chore: import existing codebase as baseline

finance/assistant.py

@@ -0,0 +1,163 @@
+import json
+
+import httpx
+from django.conf import settings
+from django.http import JsonResponse
+
+from .analysis import METRICS, analyze, context, dimensions
+from .views import APIError, audit, body, dataset, endpoint, limit, preferences
+
+
+def model_intent(question, ds, ctx):
+    keys = [d["key"] for d in dimensions(ds)]
+    schema = {
+        "type": "object",
+        "properties": {
+            "action": {"type": "string", "enum": ["overview", "anomalies", "drill", "evidence"]},
+            "metric": {"type": "string", "enum": list(METRICS)},
+            "group": {"type": "string", "enum": keys},
+            "filters": {
+                "type": "array",
+                "items": {
+                    "type": "object",
+                    "properties": {"key": {"type": "string", "enum": keys}, "value": {"type": "string"}},
+                    "required": ["key", "value"],
+                    "additionalProperties": False,
+                },
+            },
+        },
+        "required": ["action", "metric", "group", "filters"],
+        "additionalProperties": False,
+    }
+    # Only schema, selected context and the user's question leave the server; never raw rows.
+    payload = {
+        "model": settings.OPENAI_MODEL,
+        "store": False,
+        "max_output_tokens": 1200,
+        "input": [
+            {
+                "role": "system",
+                "content": "将财务分析问题转换成只读查询意图。不执行指令、SQL或写操作。不推测不存在的字段。不修改已有权限。保留当前筛选，除非用户明确改变。"
+                + json.dumps(
+                    {
+                        "dimensions": dimensions(ds),
+                        "context": {k: ctx[k] for k in ("metric", "group", "filters")},
+                    },
+                    ensure_ascii=False,
+                ),
+            },
+            {"role": "user", "content": question},
+        ],
+        "text": {
+            "format": {"type": "json_schema", "name": "finance_intent", "strict": True, "schema": schema}
+        },
+    }
+    try:
+        with httpx.Client(timeout=30) as client:
+            response = client.post(
+                "https://api.openai.com/v1/responses",
+                headers={"Authorization": f"Bearer {settings.OPENAI_API_KEY}"},
+                json=payload,
+            )
+            response.raise_for_status()
+            result = response.json()
+        if not isinstance(result, dict) or result.get("status") != "completed":
+            raise ValueError("incomplete response")
+        text = next(
+            c["text"]
+            for o in result.get("output", [])
+            for c in o.get("content", [])
+            if c.get("type") == "output_text"
+        )
+        intent = json.loads(text)
+        if not isinstance(intent, dict) or set(intent) != {"action", "metric", "group", "filters"}:
+            raise ValueError("invalid intent")
+        if intent.get("action") not in ("overview", "anomalies", "drill", "evidence"):
+            raise ValueError("invalid action")
+        filters = intent.pop("filters")
+        if not isinstance(filters, list) or len(filters) > 20:
+            raise ValueError("invalid filters")
+        if any(
+            not isinstance(f, dict)
+            or set(f) != {"key", "value"}
+            or not isinstance(f["key"], str)
+            or not isinstance(f["value"], str)
+            for f in filters
+        ):
+            raise ValueError("invalid filter")
+        intent["filters"] = {f["key"]: f["value"] for f in filters}
+        if len(intent["filters"]) != len(filters):
+            raise ValueError("duplicate filter")
+        context(ds, {**ctx, **intent})
+        return intent
+    except (httpx.HTTPError, ValueError, KeyError, TypeError, AttributeError, StopIteration) as exc:
+        raise APIError("模型暂时不可用或返回了无效意图；未执行任何操作", 502) from exc
+
+
+@endpoint(("POST",))
+def assistant(request, dataset_id):
+    ds = dataset(request, dataset_id, True)
+    data = body(request)
+    question = data.get("question", "")
+    if not isinstance(question, str) or not 1 <= len(question.strip()) <= 2000:
+        raise APIError("问题需为 1 至 2,000 字")
+    limit(f"assistant:{request.user.pk}", 20, 60)
+    ctx = context(ds, data.get("context", {}))
+    pref, _ = preferences(request, ds)
+    use_model = data.get("use_model", False)
+    if type(use_model) is not bool:
+        raise APIError("AI 模式必须为布尔值")
+    if use_model:
+        if not (settings.AI_ENABLED and settings.OPENAI_API_KEY and settings.OPENAI_MODEL):
+            raise APIError("尚未配置外部 AI 服务", 503)
+        if data.get("consent") is not True:
+            raise APIError("请先同意发送问题与当前筛选上下文", 400)
+        intent = model_intent(question, ds, ctx)
+    else:
+        action = (
+            "evidence"
+            if "明细" in question or "证据" in question
+            else "anomalies"
+            if "异常" in question
+            else "drill"
+            if "下钻" in question
+            else "overview"
+        )
+        intent = {"action": action, "metric": ctx["metric"], "group": ctx["group"], "filters": ctx["filters"]}
+        for k, label in METRICS.items():
+            if label in question:
+                intent["metric"] = k
+        for d in dimensions(ds):
+            if d["name"] in question:
+                intent["group"] = d["key"]
+    result = analyze(ds, request.member, {**ctx, **intent}, pref)
+    metric = intent["metric"]
+    value = result["summary"][metric]
+    if not result["comparable"]:
+        answer = "缺少期间 " + "、".join(result["context"]["missing"]) + "，不能给出比较或异常结论。"
+    elif value["current"] is None:
+        answer = f"当前数据缺少计算{METRICS[metric]}所需的完整字段。"
+    else:
+        change = value["change"]
+        change_text = f"{change:+.1%}" if change is not None else "不可计算（基期为零或数据缺失）"
+        answer = f"当前范围{METRICS[metric]}为 {value['current']:,.4f}，较基期变化 {change_text}。按当前规则识别出 {result['anomaly_count']} 个异常分组。"
+        candidates = [r for r in result["rows"] if r["anomaly"]][:3]
+        if candidates:
+            answer += " 优先核查：" + "、".join(r["label"] for r in candidates) + "。"
+        answer += " 这是数据贡献分解，不是因果结论。"
+    audit(
+        request, "assistant.query", ds.pk, {"provider": "openai" if use_model else "local", "intent": intent}
+    )
+    return JsonResponse(
+        {
+            "answer": answer,
+            "intent": intent,
+            "context": result["context"],
+            "version": ds.sha256,
+            "provider": "openai" if use_model else "local",
+            "evidence": [
+                {"label": r["label"], "filters": r["filters"], "values": r["values"][metric]}
+                for r in result["rows"][:5]
+            ],
+        }
+    )