feat: 分离 Alpha 检查与提交限制，优化检查统计与前端展示
This commit is contained in:
yuxuanhui
+15
-4
@@ -7,6 +7,7 @@ from datetime import datetime
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from sqlalchemy import or_, select, update
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from .models import Alpha, Research, ResearchTag, SelfCorrelation, now
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from .platform_checks import split_checks, submission_limits
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from .research.provenance import source_alpha_ids
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METRIC_FIELDS = (
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@@ -16,23 +17,24 @@ METRIC_FIELDS = (
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def failed_checks(checks):
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"""Return failed platform check names; local correlation never changes this list."""
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"""Return failed Alpha check names, excluding submission limits and local correlation."""
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return [
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check.get("name") if isinstance(check.get("name"), str) else "未命名检查"
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for check in checks if isinstance(check, dict) and check.get("result") == "FAIL"
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for check in split_checks(checks)[0] if isinstance(check, dict) and check.get("result") == "FAIL"
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] if isinstance(checks, list) else []
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def snapshot_columns(settings, metrics, checks):
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"""Derive list fields from a platform snapshot, preserving missing metrics as null.
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Only explicit FAIL results count. Empty, malformed and unfinished checks are
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Submission limits are excluded. Only explicit Alpha FAIL results count.
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Empty, malformed and unfinished Alpha checks are
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pending; all known checks passing without PROD_CORRELATION is only a pre-check.
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No submission eligibility or activity eligibility is inferred here.
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"""
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settings = settings if isinstance(settings, dict) else {}
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metrics = metrics if isinstance(metrics, dict) else {}
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checks = checks if isinstance(checks, list) else []
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checks, _ = split_checks(checks)
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valid = [check for check in checks if isinstance(check, dict)]
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failures = len(failed_checks(checks))
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by_name = {check["name"]: check for check in valid if isinstance(check.get("name"), str)}
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@@ -64,6 +66,15 @@ def snapshot_columns(settings, metrics, checks):
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}
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def check_summary(checks):
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"""Separate cached Alpha findings from submission limits; infer no live eligibility."""
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return {
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"check_type": snapshot_columns({}, {}, checks)["check_type"],
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"failed_checks": failed_checks(checks),
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"submission_limits": submission_limits(checks),
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}
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def submission_condition(submission):
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"""Match the platform list contract; a missing status is never assumed submitted."""
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return Alpha.status == "UNSUBMITTED" if submission == "UNSUBMITTED" else Alpha.status != "UNSUBMITTED"
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@@ -24,7 +24,7 @@ TOOLS = {
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"search_data_preparations": (c.PreparationSearch, "preparations", "research:read", "分页查询数据准备集合，返回固定范围、字段数及版本。研究可使用多个集合，各集合范围独立。"),
