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The current span processing dumps so much junk on the console that it makes actual understanding of what is going on in the server impossible. I am killing the console sink as a default. If you want, you are always free to change your run.yaml to add it. Before: <img width="1877" height="1107" alt="image" src="https://github.com/user-attachments/assets/3a7ad261-e2ba-4d40-9820-fcc282c8df37" /> After: <img width="1919" height="470" alt="image" src="https://github.com/user-attachments/assets/bc7cf763-fba9-4e95-a4b5-f65f6d1c5332" />
105 lines
3.1 KiB
YAML
105 lines
3.1 KiB
YAML
version: 2
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image_name: nvidia
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apis:
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- agents
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- datasetio
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- eval
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- files
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- inference
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- post_training
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- safety
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- scoring
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- telemetry
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- tool_runtime
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- vector_io
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providers:
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inference:
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- provider_id: nvidia
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provider_type: remote::nvidia
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config:
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url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}
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api_key: ${env.NVIDIA_API_KEY:=}
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append_api_version: ${env.NVIDIA_APPEND_API_VERSION:=True}
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vector_io:
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- provider_id: faiss
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provider_type: inline::faiss
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config:
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kvstore:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/faiss_store.db
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safety:
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- provider_id: nvidia
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provider_type: remote::nvidia
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config:
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guardrails_service_url: ${env.GUARDRAILS_SERVICE_URL:=http://localhost:7331}
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config_id: ${env.NVIDIA_GUARDRAILS_CONFIG_ID:=self-check}
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agents:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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persistence_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/agents_store.db
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responses_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/responses_store.db
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telemetry:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
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sinks: ${env.TELEMETRY_SINKS:=sqlite}
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sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/trace_store.db
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otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
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eval:
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- provider_id: nvidia
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provider_type: remote::nvidia
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config:
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evaluator_url: ${env.NVIDIA_EVALUATOR_URL:=http://localhost:7331}
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post_training:
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- provider_id: nvidia
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provider_type: remote::nvidia
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config:
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api_key: ${env.NVIDIA_API_KEY:=}
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dataset_namespace: ${env.NVIDIA_DATASET_NAMESPACE:=default}
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project_id: ${env.NVIDIA_PROJECT_ID:=test-project}
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customizer_url: ${env.NVIDIA_CUSTOMIZER_URL:=http://nemo.test}
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datasetio:
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- provider_id: nvidia
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provider_type: remote::nvidia
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config:
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api_key: ${env.NVIDIA_API_KEY:=}
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dataset_namespace: ${env.NVIDIA_DATASET_NAMESPACE:=default}
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project_id: ${env.NVIDIA_PROJECT_ID:=test-project}
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datasets_url: ${env.NVIDIA_DATASETS_URL:=http://nemo.test}
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scoring:
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- provider_id: basic
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provider_type: inline::basic
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tool_runtime:
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- provider_id: rag-runtime
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provider_type: inline::rag-runtime
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files:
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- provider_id: meta-reference-files
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provider_type: inline::localfs
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config:
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storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/nvidia/files}
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metadata_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/files_metadata.db
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metadata_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/registry.db
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inference_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/inference_store.db
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models: []
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shields: []
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vector_dbs: []
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datasets: []
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scoring_fns: []
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benchmarks: []
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tool_groups:
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- toolgroup_id: builtin::rag
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provider_id: rag-runtime
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server:
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port: 8321
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