llama-stack-mirror/src/llama_stack/distributions/nvidia/run.yaml
Charlie Doern d5cd0eea14
feat!: standardize base_url for inference (#4177)
# What does this PR do?

Completes #3732 by removing runtime URL transformations and requiring
users to provide full URLs in configuration. All providers now use
'base_url' consistently and respect the exact URL provided without
appending paths like /v1 or /openai/v1 at runtime.

BREAKING CHANGE: Users must update configs to include full URL paths
(e.g., http://localhost:11434/v1 instead of http://localhost:11434).

Closes #3732 

## Test Plan

Existing tests should pass even with the URL changes, due to default
URLs being altered.

Add unit test to enforce URL standardization across remote inference
providers (verifies all use 'base_url' field with HttpUrl | None type)

Signed-off-by: Charlie Doern <cdoern@redhat.com>
2025-11-19 08:44:28 -08:00

118 lines
3.1 KiB
YAML

version: 2
image_name: nvidia
apis:
- agents
- datasetio
- eval
- files
- inference
- post_training
- safety
- scoring
- tool_runtime
- vector_io
providers:
inference:
- provider_id: nvidia
provider_type: remote::nvidia
config:
base_url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com/v1}
api_key: ${env.NVIDIA_API_KEY:=}
vector_io:
- provider_id: faiss
provider_type: inline::faiss
config:
persistence:
namespace: vector_io::faiss
backend: kv_default
safety:
- provider_id: nvidia
provider_type: remote::nvidia
config:
guardrails_service_url: ${env.GUARDRAILS_SERVICE_URL:=http://localhost:7331}
config_id: ${env.NVIDIA_GUARDRAILS_CONFIG_ID:=self-check}
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: nvidia
provider_type: remote::nvidia
config:
evaluator_url: ${env.NVIDIA_EVALUATOR_URL:=http://localhost:7331}
post_training:
- provider_id: nvidia
provider_type: remote::nvidia
config:
api_key: ${env.NVIDIA_API_KEY:=}
dataset_namespace: ${env.NVIDIA_DATASET_NAMESPACE:=default}
project_id: ${env.NVIDIA_PROJECT_ID:=test-project}
customizer_url: ${env.NVIDIA_CUSTOMIZER_URL:=http://nemo.test}
datasetio:
- provider_id: nvidia
provider_type: remote::nvidia
config:
api_key: ${env.NVIDIA_API_KEY:=}
dataset_namespace: ${env.NVIDIA_DATASET_NAMESPACE:=default}
project_id: ${env.NVIDIA_PROJECT_ID:=test-project}
datasets_url: ${env.NVIDIA_DATASETS_URL:=http://nemo.test}
scoring:
- provider_id: basic
provider_type: inline::basic
tool_runtime:
- provider_id: rag-runtime
provider_type: inline::rag-runtime
files:
- provider_id: meta-reference-files
provider_type: inline::localfs
config:
storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/nvidia/files}
metadata_store:
table_name: files_metadata
backend: sql_default
storage:
backends:
kv_default:
type: kv_sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/kvstore.db
sql_default:
type: sql_sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/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: []
shields: []
vector_dbs: []
datasets: []
scoring_fns: []
benchmarks: []
tool_groups:
- toolgroup_id: builtin::rag
provider_id: rag-runtime
server:
port: 8321
telemetry:
enabled: true