feat: OpenAI-compatible API Endpoints for Embedding Models #104
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whoisj
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Oct 30, 2025
src/utils/request.py
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| pooling_params = PoolingParams(dimensions=dims, task="embed") | ||
| return pooling_params | ||
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| def create_response(self, request_output): |
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would be nice to have a type hint on request_output.
src/utils/request.py
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| async for response in response_iterator: | ||
| yield response | ||
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| def create_response(self, request_output_state, request_output, prepend_input): |
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would be nice to have type hints on request_output_state, request_output, and prepend_input.
src/utils/request.py
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| class RequestBase: | ||
| def __init__(self, request, executor_callback, output_dtype): |
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would be nice to have type hints on request, executor_callback, and output_dtype.
| from abc import abstractmethod | ||
| from io import BytesIO | ||
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| import numpy as np |
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is using numpy (CPU) good enough?
do we want to leverage cupy (GPU)?
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My understanding is that vLLM engine takes care of it.
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Enable vLLM to load embedding model and execute embedding requests