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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" />
128 lines
3.8 KiB
YAML
128 lines
3.8 KiB
YAML
version: 2
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image_name: meta-reference-gpu
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apis:
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- agents
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- datasetio
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- eval
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- inference
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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: meta-reference-inference
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provider_type: inline::meta-reference
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config:
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model: ${env.INFERENCE_MODEL}
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checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:=null}
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quantization:
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type: ${env.QUANTIZATION_TYPE:=bf16}
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model_parallel_size: ${env.MODEL_PARALLEL_SIZE:=0}
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max_batch_size: ${env.MAX_BATCH_SIZE:=1}
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max_seq_len: ${env.MAX_SEQ_LEN:=4096}
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- provider_id: sentence-transformers
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provider_type: inline::sentence-transformers
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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/meta-reference-gpu}/faiss_store.db
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safety:
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- provider_id: llama-guard
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provider_type: inline::llama-guard
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config:
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excluded_categories: []
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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/meta-reference-gpu}/agents_store.db
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responses_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/responses_store.db
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telemetry:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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service_name: "${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/meta-reference-gpu}/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: meta-reference
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provider_type: inline::meta-reference
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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/meta-reference-gpu}/meta_reference_eval.db
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datasetio:
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- provider_id: huggingface
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provider_type: remote::huggingface
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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/meta-reference-gpu}/huggingface_datasetio.db
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- provider_id: localfs
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provider_type: inline::localfs
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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/meta-reference-gpu}/localfs_datasetio.db
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scoring:
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- provider_id: basic
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provider_type: inline::basic
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- provider_id: llm-as-judge
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provider_type: inline::llm-as-judge
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- provider_id: braintrust
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provider_type: inline::braintrust
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config:
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openai_api_key: ${env.OPENAI_API_KEY:=}
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tool_runtime:
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- provider_id: brave-search
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provider_type: remote::brave-search
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config:
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api_key: ${env.BRAVE_SEARCH_API_KEY:=}
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max_results: 3
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- provider_id: tavily-search
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provider_type: remote::tavily-search
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config:
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api_key: ${env.TAVILY_SEARCH_API_KEY:=}
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max_results: 3
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- provider_id: rag-runtime
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provider_type: inline::rag-runtime
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- provider_id: model-context-protocol
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provider_type: remote::model-context-protocol
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metadata_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/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/meta-reference-gpu}/inference_store.db
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models:
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- metadata: {}
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model_id: ${env.INFERENCE_MODEL}
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provider_id: meta-reference-inference
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model_type: llm
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- metadata:
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embedding_dimension: 384
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model_id: all-MiniLM-L6-v2
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provider_id: sentence-transformers
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model_type: embedding
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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::websearch
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provider_id: tavily-search
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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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