feat: Paperless integration (content endpoint, list+sync). Add /paperless/sync and docs

README.md

@@ -212,6 +212,22 @@ curl -s -X POST http://localhost:26000/paperless/hook \
 
 해당 훅은 문서 도착을 통지받는 용도로 제공됩니다. 실제 본문 텍스트는 Paperless API로 조회해 `/index/upsert`로 추가하세요.
 
+### Paperless 배치 동기화(`/paperless/sync`)
+
+Paperless에서 다수 문서를 일괄 인덱싱합니다.
+
+```bash
+curl -s -X POST http://localhost:26000/paperless/sync \
+  -H 'Content-Type: application/json' -H 'X-API-Key: <키>' \
+  -d '{
+    "page_size": 50,
+    "ordering": "-created",
+    "tags": null,
+    "query": null,
+    "limit": 200
+  }'
+```
+
 ## 시놀로지 메일/오피스 연동 가이드(요약)
 
 - **검색/QA 호출 엔드포인트**: `http://<AI서버IP>:26000/search`, `http://<AI서버IP>:26000/chat`
@@ -229,6 +245,7 @@ curl -s -X POST http://localhost:26000/paperless/hook \
 - `BASE_MODEL`(기본 `qwen2.5:7b-instruct`)
 - `BOOST_MODEL`(기본 `qwen2.5:14b-instruct`)
 - `ENGLISH_MODEL`(기본 `llama3:8b-instruct`): 영어 감지 시 라우팅 대상
+- `ENGLISH_RATIO_THRESHOLD`(기본 `0.65`): 영어 비율 임계값(초과 시 영어 모델)
 - `EMBEDDING_MODEL`(기본 `nomic-embed-text`)
 - `INDEX_PATH`(기본 `data/index.jsonl`)
 - `PAPERLESS_BASE_URL`, `PAPERLESS_TOKEN`(선택): Paperless API 연동 시 사용

server/config.py

@@ -10,6 +10,7 @@ class Settings:
     base_model: str = os.getenv("BASE_MODEL", "qwen2.5:7b-instruct")
     boost_model: str = os.getenv("BOOST_MODEL", "qwen2.5:14b-instruct")
     english_model: str = os.getenv("ENGLISH_MODEL", "llama3:8b-instruct")
+    english_ratio_threshold: float = float(os.getenv("ENGLISH_RATIO_THRESHOLD", "0.65"))
     embedding_model: str = os.getenv("EMBEDDING_MODEL", "nomic-embed-text")
     index_path: str = os.getenv("INDEX_PATH", "data/index.jsonl")
 

server/main.py

@@ -90,7 +90,7 @@ def chat(req: ChatRequest) -> Dict[str, Any]:
         non_ascii_letters = sum((not ch.isascii()) and ch.isalpha() for ch in user_text)
         english_ratio = ascii_letters / max(ascii_letters + non_ascii_letters, 1)
         total_chars = len(user_text)
-        if english_ratio > 0.8:
+        if english_ratio > settings.english_ratio_threshold:
             model = settings.english_model
         else:
             model = settings.boost_model if (req.force_boost or total_chars > 2000) else settings.base_model
@@ -175,6 +175,55 @@ def paperless_hook(hook: PaperlessHook, _: None = Depends(require_api_key)) -> D
     return {"status": "indexed", "document_id": hook.document_id, "chunks": added}
 
 
+class PaperlessSyncRequest(BaseModel):
+    page_size: int = 50
+    ordering: str = "-created"
+    tags: List[int] | None = None
+    query: str | None = None
+    limit: int = 200
+
+
+@app.post("/paperless/sync")
+def paperless_sync(req: PaperlessSyncRequest, _: None = Depends(require_api_key)) -> Dict[str, Any]:
+    client = PaperlessClient(settings.paperless_base_url, settings.paperless_token)
+    from .index_store import IndexRow
+    added_total = 0
+    next_url: str | None = None
+    fetched = 0
+
+    while True:
+        if next_url:
+            import requests as _rq
+            resp = _rq.get(next_url, headers=client._headers(), timeout=60)
+            resp.raise_for_status()
+            data = resp.json()
+        else:
+            data = client.list_documents(page_size=req.page_size, ordering=req.ordering, tags=req.tags, query=req.query)
+        results = data.get("results", [])
+        to_append: List[IndexRow] = []
+        for doc in results:
+            doc_id = doc.get("id")
+            if not doc_id:
+                continue
+            text = client.get_document_text(int(doc_id))
+            if not text:
+                continue
+            parts = chunk_text(text)
+            for i, t in enumerate(parts):
+                vec = ollama.embeddings(settings.embedding_model, t)
+                to_append.append(IndexRow(id=f"paperless:{doc_id}:{i}", text=t, vector=vec, source="paperless"))
+        if to_append:
+            added_total += index.append(to_append)
+        fetched += len(results)
+        if fetched >= req.limit:
+            break
+        next_url = data.get("next")
+        if not next_url:
+            break
+
+    return {"status": "synced", "added": added_total}
+
+
 # OpenAI-compatible chat completions (minimal)
 class ChatCompletionsRequest(BaseModel):
     model: str | None = None

server/paperless_client.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import os
-from typing import Any, Dict
+from typing import Any, Dict, List, Optional
 import requests
 
 
@@ -16,15 +16,47 @@ class PaperlessClient:
             headers["Authorization"] = f"Token {self.token}"
         return headers
 
-    def get_document_text(self, doc_id: int) -> str:
+    def get_document(self, doc_id: int) -> Dict[str, Any]:
         if not self.base_url:
             raise RuntimeError("PAPERLESS_BASE_URL not configured")
-        # Example endpoint; adjust to real Paperless API
         url = f"{self.base_url}/api/documents/{doc_id}/"
         resp = requests.get(url, headers=self._headers(), timeout=60)
         resp.raise_for_status()
-        data = resp.json()
-        # Prefer content field if available; else title
-        text = data.get("content", "") or data.get("notes", "") or data.get("title", "")
-        return text
+        return resp.json()
+
+    def get_document_text(self, doc_id: int) -> str:
+        if not self.base_url:
+            raise RuntimeError("PAPERLESS_BASE_URL not configured")
+        # Try content endpoint
+        url_content = f"{self.base_url}/api/documents/{doc_id}/content/"
+        try:
+            r = requests.get(url_content, headers=self._headers(), timeout=60)
+            if r.status_code == 200 and r.text:
+                return r.text
+        except Exception:
+            pass
+        # Try txt download
+        url_txt = f"{self.base_url}/api/documents/{doc_id}/download/?format=txt"
+        try:
+            r = requests.get(url_txt, headers=self._headers(), timeout=60)
+            if r.status_code == 200 and r.text:
+                return r.text
+        except Exception:
+            pass
+        # Fallback to metadata fields
+        data = self.get_document(doc_id)
+        return data.get("content", "") or data.get("notes", "") or data.get("title", "")
+
+    def list_documents(self, page_size: int = 50, ordering: str = "-created", tags: Optional[List[int]] = None, query: Optional[str] = None) -> Dict[str, Any]:
+        if not self.base_url:
+            raise RuntimeError("PAPERLESS_BASE_URL not configured")
+        params: Dict[str, Any] = {"page_size": page_size, "ordering": ordering}
+        if tags:
+            params["tags__id__in"] = ",".join(str(t) for t in tags)
+        if query:
+            params["query"] = query
+        url = f"{self.base_url}/api/documents/"
+        resp = requests.get(url, headers=self._headers(), params=params, timeout=60)
+        resp.raise_for_status()
+        return resp.json()