-as-judge INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: llm-as-judge::base served by llm-as-judge INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::code_interpreter served by code-interpreter INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::rag served by rag-runtime INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::websearch served by tavily-search INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:106: Serving API eval POST /v1/eval/tasks/{task_id}/evaluations DELETE /v1/eval/tasks/{task_id}/jobs/{job_id} GET /v1/eval/tasks/{task_id}/jobs/{job_id}/result GET /v1/eval/tasks/{task_id}/jobs/{job_id} POST /v1/eval/tasks/{task_id}/jobs Serving API agents POST /v1/agents POST /v1/agents/{agent_id}/session POST /v1/agents/{agent_id}/session/{session_id}/turn DELETE /v1/agents/{agent_id} DELETE /v1/agents/{agent_id}/session/{session_id} GET /v1/agents/{agent_id}/session/{session_id} GET /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id}/step/{step_id} GET /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id} Serving API scoring_functions GET /v1/scoring-functions/{scoring_fn_id} GET /v1/scoring-functions POST /v1/scoring-functions Serving API safety POST /v1/safety/run-shield Serving API inspect GET /v1/health GET /v1/inspect/providers GET /v1/inspect/routes GET /v1/version Serving API tool_runtime POST /v1/tool-runtime/invoke GET /v1/tool-runtime/list-tools POST /v1/tool-runtime/rag-tool/insert POST /v1/tool-runtime/rag-tool/query Serving API datasetio POST /v1/datasetio/rows GET /v1/datasetio/rows Serving API shields GET /v1/shields/{identifier} GET /v1/shields POST /v1/shields Serving API eval_tasks GET /v1/eval-tasks/{eval_task_id} GET /v1/eval-tasks POST /v1/eval-tasks Serving API models GET /v1/models/{model_id} GET /v1/models POST /v1/models DELETE /v1/models/{model_id} Serving API datasets GET /v1/datasets/{dataset_id} GET /v1/datasets POST /v1/datasets DELETE /v1/datasets/{dataset_id} Serving API vector_io POST /v1/vector-io/insert POST /v1/vector-io/query Serving API inference POST /v1/inference/chat-completion POST /v1/inference/completion POST /v1/inference/embeddings Serving API tool_groups GET /v1/tools/{tool_name} GET /v1/toolgroups/{toolgroup_id} GET /v1/toolgroups GET /v1/tools POST /v1/toolgroups DELETE /v1/toolgroups/{toolgroup_id} Serving API vector_dbs GET /v1/vector-dbs/{vector_db_id} GET /v1/vector-dbs POST /v1/vector-dbs DELETE /v1/vector-dbs/{vector_db_id} Serving API scoring POST /v1/scoring/score POST /v1/scoring/score-batch Serving API telemetry GET /v1/telemetry/traces/{trace_id}/spans/{span_id} GET /v1/telemetry/spans/{span_id}/tree GET /v1/telemetry/traces/{trace_id} POST /v1/telemetry/events GET /v1/telemetry/spans GET /v1/telemetry/traces POST /v1/telemetry/spans/export Listening on ['::', '0.0.0.0']:5001 INFO: Started server process [65372] INFO: Waiting for application startup. INFO: ASGI 'lifespan' protocol appears unsupported. INFO: Application startup complete. INFO: Uvicorn running on http://['::', '0.0.0.0']:5001 (Press CTRL+C to quit) ^CINFO: Shutting down INFO: Finished server process [65372] Received signal SIGINT (2). Exiting gracefully... INFO 2025-02-12 10:21:11,215 __main__:151: Shutting down ModelsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down InferenceRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ShieldsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down SafetyRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down VectorDBsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down VectorIORouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ToolGroupsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ToolRuntimeRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down MetaReferenceAgentsImpl INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DatasetsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DatasetIORouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down TelemetryAdapter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ScoringFunctionsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ScoringRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down EvalTasksRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down EvalRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DistributionInspectImpl ``` [//]: # (## Documentation) [//]: # (- [ ] Added a Changelog entry if the change is significant) Signed-off-by: Sébastien Han <seb@redhat.com>
487 lines
17 KiB
Python
487 lines
17 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 argparse
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import asyncio
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import functools
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import logging
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import inspect
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import json
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import os
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import signal
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import sys
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import traceback
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import warnings
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from contextlib import asynccontextmanager
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from importlib.metadata import version as parse_version
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from pathlib import Path
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from typing import Any, List, Union
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import yaml
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from fastapi import Body, FastAPI, HTTPException, Path as FastapiPath, Request
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from fastapi.exceptions import RequestValidationError
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from fastapi.responses import JSONResponse, StreamingResponse
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from pydantic import BaseModel, ValidationError
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from termcolor import cprint
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from typing_extensions import Annotated
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from llama_stack.distribution.datatypes import StackRunConfig
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from llama_stack.distribution.distribution import builtin_automatically_routed_apis
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from llama_stack.distribution.request_headers import set_request_provider_data
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from llama_stack.distribution.resolver import InvalidProviderError
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from llama_stack.distribution.stack import (
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construct_stack,
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redact_sensitive_fields,
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replace_env_vars,
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validate_env_pair,
