[Frontend] Add OpenAI API support for input_audio

docs/source/serving/openai_compatible_server.md

@@ -34,9 +34,9 @@ We currently support the following OpenAI APIs:
 - [Chat Completions API](https://platform.openai.com/docs/api-reference/chat)
   - [Vision](https://platform.openai.com/docs/guides/vision)-related parameters are supported; see [Multimodal Inputs](../usage/multimodal_inputs.rst).
     - *Note: `image_url.detail` parameter is not supported.*
-  - We also support `audio_url` content type for audio files.
-    - Refer to [vllm.entrypoints.chat_utils](https://github.com/vllm-project/vllm/tree/main/vllm/entrypoints/chat_utils.py) for the exact schema.
-    - *TODO: Support `input_audio` content type as defined [here](https://github.com/openai/openai-python/blob/v1.52.2/src/openai/types/chat/chat_completion_content_part_input_audio_param.py).*
+  - We support two audio content types.
+    - Support `input_audio` content type as defined [here](https://platform.openai.com/docs/guides/audio?audio-generation-quickstart-example=audio-in).
+    - Support `audio_url` content type for audio files. Refer to [here](https://github.com/vllm-project/vllm/tree/main/vllm/entrypoints/chat_utils.py#L51) for the exact schema.
   - *Note: `parallel_tool_calls` and `user` parameters are ignored.*
 - [Embeddings API](https://platform.openai.com/docs/api-reference/embeddings)
   - Instead of `inputs`, you can pass in a list of `messages` (same schema as Chat Completions API),

docs/source/usage/multimodal_inputs.rst

@@ -315,7 +315,89 @@ You can use `these tests <https://github.com/vllm-project/vllm/blob/main/tests/e
 Audio
 ^^^^^
 
-Instead of :code:`image_url`, you can pass an audio file via :code:`audio_url`.
+Audio input is supported according to `OpenAI Audio in API <https://platform.openai.com/docs/guides/audio?audio-generation-quickstart-example=audio-in>`_.
+Here is a simple example using Ultravox-v0.3.
+
+First, launch the OpenAI-compatible server:
+
+.. code-block:: bash
+
+    vllm serve fixie-ai/ultravox-v0_3
+
+Then, you can use the OpenAI client as follows:
+
+.. code-block:: python
+
+    from openai import OpenAI
+    from vllm.assets.audio import AudioAsset
+    import requests, base64
+
+    openai_api_key = "EMPTY"
+    openai_api_base = "http://localhost:8000/v1"
+
+    client = OpenAI(
+        api_key=openai_api_key,
+        base_url=openai_api_base,
+    )
+
+    # Any format supported by librosa is supported
+    audio_url = AudioAsset("winning_call").url
+    def encode_base64_content_from_url(content_url: str) -> str:
+        """Encode a content retrieved from a remote url to base64 format."""
+
+        with requests.get(content_url) as response:
+            response.raise_for_status()
+            result = base64.b64encode(response.content).decode('utf-8')
+
+        return result
+    audio_base64 = encode_base64_content_from_url(audio_url)
+
+    chat_completion_from_base64 = client.chat.completions.create(
+        messages=[{
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": "What's in this audio?"
+                },
+                {
+                    "type": "input_audio",
+                    "input_audio": {
+                        "data": audio_base64,
+                        "format": "wav"
+                    },
+                },
+            ],
+        }],
+        model=model,
+        max_completion_tokens=64,
+    )
+
+    result = chat_completion_from_base64.choices[0].message.content
+    print("Chat completion output from input audio:", result)
+
+    chat_completion_from_url = client.chat.completions.create(
+        messages=[{
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": "What's in this audio?"
+                },
+                {
+                    "type": "audio_url",
+                    "audio_url": {
+                        "url": audio_url
+                    },
+                },
+            ],
+        }],
+        model=model,
+        max_completion_tokens=64,
+    )
+
+    result = chat_completion_from_url.choices[0].message.content
+    print("Chat completion output from audio url:", result)
 
 A full code example can be found in `examples/openai_chat_completion_client_for_multimodal.py <https://github.com/vllm-project/vllm/blob/main/examples/openai_chat_completion_client_for_multimodal.py>`_.
 

examples/openai_chat_completion_client_for_multimodal.py

@@ -207,6 +207,32 @@ def run_audio() -> None:
     result = chat_completion_from_base64.choices[0].message.content
     print("Chat completion output from base64 encoded audio:", result)
 
