43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
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# SPDX-License-Identifier: Apache-2.0
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from argparse import Namespace
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from vllm import LLM, EngineArgs
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from vllm.utils import FlexibleArgumentParser
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def main(args: Namespace):
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# Sample prompts.
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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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# Create an LLM.
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# You should pass task="embed" for embedding models
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model = LLM(**vars(args))
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# Generate embedding. The output is a list of EmbeddingRequestOutputs.
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outputs = model.embed(prompts)
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# Print the outputs.
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for prompt, output in zip(prompts, outputs):
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embeds = output.outputs.embedding
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embeds_trimmed = ((str(embeds[:16])[:-1] +
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", ...]") if len(embeds) > 16 else embeds)
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print(f"Prompt: {prompt!r} | "
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f"Embeddings: {embeds_trimmed} (size={len(embeds)})")
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if __name__ == "__main__":
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parser = FlexibleArgumentParser()
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parser = EngineArgs.add_cli_args(parser)
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# Set example specific arguments
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parser.set_defaults(model="intfloat/e5-mistral-7b-instruct",
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task="embed",
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enforce_eager=True)
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args = parser.parse_args()
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main(args)
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