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TradingAgents
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Reduce the legacy execution path before profiling it for real 

The provider itself was healthy, but the legacy dashboard path still ran the heaviest graph shape by default and had no trustworthy stage profiling story. This change narrows the default legacy execution settings to the market-only compact path with conservative timeout/retry values, injects those settings through the unified request/runtime surface, and adds a standalone graph-update profiler so stage timing comes from real node completions rather than synthetic script labels.

Constraint: Profiling evidence had to be grounded in the real provider path without adding new dependencies or polluting the runtime contract
Rejected: Keep synthetic STAGE_TIMING in the subprocess protocol | misattributes the heaviest work to the wrong phase and makes the profiling conclusion untrustworthy
Rejected: Broaden the default legacy path and rely on longer timeouts | raises cost and latency while obscuring the true bottleneck
Confidence: high
Scope-risk: narrow
Reversibility: clean
Directive: Keep operational profiling separate from runtime business contracts unless timings are sourced from real graph-stage boundaries
Tested: python -m pytest web_dashboard/backend/tests/test_executors.py web_dashboard/backend/tests/test_services_migration.py web_dashboard/backend/tests/test_api_smoke.py -q
Tested: python -m compileall web_dashboard/backend orchestrator/profile_stage_chain.py
Tested: real provider direct invoke returned OK against MiniMax anthropic-compatible endpoint
Tested: real graph profiling via orchestrator/profile_stage_chain.py produced stage timings for 600519.SS on 2026-04-10 with selected_analysts=market and compact prompt
Not-tested: legacy subprocess full end-to-end success case on the same provider path (current run still exits via protocol failure after upstream connection error)
This commit is contained in:
陈少杰 2026-04-14 02:42:53 +08:00
parent eb2ab0afcf
commit 8a4f0ad540
6 changed files with 182 additions and 1 deletions
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119
orchestrator/profile_stage_chain.py Normal file
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@ -0,0 +1,119 @@
from __future__ import annotations
import argparse
import json
import signal
import time
from collections import defaultdict
from tradingagents.graph.propagation import Propagator
from tradingagents.graph.trading_graph import TradingAgentsGraph
_PHASE_MAP = {
"Market Analyst": "analyst",
"Bull Researcher": "research",
"Bear Researcher": "research",
"Research Manager": "research",
"Trader": "trading",
"Aggressive Analyst": "risk",
"Conservative Analyst": "risk",
"Neutral Analyst": "risk",
"Portfolio Manager": "portfolio",
}
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description="Profile TradingAgents graph stage timings.")
parser.add_argument("--ticker", required=True)
parser.add_argument("--date", required=True)
parser.add_argument("--provider", default="anthropic")
parser.add_argument("--model", default="MiniMax-M2.7-highspeed")
parser.add_argument("--base-url", default="https://api.minimaxi.com/anthropic")
parser.add_argument("--timeout", type=float, default=45.0)
parser.add_argument("--max-retries", type=int, default=0)
parser.add_argument("--analysis-prompt-style", default="compact")
parser.add_argument("--selected-analysts", default="market")
parser.add_argument("--overall-timeout", type=int, default=120)
return parser
class _ProfileTimeout(Exception):
pass
def main() -> None:
args = build_parser().parse_args()
selected_analysts = [item.strip() for item in args.selected_analysts.split(",") if item.strip()]
config = {
"llm_provider": args.provider,
"deep_think_llm": args.model,
"quick_think_llm": args.model,
"backend_url": args.base_url,
"selected_analysts": selected_analysts,
"analysis_prompt_style": args.analysis_prompt_style,
"llm_timeout": args.timeout,
"llm_max_retries": args.max_retries,
"max_debate_rounds": 1,
"max_risk_discuss_rounds": 1,
}
graph = TradingAgentsGraph(selected_analysts=selected_analysts, config=config)
state = Propagator().create_initial_state(args.ticker, args.date)
config_kwargs = {"recursion_limit": 100, "max_concurrency": 1}
node_timings = []
phase_totals = defaultdict(float)
started_at = time.monotonic()
last_at = started_at
def alarm_handler(signum, frame):
raise _ProfileTimeout(f"profiling timeout after {args.overall_timeout}s")
signal.signal(signal.SIGALRM, alarm_handler)
signal.alarm(args.overall_timeout)
try:
for event in graph.graph.stream(state, stream_mode="updates", config=config_kwargs):
now = time.monotonic()
nodes = list(event.keys())
phases = sorted({_PHASE_MAP.get(node, "unknown") for node in nodes})
delta = round(now - last_at, 3)
entry = {
"nodes": nodes,
"phases": phases,
"delta_seconds": delta,
"elapsed_seconds": round(now - started_at, 3),
}
node_timings.append(entry)
for phase in phases:
phase_totals[phase] += delta
last_at = now
payload = {
"status": "ok",
"ticker": args.ticker,
"date": args.date,
"selected_analysts": selected_analysts,
"analysis_prompt_style": args.analysis_prompt_style,
"node_timings": node_timings,
"phase_totals_seconds": {key: round(value, 3) for key, value in phase_totals.items()},
}
except Exception as exc:
payload = {
"status": "error",
"ticker": args.ticker,
"date": args.date,
"selected_analysts": selected_analysts,
"analysis_prompt_style": args.analysis_prompt_style,
"error": str(exc),
"node_timings": node_timings,
"phase_totals_seconds": {key: round(value, 3) for key, value in phase_totals.items()},
}
finally:
signal.alarm(0)
print(json.dumps(payload, ensure_ascii=False, indent=2))
if __name__ == "__main__":
main()

