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StepFun / OpenRouter probe utility for sentiment V2 diagnostics.
Usage:
py -m app.stepfun_probe
py -m app.stepfun_probe --sample-size 24 --db-limit 24
py -m app.stepfun_probe --skip-db
"""
from __future__ import annotations
import argparse
import asyncio
import json
import time
from typing import Any
from sqlalchemy.orm import Session
from app.ai_engine import (
LLM_SCORING_PROVIDER_OPTIONS,
LLM_SCORING_RESPONSE_FORMAT_V2,
_build_llm_v2_user_prompt,
score_batch_with_llm_v2,
)
from app.db import SessionLocal, init_db
from app.models import NewsProcessed, NewsRaw
from app.openrouter_client import OpenRouterError, create_chat_completion
from app.settings import get_settings
def _build_handcrafted_articles() -> list[dict[str, Any]]:
return [
{
"id": 1,
"title": "Major copper mine outage in Chile removes 180k tonnes from expected supply",
"description": "Analysts expect lower exchange inventories and tighter concentrates market.",
"text": (
"Major copper mine outage in Chile removes 180k tonnes from expected supply. "
"Analysts expect lower exchange inventories and tighter concentrates market."
),
},
{
"id": 2,
"title": "China property slowdown deepens and cable demand weakens",
"description": "Fabricators report softer orders and lower cathode premiums.",
"text": (
"China property slowdown deepens and cable demand weakens. "
"Fabricators report softer orders and lower cathode premiums."
),
},
{
"id": 3,
"title": "Semiconductor patent lawsuit update",
"description": "No direct discussion of copper demand or supply.",
"text": "Semiconductor patent lawsuit update with no direct copper market linkage.",
},
]
def _load_db_articles(session: Session, limit: int) -> list[dict[str, Any]]:
rows = (
session.query(
NewsProcessed.id.label("processed_id"),
NewsRaw.title,
NewsRaw.description,
NewsProcessed.cleaned_text,
NewsRaw.published_at,
)
.join(NewsRaw, NewsProcessed.raw_id == NewsRaw.id)
.order_by(NewsRaw.published_at.desc(), NewsProcessed.id.desc())
.limit(max(1, int(limit)))
.all()
)
articles: list[dict[str, Any]] = []
for row in rows:
title = str(row.title or "")[:500]
description = str(row.description or "")[:800]
text = str(row.cleaned_text or f"{title} {description}")[:1800]
articles.append(
{
"id": int(row.processed_id),
"title": title,
"description": description,
"text": text,
}
)
return articles
async def _run_strict_probe(
*,
model: str,
articles: list[dict[str, Any]],
) -> dict[str, Any]:
settings = get_settings()
user_prompt = _build_llm_v2_user_prompt(articles, horizon_days=5)
started = time.perf_counter()
try:
data = await create_chat_completion(
api_key=settings.openrouter_api_key or "",
model=model,
messages=[
{
"role": "system",
"content": (
"You are a Senior Copper Futures Analyst. Return only valid JSON array with keys: "
"id,label,impact_score,confidence,relevance,event_type,reasoning."
),
},
{"role": "user", "content": user_prompt},
],
max_tokens=1800,
temperature=0.0,
timeout_seconds=60.0,
max_retries=settings.openrouter_max_retries,
rpm=settings.openrouter_rpm,
fallback_models=settings.openrouter_fallback_models_list,
response_format=LLM_SCORING_RESPONSE_FORMAT_V2,
provider=LLM_SCORING_PROVIDER_OPTIONS,
extra_payload={"reasoning": {"exclude": True}},
)
elapsed = time.perf_counter() - started
choice = data.get("choices", [{}])[0]
content = choice.get("message", {}).get("content")
return {
"ok": True,
"elapsed_sec": round(elapsed, 2),
"finish_reason": choice.get("finish_reason"),
"content_len": len(content or ""),
"preview": str(content)[:240],
}
except OpenRouterError as exc:
elapsed = time.perf_counter() - started
return {
"ok": False,
"elapsed_sec": round(elapsed, 2),
"error_type": "OpenRouterError",
"status_code": exc.status_code,
"message": str(exc)[:280],
}
except Exception as exc: # noqa: BLE001
elapsed = time.perf_counter() - started
return {
"ok": False,
"elapsed_sec": round(elapsed, 2),
"error_type": type(exc).__name__,
"message": str(exc)[:280],
}
async def _run_v2_probe(
*,
articles: list[dict[str, Any]],
horizon_days: int,
) -> dict[str, Any]:
started = time.perf_counter()
bundle = await score_batch_with_llm_v2(articles, horizon_days=horizon_days)
elapsed = time.perf_counter() - started
sample_results = []
for item in bundle.get("results", [])[:3]:
sample_results.append(
{
"id": item.get("id"),
"label": item.get("label"),
"impact_score": item.get("impact_score"),
"confidence": item.get("confidence"),
"relevance": item.get("relevance"),
"event_type": item.get("event_type"),
}
)
return {
"elapsed_sec": round(elapsed, 2),
"result_count": len(bundle.get("results", [])),
"fallback_count": int(bundle.get("fallback_count", 0)),
"parse_fail_count": int(bundle.get("parse_fail_count", 0)),
"escalation_count": int(bundle.get("escalation_count", 0)),
"failed_ids": bundle.get("failed_ids", []),
"model_fast": bundle.get("model_fast"),
"model_reliable": bundle.get("model_reliable"),
"sample_results": sample_results,
}
async def _run_probe(sample_size: int, db_limit: int, skip_db: bool) -> None:
settings = get_settings()
fast_model = settings.resolved_scoring_fast_model
reliable_model = settings.resolved_scoring_reliable_model
print("=== StepFun Probe ===")
print(f"fast_model={fast_model}")
print(f"reliable_model={reliable_model}")
print(f"openrouter_rpm={settings.openrouter_rpm} max_retries={settings.openrouter_max_retries}")
handcrafted = _build_handcrafted_articles()
strict_summary = await _run_strict_probe(model=fast_model, articles=handcrafted)
print("\n[1] strict_schema_probe")
print(json.dumps(strict_summary, ensure_ascii=True, indent=2))
v2_smoke = await _run_v2_probe(articles=handcrafted, horizon_days=5)
print("\n[2] v2_smoke_probe_handcrafted")
print(json.dumps(v2_smoke, ensure_ascii=True, indent=2))
if skip_db:
return
with SessionLocal() as session:
db_articles = _load_db_articles(session, limit=db_limit)
if not db_articles:
print("\n[3] v2_db_probe: no articles found in news_processed")
return
db_probe_articles = db_articles[: max(1, min(sample_size, len(db_articles)))]
v2_db = await _run_v2_probe(articles=db_probe_articles, horizon_days=5)
print("\n[3] v2_db_probe")
print(f"sampled_articles={len(db_probe_articles)}")
print(json.dumps(v2_db, ensure_ascii=True, indent=2))
def main() -> None:
parser = argparse.ArgumentParser(description="Probe StepFun/OpenRouter behavior for sentiment V2.")
parser.add_argument("--sample-size", type=int, default=12, help="How many DB articles to score in DB probe.")
parser.add_argument("--db-limit", type=int, default=24, help="How many latest DB articles to fetch before sampling.")
parser.add_argument("--skip-db", action="store_true", help="Skip DB probe; run only strict + handcrafted tests.")
args = parser.parse_args()
init_db()
asyncio.run(_run_probe(sample_size=args.sample_size, db_limit=args.db_limit, skip_db=args.skip_db))
if __name__ == "__main__":
main()
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