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fix(streaming): keep finish_reason and provider usage when rebuilding streamed text completions
stream_chunk_builder_text_completion read finish_reason from chunks[-1] and recounted usage from messages. With include_usage the last chunk is a usage-only trailer, so finish_reason came back None (or raised IndexError when the trailer had no choices), and prompt_tokens was 0 because a text-completion prompt is not in messages. Scan for the last finish_reason and prefer the provider-reported usage, as the chat path already does. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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2 changed files with 54 additions and 11 deletions
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@ -8843,8 +8843,14 @@ def stream_chunk_builder_text_completion(chunks: list, messages: Sequence | None
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created: Final = chunks[0]["created"]
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model: Final = chunks[0]["model"]
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system_fingerprint: Final = chunks[0].get("system_fingerprint", None)
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finish_reason: Final = chunks[-1]["choices"][0]["finish_reason"]
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logprobs: Final = chunks[-1]["choices"][0]["logprobs"]
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# With stream_options.include_usage the last chunk is a usage-only trailer, and some providers
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# (e.g. vLLM) send finish_reason on a text-less chunk before it, so scan rather than read chunks[-1].
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chunks_with_choices: Final = [chunk for chunk in chunks if chunk["choices"]]
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finish_reason: Final = next(
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(c["choices"][0]["finish_reason"] for c in reversed(chunks_with_choices) if c["choices"][0]["finish_reason"]),
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None,
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)
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logprobs: Final = chunks_with_choices[-1]["choices"][0]["logprobs"] if chunks_with_choices else None
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content_list: Final = []
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for chunk in chunks:
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@ -8857,16 +8863,26 @@ def stream_chunk_builder_text_completion(chunks: list, messages: Sequence | None
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# Combine the "content" strings into a single string || combine the 'function' strings into a single string
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combined_content: Final = "".join(content_list)
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try:
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prompt_tokens = token_counter(model=model, messages=messages)
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except Exception: # don't allow this failing to block a complete streaming response from being returned
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print_verbose("token_counter failed, assuming prompt tokens is 0")
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prompt_tokens = 0
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completion_tokens: Final = token_counter(
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model=model,
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text=combined_content,
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count_response_tokens=True, # count_response_tokens is a Flag to tell token counter this is a response, No need to add extra tokens we do for input messages
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# Prefer the usage the provider reported (the include_usage trailer) over a local recount, which
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# cannot see a text-completion prompt (it is not in `messages`) and so reports 0 prompt tokens.
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provider_usage: Final = next(
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(c.get("usage") for c in reversed(chunks) if c.get("usage") and c["usage"].get("total_tokens")),
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None,
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)
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if provider_usage is not None:
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prompt_tokens = provider_usage.get("prompt_tokens") or 0
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completion_tokens = provider_usage.get("completion_tokens") or 0
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else:
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try:
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prompt_tokens = token_counter(model=model, messages=messages)
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except Exception: # don't allow this failing to block a complete streaming response from being returned
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print_verbose("token_counter failed, assuming prompt tokens is 0")
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prompt_tokens = 0
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completion_tokens = token_counter(
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model=model,
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text=combined_content,
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count_response_tokens=True, # count_response_tokens is a Flag to tell token counter this is a response, No need to add extra tokens we do for input messages
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)
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response: Final = {
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"id": id,
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@ -3263,6 +3263,33 @@ def test_stream_chunk_builder_text_completion_combines_text_and_usage():
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assert response.usage.total_tokens == response.usage.prompt_tokens + response.usage.completion_tokens
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@pytest.mark.parametrize("trailer_choices", [[], [{"text": None, "index": 0, "logprobs": None, "finish_reason": None}]])
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def test_stream_chunk_builder_text_completion_keeps_finish_reason_and_provider_usage(trailer_choices):
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"""vLLM-style include_usage stream: finish_reason arrives on a text-less chunk, then a
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usage-only trailer. The rebuilt response must keep both instead of reading chunks[-1]
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and recounting the prompt from `messages` (which a text completion doesn't have)."""
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from litellm.main import stream_chunk_builder_text_completion
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from litellm.types.utils import TextCompletionResponse
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def chunk(choices, **extra):
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return TextCompletionResponse(
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id="cmpl-1", object="text_completion", created=1, model="my-model", choices=choices, **extra
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)
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chunks = [
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chunk([{"text": "Hello", "index": 0, "logprobs": None, "finish_reason": None}]),
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chunk([{"text": " world", "index": 0, "logprobs": None, "finish_reason": None}]),
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chunk([{"text": "", "index": 0, "logprobs": None, "finish_reason": "length"}]),
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chunk(trailer_choices, usage={"prompt_tokens": 7, "completion_tokens": 2, "total_tokens": 9}),
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]
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response = stream_chunk_builder_text_completion(chunks=chunks, messages=None)
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assert response.choices[0].text == "Hello world"
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assert response.choices[0].finish_reason == "length"
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assert (response.usage.prompt_tokens, response.usage.completion_tokens, response.usage.total_tokens) == (7, 2, 9)
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def test_completion_forwards_store_and_prompt_cache_key_to_openai():
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"""
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Regression test for https://github.com/BerriAI/litellm/issues/33184
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