Add multimodel context to market opportunities
This commit is contained in:
2569718930@qq.com
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# Ops Market Multimodel Context Implementation Plan
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> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
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**Goal:** Make Ops market opportunities evaluate and display full multi-model context instead of relying mainly on DEB and median.
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**Architecture:** Keep the existing Ops opportunities API and page. Extend each opportunity row with multi-model source values and bucket-relative counts, then use those counts in the late NO filter so high/low multi-model consensus is preserved for manual review.
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**Tech Stack:** Python FastAPI service code, pytest, Next.js React TypeScript, business state tests.
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---
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### Task 1: Backend Multi-Model Signals
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**Files:**
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- Modify: `web/services/ops/market_opportunities.py`
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- Test: `tests/test_ops_market_opportunities.py`
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- [ ] **Step 1: Add tests**
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Add tests asserting opportunities include `model_cluster_sources`, `model_min`, `model_max`, `models_in_bucket`, `models_above_bucket`, `models_below_bucket`, and `models_above_deb`.
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- [ ] **Step 2: Implement source extraction**
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Create helper functions to parse `row["model_cluster_sources"]`, classify model values against a market option, and return counts plus min/max.
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- [ ] **Step 3: Return fields on opportunity rows**
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Include the new fields in every row produced by `build_market_opportunity_rows`.
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- [ ] **Step 4: Verify**
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Run `python -m pytest tests/test_ops_market_opportunities.py -q`.
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### Task 2: Conservative Late NO Filtering
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**Files:**
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- Modify: `web/services/ops/market_opportunities.py`
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- Test: `tests/test_ops_market_opportunities.py`
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- [ ] **Step 1: Update tests**
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Change the late NO tests so rows are filtered only when multi-model consensus is inside the target bucket, and preserved when models mostly sit above or below the target bucket.
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- [ ] **Step 2: Implement filtering**
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Pass model relation counts into `_is_late_priced_no_noise`; return `False` when outside-bucket model count is greater than inside-bucket count.
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- [ ] **Step 3: Verify**
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Run `python -m pytest tests/test_ops_market_opportunities.py -q`.
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### Task 3: Frontend Display
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**Files:**
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- Modify: `frontend/components/ops/market-opportunities/MarketOpportunitiesPageClient.tsx`
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- Test: `frontend/components/ops/__tests__/opsMarketOpportunities.test.ts`
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- [ ] **Step 1: Add frontend assertions**
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Assert the Ops market opportunities page includes `多模型`, `models_above_bucket`, and `model_cluster_sources`.
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- [ ] **Step 2: Display compact context**
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Add a `多模型` column showing min/max range, in/high/low bucket counts, and compact source values.
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- [ ] **Step 3: Verify**
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Run `cd frontend && npm run test:business` and `cd frontend && npm run typecheck`.
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### Task 4: Final Validation and Deploy
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**Files:**
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- No new source files.
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- [ ] **Step 1: Run full checks**
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Run `python -m ruff check .`, `python -m pytest`, `cd frontend && npm run test:business`, and `cd frontend && npm run typecheck`.
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- [ ] **Step 2: Commit and push**
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Commit the backend and frontend changes, push `main`, monitor GitHub Actions, and smoke check production.
