Initial commit of integrated agent system

backend/tests/test_llm_enricher.py

@@ -0,0 +1,133 @@
+# -*- coding: utf-8 -*-
+
+from backend.enrich import llm_enricher
+
+
+class DummyResponse:
+    def __init__(self, metadata):
+        self.metadata = metadata
+
+
+class DummyModel:
+    def __init__(self, metadata):
+        self.metadata = metadata
+        self.calls = []
+
+    async def __call__(self, messages, structured_model=None, **kwargs):
+        self.calls.append(
+            {
+                "messages": messages,
+                "structured_model": structured_model,
+                "kwargs": kwargs,
+            }
+        )
+        return DummyResponse(self.metadata)
+
+
+def test_analyze_news_row_with_llm_uses_agentscope_model(monkeypatch):
+    model = DummyModel(
+        {
+            "id": "news-1",
+            "relevance": "high",
+            "sentiment": "positive",
+            "key_discussion": "Demand remains resilient",
+            "summary": "Structured summary",
+            "reason_growth": "Orders improved",
+            "reason_decrease": "",
+        }
+    )
+    monkeypatch.setattr(llm_enricher, "llm_enrichment_enabled", lambda: True)
+    monkeypatch.setattr(llm_enricher, "_get_explain_model", lambda: model)
+    monkeypatch.setattr(
+        llm_enricher,
+        "get_explain_model_info",
+        lambda: {"provider": "DASHSCOPE", "model_name": "qwen-max", "label": "DASHSCOPE:qwen-max"},
+    )
+
+    result = llm_enricher.analyze_news_row_with_llm(
+        {
+            "id": "news-1",
+            "title": "Apple expands AI features",
+            "summary": "New devices and software updates were announced.",
+        }
+    )
+
+    assert result["sentiment"] == "positive"
+    assert result["summary"] == "Structured summary"
+    assert result["raw_json"]["model_label"] == "DASHSCOPE:qwen-max"
+    assert model.calls
+    assert model.calls[0]["structured_model"] is llm_enricher.EnrichedNewsItem
+
+
+def test_analyze_news_rows_with_llm_uses_agentscope_structured_batch(monkeypatch):
+    model = DummyModel(
+        {
+            "items": [
+                {
+                    "id": "news-1",
+                    "relevance": "high",
+                    "sentiment": "negative",
+                    "key_discussion": "Margin pressure",
+                    "summary": "Batch summary",
+                    "reason_growth": "",
+                    "reason_decrease": "Costs rose",
+                }
+            ]
+        }
+    )
+    monkeypatch.setattr(llm_enricher, "llm_enrichment_enabled", lambda: True)
+    monkeypatch.setattr(llm_enricher, "_get_explain_model", lambda: model)
+    monkeypatch.setattr(
+        llm_enricher,
+        "get_explain_model_info",
+        lambda: {"provider": "DASHSCOPE", "model_name": "qwen-max", "label": "DASHSCOPE:qwen-max"},
+    )
+
+    result = llm_enricher.analyze_news_rows_with_llm(
+        [
+            {
+                "id": "news-1",
+                "title": "Apple margins pressured",
+                "summary": "Costs increased this quarter.",
+            }
+        ]
+    )
+
+    assert result["news-1"]["sentiment"] == "negative"
+    assert result["news-1"]["reason_decrease"] == "Costs rose"
+    assert result["news-1"]["raw_json"]["model_label"] == "DASHSCOPE:qwen-max"
+    assert model.calls
+    assert model.calls[0]["structured_model"] is llm_enricher.EnrichedNewsBatch
+
+
+def test_analyze_range_with_llm_uses_agentscope_structured_output(monkeypatch):
+    model = DummyModel(
+        {
+            "summary": "该股在区间内震荡下行，相关新闻主要集中在盈利预期和供应链扰动。",
+            "trend_analysis": "前半段受利空新闻压制，后半段跌幅收敛。",
+            "bullish_factors": ["估值消化后出现部分承接"],
+            "bearish_factors": ["盈利预期下修", "供应链扰动持续"],
+        }
+    )
+    monkeypatch.setattr(llm_enricher, "llm_range_analysis_enabled", lambda: True)
+    monkeypatch.setattr(llm_enricher, "_get_explain_model", lambda: model)
+    monkeypatch.setattr(
+        llm_enricher,
+        "get_explain_model_info",
+        lambda: {"provider": "DASHSCOPE", "model_name": "qwen-max", "label": "DASHSCOPE:qwen-max"},
+    )
+
+    result = llm_enricher.analyze_range_with_llm(
+        {
+            "ticker": "AAPL",
+            "start_date": "2026-03-10",
+            "end_date": "2026-03-16",
+            "price_change_pct": -3.42,
+        }
+    )
+
+    assert result["summary"].startswith("该股在区间内震荡下行")
+    assert result["model_label"] == "DASHSCOPE:qwen-max"
+    assert result["bearish_factors"] == ["盈利预期下修", "供应链扰动持续"]
+    assert model.calls
+    assert model.calls[0]["structured_model"] is llm_enricher.RangeAnalysisPayload