[Bugfix] Fix include prompt in stream response when echo=true (#15233)

Signed-off-by: Yuan Fang <yuanfang@alauda.io>

Author: fyuan1316

tests/entrypoints/openai/test_completion.py

@@ -779,3 +779,57 @@ async def test_guided_decoding_type_error(client: openai.AsyncOpenAI,
             prompt="Give an example string that fits this regex",
             extra_body=dict(guided_regex=sample_regex,
                             guided_json=sample_json_schema))
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "model_name,stream,echo",
+    [
+        (MODEL_NAME, False, False),
+        (MODEL_NAME, False, True),
+        (MODEL_NAME, True, False),
+        (MODEL_NAME, True, True)  # should not raise BadRequestError error
+    ],
+)
+async def test_echo_stream_completion(client: openai.AsyncOpenAI,
+                                      model_name: str, stream: bool,
+                                      echo: bool):
+    saying: str = "Hello, my name is"
+    result = await client.completions.create(model=model_name,
+                                             prompt=saying,
+                                             max_tokens=10,
+                                             temperature=0.0,
+                                             echo=echo,
+                                             stream=stream)
+
+    stop_reason = "length"
+
+    if not stream:
+        completion = result
+        assert completion.id is not None
+        assert completion.choices is not None and len(completion.choices) == 1
+
+        choice = completion.choices[0]
+        assert len(choice.text) >= 5
+        assert choice.finish_reason == stop_reason
+
+        if echo:
+            assert choice.text is not None and saying in choice.text
+        else:
+            assert choice.text is not None and saying not in choice.text
+
+    else:
+        chunks: list[str] = []
+        final_finish_reason = None
+        async for chunk in result:
+            if chunk.choices and chunk.choices[0].text:
+                chunks.append(chunk.choices[0].text)
+            if chunk.choices and chunk.choices[0].finish_reason:
+                final_finish_reason = chunk.choices[0].finish_reason
+
+        assert final_finish_reason == stop_reason
+        content = "".join(chunks)
+        if echo:
+            assert content is not None and saying in content
+        else:
+            assert content is not None and saying not in content

vllm/entrypoints/openai/serving_completion.py

@@ -25,10 +25,13 @@
                                               ErrorResponse,
                                               RequestResponseMetadata,
                                               UsageInfo)
-# yapf: enable
+from vllm.entrypoints.openai.serving_engine import (
+    EmbedsPrompt as ServingEngineEmbedsPrompt)
 from vllm.entrypoints.openai.serving_engine import (OpenAIServing,
+                                                    TextTokensPrompt,
                                                     clamp_prompt_logprobs,
                                                     is_text_tokens_prompt)
+# yapf: enable
 from vllm.entrypoints.openai.serving_models import OpenAIServingModels
 from vllm.inputs.data import (EmbedsPrompt, TokensPrompt, is_embeds_prompt,
                               is_tokens_prompt)
@@ -223,6 +226,7 @@ async def create_completion(
         if stream:
             return self.completion_stream_generator(
                 request,
+                request_prompts,
                 result_generator,
                 request_id,
                 created_time,
@@ -285,6 +289,8 @@ async def fake_stream_generator() -> AsyncGenerator[str, None]:
     async def completion_stream_generator(
         self,
         request: CompletionRequest,
+        request_prompts: list[Union[TextTokensPrompt,
+                                    ServingEngineEmbedsPrompt]],
         result_generator: AsyncIterator[tuple[int, RequestOutput]],
         request_id: str,
         created_time: int,
@@ -313,7 +319,15 @@ async def completion_stream_generator(
             async for prompt_idx, res in result_generator:
                 prompt_token_ids = res.prompt_token_ids
                 prompt_logprobs = res.prompt_logprobs
-                prompt_text = res.prompt
+
+                if res.prompt is not None:
+                    prompt_text = res.prompt
+                else:
+                    request_prompt = request_prompts[prompt_idx]
+                    if is_text_tokens_prompt(request_prompt):
+                        prompt_text = request_prompt["prompt"]
+                    else:
+                        prompt_text = None
 
                 # Prompt details are excluded from later streamed outputs
                 if prompt_token_ids is not None:
@@ -336,14 +350,13 @@ async def completion_stream_generator(
                             delta_token_ids = prompt_token_ids
                             out_logprobs = prompt_logprobs
                         else:
-                            assert prompt_logprobs is not None
                             # echo the prompt and first token
                             delta_text = prompt_text + output.text
                             delta_token_ids = [
                                 *prompt_token_ids, *output.token_ids
                             ]
                             out_logprobs = [
-                                *prompt_logprobs,
+                                *(prompt_logprobs or []),
                                 *(output.logprobs or []),
                             ]
                         has_echoed[i] = True