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@@ -49,6 +49,7 @@ export function runTests() {
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"买入价",
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"方向概率",
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"Edge",
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"多模型",
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"市场链接",
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]) {
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assert(client.includes(column), `market opportunities table must include ${column}`);
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@@ -69,4 +70,11 @@ export function runTests() {
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client.includes("YES"),
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"NO opportunities must show side probability while keeping the underlying YES probability visible",
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);
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assert(
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client.includes("model_cluster_sources") &&
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client.includes("models_above_bucket") &&
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client.includes("models_below_bucket") &&
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client.includes("models_in_bucket"),
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"market opportunities must expose multi-model context and bucket-relative model counts",
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);
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}
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@@ -17,6 +17,14 @@ type MarketOpportunityRow = {
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model_probability?: number;
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yes_probability?: number;
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side_probability?: number;
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model_cluster_sources?: Record<string, number>;
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model_count?: number;
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model_min?: number | null;
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model_max?: number | null;
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models_below_bucket?: number;
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models_in_bucket?: number;
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models_above_bucket?: number;
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models_above_deb?: number;
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edge?: number;
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liquidity?: number | null;
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volume?: number | null;
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@@ -89,6 +97,16 @@ function sideProbability(row: MarketOpportunityRow) {
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return yes;
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}
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function modelSourceSummary(row: MarketOpportunityRow) {
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const sources = row.model_cluster_sources || {};
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return Object.entries(sources)
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.filter(([, value]) => typeof value === "number" && Number.isFinite(value))
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.sort(([left], [right]) => left.localeCompare(right))
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.slice(0, 6)
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.map(([name, value]) => `${name} ${value.toFixed(1)}`)
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.join(" · ");
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}
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function Stat({
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label,
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value,
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@@ -251,7 +269,7 @@ export function MarketOpportunitiesPageClient() {
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</div>
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) : null}
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<div className="overflow-x-auto rounded-lg border border-slate-200">
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<table className="min-w-[1320px] w-full border-collapse text-sm">
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<table className="min-w-[1460px] w-full border-collapse text-sm">
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<thead className="bg-slate-50 text-left text-xs font-black uppercase tracking-wide text-slate-500">
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<tr>
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<th className="px-3 py-2">城市</th>
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@@ -263,6 +281,7 @@ export function MarketOpportunitiesPageClient() {
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<th className="px-3 py-2 text-right">当前最高</th>
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<th className="px-3 py-2 text-right">DEB</th>
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<th className="px-3 py-2 text-right">模型中位数</th>
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<th className="px-3 py-2">多模型</th>
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<th className="px-3 py-2 text-right">分歧</th>
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<th className="px-3 py-2 text-right">流动性</th>
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<th className="px-3 py-2 text-right">成交量</th>
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@@ -272,7 +291,7 @@ export function MarketOpportunitiesPageClient() {
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<tbody className="divide-y divide-slate-100 bg-white">
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{loading ? (
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<tr>
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<td colSpan={13} className="px-3 py-10 text-center text-sm font-semibold text-slate-400">
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<td colSpan={14} className="px-3 py-10 text-center text-sm font-semibold text-slate-400">
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加载中...
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</td>
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</tr>
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@@ -304,6 +323,17 @@ export function MarketOpportunitiesPageClient() {
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<td className="px-3 py-2 text-right font-semibold text-slate-700">{tempLabel(row.current_max_so_far)}</td>
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<td className="px-3 py-2 text-right font-semibold text-orange-700">{tempLabel(row.deb_prediction)}</td>
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<td className="px-3 py-2 text-right font-semibold text-slate-700">{tempLabel(row.model_median)}</td>
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<td className="px-3 py-2">
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<div className="font-bold text-slate-800">
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{tempLabel(row.model_min)}-{tempLabel(row.model_max)}
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</div>
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<div className="mt-0.5 text-[11px] font-semibold text-slate-500">
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低 {row.models_below_bucket ?? 0} · 内 {row.models_in_bucket ?? 0} · 高 {row.models_above_bucket ?? 0}
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</div>
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<div className="mt-0.5 max-w-[260px] truncate text-[11px] font-semibold text-slate-400" title={modelSourceSummary(row)}>
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{modelSourceSummary(row) || "—"}
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</div>
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</td>
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<td className="px-3 py-2 text-right font-semibold text-slate-700">{tempLabel(row.model_spread)}</td>
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<td className="px-3 py-2 text-right text-slate-600">{numberLabel(row.liquidity)}</td>
