refactor: 清理冗余代码和过时配置

.env.example

@@ -12,7 +12,6 @@ SECRET_KEY=your_random_secret_key
 
 # ─── HuggingFace / arXiv ────────────────
 HF_API_BASE=https://huggingface.co/api
-HF_PROXY=
 TOP_N=20
 HTTP_TIMEOUT_SECONDS=30
 HTTP_MAX_RETRIES=3

app/config.py

@@ -22,7 +22,6 @@ class Settings(BaseSettings):
 
     # HuggingFace / arXiv
     HF_API_BASE: str = "https://huggingface.co/api"
-    HF_PROXY: str = ""
     TOP_N: int = 20
     HTTP_TIMEOUT_SECONDS: int = 30
     HTTP_MAX_RETRIES: int = 3

app/services/pdf_image_extractor.py

@@ -501,10 +501,6 @@ def _image_sort_key(name: str) -> tuple[int, int]:
     m = re.search(r"(?:figure|table)_(\d+)", name)
     if m:
         return (0, int(m.group(1)))
-    # 旧格式：page2_img1.png, page5_table1.png, figure_1.png
-    m2 = re.search(r"page(\d+)_(?:img|table)(\d+)", name)
-    if m2:
-        return (int(m2.group(1)), int(m2.group(2)))
     return (0, 0)
 
 

app/services/pi_client.py

@@ -13,11 +13,8 @@ from pathlib import Path
 from app.config import settings
 from app.utils import truncate_error
 from app.services.summary_utils import (
-    JsonNotFoundError,
     build_prompt,
-    extract_json,
     extract_pdf_text,
-    write_meta_json,
 )
 
 logger = logging.getLogger(__name__)
@@ -25,18 +22,6 @@ logger = logging.getLogger(__name__)
 # PDF 全文注入模式的字符上限 — 超过此阈值自动切换到 search 模式
 _PDF_MAX_CHARS = 80_000
 
-# 重新导出，保持向后兼容
-__all__ = [
-    "PiTimeoutError",
-    "PiProcessError",
-    "JsonNotFoundError",
-    "call_pi",
-    "write_meta_json",
-    "extract_pdf_text",
-    "build_prompt",
-    "extract_json",
-]
-
 
 # ── 自定义异常 ──────────────────────────────────────────────────────────
 

app/services/summary_persister.py

@@ -24,22 +24,6 @@ from app.utils import TMP_DIR, truncate_error, utc_now
 logger = logging.getLogger(__name__)
 
 
-# ── FTS5 文本构建 ───────────────────────────────────────────────────────
-
-
-def _build_fts_summary_text(schema: SummarySchema) -> str:
-    """拼接用于 FTS5 索引的总结文本。"""
-    parts = [
-        schema.one_line or "",
-        schema.motivation.problem or "",
-        schema.motivation.goal or "",
-        schema.method.overview or "",
-        schema.method.key_idea or "",
-        schema.results.main_findings or "",
-    ]
-    return " ".join(p for p in parts if p)
-
-
 # ── DB 更新 ─────────────────────────────────────────────────────────────
 
 

scripts/manual_crawl.py

@@ -1,7 +0,0 @@
-"""快捷脚本：手动抓取指定日期。用法: python scripts/manual_crawl.py [YYYY-MM-DD] [--top N]"""
-
-if __name__ == "__main__":
-    import sys
-    from app.cli import cli_app
-
-    cli_app(["crawl"] + sys.argv[1:])

