fix: report cache reads in streaming and correct cost calculation (#577)

* fix: report cache reads in streaming and correct cost calculation

Fix two bugs in how the OpenAI-to-Anthropic shim handles cached tokens:

1. codexShim: streaming message_delta missing cache_read_input_tokens
   The codexStreamToAnthropic() function builds the final message_delta
   usage object inline (not through makeUsage()), and only included
   input_tokens and output_tokens. cache_read_input_tokens was always 0,
   so /cost never showed cache reads for Responses API models (GPT-5+).

   Also fix makeUsage() to read input_tokens_details.cached_tokens and
   prompt_tokens_details.cached_tokens for the non-streaming path.

2. Both shims: cost double-counting from convention mismatch
   OpenAI includes cached tokens in input_tokens/prompt_tokens (i.e.,
   input_tokens = uncached + cached). Anthropic treats input_tokens as
   uncached only. The cost formula was:
     cost = input_tokens * inputRate + cache_read * cacheRate
   This double-counts cached tokens. Fix by subtracting cached from
   input during the conversion:
     input_tokens = prompt_tokens - cached_tokens

   In practice this was inflating reported costs by ~2x for sessions
   with high cache hit rates (which is most sessions, since Copilot
   auto-caches server-side).

Fixes #515

* fix: omit zero cache read/write fields from /cost output

Only show "cache read" and "cache write" in /cost per-model usage when
the value is > 0. Providers like GitHub Copilot never report
cache_creation_input_tokens (the server manages its own cache), so
showing "0 cache write" on every line is misleading — it implies caching
is not working when it actually is.

Before:
  claude-haiku:  2.6k input, 151 output, 39.8k cache read, 0 cache write ($0.04)

After:
  claude-haiku:  2.6k input, 151 output, 39.8k cache read ($0.04)

---------

Co-authored-by: Zartris <14197299+Zartris@users.noreply.github.com>

src/services/api/openaiShim.ts

@@ -564,11 +564,14 @@ function convertChunkUsage(
 ): Partial<AnthropicUsage> | undefined {
   if (!usage) return undefined
 
+  const cached = usage.prompt_tokens_details?.cached_tokens ?? 0
   return {
-    input_tokens: usage.prompt_tokens ?? 0,
+    // Subtract cached tokens: OpenAI includes them in prompt_tokens,
+    // but Anthropic convention treats input_tokens as non-cached only.
+    input_tokens: (usage.prompt_tokens ?? 0) - cached,
     output_tokens: usage.completion_tokens ?? 0,
     cache_creation_input_tokens: 0,
-    cache_read_input_tokens: usage.prompt_tokens_details?.cached_tokens ?? 0,
+    cache_read_input_tokens: cached,
   }
 }