Improve LLM rewrite classification pipeline

ai_daily_report/assemble.py

@@ -54,10 +54,6 @@ def assemble_markdown(items: list[NewsItem], guide: dict[str, Any] | None = None
     intro = _ensure_sentence(str(guide.get("intro") or "")) or _fallback_intro(items)
     lines.extend(["## 引言", "", f"> {intro}", ""])
 
-    theme = _clean_text(str(guide.get("theme") or ""))
-    if theme:
-        lines.extend(["## 导览", "", f"> {_ensure_sentence(theme)}", ""])
-
     item_number = 1
     for section in SECTION_ORDER:
         section_items = [item for item in items if item.section == section]

ai_daily_report/classify.py

@@ -75,10 +75,18 @@ def rank_score(item: NewsItem) -> int:
 
 
 def classify_and_order_items(items: list[NewsItem]) -> tuple[list[NewsItem], dict[str, Any]]:
+    llm_classified = 0
     hint_classified = 0
     rule_classified = 0
+    invalid_llm_section_count = 0
 
     for item in items:
+        if item.section:
+            if item.section in SECTION_ORDER:
+                llm_classified += 1
+                continue
+            invalid_llm_section_count += 1
+
         mapped = normalize_section_hint(item.section_hint)
         if mapped:
             item.section = mapped
@@ -102,8 +110,9 @@ def classify_and_order_items(items: list[NewsItem]) -> tuple[list[NewsItem], dic
         "section_counts": dict(section_counts),
         "hint_classified": hint_classified,
         "rule_classified": rule_classified,
-        "llm_classified": 0,
+        "llm_classified": llm_classified,
-        "fallback_classified": 0,
+        "fallback_classified": hint_classified + rule_classified,
+        "invalid_llm_section_count": invalid_llm_section_count,
         "invalid_section_count": sum(1 for item in ordered if item.section not in SECTION_ORDER),
     }
     return ordered, report

ai_daily_report/rewrite.py

@@ -4,6 +4,7 @@ import json
 from typing import Any, Callable
 from urllib.error import HTTPError
 
+from .classify import SECTION_ORDER
 from .llm import parse_json_object
 from .models import NewsItem
 
@@ -18,9 +19,21 @@ def _chunks(items: list[NewsItem], size: int) -> list[list[NewsItem]]:
 def _build_prompt(batch: list[NewsItem]) -> str:
     payload = {
         "task": (
-            "Rewrite AI news titles and summaries into concise Chinese. Preserve brand/model/API names "
+            "For each AI news item, translate when needed, rewrite the title and summary into concise Chinese, "
-            "such as GPT-5, Codex, Gemini, Claude, API, MCP. Do not add facts."
+            "and classify it into exactly one allowed section. Preserve brand/model/API names such as GPT-5, "
+            "Codex, Gemini, Claude, API, MCP. Do not add facts."
         ),
+        "allowed_sections": SECTION_ORDER,
+        "section_guidance": {
+            "模型与能力": "model releases, capability upgrades, modalities, context windows, inference, benchmarks tied to model ability",
+            "产品与应用": "end-user products, apps, agents, workflows, product launches, practical business or consumer use cases",
+            "开发与基础设施": "developer tools, APIs, SDKs, MCP, frameworks, deployment, chips, cloud, infra, open source engineering",
+            "公司与资本": "company strategy, financing, IPO, acquisitions, partnerships, revenue, business competition",
+            "政策与安全": "policy, regulation, safety, privacy, copyright, misuse, security incidents, governance",
+            "论文与研究": "papers, academic research, arXiv, methods, experiments, datasets, evaluations",
+            "观点与教程": "opinions, analysis, explainers, tutorials, guides, practices",
+            "人物与动态": "people-focused interviews, speeches, career moves, public appearances",
+        },
         "items": [
             {
                 "id": item.id,
@@ -28,6 +41,7 @@ def _build_prompt(batch: list[NewsItem]) -> str:
                 "summary_raw": item.summary_raw,
                 "source": item.source_label,
                 "language_hint": item.language_hint,
+                "source_section_hint": item.section_hint,
             }
             for item in batch
         ],
@@ -37,6 +51,8 @@ def _build_prompt(batch: list[NewsItem]) -> str:
                     "id": "item id",
                     "title": "display title",
                     "summary": "display summary",
+                    "section": "one allowed section",
+                    "confidence": 0.0,
                     "flags": [],
                 }
             ]
@@ -58,13 +74,14 @@ def _is_transient_llm_error(exc: Exception) -> bool:
     return False
 
