fix: handle None values in _extract_usage to prevent TypeError (#4244)

* fix: handle None values in _extract_usage to prevent TypeError

Some LLM providers (especially API proxies) may return None for
prompt_tokens and completion_tokens in the usage response. This
causes a TypeError when attempting arithmetic operations.

Added null checks with fallback to 0 for both prompt_tokens and
completion_tokens before performing calculations.

* refactor: use explicit None check and reuse cached variable

- Use `is None` instead of `or 0` to avoid masking unexpected falsy values
- Reuse `cached` variable for `input_cached` to avoid redundant calculation

* ruff format

---------

Co-authored-by: Soulter <905617992@qq.com>

astrbot/core/provider/sources/openai_source.py

@@ -251,10 +251,14 @@ class ProviderOpenAIOfficial(Provider):
     def _extract_usage(self, usage: CompletionUsage) -> TokenUsage:
         ptd = usage.prompt_tokens_details
         cached = ptd.cached_tokens if ptd and ptd.cached_tokens else 0
+        prompt_tokens = 0 if usage.prompt_tokens is None else usage.prompt_tokens
+        completion_tokens = (
+            0 if usage.completion_tokens is None else usage.completion_tokens
+        )
         return TokenUsage(
-            input_other=usage.prompt_tokens - cached,
-            input_cached=ptd.cached_tokens if ptd and ptd.cached_tokens else 0,
-            output=usage.completion_tokens,
+            input_other=prompt_tokens - cached,
+            input_cached=cached,
+            output=completion_tokens,
         )
 
     async def _parse_openai_completion(