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)
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from llama_stack.providers.datatypes import Api
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from llama_stack.providers.inline.telemetry.meta_reference.config import TelemetryConfig
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from llama_stack.providers.inline.telemetry.meta_reference.telemetry import (
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TelemetryAdapter,
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)
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from llama_stack.providers.utils.telemetry.tracing import (
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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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from .endpoints import get_all_api_endpoints
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REPO_ROOT = Path(__file__).parent.parent.parent.parent
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logging.basicConfig(level=logging.INFO, format="%(levelname)s %(asctime)s %(name)s:%(lineno)d: %(message)s")
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logger = logging.getLogger(__name__)
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def warn_with_traceback(message, category, filename, lineno, file=None, line=None):
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log = file if hasattr(file, "write") else sys.stderr
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traceback.print_stack(file=log)
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log.write(warnings.formatwarning(message, category, filename, lineno, line))
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if os.environ.get("LLAMA_STACK_TRACE_WARNINGS"):
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warnings.showwarning = warn_with_traceback
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def create_sse_event(data: Any) -> str:
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if isinstance(data, BaseModel):
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data = data.model_dump_json()
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else:
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data = json.dumps(data)
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return f"data: {data}\n\n"
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async def global_exception_handler(request: Request, exc: Exception):
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traceback.print_exception(exc)
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http_exc = translate_exception(exc)
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return JSONResponse(status_code=http_exc.status_code, content={"error": {"detail": http_exc.detail}})
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def translate_exception(exc: Exception) -> Union[HTTPException, RequestValidationError]:
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if isinstance(exc, ValidationError):
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exc = RequestValidationError(exc.raw_errors)
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if isinstance(exc, RequestValidationError):
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return HTTPException(
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status_code=400,
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detail={
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"errors": [
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{
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"loc": list(error["loc"]),
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"msg": error["msg"],
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"type": error["type"],
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}
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for error in exc.errors()
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]
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},
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)
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elif isinstance(exc, ValueError):
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return HTTPException(status_code=400, detail=f"Invalid value: {str(exc)}")
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elif isinstance(exc, PermissionError):
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return HTTPException(status_code=403, detail=f"Permission denied: {str(exc)}")
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elif isinstance(exc, TimeoutError):
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return HTTPException(status_code=504, detail=f"Operation timed out: {str(exc)}")
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elif isinstance(exc, NotImplementedError):
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return HTTPException(status_code=501, detail=f"Not implemented: {str(exc)}")
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else:
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return HTTPException(
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status_code=500,
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detail="Internal server error: An unexpected error occurred.",
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)
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def handle_signal(app, signum, _) -> None:
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"""
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Handle incoming signals and initiate a graceful shutdown of the application.
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This function is intended to be used as a signal handler for various signals
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(e.g., SIGINT, SIGTERM). Upon receiving a signal, it will print a message
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indicating the received signal and initiate a shutdown process.
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Args:
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app: The application instance containing implementations to be shut down.
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signum (int): The signal number received.
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frame: The current stack frame (not used in this function).
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The shutdown process involves:
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- Shutting down all implementations registered in the application.
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- Gathering all running asyncio tasks.
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- Cancelling all gathered tasks.
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- Waiting for all tasks to finish.
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- Stopping the event loop.
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Note:
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This function schedules the shutdown process as an asyncio task and does
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not block the current execution.
