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chore: update the vLLM inference impl to use OpenAIMixin for openai-compat functions
inference recordings from Qwen3-0.6B and vLLM 0.8.3 - ``` docker run --gpus all -v ~/.cache/huggingface:/root/.cache/huggingface -p 8000:8000 --ipc=host \ vllm/vllm-openai:latest \ --model Qwen/Qwen3-0.6B --enable-auto-tool-choice --tool-call-parser hermes ``` test with - ``` ./scripts/integration-tests.sh --stack-config server:ci-tests --setup vllm --subdirs inference ```
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33 changed files with 51813 additions and 203 deletions
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tests/integration/recordings/responses/27463384d1a3.json
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59
tests/integration/recordings/responses/27463384d1a3.json
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{
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"request": {
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"method": "POST",
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"url": "http://localhost:8000/v1/v1/chat/completions",
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"headers": {},
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"body": {
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"model": "Qwen/Qwen3-0.6B",
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"messages": [
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{
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"role": "user",
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"content": "Hello, world!"
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}
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],
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"stream": false
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},
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"endpoint": "/v1/chat/completions",
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"model": "Qwen/Qwen3-0.6B"
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},
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"response": {
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"body": {
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"__type__": "openai.types.chat.chat_completion.ChatCompletion",
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"__data__": {
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"id": "chatcmpl-5434d48fcb354eb498e3909a87c4bf39",
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"choices": [
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{
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"finish_reason": "stop",
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"index": 0,
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"logprobs": null,
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"message": {
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"content": "<think>\nOkay, the user just said \"Hello, world!\" so I need to respond in a friendly way. Let me start by acknowledging their input. Maybe say \"Hello, world!\" and then offer help. Keep it simple and positive. No need for any complex messages. Just a straightforward reply.\n</think>\n\nHello, world! \ud83d\ude0a How can I assist you today?",
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"refusal": null,
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"role": "assistant",
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"annotations": null,
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"audio": null,
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"function_call": null,
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"tool_calls": [],
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"reasoning_content": null
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},
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"stop_reason": null
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}
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],
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"created": 1757524166,
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"model": "Qwen/Qwen3-0.6B",
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"object": "chat.completion",
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"service_tier": null,
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"system_fingerprint": null,
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"usage": {
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"completion_tokens": 77,
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"prompt_tokens": 12,
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"total_tokens": 89,
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"completion_tokens_details": null,
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"prompt_tokens_details": null
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},
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"prompt_logprobs": null
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}
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},
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"is_streaming": false
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}
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}
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