forked from phoenix-oss/llama-stack-mirror
516e1a3e59
# What does this PR do? Adds the sentence transformer provider and the `all-MiniLM-L6-v2` embedding model to the default models to register in the run.yaml for all providers. ## Test Plan llama stack build --template together --image-type conda llama stack run ~/.llama/distributions/llamastack-together/together-run.yaml
77 lines
2 KiB
YAML
77 lines
2 KiB
YAML
version: '2'
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image_name: cerebras
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docker_image: null
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conda_env: cerebras
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apis:
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- agents
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- inference
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- memory
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- safety
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- telemetry
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providers:
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inference:
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- provider_id: cerebras
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provider_type: remote::cerebras
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config:
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base_url: https://api.cerebras.ai
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api_key: ${env.CEREBRAS_API_KEY}
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- provider_id: sentence-transformers
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provider_type: inline::sentence-transformers
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config: {}
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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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memory:
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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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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/cerebras}/faiss_store.db
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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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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/cerebras}/agents_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:llama-stack}
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sinks: ${env.TELEMETRY_SINKS:console,sqlite}
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sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/cerebras/trace_store.db}
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metadata_store:
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namespace: null
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/cerebras}/registry.db
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models:
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- metadata: {}
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model_id: meta-llama/Llama-3.1-8B-Instruct
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provider_id: cerebras
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provider_model_id: llama3.1-8b
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model_type: llm
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- metadata: {}
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model_id: meta-llama/Llama-3.1-70B-Instruct
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provider_id: cerebras
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provider_model_id: llama3.1-70b
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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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provider_model_id: null
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model_type: embedding
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shields:
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- params: null
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shield_id: meta-llama/Llama-Guard-3-8B
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provider_id: null
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provider_shield_id: null
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memory_banks: []
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datasets: []
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scoring_fns: []
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eval_tasks: []
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