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"""
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signame = signal.Signals(signum).name
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print(f"Received signal {signame} ({signum}). Exiting gracefully...")
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async def shutdown():
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try:
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# Gracefully shut down implementations
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for impl in app.__llama_stack_impls__.values():
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impl_name = impl.__class__.__name__
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logger.info("Shutting down %s", impl_name)
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try:
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if hasattr(impl, "shutdown"):
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await asyncio.wait_for(impl.shutdown(), timeout=5)
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else:
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logger.warning("No shutdown method for %s", impl_name)
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except asyncio.TimeoutError:
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logger.exception("Shutdown timeout for %s ", impl_name, exc_info=True)
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except Exception as e:
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logger.exception("Failed to shutdown %s: %s", impl_name, {e})
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# Gather all running tasks
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loop = asyncio.get_running_loop()
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tasks = [task for task in asyncio.all_tasks(loop) if task is not asyncio.current_task()]
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# Cancel all tasks
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for task in tasks:
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task.cancel()
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# Wait for all tasks to finish
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try:
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await asyncio.wait_for(asyncio.gather(*tasks, return_exceptions=True), timeout=10)
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except asyncio.TimeoutError:
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logger.exception("Timeout while waiting for tasks to finish")
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except asyncio.CancelledError:
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pass
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finally:
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loop.stop()
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loop = asyncio.get_running_loop()
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loop.create_task(shutdown())
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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print("Starting up")
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yield
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print("Shutting down")
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for impl in app.__llama_stack_impls__.values():
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await impl.shutdown()
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|
def is_streaming_request(func_name: str, request: Request, **kwargs):
|
|
# TODO: pass the api method and punt it to the Protocol definition directly
|
|
return kwargs.get("stream", False)
|
|
|
|
|
|
async def maybe_await(value):
|
|
if inspect.iscoroutine(value):
|
|
return await value
|
|
return value
|
|
|
|
|
|
async def sse_generator(event_gen):
|
|
try:
|
|
event_gen = await event_gen
|
|
async for item in event_gen:
|
|
yield create_sse_event(item)
|
|
await asyncio.sleep(0.01)
|
|
except asyncio.CancelledError:
|
|
print("Generator cancelled")
|
|
await event_gen.aclose()
|
|
except Exception as e:
|
|
traceback.print_exception(e)
|
|
yield create_sse_event(
|
|
{
|
|
"error": {
|
|
"message": str(translate_exception(e)),
|
|
},
|
|
}
|
|
)
|
|
|
|
|
|
def create_dynamic_typed_route(func: Any, method: str, route: str):
|
|
async def endpoint(request: Request, **kwargs):
|
|
set_request_provider_data(request.headers)
|
|
|
|
is_streaming = is_streaming_request(func.__name__, request, **kwargs)
|
|
try:
|
|
if is_streaming:
|
|
return StreamingResponse(sse_generator(func(**kwargs)), media_type="text/event-stream")
|
|
else:
|
|
value = func(**kwargs)
|
|
return await maybe_await(value)
|
|
except Exception as e:
|
|
traceback.print_exception(e)
|
|
raise translate_exception(e) from e
|
|
|
|
sig = inspect.signature(func)
|
|
|
|
new_params = [inspect.Parameter("request", inspect.Parameter.POSITIONAL_OR_KEYWORD, annotation=Request)]
|
|
new_params.extend(sig.parameters.values())
|
|
|
|
path_params = extract_path_params(route)
|
|
if method == "post":
