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chore: kill inline::vllm (#2824)

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Inline _inference_ providers haven't proved to be very useful -- they
are rarely used. And for good reason -- it is almost never a good idea
to include a complex (distributed) inference engine bundled into a
distributed stateful front-end server serving many other things.
Responsibility should be split properly.

See Discord discussion:
1395849853
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Ashwin Bharambe 2025-07-18 15:52:18 -07:00 • committed by GitHub
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1
docs/source/providers/inference/index.md
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@ -4,7 +4,6 @@ This section contains documentation for all available providers for the **infere
- [inline::meta-reference](inline_meta-reference.md)
- [inline::sentence-transformers](inline_sentence-transformers.md)
- [inline::vllm](inline_vllm.md)
- [remote::anthropic](remote_anthropic.md)
- [remote::bedrock](remote_bedrock.md)
- [remote::cerebras](remote_cerebras.md)

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docs/source/providers/inference/inline_vllm.md
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@ -1,29 +0,0 @@
# inline::vllm
## Description
vLLM inference provider for high-performance model serving with PagedAttention and continuous batching.
## Configuration
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `tensor_parallel_size` | `<class 'int'>` | No | 1 | Number of tensor parallel replicas (number of GPUs to use). |
| `max_tokens` | `<class 'int'>` | No | 4096 | Maximum number of tokens to generate. |
| `max_model_len` | `<class 'int'>` | No | 4096 | Maximum context length to use during serving. |
| `max_num_seqs` | `<class 'int'>` | No | 4 | Maximum parallel batch size for generation. |
| `enforce_eager` | `<class 'bool'>` | No | False | Whether to use eager mode for inference (otherwise cuda graphs are used). |
| `gpu_memory_utilization` | `<class 'float'>` | No | 0.3 | How much GPU memory will be allocated when this provider has finished loading, including memory that was already allocated before loading. |
## Sample Configuration
```yaml
tensor_parallel_size: ${env.TENSOR_PARALLEL_SIZE:=1}
max_tokens: ${env.MAX_TOKENS:=4096}
max_model_len: ${env.MAX_MODEL_LEN:=4096}
max_num_seqs: ${env.MAX_NUM_SEQS:=4}
enforce_eager: ${env.ENFORCE_EAGER:=False}
gpu_memory_utilization: ${env.GPU_MEMORY_UTILIZATION:=0.3}
```