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core/agent: count the prompt a search turn really sent
The compat opens with the question alone (``message_start`` reports 165 tokens) and puts what the search then pulled in on ``message_delta`` (12468); merging preferred the earlier value, so the CLI's context gauge and the auto-compact threshold ran ~12k short of the request. The larger of the two wins now (output tokens are the delta's cumulative count either way).
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@@ -66,11 +66,17 @@ class _ToolBlockState:
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def _merge_usage(previous: dict[str, Any] | None, new: dict[str, Any]) -> dict[str, Any]:
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"""Merge message_start input tokens with message_delta output tokens."""
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"""Merge ``message_start`` usage with the later ``message_delta`` usage.
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DeepSeek's compat reports a search turn's real prompt tokens only on the
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delta (``message_start`` sees the question alone, the delta counts what the
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search pulled in), so the larger of the two wins; output tokens are the
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delta's cumulative count either way.
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"""
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if previous is None:
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return new
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prompt = int(previous.get("prompt_tokens", 0) or new.get("prompt_tokens", 0) or 0)
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completion = int(new.get("completion_tokens", 0) or previous.get("completion_tokens", 0) or 0)
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prompt = max(int(previous.get("prompt_tokens", 0) or 0), int(new.get("prompt_tokens", 0) or 0))
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completion = max(int(previous.get("completion_tokens", 0) or 0), int(new.get("completion_tokens", 0) or 0))
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return {
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"prompt_tokens": prompt,
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"completion_tokens": completion,
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@@ -497,3 +497,38 @@ async def test_dispatch_messages_without_provider_tools_sends_no_server_tool() -
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param = ChatCompletionsParam(model="deepseek-flash", messages=[UserChatMessage(content="hi")])
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_ = await dispatch_messages(cast("Any", client), param, provider_tools=[])
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assert client.calls[0].tools is UNSET
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async def test_search_turn_reports_the_prompt_the_delta_counts() -> None:
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"""A search turn's real prompt size only shows up on ``message_delta``.
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DeepSeek's compat opens with the question alone (``message_start`` sees 165
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tokens) and reports what the search then pulled in on the delta (12468);
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keeping the smaller one leaves the CLI's context gauge — and the
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auto-compact threshold — that far short of what the model was sent.
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"""
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events: list[AnthropicStreamEvent] = [
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AnthropicMessageStart(
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message=AnthropicMessageResponse(
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id="msg_s",
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model="deepseek-flash",
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content=[],
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usage=AnthropicUsage(input_tokens=165, output_tokens=0),
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)
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),
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AnthropicContentBlockStart(index=0, content_block=AnthropicRawContentBlock(type="text", text="")),
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AnthropicContentBlockDelta(index=0, delta=AnthropicRawContentBlock(type="text_delta", text="done")),
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AnthropicMessageDelta(
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delta={"stop_reason": "end_turn"},
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usage=AnthropicUsage(input_tokens=12468, output_tokens=198),
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),
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AnthropicMessageStop(),
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]
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client = ScriptedMessagesClient(stream_events=[events])
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param = ChatCompletionsParam(model="deepseek-flash", messages=[UserChatMessage(content="hi")])
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stream = await dispatch_messages(cast("Any", client), param, stream=True)
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chunks = [chunk async for chunk in cast("Any", stream)]
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usage = next(getattr(chunk, "usage", None) for chunk in chunks if getattr(chunk, "usage", None))
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assert isinstance(usage, dict)
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assert usage["prompt_tokens"] == 12468
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assert usage["completion_tokens"] == 198
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