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

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