scripts/validate_summary.py

@@ -1,174 +0,0 @@
-import json
-import sys
-
-schema = {
-    "type": "object",
-    "required": [
-        "arxiv_id",
-        "title_zh",
-        "one_line",
-        "tags",
-        "difficulty",
-        "prerequisites",
-        "motivation",
-        "method",
-        "results",
-        "improvements",
-        "figures",
-    ],
-    "properties": {
-        "arxiv_id": {"type": "string"},
-        "title_zh": {"type": "string"},
-        "one_line": {"type": "string"},
-        "tags": {"type": "array", "items": {"type": "string"}},
-        "difficulty": {"type": "string", "enum": ["入门", "进阶", "前沿"]},
-        "prerequisites": {
-            "type": "object",
-            "required": ["concepts"],
-            "properties": {
-                "concepts": {
-                    "type": "array",
-                    "items": {
-                        "type": "object",
-                        "required": ["term", "explanation", "why_matters"],
-                        "properties": {
-                            "term": {"type": "string"},
-                            "explanation": {"type": "string"},
-                            "why_matters": {"type": "string"},
-                        },
-                    },
-                }
-            },
-        },
-        "motivation": {
-            "type": "object",
-            "required": ["problem", "goal", "gap"],
-            "properties": {
-                "problem": {"type": "string"},
-                "goal": {"type": "string"},
-                "gap": {"type": "string"},
-            },
-        },
-        "method": {
-            "type": "object",
-            "required": ["overview", "key_idea", "steps", "novelty"],
-            "properties": {
-                "overview": {"type": "string"},
-                "key_idea": {"type": "string"},
-                "steps": {"type": "string"},
-                "novelty": {"type": "string"},
-            },
-        },
-        "results": {
-            "type": "object",
-            "required": ["main_findings", "benchmarks", "limitations"],
-            "properties": {
-                "main_findings": {"type": "string"},
-                "benchmarks": {
-                    "type": "array",
-                    "items": {
-                        "type": "object",
-                        "required": [
-                            "task",
-                            "metric",
-                            "this_work",
-                            "baseline",
-                            "improvement",
-                        ],
-                        "properties": {
-                            "task": {"type": "string"},
-                            "metric": {"type": "string"},
-                            "this_work": {"type": "string"},
-                            "baseline": {"type": "string"},
-                            "improvement": {"type": "string"},
-                        },
-                    },
-                },
-                "limitations": {"type": "string"},
-            },
-        },
-        "improvements": {
-            "type": "object",
-            "required": ["weaknesses", "future_work", "reproducibility"],
-            "properties": {
-                "weaknesses": {"type": "string"},
-                "future_work": {"type": "string"},
-                "reproducibility": {"type": "string"},
-            },
-        },
-        "figures": {
-            "type": "array",
-            "items": {
-                "type": "object",
-                "required": ["id", "caption", "description", "reason", "section"],
-                "properties": {
-                    "id": {"type": "string"},
-                    "caption": {"type": "string"},
-                    "description": {"type": "string"},
-                    "reason": {"type": "string"},
-                    "section": {
-                        "type": "string",
-                        "enum": ["motivation", "method", "results", "limitations"],
-                    },
-                },
-            },
-        },
-    },
-}
-
-
-def validate_file(filepath):
-    try:
-        with open(filepath, "r", encoding="utf-8") as f:
-            data = json.load(f)
-
-        # Check required fields
-        for field in schema["required"]:
-            if field not in data:
-                print(f"❌ Missing field: {field}")
-                return False
-
-        # Validate nested structure
-        for field, spec in schema["properties"].items():
-            if field in data:
-                if spec["type"] == "string":
-                    if not isinstance(data[field], str):
-                        print(f"❌ Field '{field}' should be string")
-                        return False
-                elif spec["type"] == "array":
-                    if not isinstance(data[field], list):
-                        print(f"❌ Field '{field}' should be array")
-                        return False
-                elif spec["type"] == "object":
-                    if not isinstance(data[field], dict):
-                        print(f"❌ Field '{field}' should be object")
-                        return False
-                    if "required" in spec:
-                        for subfield in spec["required"]:
-                            if subfield not in data[field]:
-                                print(f"❌ Missing subfield: {field}.{subfield}")
-                                return False
-
-        # Validate section enum in figures
-        valid_sections = ["motivation", "method", "results", "limitations"]
-        for fig in data.get("figures", []):
-            if fig["section"] not in valid_sections:
-                print(f"❌ Invalid section in figure: {fig['section']}")
-                return False
-
-        print("✅ JSON validation passed!")
-        return True
-
-    except json.JSONDecodeError as e:
-        print(f"❌ JSON decode error: {e}")
-        return False
-    except Exception as e:
-        print(f"❌ Validation error: {e}")
-        return False
-
-
-if __name__ == "__main__":
-    filepath = (
-        sys.argv[1] if len(sys.argv) > 1 else "data/papers/2601.10592/summary.json"
-    )
-    validate_file(filepath)

tests/test_schemas.py

@@ -7,11 +7,13 @@ import json
 import pytest
 from pydantic import ValidationError
 
-from app.services.pi_client import (
+from app.services.summary_utils import (
     JsonNotFoundError,
+    extract_json as _extract_json,
+)
+from app.services.pi_client import (
     PiProcessError,
     PiTimeoutError,
-    extract_json as _extract_json,
 )
 from app.services.pdf_downloader import PdfDownloadError
 from app.services.schemas import (