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<td className="px-3 py-2 text-right text-slate-600">{numberLabel(row.volume)}</td>
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@@ -325,7 +355,7 @@ export function MarketOpportunitiesPageClient() {
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))
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) : (
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<tr>
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<td colSpan={13} className="px-3 py-10 text-center text-sm font-semibold text-slate-400">
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<td colSpan={14} className="px-3 py-10 text-center text-sm font-semibold text-slate-400">
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当前筛选下没有低价市场机会。
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</td>
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</tr>
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@@ -103,6 +103,13 @@ def test_build_market_opportunities_scans_yes_and_no_low_price_edges():
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assert yes["model_probability"] == 0.46
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assert yes["yes_probability"] == 0.46
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assert yes["side_probability"] == 0.46
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assert yes["model_cluster_sources"] == {"ECMWF": 32.0, "GFS": 33.0, "ICON": 31.0}
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assert yes["model_min"] == 31.0
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assert yes["model_max"] == 33.0
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assert yes["models_below_bucket"] == 2
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assert yes["models_in_bucket"] == 1
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assert yes["models_above_bucket"] == 0
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assert yes["models_above_deb"] == 1
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assert yes["ask_price"] == 0.18
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assert round(yes["edge"], 2) == 0.28
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assert no["model_probability"] == 0.10
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@@ -185,7 +192,7 @@ def test_build_market_opportunities_aggregates_fahrenheit_distribution():
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assert round(rows[0]["edge"], 2) == 0.46
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def test_build_market_opportunities_filters_late_priced_no_noise():
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def test_build_market_opportunities_filters_late_priced_no_when_models_are_in_bucket():
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event = {
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"slug": "highest-temperature-in-jeddah-on-july-3-2026",
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"markets": [
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@@ -205,8 +212,8 @@ def test_build_market_opportunities_filters_late_priced_no_noise():
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row = _row("jeddah")
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row["local_time"] = "19:22"
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row["current_max_so_far"] = None
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row["deb_prediction"] = 35.3
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row["model_cluster_sources"] = {"ECMWF": 34.5, "GFS": 44.0, "ICON": 35.0}
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row["deb_prediction"] = 35.8
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row["model_cluster_sources"] = {"ECMWF": 35.7, "GFS": 36.1, "ICON": 36.2}
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row["distribution_full"] = [
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{"value": 36, "probability": 0.10},
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{"value": 37, "probability": 0.90},
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@@ -270,6 +277,50 @@ def test_build_market_opportunities_keeps_late_no_when_bucket_conflicts_with_anc
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assert rows[0]["side_probability"] == 0.90
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def test_build_market_opportunities_keeps_late_no_when_models_are_above_bucket():
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event = {
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"slug": "highest-temperature-in-jeddah-on-july-3-2026",
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"markets": [
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{
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"question": "Will the highest temperature in Jeddah be 36°C on July 3?",
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"slug": "highest-temperature-in-jeddah-on-july-3-2026-36c",
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"active": True,
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"closed": False,
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"enableOrderBook": True,
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"liquidity": "154",
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"volume": "6833",
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"outcomes": '["Yes", "No"]',
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"clobTokenIds": '["yes-36", "no-36"]',
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}
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],
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}
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row = _row("jeddah")
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row["local_time"] = "19:22"
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row["current_max_so_far"] = None
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row["deb_prediction"] = 35.3
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row["model_cluster_sources"] = {"ECMWF": 37.0, "GFS": 38.5, "ICON": 36.8}
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row["distribution_full"] = [
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{"value": 36, "probability": 0.10},
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{"value": 37, "probability": 0.90},
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]
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rows = build_market_opportunity_rows(
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[row],
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{"jeddah": event},
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{"yes-36": 0.99, "no-36": 0.01},
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max_price=0.20,
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side="both",
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positive_edge_only=True,
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min_edge=0.0,
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limit=20,
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)
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assert len(rows) == 1
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assert rows[0]["models_above_bucket"] == 3
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assert rows[0]["models_in_bucket"] == 0
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assert rows[0]["side"] == "no"
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def test_ops_market_opportunities_requires_ops_admin(monkeypatch):
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def deny(_request):
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raise HTTPException(status_code=403, detail="ops only")
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@@ -213,15 +213,21 @@ def _bucket_probability(row: Mapping[str, Any], option: Mapping[str, Any]) -> Op
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return _round_probability(probability)
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def _model_stats(row: Mapping[str, Any]) -> Tuple[Optional[float], Optional[float]]:
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def _model_sources(row: Mapping[str, Any]) -> Dict[str, float]:
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sources = row.get("model_cluster_sources") or {}
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if not isinstance(sources, Mapping):
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return None, None
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values = sorted(
