fix(llm): coerce None output_tokens to 0 in completion_result_to_response (#809)

Some providers return output_tokens=None on certain completions (observed with
Gemini on tool-loop completions). HonchoLLMCallResponse types output_tokens as
int, so the None propagates into a Pydantic validation error that aborts the
call. In practice this surfaces in the Dreamer: a dream starts, deduction
succeeds, then induction crashes before inductive conclusions are persisted.

Coerce None -> 0 so token accounting degrades gracefully (under-counts rather
than crashing) for providers that omit output token counts.

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

src/llm/executor.py

@@ -167,7 +167,7 @@ def completion_result_to_response(
     return HonchoLLMCallResponse(
         content=result.content,
         input_tokens=result.input_tokens,
-        output_tokens=result.output_tokens,
+        output_tokens=result.output_tokens or 0,
         cache_creation_input_tokens=result.cache_creation_input_tokens,
         cache_read_input_tokens=result.cache_read_input_tokens,
         finish_reasons=[result.finish_reason] if result.finish_reason else [],