refactor(backend): extract shared helper modules per architecture rules

- Add backend/ai/utils.py — parse_classification, parse_suggestions, strip_code_fences
  shared by all AI providers; removes duplicated private functions from
  anthropic_provider.py and openai_provider.py
- Add backend/deps/utils.py — get_client_ip, parse_uuid request-parsing helpers;
  removes local _ip() variants from admin.py, auth.py, shares.py, folders.py
- Add backend/storage/exceptions.py — canonical CloudConnectionError definition;
  all routers and backends import from here instead of redefining
- Move validate_password_strength to backend/services/auth.py; removes duplicated
  _validate_password_strength from admin.py and auth.py

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/ai/anthropic_provider.py

@@ -1,7 +1,6 @@
-import json
-import re
 import anthropic
 from ai.base import AIProvider, ClassificationResult
+from ai.utils import parse_classification, parse_suggestions
 
 MAX_AI_CHARS = 8_000
 
@@ -33,7 +32,7 @@ class AnthropicProvider(AIProvider):
             messages=[{"role": "user", "content": user_msg}],
         )
         raw = response.content[0].text
-        return _parse_classification(raw)
+        return parse_classification(raw)
 
     async def suggest_topics(
         self,
@@ -53,7 +52,7 @@ class AnthropicProvider(AIProvider):
             messages=[{"role": "user", "content": user_msg}],
         )
         raw = response.content[0].text
-        return _parse_suggestions(raw)
+        return parse_suggestions(raw)
 
     async def health_check(self) -> bool:
         try:
@@ -68,36 +67,3 @@ class AnthropicProvider(AIProvider):
             return False
 
 
-def _strip_code_fences(text: str) -> str:
-    text = re.sub(r"```(?:json)?\s*", "", text)
-    text = re.sub(r"```", "", text)
-    return text.strip()
-
-
-def _parse_classification(raw: str) -> ClassificationResult:
-    raw = _strip_code_fences(raw)
-    # Try to find JSON object
-    match = re.search(r"\{.*\}", raw, re.DOTALL)
-    if match:
-        try:
-            data = json.loads(match.group())
-            return ClassificationResult(
-                topics=data.get("assigned_topics", []),
-                suggested_new_topics=data.get("new_topic_suggestions", []),
-                reasoning=data.get("reasoning", ""),
-            )
-        except json.JSONDecodeError:
-            pass
-    return ClassificationResult()
-
-
-def _parse_suggestions(raw: str) -> list[str]:
-    raw = _strip_code_fences(raw)
-    match = re.search(r"\{.*\}", raw, re.DOTALL)
-    if match:
-        try:
-            data = json.loads(match.group())
-            return data.get("suggested_topics", [])
-        except json.JSONDecodeError:
-            pass
-    return []

backend/ai/openai_provider.py

@@ -1,7 +1,6 @@
-import json
-import re
 from openai import AsyncOpenAI
 from ai.base import AIProvider, ClassificationResult
+from ai.utils import parse_classification, parse_suggestions
 
 MAX_AI_CHARS = 8_000
 
@@ -35,7 +34,7 @@ class OpenAIProvider(AIProvider):
             ],
         )
         raw = response.choices[0].message.content or ""
-        return _parse_classification(raw)
+        return parse_classification(raw)
 
     async def suggest_topics(
         self,
@@ -56,7 +55,7 @@ class OpenAIProvider(AIProvider):
             ],
         )
         raw = response.choices[0].message.content or ""
-        return _parse_suggestions(raw)
+        return parse_suggestions(raw)
 
     async def health_check(self) -> bool:
         try:
@@ -70,35 +69,3 @@ class OpenAIProvider(AIProvider):
             return False
 
 
-def _strip_code_fences(text: str) -> str:
-    text = re.sub(r"```(?:json)?\s*", "", text)
-    text = re.sub(r"```", "", text)
-    return text.strip()
-
-
-def _parse_classification(raw: str) -> ClassificationResult:
-    raw = _strip_code_fences(raw)
-    match = re.search(r"\{.*\}", raw, re.DOTALL)
-    if match:
-        try:
-            data = json.loads(match.group())
-            return ClassificationResult(
-                topics=data.get("assigned_topics", []),
-                suggested_new_topics=data.get("new_topic_suggestions", []),
-                reasoning=data.get("reasoning", ""),
-            )
-        except json.JSONDecodeError:
-            pass
-    return ClassificationResult()
-
-
-def _parse_suggestions(raw: str) -> list[str]:
-    raw = _strip_code_fences(raw)
-    match = re.search(r"\{.*\}", raw, re.DOTALL)
-    if match:
-        try:
-            data = json.loads(match.group())
-            return data.get("suggested_topics", [])
-        except json.JSONDecodeError:
-            pass
-    return []

backend/ai/utils.py

@@ -0,0 +1,51 @@
+"""Shared AI response parsing utilities — used by all provider implementations."""
+from __future__ import annotations
+
+import json
+import re
+
+from ai.base import ClassificationResult
+
+
+def strip_code_fences(text: str) -> str:
+    """Remove markdown code fences (```json ... ```) from *text*."""
+    text = re.sub(r"```(?:json)?\s*", "", text)
+    text = re.sub(r"```", "", text)
+    return text.strip()
+
+
+def parse_classification(raw: str) -> ClassificationResult:
+    """Parse a classification JSON response into a ClassificationResult.
+
+    Tolerates markdown code fences and extracts the first JSON object found.
+    Returns an empty ClassificationResult on any parse failure.
+    """
+    raw = strip_code_fences(raw)
+    match = re.search(r"\{.*\}", raw, re.DOTALL)
+    if match:
+        try:
+            data = json.loads(match.group())
+            return ClassificationResult(
+                topics=data.get("assigned_topics", []),
+                suggested_new_topics=data.get("new_topic_suggestions", []),
+                reasoning=data.get("reasoning", ""),
+            )
+        except json.JSONDecodeError:
+            pass
+    return ClassificationResult()
+
+
+def parse_suggestions(raw: str) -> list[str]:
+    """Parse a topic-suggestion JSON response into a list of topic name strings.
+
+    Tolerates markdown code fences. Returns an empty list on parse failure.
+    """
+    raw = strip_code_fences(raw)
+    match = re.search(r"\{.*\}", raw, re.DOTALL)
+    if match:
+        try:
+            data = json.loads(match.group())
+            return data.get("suggested_topics", [])
+        except json.JSONDecodeError:
+            pass
+    return []