feat: add AI embedding dimension configuration

api/routes/config.py

@@ -1,10 +1,11 @@
 import httpx
 import time
-from fastapi import APIRouter, Depends, Form
+from fastapi import APIRouter, Depends, Form, HTTPException
 from typing import Annotated
 from services.config import ConfigCenter, VERSION
 from services.auth import get_current_active_user, User, has_users
 from api.response import success
+from services.vector_db import VectorDBService
 router = APIRouter(prefix="/api/config", tags=["config"])
 
 
@@ -23,8 +24,27 @@ async def set_config(
     key: str = Form(...),
     value: str = Form(...)
 ):
-    await ConfigCenter.set(key, value)
-    return success({"key": key, "value": value})
+    original_value = await ConfigCenter.get(key)
+    value_to_save = value
+    if key == "AI_EMBED_DIM":
+        try:
+            parsed_value = int(value)
+        except (TypeError, ValueError):
+            raise HTTPException(status_code=400, detail="AI_EMBED_DIM must be an integer")
+        if parsed_value <= 0:
+            raise HTTPException(status_code=400, detail="AI_EMBED_DIM must be greater than zero")
+        value_to_save = str(parsed_value)
+
+    await ConfigCenter.set(key, value_to_save)
+
+    if key == "AI_EMBED_DIM" and str(original_value) != value_to_save:
+        try:
+            service = VectorDBService()
+            service.clear_all_data()
+        except Exception as exc:
+            raise HTTPException(status_code=500, detail=f"Failed to clear vector database: {exc}")
+
+    return success({"key": key, "value": value_to_save})
 
 
 @router.get("/all")