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"get_data_preparation": (c.PreparationRead, "preparation", "research:read", "按集合 ID 与版本分页预览字段、类型、描述和数据集归属。提交回测时携带 preparation_refs，由服务端核对版本并固定独立输入快照；空集合不能用于研究。"),
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"create_research_template": (c.CreateTemplate, "create_template", "research:write", "将调用方大模型研究后自行总结的参数化模板保存到模板工坊，供用户后续批量回测。先用 get_backtest_results 阅读实际指标和检查，选择 1–20 个已完成采集的 source_item_ids，并说明 hypothesis；不要把 completed 当作检查通过。template 使用 {name} 占位符及逐一对应的 variables，字段变量须声明 MATRIX/VECTOR/GROUP，VECTOR 聚合须明确写入表达式。提供唯一名称和 idempotency_key，可附 reference。返回模板 ID、版本和理论组合数；仅核验结构及来源，不验证所有参数组合，不再次调用模型、不执行回测、不覆盖已有模板。"),
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"get_submission_check": (c.SelfCorrelationReference, "submission_check_context", "research:read", "读取已导入 Alpha 的表达式、Description、snapshot 和缓存检查结果；不发起检查。先核对或生成三段 Description，再调用 check_submission。"),
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"get_submission_check": (c.SelfCorrelationReference, "submission_check_context", "research:read", "读取已导入 Alpha 的表达式、Description、snapshot 和缓存检查结果；check_summary 分离 Alpha 检查和 REGULAR_SUBMISSION 提交限制，原始 checks 保留；限制不代表当前额度。不发起检查。先核对或生成三段 Description，再调用 check_submission。"),
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"check_submission": (c.SubmissionCheck, "check_submission", "research:refresh", "对单个待提交 Alpha 写回已获用户授权的 Description 并调用平台 GET /check，返回 job_id。须先用 get_submission_check 获取 snapshot；保留本地自相关门槛和冲突保护。通过 get_refresh_job 查进度、get_submission_check 读结果。无论检查结果如何，都不会调用 /submit 或正式提交 Alpha。"),
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"get_worldquant_connection": (c.ConnectionReference, "connection", "research:read", "读取 WorldQuant 连接状态及可选认证 job_id 的进度，不发起认证；人工验证在网页完成。"),
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"authenticate_worldquant": (c.Authentication, "authenticate", "research:refresh", "使用服务端已保存凭据连接或重新认证 WorldQuant，返回 job_id；action=connect（默认）或人工验证后 verify。用 get_worldquant_connection 查询，不接收密码，不修改账户配置。"),
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@@ -38,7 +38,7 @@ TOOLS = {
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"search_backtests": (c.History, "history", "research:read", "分页查历史候选与固定设置；candidates 按完整输入精确匹配，不推断数学等价。"),
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"submit_backtests": (c.Submit, "submit", "backtests:execute", "执行用户已授权的固定批次，自动留痕并立即返回运行 ID。可携带 preparation_refs 选择集合，版本变化须重新读取；每项必须完整设置；重复默认拒绝，rerun 明确重跑。不需要研究资产。"),
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"get_backtest": (c.RunReference, "run", "research:read", "读取真实运行进度、提交数量和可选增量事件；受理不等于成功。"),
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"get_backtest_results": (c.Results, "results", "research:read", "分页读取固定快照指标、全部非通过检查及三层状态；缺失指标不补零。"),
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"get_backtest_results": (c.Results, "results", "research:read", "分页读取固定快照指标、Alpha 非通过检查及三层状态；REGULAR_SUBMISSION 单列 submission_limits，不计入 Alpha 失败统计。缺失指标不补零。"),
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"get_backtest_artifact": (c.Artifact, "artifact", "research:read", "分页读取候选脱敏快照的顶层键值或独立采集的 PnL；缺缓存不自动刷新。"),
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"control_backtest": (c.Control, "control", "backtests:control", "对已授权运行暂停、继续、停止或恢复采集；不远程取消、不重提未知模拟。需要版本和幂等键。"),
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}
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@@ -0,0 +1,23 @@
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"""Classify platform evidence without discarding unknown checks or inferring eligibility."""
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def is_submission_limit(check):
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"""Recognize only the confirmed account-limit check; unknown names remain Alpha checks."""
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return isinstance(check, dict) and check.get("name") == "REGULAR_SUBMISSION"
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def split_checks(checks):
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"""Return Alpha checks and submission limits, retaining malformed Alpha evidence."""
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items = checks if isinstance(checks, list) else []
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return ([c for c in items if not is_submission_limit(c)],
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[c for c in items if is_submission_limit(c)])
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def submission_limits(checks):
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"""Summarize the observed limit, never the account's current allowance or reset time."""
