mirror of https://github.com/vllm-project/vllm.git
75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import asyncio
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import json
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import httpx
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from openai import OpenAI
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from vllm.assets.audio import AudioAsset
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mary_had_lamb = AudioAsset("mary_had_lamb").get_local_path()
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winning_call = AudioAsset("winning_call").get_local_path()
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# Modify OpenAI's API key and API base to use vLLM's API server.
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openai_api_key = "EMPTY"
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openai_api_base = "http://localhost:8000/v1"
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client = OpenAI(
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api_key=openai_api_key,
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base_url=openai_api_base,
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)
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def sync_openai():
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with open(str(mary_had_lamb), "rb") as f:
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transcription = client.audio.transcriptions.create(
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file=f,
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model="openai/whisper-large-v3",
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language="en",
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response_format="json",
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temperature=0.0,
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# Additional sampling params not provided by OpenAI API.
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extra_body=dict(
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seed=4419,
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repetition_penalty=1.3,
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),
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)
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print("transcription result:", transcription.text)
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sync_openai()
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# OpenAI Transcription API client does not support streaming.
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async def stream_openai_response():
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data = {
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"language": "en",
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"stream": True,
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"model": "openai/whisper-large-v3",
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}
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url = openai_api_base + "/audio/transcriptions"
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headers = {"Authorization": f"Bearer {openai_api_key}"}
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print("transcription result:", end=" ")
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async with httpx.AsyncClient() as client:
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with open(str(winning_call), "rb") as f:
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async with client.stream(
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"POST", url, files={"file": f}, data=data, headers=headers
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) as response:
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async for line in response.aiter_lines():
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# Each line is a JSON object prefixed with 'data: '
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if line:
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if line.startswith("data: "):
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line = line[len("data: ") :]
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# Last chunk, stream ends
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if line.strip() == "[DONE]":
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break
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# Parse the JSON response
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chunk = json.loads(line)
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# Extract and print the content
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content = chunk["choices"][0].get("delta", {}).get("content")
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print(content, end="")
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# Run the asynchronous function
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asyncio.run(stream_openai_response())
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