 
-def _apply_rewrite_batch(batch: list[NewsItem], llm_call: RewriteLlmCall) -> int:
+def _apply_rewrite_batch(batch: list[NewsItem], llm_call: RewriteLlmCall) -> tuple[int, int]:
     obj = parse_json_object(llm_call(_build_prompt(batch)))
     rewrites = obj.get("rewrites", [])
     if not isinstance(rewrites, list):
         raise ValueError("rewrites is not a list")
     by_id = {item.id: item for item in batch}
     seen_ids: set[str] = set()
+    section_count = 0
     for entry in rewrites:
         item_id = entry.get("id")
         title = str(entry.get("title") or "").strip()
@@ -72,8 +89,12 @@ def _apply_rewrite_batch(batch: list[NewsItem], llm_call: RewriteLlmCall) -> int
         if item_id in by_id and title and summary:
             by_id[item_id].title = title
             by_id[item_id].summary = summary
+            section = str(entry.get("section") or "").strip()
+            if section in SECTION_ORDER:
+                by_id[item_id].section = section
+                section_count += 1
             seen_ids.add(item_id)
-    return len(seen_ids)
+    return len(seen_ids), section_count
 
 
 def rewrite_items(
@@ -85,14 +106,16 @@ def rewrite_items(
     retry_single_items: bool = False,
 ) -> tuple[list[NewsItem], dict[str, Any]]:
     rewritten_count = 0
+    llm_section_count = 0
     fallback_count = 0
     missing_rewrite_count = 0
     errors: list[str] = []
 
     for batch in _chunks(items, max(1, batch_size)):
         try:
-            batch_rewritten_count = _apply_rewrite_batch(batch, llm_call)
+            batch_rewritten_count, batch_section_count = _apply_rewrite_batch(batch, llm_call)
             rewritten_count += batch_rewritten_count
+            llm_section_count += batch_section_count
             for item in batch:
                 if item.title is None or item.summary is None:
                     errors.append(f"missing_rewrite_for_item: {item.id}")
@@ -113,7 +136,9 @@ def rewrite_items(
                 continue
             for item in batch:
                 try:
-                    rewritten_count += _apply_rewrite_batch([item], llm_call)
+                    item_rewritten_count, item_section_count = _apply_rewrite_batch([item], llm_call)
+                    rewritten_count += item_rewritten_count
+                    llm_section_count += item_section_count
                 except Exception as item_exc:
                     errors.append(f"item:{item.id}:{type(item_exc).__name__}: {item_exc}")
                     _fallback(item)
@@ -127,6 +152,7 @@ def rewrite_items(
     report = {
         "input_count": len(items),
         "rewritten_count": rewritten_count,
+        "llm_section_count": llm_section_count,
         "fallback_count": fallback_count,
         "missing_rewrite_count": missing_rewrite_count,
         "fallback_ratio": round(fallback_ratio, 4),

tests/test_markdown_rendering.py

@@ -27,7 +27,7 @@ class MarkdownRenderingTests(unittest.TestCase):
 
         md, _ = assemble_markdown(items, guide)
 
-        self.assertIn("## 导览", md)
+        self.assertNotIn("## 导览", md)
         self.assertIn("## 模型与能力", md)
         self.assertIn("[OpenAI：Blog ↗](https://openai.com/blog/test)", md)
         self.assertNotIn("> >", md)

tests/test_stage0_to_5_pipeline.py

@@ -37,6 +37,7 @@ class Stage0To5PipelineTests(unittest.TestCase):
                             "id": entry["id"],
                             "title": entry["title_raw"],
                             "summary": entry["summary_raw"],
+                            "section": "模型与能力" if "GPT-5" in entry["title_raw"] else "公司与资本",
                             "flags": [],
                         }
                         for entry in payload["items"]

tests/test_stage0_to_7_pipeline.py

@@ -66,7 +66,7 @@ class Stage0To7PipelineTests(unittest.TestCase):
             guide_llm_call=guide_llm_call,
         )
 