|
|
# Annotate parameters that are in the path with Path(...) and others with Body(...)
|
|
new_params = [new_params[0]] + [
|
|
(
|
|
param.replace(annotation=Annotated[param.annotation, FastapiPath(..., title=param.name)])
|
|
if param.name in path_params
|
|
else param.replace(annotation=Annotated[param.annotation, Body(..., embed=True)])
|
|
)
|
|
for param in new_params[1:]
|
|
]
|
|
|
|
endpoint.__signature__ = sig.replace(parameters=new_params)
|
|
|
|
return endpoint
|
|
|
|
|
|
class TracingMiddleware:
|
|
def __init__(self, app):
|
|
self.app = app
|
|
|
|
async def __call__(self, scope, receive, send):
|
|
path = scope["path"]
|
|
await start_trace(path, {"__location__": "server"})
|
|
try:
|
|
return await self.app(scope, receive, send)
|
|
finally:
|
|
await end_trace()
|
|
|
|
|
|
class ClientVersionMiddleware:
|
|
def __init__(self, app):
|
|
self.app = app
|
|
self.server_version = parse_version("llama-stack")
|
|
|
|
async def __call__(self, scope, receive, send):
|
|
if scope["type"] == "http":
|
|
headers = dict(scope.get("headers", []))
|
|
client_version = headers.get(b"x-llamastack-client-version", b"").decode()
|
|
if client_version:
|
|
try:
|
|
client_version_parts = tuple(map(int, client_version.split(".")[:2]))
|
|
server_version_parts = tuple(map(int, self.server_version.split(".")[:2]))
|
|
if client_version_parts != server_version_parts:
|
|
|
|
async def send_version_error(send):
|
|
await send(
|
|
{
|
|
"type": "http.response.start",
|
|
"status": 426,
|
|
"headers": [[b"content-type", b"application/json"]],
|
|
}
|
|
)
|
|
error_msg = json.dumps(
|
|
{
|
|
"error": {
|
|
"message": f"Client version {client_version} is not compatible with server version {self.server_version}. Please update your client."
|
|
}
|
|
}
|
|
).encode()
|
|
await send({"type": "http.response.body", "body": error_msg})
|
|
|
|
return await send_version_error(send)
|
|
except (ValueError, IndexError):
|
|
# If version parsing fails, let the request through
|
|
pass
|
|
|
|
return await self.app(scope, receive, send)
|
|
|
|
|
|
def main():
|
|
"""Start the LlamaStack server."""
|
|
parser = argparse.ArgumentParser(description="Start the LlamaStack server.")
|
|
parser.add_argument(
|
|
"--yaml-config",
|
|
help="Path to YAML configuration file",
|
|
)
|
|
parser.add_argument(
|
|
"--template",
|
|
help="One of the template names in llama_stack/templates (e.g., tgi, fireworks, remote-vllm, etc.)",
|
|
)
|
|
parser.add_argument(
|
|
"--port",
|
|
type=int,
|
|
default=int(os.getenv("LLAMA_STACK_PORT", 8321)),
|
|
help="Port to listen on",
|
|
)
|
|
parser.add_argument("--disable-ipv6", action="store_true", help="Whether to disable IPv6 support")
|
|
parser.add_argument(
|
|
"--env",
|
|
action="append",
|
|
help="Environment variables in KEY=value format. Can be specified multiple times.",
|
|
)
|
|
parser.add_argument(
|
|
"--tls-keyfile",
|
|
help="Path to TLS key file for HTTPS",
|
|
required="--tls-certfile" in sys.argv,
|
|
)
|
|
parser.add_argument(
|
|
"--tls-certfile",
|
|
help="Path to TLS certificate file for HTTPS",
|
|
required="--tls-keyfile" in sys.argv,
|
|
)
|
|
|
|
args = parser.parse_args()
|
|
|
|
if args.env:
|
|
for env_pair in args.env:
|
|
try:
|
|
key, value = validate_env_pair(env_pair)
|
|
print(f"Setting CLI environment variable {key} => {value}")
|
|
os.environ[key] = value
|
|
except ValueError as e:
|
|
print(f"Error: {str(e)}")
|
|
sys.exit(1)
|
|
|
|
if args.yaml_config:
|
|
# if the user provided a config file, use it, even if template was specified
|
|
config_file = Path(args.yaml_config)
|
|
if not config_file.exists():
|
|
raise ValueError(f"Config file {config_file} does not exist")
|
|
print(f"Using config file: {config_file}")
|
|
elif args.template:
|
|