+    chat_completion_from_base64 = client.chat.completions.create(
+        messages=[{
+            "role":
+            "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": "What's in this audio?"
+                },
+                {
+                    "type": "input_audio",
+                    "input_audio": {
+                        # Any format supported by librosa is supported
+                        "data": audio_base64,
+                        "format": "wav"
+                    },
+                },
+            ],
+        }],
+        model=model,
+        max_completion_tokens=64,
+    )
+
+    result = chat_completion_from_base64.choices[0].message.content
+    print("Chat completion output from input audio:", result)
+
 
 example_function_map = {
     "text-only": run_text_only,

tests/entrypoints/openai/test_audio.py

@@ -154,6 +154,61 @@ async def test_single_chat_session_audio_base64encoded(
     assert message.content is not None and len(message.content) >= 0
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+@pytest.mark.parametrize("audio_url", TEST_AUDIO_URLS)
+async def test_single_chat_session_input_audio(
+        client: openai.AsyncOpenAI, model_name: str, audio_url: str,
+        base64_encoded_audio: Dict[str, str]):
+    messages = [{
+        "role":
+        "user",
+        "content": [
+            {
+                "type": "input_audio",
+                "input_audio": {
+                    "data": base64_encoded_audio[audio_url],
+                    "format": "wav"
+                }
+            },
+            {
+                "type": "text",
+                "text": "What's happening in this audio?"
+            },
+        ],
+    }]
+
+    # test single completion
+    chat_completion = await client.chat.completions.create(
+        model=model_name,
+        messages=messages,
+        max_completion_tokens=10,
+        logprobs=True,
+        top_logprobs=5)
+    assert len(chat_completion.choices) == 1
+
+    choice = chat_completion.choices[0]
+    assert choice.finish_reason == "length"
+    assert chat_completion.usage == openai.types.CompletionUsage(
+        completion_tokens=10, prompt_tokens=202, total_tokens=212)
+
+    message = choice.message
+    message = chat_completion.choices[0].message
+    assert message.content is not None and len(message.content) >= 10
+    assert message.role == "assistant"
+    messages.append({"role": "assistant", "content": message.content})
+
+    # test multi-turn dialogue
+    messages.append({"role": "user", "content": "express your result in json"})
+    chat_completion = await client.chat.completions.create(
+        model=model_name,
+        messages=messages,
+        max_completion_tokens=10,
+    )
+    message = chat_completion.choices[0].message
+    assert message.content is not None and len(message.content) >= 0
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize("model_name", [MODEL_NAME])
 @pytest.mark.parametrize("audio_url", TEST_AUDIO_URLS)
@@ -211,11 +266,72 @@ async def test_chat_streaming_audio(client: openai.AsyncOpenAI,
     assert "".join(chunks) == output
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+@pytest.mark.parametrize("audio_url", TEST_AUDIO_URLS)
+async def test_chat_streaming_input_audio(client: openai.AsyncOpenAI,
+                                          model_name: str, audio_url: str,
+                                          base64_encoded_audio: Dict[str,
+                                                                     str]):
+    messages = [{
+        "role":
+        "user",
+        "content": [
+            {
+                "type": "input_audio",
+                "input_audio": {
+                    "data": base64_encoded_audio[audio_url],
+                    "format": "wav"
+                }
+            },
+            {
+                "type": "text",
+                "text": "What's happening in this audio?"
+            },
+        ],
+    }]
+
+    # test single completion
+    chat_completion = await client.chat.completions.create(
+        model=model_name,
+        messages=messages,
+        max_completion_tokens=10,
+        temperature=0.0,
+    )
+    output = chat_completion.choices[0].message.content
+    stop_reason = chat_completion.choices[0].finish_reason
+
+    # test streaming
+    stream = await client.chat.completions.create(
+        model=model_name,
+        messages=messages,
+        max_completion_tokens=10,
+        temperature=0.0,
+        stream=True,
+    )
+    chunks: List[str] = []
+    finish_reason_count = 0
+    async for chunk in stream:
+        delta = chunk.choices[0].delta
+        if delta.role:
+            assert delta.role == "assistant"
+        if delta.content:
+            chunks.append(delta.content)
+        if chunk.choices[0].finish_reason is not None:
+            finish_reason_count += 1
+    # finish reason should only return in last block
+    assert finish_reason_count == 1
+    assert chunk.choices[0].finish_reason == stop_reason
+    assert delta.content
+    assert "".join(chunks) == output
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize("model_name", [MODEL_NAME])
 @pytest.mark.parametrize("audio_url", TEST_AUDIO_URLS)
 async def test_multi_audio_input(client: openai.AsyncOpenAI, model_name: str,
-                                 audio_url: str):
+                                 audio_url: str,
+                                 base64_encoded_audio: Dict[str, str]):
 
     messages = [{
         "role":
@@ -228,9 +344,10 @@ async def test_multi_audio_input(client: openai.AsyncOpenAI, model_name: str,
                 }
             },
             {
-                "type": "audio_url",
-                "audio_url": {
-                    "url": audio_url
+                "type": "input_audio",
+                "input_audio": {
+                    "data": base64_encoded_audio[audio_url],
+                    "format": "wav"
                 }
             },
             {