-        self.assertIn("## 导览", result["markdown"])
+        self.assertNotIn("## 导览", result["markdown"])
         self.assertIn("## 模型与能力", result["markdown"])
         self.assertIn("## 今日脉络", result["markdown"])
         self.assertEqual(result["reports"]["stage7"]["blocking_errors"], [])

tests/test_stage4_rewrite.py

@@ -48,6 +48,31 @@ class Stage4RewriteTests(unittest.TestCase):
         self.assertEqual(report["rewritten_count"], 1)
         self.assertEqual(report["fallback_count"], 0)
 
+    def test_rewrite_items_accepts_llm_section_classification(self):
+        items = [news_item("a")]
+
+        def llm_call(prompt):
+            return json.dumps(
+                {
+                    "rewrites": [
+                        {
+                            "id": "a",
+                            "title": "OpenAI 发布 GPT-5 API",
+                            "summary": "OpenAI 发布 GPT-5 API，延迟表现更好。",
+                            "section": "模型与能力",
+                            "confidence": 0.92,
+                            "flags": [],
+                        }
+                    ]
+                },
+                ensure_ascii=False,
+            )
+
+        rewritten, report = rewrite_items(items, llm_call=llm_call, batch_size=10)
+
+        self.assertEqual(rewritten[0].section, "模型与能力")
+        self.assertEqual(report["llm_section_count"], 1)
+
     def test_rewrite_items_falls_back_when_llm_fails(self):
         items = [news_item("a")]
 

tests/test_stage5_classify.py

@@ -45,6 +45,33 @@ class Stage5ClassifyTests(unittest.TestCase):
         self.assertEqual(by_id["b"].section, "开发与基础设施")
         self.assertEqual(report["rule_classified"], 2)
 
+    def test_classify_prefers_valid_llm_section_from_rewrite_stage(self):
+        item = news_item(
+            "a",
+            "API 发布",
+            summary="这其实是一个面向开发者的基础设施能力更新。",
+            section_hint="产品发布/更新",
+        )
+        item.section = "开发与基础设施"
+
+        classified, report = classify_and_order_items([item])
+
+        self.assertEqual(classified[0].section, "开发与基础设施")
+        self.assertEqual(report["llm_classified"], 1)
+        self.assertEqual(report["hint_classified"], 0)
+        self.assertEqual(report["rule_classified"], 0)
+
+    def test_classify_falls_back_when_llm_section_is_invalid(self):
+        item = news_item("a", "GPT-5 发布", section_hint="模型发布/更新")
+        item.section = "热点新闻"
+
+        classified, report = classify_and_order_items([item])
+
+        self.assertEqual(classified[0].section, "模型与能力")
+        self.assertEqual(report["llm_classified"], 0)
+        self.assertEqual(report["hint_classified"], 1)
+        self.assertEqual(report["invalid_llm_section_count"], 1)
+
     def test_classify_orders_items_by_local_rank_score_within_sections(self):
         items = [
             news_item("low", "普通模型更新", section_hint="模型发布/更新", source_priority=80),

tests/test_stage7_assemble.py

@@ -45,8 +45,8 @@ class Stage7AssembleTests(unittest.TestCase):
         md, report = assemble_markdown(items, guide)
 
         self.assertTrue(md.startswith("## 引言\n\n> 今天的 AI 行业继续围绕模型、产品和资本展开。"))
-        self.assertIn("## 导览", md)
+        self.assertNotIn("## 导览", md)
-        self.assertIn("> 模型和资本两条线都在推进。", md)
+        self.assertNotIn("> 模型和资本两条线都在推进。", md)
         self.assertIn("## 模型与能力", md)
         self.assertIn("**1. GPT-5 API 发布**", md)
         self.assertIn("**2. Anthropic 提交 IPO 文件**", md)