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_, limits = split_checks(checks)
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status = "blocked" if any(c.get("result") == "FAIL" for c in limits) else (
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"not_blocked" if limits and all(c.get("result") == "PASS" for c in limits) else "unknown"
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)
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return {"status": status, "checks": limits,
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"meaning": "仅反映缓存观测时的提交限制，不代表当前额度或正式提交资格"}
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@@ -7,6 +7,7 @@ from sqlalchemy import select
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from ..backtests.service import Backtests, uid
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from ..models import Alpha, ResearchEvaluation, ResearchExperiment, SelfCorrelation
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from ..platform_checks import split_checks, submission_limits
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from .experiments import Experiments
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from .serialization import encode_snapshot as jsonable_encoder
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@@ -30,13 +31,14 @@ def assess(snapshot, rules):
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evidence.append(
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{"metric": key, "value": value, "bound": bound, "direction": direction, "status": status}
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)
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checks = metrics.get("checks") or []
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raw_checks = metrics.get("checks") or []
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checks, _ = split_checks(raw_checks)
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if not checks:
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missing.append("platform_checks")
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for check in checks:
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if check.get("result") == "FAIL":
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if isinstance(check, dict) and check.get("result") == "FAIL":
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failed.append(f"platform:{check.get('name', 'unknown')}")
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unknown_checks = [check for check in checks if check.get("result") not in ("PASS", "FAIL")]
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unknown_checks = [check for check in checks if not isinstance(check, dict) or check.get("result") not in ("PASS", "FAIL")]
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if unknown_checks:
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missing.append("unresolved_platform_checks")
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return {
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@@ -44,7 +46,8 @@ def assess(snapshot, rules):
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"evidence": evidence,
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"failed": failed,
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"missing": missing,
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"existing_platform_checks": checks,
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"existing_platform_checks": raw_checks,
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"submission_limits": submission_limits(raw_checks),
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"meaning": "本地研究筛选结果，不是官方提交资格",
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}
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@@ -7,6 +7,7 @@ from sqlalchemy import func, select
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from ..alphas import number, sanitize
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from ..backtests.contracts import fingerprint
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from ..models import BacktestItem, BacktestResult, BacktestRun, Pnl
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from ..platform_checks import is_submission_limit
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from ..research.serialization import encode_snapshot
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@@ -26,6 +27,8 @@ def checks_summary(snapshot):
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if "checks" in snapshot:
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raw = snapshot["checks"]
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checks.extend({"section": "root", "raw": c} for c in (raw if isinstance(raw, list) else [raw]))
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submission_checks = [c for c in checks if is_submission_limit(c["raw"])]
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checks = [c for c in checks if not is_submission_limit(c["raw"])]
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counts = Counter({key: 0 for key in ("PASS", "FAIL", "PENDING", "WARNING", "UNKNOWN")})
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non_pass = []
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for check in checks:
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@@ -36,7 +39,9 @@ def checks_summary(snapshot):
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if state != "PASS":
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non_pass.append({**check, "status": state})
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return {"status": "unknown" if not checks else "reported", "counts": dict(counts),
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"total": len(checks), "non_pass": non_pass}
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"total": len(checks), "non_pass": non_pass,
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"submission_limits": submission_checks,
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"meaning": "Alpha 检查统计不含提交限制；限制为快照观测，不代表实时提交资格"}
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def item_summary(item, result):
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@@ -9,6 +9,7 @@ from uuid import uuid4
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from sqlalchemy import func, select
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from ..alphas import check_summary
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from ..backtests.contracts import ControlInput, DraftInput, PreviewInput, Source, StartInput, fingerprint
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from ..backtests.service import Backtests
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from ..business import Business
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@@ -221,7 +222,7 @@ class ResearchAccess:
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return {"alpha_id": args.alpha_id, "snapshot": submission_fingerprint(context),
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**context, "descriptions": {key: item["description"] for key, item in context["sections"].items()},
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"can_check": alpha.status == "UNSUBMITTED" and await correlation_allows_check(self.db, args.alpha_id),
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"checks": alpha.checks, "source": "local_cache", "production_submission": False,
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"checks": alpha.checks, "check_summary": check_summary(alpha.checks), "source": "local_cache", "production_submission": False,
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"job_id": job.id if job else None, "job_status": job.status if job else None,
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"checked_at": job.checkpoint.get("checked_at") if job else None}
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@@ -15,7 +15,7 @@ from pydantic_ai.usage import UsageLimits
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from sqlalchemy import select
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from .ai.provider import public_error
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from .alphas import code, sanitize, snapshot_columns, submission_condition
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from .alphas import check_summary, code, sanitize, snapshot_columns, submission_condition
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from .jobs import ACTIVE
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from .models import Account, AISettings, Alpha, Job, JobItem, SelfCorrelation, now
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from .schemas import Contract, JobOutput, valid_ids
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@@ -206,6 +206,8 @@ def router(runner, ai):
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)
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return {
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"snapshot": fingerprint(context),
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"checks": alpha.checks,
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"check_summary": check_summary(alpha.checks),
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"sections": context["sections"],
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"descriptions": {key: item["description"] for key, item in context["sections"].items()},
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"model": config.description_model,
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