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A high-throughput and memory-efficient inference and serving engine for LLMs

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Update openai_compatible_server.md (#16507)

Signed-off-by: Christian Sears <csears@redhat.com>

Christian Sears committed Apr 11, 2025 at 18:54 UTC c09632a66c0a4576518eef598aa13aa2d34bd337
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docs/source/serving/openai_compatible_server.md
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3 # OpenAI-Compatible Server
4
5 -vLLM provides an HTTP server that implements OpenAI's [Completions API](https://platform.openai.com/docs/api-reference/completions), [Chat API](https://platform.openai.com/docs/api-reference/chat), and more!
5 +vLLM provides an HTTP server that implements OpenAI's [Completions API](https://platform.openai.com/docs/api-reference/completions), [Chat API](https://platform.openai.com/docs/api-reference/chat), and more! This functionality lets you serve models and interact with them using an HTTP client.
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7 -You can start the server via the [`vllm serve`](#vllm-serve) command, or through [Docker](#deployment-docker):
7 +In your terminal, you can [install](../getting_started/installation.md) vLLM, then start the server with the [`vllm serve`](#vllm-serve) command. (You can also use our [Docker](#deployment-docker) image.)
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9 ```bash
10 vllm serve NousResearch/Meta-Llama-3-8B-Instruct --dtype auto --api-key token-abc123
11 ```
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13 -To call the server, you can use the [official OpenAI Python client](https://github.com/openai/openai-python), or any other HTTP client.
13 +To call the server, in your preferred text editor, create a script that uses an HTTP client. Include any messages that you want to send to the model. Then run that script. Below is an example script using the [official OpenAI Python client](https://github.com/openai/openai-python).
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15 ```python
16 from openai import OpenAI