13
web_dashboard/backend/main.py
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@ -228,11 +228,20 @@ def _resolve_analysis_runtime_settings() -> dict:
or os.environ.get("TRADINGAGENTS_MODEL")
or defaults.get("quick_think_llm")
)
selected_analysts_raw = os.environ.get("TRADINGAGENTS_SELECTED_ANALYSTS", "market")
selected_analysts = [item.strip() for item in selected_analysts_raw.split(",") if item.strip()]
analysis_prompt_style = os.environ.get("TRADINGAGENTS_ANALYSIS_PROMPT_STYLE", "compact")
llm_timeout = float(os.environ.get("TRADINGAGENTS_LLM_TIMEOUT", "45"))
llm_max_retries = int(os.environ.get("TRADINGAGENTS_LLM_MAX_RETRIES", "0"))
return {
"llm_provider": provider,
"backend_url": backend_url,
"deep_think_llm": deep_model,
"quick_think_llm": quick_model,
"selected_analysts": selected_analysts,
"analysis_prompt_style": analysis_prompt_style,
"llm_timeout": llm_timeout,
"llm_max_retries": llm_max_retries,
"provider_api_key": _get_analysis_provider_api_key(provider, saved.get("api_key")),
}
@ -247,6 +256,10 @@ def _build_analysis_request_context(request: Request, auth_key: Optional[str]):
backend_url=settings["backend_url"],
deep_think_llm=settings["deep_think_llm"],
quick_think_llm=settings["quick_think_llm"],
selected_analysts=settings["selected_analysts"],
analysis_prompt_style=settings["analysis_prompt_style"],
llm_timeout=settings["llm_timeout"],
llm_max_retries=settings["llm_max_retries"],
)

19
web_dashboard/backend/services/executor.py
View File

@ -60,7 +60,16 @@ if os.environ.get("TRADINGAGENTS_DEEP_MODEL"):
trading_config["deep_think_llm"] = os.environ["TRADINGAGENTS_DEEP_MODEL"]
if os.environ.get("TRADINGAGENTS_QUICK_MODEL"):
trading_config["quick_think_llm"] = os.environ["TRADINGAGENTS_QUICK_MODEL"]
if os.environ.get("TRADINGAGENTS_SELECTED_ANALYSTS"):
trading_config["selected_analysts"] = [
item.strip() for item in os.environ["TRADINGAGENTS_SELECTED_ANALYSTS"].split(",") if item.strip()
]
if os.environ.get("TRADINGAGENTS_ANALYSIS_PROMPT_STYLE"):
trading_config["analysis_prompt_style"] = os.environ["TRADINGAGENTS_ANALYSIS_PROMPT_STYLE"]
if os.environ.get("TRADINGAGENTS_LLM_TIMEOUT"):
trading_config["llm_timeout"] = float(os.environ["TRADINGAGENTS_LLM_TIMEOUT"])
if os.environ.get("TRADINGAGENTS_LLM_MAX_RETRIES"):
trading_config["llm_max_retries"] = int(os.environ["TRADINGAGENTS_LLM_MAX_RETRIES"])
print("STAGE:analysts", flush=True)
print("STAGE:research", flush=True)
@ -305,6 +314,14 @@ class LegacySubprocessAnalysisExecutor:
clean_env["TRADINGAGENTS_DEEP_MODEL"] = request_context.deep_think_llm
if request_context.quick_think_llm:
clean_env["TRADINGAGENTS_QUICK_MODEL"] = request_context.quick_think_llm
if request_context.selected_analysts:
clean_env["TRADINGAGENTS_SELECTED_ANALYSTS"] = ",".join(request_context.selected_analysts)
if request_context.analysis_prompt_style:
clean_env["TRADINGAGENTS_ANALYSIS_PROMPT_STYLE"] = request_context.analysis_prompt_style
if request_context.llm_timeout is not None:
clean_env["TRADINGAGENTS_LLM_TIMEOUT"] = str(request_context.llm_timeout)
if request_context.llm_max_retries is not None:
clean_env["TRADINGAGENTS_LLM_MAX_RETRIES"] = str(request_context.llm_max_retries)
for env_name in self._provider_api_env_names(llm_provider):
if analysis_api_key:
clean_env[env_name] = analysis_api_key

