mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-06 18:40:57 +00:00
feat: ability to use postgres as store for starter distro
The starter distribution now comes with all the required packages to support persistent stores—like the agent store, metadata, and inference—using PostgreSQL. We’ve added a new run YAML file, run-with-postgres-store.yaml, to make this setup easy. The file is included in the container image, so users can simply override the entrypoint to use the Postgres-specific config. The documentation has been updated with instructions on how to do that. Closes: #2619 Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
parent
392e01dc79
commit
3b34efb81a
14 changed files with 450 additions and 215 deletions
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@ -57,4 +57,5 @@ image_type: venv
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additional_pip_packages:
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- aiosqlite
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- asyncpg
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- psycopg2-binary
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- sqlalchemy[asyncio]
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@ -0,0 +1,278 @@
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version: 2
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image_name: starter
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apis:
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- agents
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- batches
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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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- tool_runtime
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- vector_io
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providers:
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inference:
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- provider_id: ${env.CEREBRAS_API_KEY:+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: ${env.OLLAMA_URL:+ollama}
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provider_type: remote::ollama
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config:
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url: ${env.OLLAMA_URL:=http://localhost:11434}
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- provider_id: ${env.VLLM_URL:+vllm}
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provider_type: remote::vllm
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config:
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url: ${env.VLLM_URL:=}
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max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
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api_token: ${env.VLLM_API_TOKEN:=fake}
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tls_verify: ${env.VLLM_TLS_VERIFY:=true}
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- provider_id: ${env.TGI_URL:+tgi}
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provider_type: remote::tgi
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config:
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url: ${env.TGI_URL:=}
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- provider_id: fireworks
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provider_type: remote::fireworks
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config:
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url: https://api.fireworks.ai/inference/v1
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api_key: ${env.FIREWORKS_API_KEY:=}
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- provider_id: together
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provider_type: remote::together
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config:
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url: https://api.together.xyz/v1
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api_key: ${env.TOGETHER_API_KEY:=}
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- provider_id: bedrock
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provider_type: remote::bedrock
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- provider_id: ${env.NVIDIA_API_KEY:+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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- provider_id: openai
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provider_type: remote::openai
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config:
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api_key: ${env.OPENAI_API_KEY:=}
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base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
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- provider_id: anthropic
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provider_type: remote::anthropic
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config:
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api_key: ${env.ANTHROPIC_API_KEY:=}
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- provider_id: gemini
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provider_type: remote::gemini
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config:
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api_key: ${env.GEMINI_API_KEY:=}
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- provider_id: ${env.VERTEX_AI_PROJECT:+vertexai}
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provider_type: remote::vertexai
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config:
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project: ${env.VERTEX_AI_PROJECT:=}
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location: ${env.VERTEX_AI_LOCATION:=us-central1}
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- provider_id: groq
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provider_type: remote::groq
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config:
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url: https://api.groq.com
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api_key: ${env.GROQ_API_KEY:=}
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- provider_id: sambanova
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provider_type: remote::sambanova
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config:
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url: https://api.sambanova.ai/v1
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api_key: ${env.SAMBANOVA_API_KEY:=}
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- provider_id: ${env.AZURE_API_KEY:+azure}
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provider_type: remote::azure
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config:
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api_key: ${env.AZURE_API_KEY:=}
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api_base: ${env.AZURE_API_BASE:=}
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api_version: ${env.AZURE_API_VERSION:=}
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api_type: ${env.AZURE_API_TYPE:=}
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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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persistence:
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namespace: vector_io::faiss
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backend: kv_default
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- provider_id: sqlite-vec
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provider_type: inline::sqlite-vec
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config:
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec.db
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persistence:
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namespace: vector_io::sqlite_vec
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backend: kv_default
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- provider_id: ${env.MILVUS_URL:+milvus}
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provider_type: inline::milvus
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config:
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db_path: ${env.MILVUS_DB_PATH:=~/.llama/distributions/starter}/milvus.db
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persistence:
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namespace: vector_io::milvus
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backend: kv_default
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- provider_id: ${env.CHROMADB_URL:+chromadb}
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provider_type: remote::chromadb
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config:
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url: ${env.CHROMADB_URL:=}
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persistence:
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namespace: vector_io::chroma_remote
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backend: kv_default
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- provider_id: ${env.PGVECTOR_DB:+pgvector}
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provider_type: remote::pgvector
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config:
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host: ${env.PGVECTOR_HOST:=localhost}
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port: ${env.PGVECTOR_PORT:=5432}
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db: ${env.PGVECTOR_DB:=}
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user: ${env.PGVECTOR_USER:=}
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password: ${env.PGVECTOR_PASSWORD:=}
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persistence:
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namespace: vector_io::pgvector
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backend: kv_default
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- provider_id: ${env.QDRANT_URL:+qdrant}
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provider_type: remote::qdrant
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config:
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api_key: ${env.QDRANT_API_KEY:=}
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persistence:
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namespace: vector_io::qdrant_remote
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backend: kv_default
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- provider_id: ${env.WEAVIATE_CLUSTER_URL:+weaviate}
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provider_type: remote::weaviate
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config:
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weaviate_api_key: null
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weaviate_cluster_url: ${env.WEAVIATE_CLUSTER_URL:=localhost:8080}
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persistence:
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namespace: vector_io::weaviate
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backend: kv_default
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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/starter/files}
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metadata_store:
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table_name: files_metadata
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backend: sql_default
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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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- provider_id: code-scanner
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provider_type: inline::code-scanner
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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: sql_postgres
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host: ${env.POSTGRES_HOST:=localhost}
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port: ${env.POSTGRES_PORT:=5432}
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db: ${env.POSTGRES_DB:=llamastack}
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user: ${env.POSTGRES_USER:=llamastack}
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password: ${env.POSTGRES_PASSWORD:=llamastack}
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responses_store:
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type: sql_postgres
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host: ${env.POSTGRES_HOST:=localhost}
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port: ${env.POSTGRES_PORT:=5432}
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db: ${env.POSTGRES_DB:=llamastack}
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user: ${env.POSTGRES_USER:=llamastack}
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password: ${env.POSTGRES_PASSWORD:=llamastack}
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post_training:
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- provider_id: torchtune-cpu
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provider_type: inline::torchtune-cpu
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config:
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checkpoint_format: meta
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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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namespace: eval
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backend: kv_default
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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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namespace: datasetio::huggingface
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backend: kv_default
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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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namespace: datasetio::localfs
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backend: kv_default
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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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batches:
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- provider_id: reference
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provider_type: inline::reference
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config:
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kvstore:
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namespace: batches
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backend: kv_default
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storage:
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backends:
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kv_postgres:
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type: kv_postgres
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host: ${env.POSTGRES_HOST:=localhost}
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port: ${env.POSTGRES_PORT:=5432}
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db: ${env.POSTGRES_DB:=llamastack}
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user: ${env.POSTGRES_USER:=llamastack}
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password: ${env.POSTGRES_PASSWORD:=llamastack}
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table_name: ${env.POSTGRES_TABLE_NAME:=llamastack_kvstore}
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sql_postgres:
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type: sql_postgres
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host: ${env.POSTGRES_HOST:=localhost}
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port: ${env.POSTGRES_PORT:=5432}
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db: ${env.POSTGRES_DB:=llamastack}
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user: ${env.POSTGRES_USER:=llamastack}
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password: ${env.POSTGRES_PASSWORD:=llamastack}
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stores:
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metadata:
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namespace: registry
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backend: kv_postgres
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inference:
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table_name: inference_store
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backend: sql_postgres
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max_write_queue_size: 10000
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num_writers: 4
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conversations:
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table_name: openai_conversations
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backend: sql_postgres
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prompts:
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namespace: prompts
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backend: kv_postgres
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registered_resources:
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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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server:
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port: 8321
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telemetry:
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enabled: true
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@ -17,6 +17,11 @@ from llama_stack.core.datatypes import (
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ToolGroupInput,
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VectorStoresConfig,
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)
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from llama_stack.core.storage.datatypes import (
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InferenceStoreReference,
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KVStoreReference,
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SqlStoreReference,
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)
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from llama_stack.core.utils.dynamic import instantiate_class_type
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from llama_stack.distributions.template import DistributionTemplate, RunConfigSettings
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from llama_stack.providers.datatypes import RemoteProviderSpec
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@ -36,6 +41,7 @@ from llama_stack.providers.remote.vector_io.pgvector.config import (
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)
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from llama_stack.providers.remote.vector_io.qdrant.config import QdrantVectorIOConfig
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from llama_stack.providers.remote.vector_io.weaviate.config import WeaviateVectorIOConfig
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from llama_stack.providers.utils.kvstore.config import PostgresKVStoreConfig
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from llama_stack.providers.utils.sqlstore.sqlstore import PostgresSqlStoreConfig
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@ -181,6 +187,62 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
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provider_shield_id="${env.CODE_SCANNER_MODEL:=}",
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),
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]
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postgres_config = PostgresSqlStoreConfig.sample_run_config()
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default_overrides = {
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"inference": remote_inference_providers + [embedding_provider],
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"vector_io": [
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Provider(
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provider_id="faiss",
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provider_type="inline::faiss",
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config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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),
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Provider(
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provider_id="sqlite-vec",
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provider_type="inline::sqlite-vec",
