Add gpt-oss, qwen25-coder-32b, qwen3-coder-30b presets; use hostname for WireGuard

New vLLM model presets (all end-to-end tested on A100 80GB):
- gpt-oss-20b: openai/gpt-oss-20b — MoE 20B, ~14 GB MXFP4, ultra-fast (3.6B active)
- gpt-oss-120b: openai/gpt-oss-120b — MoE 120B, ~65 GB MXFP4, powerful reasoning
- qwen25-coder-32b: Qwen/Qwen2.5-Coder-32B-Instruct-AWQ — ~18 GB, best 32B coder
- qwen3-coder-30b: QuantTrio/Qwen3-Coder-30B-A3B-Instruct-AWQ — ~18 GB Qwen3 coder

gpt-oss models disable --enable-auto-tool-choice (tool_call_parser = ""): vLLM 0.17.1's
llama3_json parser crashes on gpt-oss responses because the new token_ids field in the
response is passed as an unexpected keyword argument to extract_tool_calls().

gpt-oss-120b max_model_len raised to 40960: Claude Code's system prompt alone is ~33K
tokens, so 16K was insufficient. 40K allows Claude Code to connect with headroom.

Use wireguard_gateway_hostname (hyperstack.wg1) instead of raw 192.168.3.1 IP for all
connection URLs (tests, ready message, dry-run output). The hostname is derived from the
wg interface name and resolves via /etc/hosts.

Fix test max_tokens: raised from 50 to 500 so reasoning models (e.g. gpt-oss) have
enough tokens to complete chain-of-thought before producing content.

Fix qwen25-coder-32b max_model_len: model config has max_position_embeddings=32768,
not 128K as assumed. Using 65536 caused a vLLM pydantic validation error.

Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>

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