12
web_dashboard/backend/services/request_context.py
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@ -24,6 +24,10 @@ class RequestContext:
backend_url: Optional[str] = None
deep_think_llm: Optional[str] = None
quick_think_llm: Optional[str] = None
selected_analysts: tuple[str, ...] = ()
analysis_prompt_style: Optional[str] = None
llm_timeout: Optional[float] = None
llm_max_retries: Optional[int] = None
client_host: Optional[str] = None
is_local: bool = False
metadata: dict[str, str] = field(default_factory=dict)
@ -38,6 +42,10 @@ def build_request_context(
backend_url: Optional[str] = None,
deep_think_llm: Optional[str] = None,
quick_think_llm: Optional[str] = None,
selected_analysts: Optional[list[str] | tuple[str, ...]] = None,
analysis_prompt_style: Optional[str] = None,
llm_timeout: Optional[float] = None,
llm_max_retries: Optional[int] = None,
request_id: Optional[str] = None,
contract_version: str = CONTRACT_VERSION,
executor_type: str = DEFAULT_EXECUTOR_TYPE,
@ -56,6 +64,10 @@ def build_request_context(
backend_url=backend_url,
deep_think_llm=deep_think_llm,
quick_think_llm=quick_think_llm,
selected_analysts=tuple(selected_analysts or ()),
analysis_prompt_style=analysis_prompt_style,
llm_timeout=llm_timeout,
llm_max_retries=llm_max_retries,
client_host=client_host,
is_local=is_local,
metadata=dict(metadata or {}),

8
web_dashboard/backend/tests/test_executors.py
View File

@ -197,6 +197,10 @@ def test_executor_injects_provider_specific_env(monkeypatch):
backend_url="https://api.openai.com/v1",
deep_think_llm="gpt-5.4",
quick_think_llm="gpt-5.4-mini",
selected_analysts=["market"],
analysis_prompt_style="compact",
llm_timeout=45,
llm_max_retries=0,
),
)
@ -205,6 +209,10 @@ def test_executor_injects_provider_specific_env(monkeypatch):
assert captured["env"]["TRADINGAGENTS_LLM_PROVIDER"] == "openai"
assert captured["env"]["TRADINGAGENTS_BACKEND_URL"] == "https://api.openai.com/v1"
assert captured["env"]["OPENAI_API_KEY"] == "provider-key"
assert captured["env"]["TRADINGAGENTS_SELECTED_ANALYSTS"] == "market"
assert captured["env"]["TRADINGAGENTS_ANALYSIS_PROMPT_STYLE"] == "compact"
assert captured["env"]["TRADINGAGENTS_LLM_TIMEOUT"] == "45"
assert captured["env"]["TRADINGAGENTS_LLM_MAX_RETRIES"] == "0"
assert "ANTHROPIC_API_KEY" not in captured["env"]

12
web_dashboard/backend/tests/test_services_migration.py
View File

@ -52,6 +52,10 @@ def test_build_request_context_defaults():
backend_url="https://api.minimaxi.com/anthropic",
deep_think_llm="MiniMax-M2.7-highspeed",
quick_think_llm="MiniMax-M2.7-highspeed",
selected_analysts=["market"],
analysis_prompt_style="compact",
llm_timeout=45,
llm_max_retries=0,
metadata={"source": "test"},
)
@ -59,6 +63,10 @@ def test_build_request_context_defaults():
assert context.provider_api_key == "provider-secret"
assert context.llm_provider == "anthropic"
assert context.backend_url == "https://api.minimaxi.com/anthropic"
assert context.selected_analysts == ("market",)
assert context.analysis_prompt_style == "compact"
assert context.llm_timeout == 45
assert context.llm_max_retries == 0
assert context.request_id
assert context.contract_version == "v1alpha1"
assert context.executor_type == "legacy_subprocess"
@ -225,6 +233,10 @@ def test_analysis_service_start_analysis_uses_executor(tmp_path):
provider_api_key="provider-secret",
llm_provider="anthropic",
backend_url="https://api.minimaxi.com/anthropic",
selected_analysts=["market"],
analysis_prompt_style="compact",
llm_timeout=45,
llm_max_retries=0,
),
broadcast_progress=_broadcast,
)