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number
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for number in (_finite_number(value) for value in sources.values())
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if number is not None
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)
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return {}
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result: Dict[str, float] = {}
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for name, value in sources.items():
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number = _finite_number(value)
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if number is None:
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continue
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result[str(name)] = round(number, 1)
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return result
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def _model_stats(row: Mapping[str, Any]) -> Tuple[Optional[float], Optional[float]]:
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values = sorted(_model_sources(row).values())
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if not values:
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return None, None
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mid = len(values) // 2
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@@ -229,6 +235,42 @@ def _model_stats(row: Mapping[str, Any]) -> Tuple[Optional[float], Optional[floa
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return round(median, 1), round(max(values) - min(values), 1)
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def _model_option_relation(
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row: Mapping[str, Any],
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option: Mapping[str, Any],
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) -> Dict[str, Any]:
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sources = _model_sources(row)
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values = list(sources.values())
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lower = _finite_number(option.get("lower"))
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upper = _finite_number(option.get("upper"))
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unit = str(option.get("unit") or "").upper()
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half_width = 1.0 if "F" in unit and lower != upper else 0.5
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effective_lower = lower - half_width if lower is not None else None
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effective_upper = upper + half_width if upper is not None else None
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below = 0
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inside = 0
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above = 0
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for value in values:
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if effective_lower is not None and value < effective_lower:
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below += 1
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elif effective_upper is not None and value > effective_upper:
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above += 1
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else:
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inside += 1
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deb = _finite_number(row.get("deb_prediction"))
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above_deb = sum(1 for value in values if deb is not None and value > deb)
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return {
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"model_cluster_sources": sources,
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"model_count": len(values),
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"model_min": round(min(values), 1) if values else None,
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"model_max": round(max(values), 1) if values else None,
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"models_below_bucket": below,
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"models_in_bucket": inside,
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"models_above_bucket": above,
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"models_above_deb": above_deb,
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}
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def _local_hour(row: Mapping[str, Any]) -> Optional[int]:
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text = str(row.get("local_time") or "").strip()
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if not text:
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@@ -265,6 +307,7 @@ def _is_late_priced_no_noise(
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*,
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no_ask: float,
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model_median: Optional[float],
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model_relation: Optional[Mapping[str, Any]] = None,
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) -> bool:
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if no_ask > 0.05:
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return False
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@@ -275,6 +318,11 @@ def _is_late_priced_no_noise(
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yes_ask = _finite_number(ask_prices_by_token.get(yes_token)) if yes_token else None
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if yes_ask is not None and yes_ask < 0.80:
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return False
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relation = model_relation or _model_option_relation(row, option)
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outside = int(relation.get("models_above_bucket") or 0) + int(relation.get("models_below_bucket") or 0)
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inside = int(relation.get("models_in_bucket") or 0)
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if outside > inside:
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return False
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anchors = (
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row.get("current_max_so_far"),
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row.get("deb_prediction"),
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@@ -361,6 +409,7 @@ def build_market_opportunity_rows(
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if model_probability is None:
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continue
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tokens = _market_tokens(market)
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model_relation = _model_option_relation(scan_row, option)
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for option_side in _iter_market_sides(side):
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token_id = tokens.get(option_side)
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if not token_id:
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@@ -376,6 +425,7 @@ def build_market_opportunity_rows(
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tokens,
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no_ask=ask_number,
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model_median=model_median,
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model_relation=model_relation,
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):
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continue
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target_probability = (
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@@ -411,6 +461,7 @@ def build_market_opportunity_rows(
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"deb_prediction": _finite_number(scan_row.get("deb_prediction")),
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"model_median": model_median,
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"model_spread": model_spread,
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**model_relation,
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"local_time": scan_row.get("local_time"),
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"region": row_region,
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}
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