feat: 可配置方案引擎通用原型（Mock 检索）

需求未定稿时可先跑通追问/判定/出方案；槽位与判定树外置 YAML，后续可接 Ragflow。

Co-authored-by: haijd <haijd@163.com>

engine/app/retrieval.py

@@ -0,0 +1,94 @@
+from __future__ import annotations
+
+from typing import Any
+
+import httpx
+
+from .config_loader import business_config
+from .settings import settings
+
+
+class RetrievalResult:
+    def __init__(self, chunks: list[dict[str, Any]]):
+        self.chunks = chunks
+
+
+def retrieve_for_scheme(slots: dict[str, str], bundle: list[str]) -> RetrievalResult:
+    backend = (settings.retrieval_backend or "mock").lower()
+    if backend == "ragflow":
+        return _retrieve_ragflow(slots, bundle)
+    return _retrieve_mock(slots, bundle)
+
+
+def _retrieve_mock(slots: dict[str, str], bundle: list[str]) -> RetrievalResult:
+    chunks = business_config.chunks
+    picked: list[dict[str, Any]] = []
+    bundle_set = set(bundle)
+    for c in chunks:
+        if c.get("product") in bundle_set:
+            picked.append(c)
+    # tag overlap with slot values
+    blob = " ".join(slots.values())
+    for c in chunks:
+        if c in picked:
+            continue
+        tags = c.get("tags") or []
+        if any(str(t) in blob for t in tags):
+            picked.append(c)
+        if len(picked) >= 4:
+            break
+    if not picked:
+        picked = chunks[:2]
+    return RetrievalResult(picked[:4])
+
+
+def _retrieve_ragflow(slots: dict[str, str], bundle: list[str]) -> RetrievalResult:
+    """Minimal Ragflow retrieval hook. Falls back to mock if not configured/unavailable."""
+    if not settings.ragflow_api_key:
+        return _retrieve_mock(slots, bundle)
+
+    query = " ".join(
+        [
+            slots.get("tech_category", ""),
+            slots.get("scenario", ""),
+            slots.get("key_metric", ""),
+            " ".join(bundle),
+        ]
+    ).strip() or "产品方案"
+    dataset_ids = [x for x in settings.ragflow_dataset_ids.split(",") if x.strip()]
+    url = settings.ragflow_base_url.rstrip("/") + "/api/v1/retrieval"
+    headers = {"Authorization": f"Bearer {settings.ragflow_api_key}"}
+    payload: dict[str, Any] = {"question": query, "top_k": 4}
+    if dataset_ids:
+        payload["dataset_ids"] = dataset_ids
+
+    try:
+        with httpx.Client(timeout=20.0) as client:
+            resp = client.post(url, headers=headers, json=payload)
+            resp.raise_for_status()
+            data = resp.json()
+    except Exception:
+        return _retrieve_mock(slots, bundle)
+
+    # Ragflow response shapes vary by version; normalize best-effort
+    records = []
+    if isinstance(data, dict):
+        records = data.get("data") or data.get("chunks") or data.get("records") or []
+        if isinstance(records, dict):
+            records = records.get("chunks") or records.get("records") or []
+    normalized = []
+    for i, r in enumerate(records[:4]):
+        if not isinstance(r, dict):
+            continue
+        normalized.append(
+            {
+                "id": r.get("id") or f"rf-{i}",
+                "title": r.get("document_keyword") or r.get("title") or "Ragflow片段",
+                "product": r.get("document_id") or "",
+                "content": r.get("content") or r.get("text") or "",
+                "tags": [],
+            }
+        )
+    if not normalized:
+        return _retrieve_mock(slots, bundle)
+    return RetrievalResult(normalized)