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55 lines
1.4 KiB
Python
55 lines
1.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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Example online usage of Pooling API for multi vector retrieval.
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Run `vllm serve <model> --runner pooling`
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to start up the server in vLLM. e.g.
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vllm serve BAAI/bge-m3
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"""
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import argparse
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import requests
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import torch
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def post_http_request(prompt: dict, api_url: str) -> requests.Response:
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headers = {"User-Agent": "Test Client"}
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response = requests.post(api_url, headers=headers, json=prompt)
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return response
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def parse_args():
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parser = argparse.ArgumentParser()
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parser.add_argument("--host", type=str, default="localhost")
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parser.add_argument("--port", type=int, default=8000)
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parser.add_argument("--model", type=str, default="BAAI/bge-m3")
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return parser.parse_args()
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def main(args):
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api_url = f"http://{args.host}:{args.port}/pooling"
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model_name = args.model
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prompts = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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prompt = {"model": model_name, "input": prompts}
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pooling_response = post_http_request(prompt=prompt, api_url=api_url)
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for output in pooling_response.json()["data"]:
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multi_vector = torch.tensor(output["data"])
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print(multi_vector.shape)
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if __name__ == "__main__":
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args = parse_args()
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main(args)
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