config_file = Path(REPO_ROOT) / "llama_stack" / "templates" / args.template / "run.yaml"
|
|
if not config_file.exists():
|
|
raise ValueError(f"Template {args.template} does not exist")
|
|
print(f"Using template {args.template} config file: {config_file}")
|
|
else:
|
|
raise ValueError("Either --yaml-config or --template must be provided")
|
|
|
|
with open(config_file, "r") as fp:
|
|
config = replace_env_vars(yaml.safe_load(fp))
|
|
config = StackRunConfig(**config)
|
|
|
|
print("Run configuration:")
|
|
safe_config = redact_sensitive_fields(config.model_dump())
|
|
print(yaml.dump(safe_config, indent=2))
|
|
|
|
app = FastAPI(lifespan=lifespan)
|
|
app.add_middleware(TracingMiddleware)
|
|
if not os.environ.get("LLAMA_STACK_DISABLE_VERSION_CHECK"):
|
|
app.add_middleware(ClientVersionMiddleware)
|
|
|
|
try:
|
|
impls = asyncio.run(construct_stack(config))
|
|
except InvalidProviderError:
|
|
sys.exit(1)
|
|
|
|
if Api.telemetry in impls:
|
|
setup_logger(impls[Api.telemetry])
|
|
else:
|
|
setup_logger(TelemetryAdapter(TelemetryConfig()))
|
|
|
|
all_endpoints = get_all_api_endpoints()
|
|
|
|
if config.apis:
|
|
apis_to_serve = set(config.apis)
|
|
else:
|
|
apis_to_serve = set(impls.keys())
|
|
|
|
for inf in builtin_automatically_routed_apis():
|
|
# if we do not serve the corresponding router API, we should not serve the routing table API
|
|
if inf.router_api.value not in apis_to_serve:
|
|
continue
|
|
apis_to_serve.add(inf.routing_table_api.value)
|
|
|
|
apis_to_serve.add("inspect")
|
|
for api_str in apis_to_serve:
|
|
api = Api(api_str)
|
|
|
|
endpoints = all_endpoints[api]
|
|
impl = impls[api]
|
|
|
|
for endpoint in endpoints:
|
|
if not hasattr(impl, endpoint.name):
|
|
# ideally this should be a typing violation already
|
|
raise ValueError(f"Could not find method {endpoint.name} on {impl}!!")
|
|
|
|
impl_method = getattr(impl, endpoint.name)
|
|
|
|
with warnings.catch_warnings():
|
|
warnings.filterwarnings("ignore", category=UserWarning, module="pydantic._internal._fields")
|
|
getattr(app, endpoint.method)(endpoint.route, response_model=None)(
|
|
create_dynamic_typed_route(
|
|
impl_method,
|
|
endpoint.method,
|
|
endpoint.route,
|
|
)
|
|
)
|
|
|
|
cprint(f"Serving API {api_str}", "white", attrs=["bold"])
|
|
for endpoint in endpoints:
|
|
cprint(f" {endpoint.method.upper()} {endpoint.route}", "white")
|
|
|
|
print("")
|
|
app.exception_handler(RequestValidationError)(global_exception_handler)
|
|
app.exception_handler(Exception)(global_exception_handler)
|
|
signal.signal(signal.SIGINT, functools.partial(handle_signal, app))
|
|
signal.signal(signal.SIGTERM, functools.partial(handle_signal, app))
|
|
|
|
app.__llama_stack_impls__ = impls
|
|
|
|
import uvicorn
|
|
|
|
# Configure SSL if certificates are provided
|
|
port = args.port or config.server.port
|
|
|
|
ssl_config = None
|
|
if args.tls_keyfile:
|
|
keyfile = args.tls_keyfile
|
|
certfile = args.tls_certfile
|
|
else:
|
|
keyfile = config.server.tls_keyfile
|
|
certfile = config.server.tls_certfile
|
|
|
|
if keyfile and certfile:
|
|
ssl_config = {
|
|
"ssl_keyfile": keyfile,
|
|
"ssl_certfile": certfile,
|
|
}
|
|
print(f"HTTPS enabled with certificates:\n Key: {keyfile}\n Cert: {certfile}")
|
|
|
|
listen_host = ["::", "0.0.0.0"] if not args.disable_ipv6 else "0.0.0.0"
|
|
print(f"Listening on {listen_host}:{port}")
|
|
|
|
uvicorn_config = {
|
|
"app": app,
|
|
"host": listen_host,
|
|
"port": port,
|
|
}
|
|
if ssl_config:
|
|
uvicorn_config.update(ssl_config)
|
|
|
|
uvicorn.run(**uvicorn_config)
|
|
|
|
|
|
def extract_path_params(route: str) -> List[str]:
|
|
segments = route.split("/")
|
|
params = [seg[1:-1] for seg in segments if seg.startswith("{") and seg.endswith("}")]
|
|
return params
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|