A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 8, 00:00 UTC
[CI/Build] Add opentelemetry libs in default vllm build (requirements/common.txt) (#34466)
Signed-off-by: Vlad Mihailescu <vtmihailescu@gmail.com>
Vlad Tiberiu Mihailescu committed
Feb 20, 2026 at 19:54 UTC
e739c29ea451869e073a31b5d8cbc6b88f162e8d
2 files changed
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examples/online_serving/opentelemetry/README.md
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@@ -1,14 +1,6 @@
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# Setup OpenTelemetry POC
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-1. Install OpenTelemetry packages:
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-
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- ```bash
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- pip install \
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- 'opentelemetry-sdk>=1.26.0,<1.27.0' \
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- 'opentelemetry-api>=1.26.0,<1.27.0' \
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- 'opentelemetry-exporter-otlp>=1.26.0,<1.27.0' \
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- 'opentelemetry-semantic-conventions-ai>=0.4.1,<0.5.0'
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- ```
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+> **Note:** The core OpenTelemetry packages (`opentelemetry-sdk`, `opentelemetry-api`, `opentelemetry-exporter-otlp`, `opentelemetry-semantic-conventions-ai`) are bundled with vLLM. Manual installation is not required.
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1. Start Jaeger in a docker container:
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requirements/common.txt
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@@ -53,3 +53,7 @@ model-hosting-container-standards >= 0.1.13, < 1.0.0
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mcp
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grpcio
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grpcio-reflection
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+opentelemetry-sdk >= 1.27.0
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+opentelemetry-api >= 1.27.0
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+opentelemetry-exporter-otlp >= 1.27.0
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+opentelemetry-semantic-conventions-ai >= 0.4.1