llama-stack-mirror/llama_stack/distributions/dell/run-with-safety.yaml
Ashwin Bharambe 81e44b06ff fix: harden storage semantics (#4118)
Fixes issues in the storage system by guaranteeing immediate durability
for responses and ensuring background writers stay alive. Three related
fixes:

* Responses to the OpenAI-compatible API now write directly to
Postgres/SQLite inside the request instead of detouring through an async
queue that might never drain; this restores the expected
read-after-write behavior and removes the "response not found" races
reported by users.

* The access-control shim was stamping owner_principal/access_attributes
as SQL NULL, which Postgres interprets as non-public rows; fixing it to
use the empty-string/JSON-null pattern means conversations and responses
stored without an authenticated user stay queryable (matching SQLite).

* The inference-store queue remains for batching, but its worker tasks
now start lazily on the live event loop so server startup doesn't cancel
them—writes keep flowing even when the stack is launched via llama stack
run.

Closes #4115

Added a matrix entry to test our "base" suite against Postgres as the
store.
2025-11-12 12:40:23 -08:00

144 lines
3.4 KiB
YAML

version: 2
image_name: dell
apis:
- agents
- datasetio
- eval
- inference
- safety
- scoring
- tool_runtime
- vector_io
providers:
inference:
- provider_id: tgi0
provider_type: remote::tgi
config:
url: ${env.DEH_URL}
- provider_id: tgi1
provider_type: remote::tgi
config:
url: ${env.DEH_SAFETY_URL}
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
vector_io:
- provider_id: chromadb
provider_type: remote::chromadb
config:
url: ${env.CHROMADB_URL:=}
persistence:
namespace: vector_io::chroma_remote
backend: kv_default
safety:
- provider_id: llama-guard
provider_type: inline::llama-guard
config:
excluded_categories: []
agents:
- provider_id: meta-reference
provider_type: inline::meta-reference
config:
persistence:
agent_state:
namespace: agents
backend: kv_default
responses:
table_name: responses
backend: sql_default
max_write_queue_size: 10000
num_writers: 4
eval:
- provider_id: meta-reference
provider_type: inline::meta-reference
config:
kvstore:
namespace: eval
backend: kv_default
datasetio:
- provider_id: huggingface
provider_type: remote::huggingface
config:
kvstore:
namespace: datasetio::huggingface
backend: kv_default
- provider_id: localfs
provider_type: inline::localfs
config:
kvstore:
namespace: datasetio::localfs
backend: kv_default
scoring:
- provider_id: basic
provider_type: inline::basic
- provider_id: llm-as-judge
provider_type: inline::llm-as-judge
- provider_id: braintrust
provider_type: inline::braintrust
config:
openai_api_key: ${env.OPENAI_API_KEY:=}
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search
config:
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
max_results: 3
- provider_id: tavily-search
provider_type: remote::tavily-search
config:
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
max_results: 3
- provider_id: rag-runtime
provider_type: inline::rag-runtime
storage:
backends:
kv_default:
type: kv_sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/kvstore.db
sql_default:
type: sql_sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/sql_store.db
stores:
metadata:
namespace: registry
backend: kv_default
inference:
table_name: inference_store
backend: sql_default
max_write_queue_size: 10000
num_writers: 4
conversations:
table_name: openai_conversations
backend: sql_default
prompts:
namespace: prompts
backend: kv_default
registered_resources:
models:
- metadata: {}
model_id: ${env.INFERENCE_MODEL}
provider_id: tgi0
model_type: llm
- metadata: {}
model_id: ${env.SAFETY_MODEL}
provider_id: tgi1
model_type: llm
- metadata:
embedding_dimension: 768
model_id: nomic-embed-text-v1.5
provider_id: sentence-transformers
model_type: embedding
shields:
- shield_id: ${env.SAFETY_MODEL}
vector_dbs: []
datasets: []
scoring_fns: []
benchmarks: []
tool_groups:
- toolgroup_id: builtin::websearch
provider_id: brave-search
- toolgroup_id: builtin::rag
provider_id: rag-runtime
server:
port: 8321
telemetry:
enabled: true