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config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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),
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Provider(
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provider_id="${env.MILVUS_URL:+milvus}",
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provider_type="inline::milvus",
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config=MilvusVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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),
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Provider(
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provider_id="${env.CHROMADB_URL:+chromadb}",
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provider_type="remote::chromadb",
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config=ChromaVectorIOConfig.sample_run_config(
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f"~/.llama/distributions/{name}/",
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url="${env.CHROMADB_URL:=}",
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),
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),
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Provider(
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provider_id="${env.PGVECTOR_DB:+pgvector}",
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provider_type="remote::pgvector",
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config=PGVectorVectorIOConfig.sample_run_config(
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f"~/.llama/distributions/{name}",
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db="${env.PGVECTOR_DB:=}",
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user="${env.PGVECTOR_USER:=}",
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password="${env.PGVECTOR_PASSWORD:=}",
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),
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),
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Provider(
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provider_id="${env.QDRANT_URL:+qdrant}",
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provider_type="remote::qdrant",
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config=QdrantVectorIOConfig.sample_run_config(
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f"~/.llama/distributions/{name}",
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url="${env.QDRANT_URL:=}",
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),
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),
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Provider(
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provider_id="${env.WEAVIATE_CLUSTER_URL:+weaviate}",
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provider_type="remote::weaviate",
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config=WeaviateVectorIOConfig.sample_run_config(
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f"~/.llama/distributions/{name}",
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cluster_url="${env.WEAVIATE_CLUSTER_URL:=}",
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),
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),
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],
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"files": [files_provider],
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}
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return DistributionTemplate(
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name=name,
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@ -189,64 +251,10 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
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container_image=None,
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template_path=None,
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providers=providers,
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additional_pip_packages=PostgresSqlStoreConfig.pip_packages(),
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additional_pip_packages=list(set(PostgresSqlStoreConfig.pip_packages() + PostgresKVStoreConfig.pip_packages())),
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run_configs={
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"run.yaml": RunConfigSettings(
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provider_overrides={
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"inference": remote_inference_providers + [embedding_provider],
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"vector_io": [
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Provider(
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provider_id="faiss",
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provider_type="inline::faiss",
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config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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),
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Provider(
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provider_id="sqlite-vec",
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provider_type="inline::sqlite-vec",
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config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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),
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Provider(
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provider_id="${env.MILVUS_URL:+milvus}",
|
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provider_type="inline::milvus",
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config=MilvusVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
|
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),
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Provider(
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provider_id="${env.CHROMADB_URL:+chromadb}",
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provider_type="remote::chromadb",
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||||
config=ChromaVectorIOConfig.sample_run_config(
|
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f"~/.llama/distributions/{name}/",
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url="${env.CHROMADB_URL:=}",
|
||||
),
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||||
),
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Provider(
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provider_id="${env.PGVECTOR_DB:+pgvector}",
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provider_type="remote::pgvector",
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config=PGVectorVectorIOConfig.sample_run_config(
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f"~/.llama/distributions/{name}",
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db="${env.PGVECTOR_DB:=}",
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user="${env.PGVECTOR_USER:=}",
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password="${env.PGVECTOR_PASSWORD:=}",
|
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),
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||||
),
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Provider(
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provider_id="${env.QDRANT_URL:+qdrant}",
|
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provider_type="remote::qdrant",
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config=QdrantVectorIOConfig.sample_run_config(
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f"~/.llama/distributions/{name}",
|
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url="${env.QDRANT_URL:=}",
|
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),
|
||||
),
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Provider(
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provider_id="${env.WEAVIATE_CLUSTER_URL:+weaviate}",
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provider_type="remote::weaviate",
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config=WeaviateVectorIOConfig.sample_run_config(
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f"~/.llama/distributions/{name}",
|
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cluster_url="${env.WEAVIATE_CLUSTER_URL:=}",
|
||||
),
|
||||
),
|
||||
],
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"files": [files_provider],
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},
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provider_overrides=default_overrides,
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default_models=[],
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default_tool_groups=default_tool_groups,
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default_shields=default_shields,
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|
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@ -261,6 +269,43 @@ def get_distribution_template(name: str = "starter") -> DistributionTemplate:
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default_shield_id="llama-guard",
|
||||
),
|
||||
),
|
||||
"run-with-postgres-store.yaml": RunConfigSettings(
|
||||
provider_overrides={
|
||||
**default_overrides,
|
||||
"agents": [
|
||||
Provider(
|
||||
provider_id="meta-reference",
|
||||
provider_type="inline::meta-reference",
|
||||
config=dict(
|
||||
persistence_store=postgres_config,
|
||||
responses_store=postgres_config,
|
||||
),
|
||||
)
|
||||
],
|
||||
},
|
||||
storage_backends={
|
||||
"kv_postgres": PostgresKVStoreConfig.sample_run_config(),
|
||||
"sql_postgres": postgres_config,
|
||||
},
|
||||
storage_stores={
|
||||
"metadata": KVStoreReference(
|
||||
backend="kv_postgres",
|
||||
namespace="registry",
|
||||
).model_dump(exclude_none=True),
|
||||
"inference": InferenceStoreReference(
|
||||
backend="sql_postgres",
|
||||
table_name="inference_store",
|
||||
).model_dump(exclude_none=True),
|
||||
"conversations": SqlStoreReference(
|
||||
backend="sql_postgres",
|
||||
table_name="openai_conversations",
|
||||
).model_dump(exclude_none=True),
|
||||
"prompts": KVStoreReference(
|
||||
backend="kv_postgres",
|
||||
namespace="prompts",
|
||||
).model_dump(exclude_none=True),
|
||||
},
|
||||
),
|
||||
},
|
||||
run_config_env_vars={
|
||||
"LLAMA_STACK_PORT": (
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue