fix(P0-03): Prediction 幂等指纹——只追加,不覆盖

_upsert_prediction 改为 _insert_or_find_by_fingerprint:
- 同 input_hash → 返回已有行(绝不 UPDATE pred_/reasoning/agent_outputs)
- 不同 input_hash → INSERT 新行

input_hash 升级为规范 JSON SHA-256,捕获:match_id, cutoff, prompt_version,
prompt_hash, system_prompt_hash, provider, model, mode, run_type, temperature,
context_hash, agent_ids。移除旧 (match, provider, model, mode, run_type) 唯一约束,
改为 partial unique index(WHERE input_hash IS NOT NULL,兼容旧 NULL 数据)。

三条路径(single/multi/baseline)统一传足指纹字段。
迁移 0024 + 测试 test_p0_prediction_fingerprint(10/10);全量 295 通过。

src/llm/agents/orchestrator.py

@@ -12,7 +12,7 @@ from src.core.config import settings
 from src.db.base import AsyncSessionLocal
 from src.db.models import Match, Prediction
 from src.db.unit_of_work import get_uow
-from src.llm.predict import PredictResult, _upsert_prediction
+from src.llm.predict import PredictResult, _insert_or_find_by_fingerprint
 from src.llm.agents.base import AgentReport, AgentSpec, load_agent_prompt
 from src.llm.context_builder import (
     MatchHeader,
@@ -285,10 +285,13 @@ async def predict_match_multi(
 
     latency_ms = int((time.perf_counter() - start) * 1000)
 
-    # 3.5 计算输入 hash(基于终裁报告)
-    input_hash = hashlib.sha256(
-        _reports_to_json(reports).encode("utf-8")
-    ).hexdigest()
+    # P0-03: 指纹输入——终裁报告 hash 作 context_hash,专家列表作 agent_ids
+    reports_json = _reports_to_json(reports)
+    context_hash = hashlib.sha256(reports_json.encode("utf-8")).hexdigest()
+    agent_ids = sorted([r.agent for r in reports]) if reports else []
+    # 终裁模板 hash(规范:复用 prompt 版本 + 终裁 system prompt)
+    prompt_hash = hashlib.sha256(f"multi_{version}".encode("utf-8")).hexdigest()
+    system_prompt_hash = hashlib.sha256(AGGREGATOR_SYSTEM.encode("utf-8")).hexdigest()
 
     # 4. 存库(使用 UnitOfWork)
     async with get_uow() as session:
@@ -315,15 +318,20 @@ async def predict_match_multi(
             pred_status = "degraded"
             model_name = aggregator_model
 
-        pred = await _upsert_prediction(
+        pred = await _insert_or_find_by_fingerprint(
             session,
-            match_id=match_id,
-            provider_name=settings.LLM_PROVIDER,
-            model=model_name,
-            mode="multi",
-            run_type="backtest" if backtest else "live",
             values={
+                "match_id": match_id,
+                "provider": settings.LLM_PROVIDER,
+                "model": model_name,
+                "mode": "multi",
+                "run_type": "backtest" if backtest else "live",
                 "prompt_version": f"multi_{version}",
+                "prompt_hash": prompt_hash,
+                "system_prompt_hash": system_prompt_hash,
+                "temperature": 0.2,
+                "context_hash": context_hash,
+                "agent_ids": agent_ids,
                 "prompt_tokens": sum(r.prompt_tokens or 0 for r in reports) + agg_prompt_tokens,
                 "completion_tokens": sum(r.completion_tokens or 0 for r in reports) + agg_completion_tokens,
                 "latency_ms": latency_ms,
@@ -341,7 +349,6 @@ async def predict_match_multi(
                 "match_kickoff_at": match_kickoff_at,
                 "prediction_cutoff_at": prediction_cutoff_at,
                 "prediction_created_at": now,
-                "input_hash": input_hash,
             },
         )