test: add openai compatible tests for responses, vector stores and files api

Author: Ygnas

tests/llama_stack/conftest.py

@@ -10,6 +10,7 @@
 from ocp_resources.deployment import Deployment
 from ocp_resources.llama_stack_distribution import LlamaStackDistribution
 from ocp_resources.namespace import Namespace
+from ocp_resources.config_map import ConfigMap
 from simple_logger.logger import get_logger
 
 from tests.llama_stack.utils import create_llama_stack_distribution, wait_for_llama_stack_client_ready
@@ -81,22 +82,187 @@ def llama_stack_server_config(
                 },
                 {"name": "FMS_ORCHESTRATOR_URL", "value": fms_orchestrator_url},
             ],
+            "command": ["/bin/sh", "-c", "llama stack run /etc/llama-stack/run.yaml"],
             "name": "llama-stack",
             "port": 8321,
         },
         "distribution": {"name": "rh-dev"},
+        "userConfig": {"configMapName": "rag-llama-stack-config-map"},
         "storage": {
             "size": "20Gi",
         },
     }
 
 
+@pytest.fixture(scope="class")
+def llama_stack_config_map(
+    admin_client: DynamicClient,
+    model_namespace: Namespace,
+) -> Generator[ConfigMap, Any, Any]:
+    with ConfigMap(
+        client=admin_client,
+        namespace=model_namespace.name,
+        name="rag-llama-stack-config-map",
+        data={
+            "run.yaml": """version: 2
+image_name: rh
+apis:
+- agents
+- datasetio
+- eval
+- inference
+- safety
+- files
+- scoring
+- telemetry
+- tool_runtime
+- vector_io
+providers:
+  inference:
+  - provider_id: vllm-inference
+    provider_type: remote::vllm
+    config:
+      url: ${env.VLLM_URL:=http://localhost:8000/v1}
+      max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
+      api_token: ${env.VLLM_API_TOKEN:=fake}
+      tls_verify: ${env.VLLM_TLS_VERIFY:=true}
+  - provider_id: sentence-transformers
+    provider_type: inline::sentence-transformers
+    config: {}
+  vector_io:
+  - provider_id: milvus
+    provider_type: inline::milvus
+    config:
+      db_path: /opt/app-root/src/.llama/distributions/rh/milvus.db
+      kvstore:
+        type: sqlite
+        namespace: null
+        db_path: /opt/app-root/src/.llama/distributions/rh/milvus_registry.db
+  files:
+  - provider_id: meta-reference-files
+    provider_type: inline::localfs
+    config:
+      storage_dir: /opt/app-root/src/.llama/distributions/rh/files
+      metadata_store:
+        type: sqlite
+        db_path: /opt/app-root/src/.llama/distributions/rh/files/files_metadata.db
+  safety:
+    - provider_id: trustyai_fms
+      provider_type: remote::trustyai_fms
+      config:
+        orchestrator_url: ${env.FMS_ORCHESTRATOR_URL:=}
+        ssl_cert_path: ${env.FMS_SSL_CERT_PATH:=}
+        shields: {}
+  agents:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      persistence_store:
+        type: sqlite
+        namespace: null
+        db_path: /opt/app-root/src/.llama/distributions/rh/agents_store.db
+      responses_store:
+        type: sqlite
+        db_path: /opt/app-root/src/.llama/distributions/rh/responses_store.db
+  eval:
+  - provider_id: trustyai_lmeval
+    provider_type: remote::trustyai_lmeval
+    config:
+        use_k8s: True
+        base_url: ${env.VLLM_URL:=http://localhost:8000/v1}
+  datasetio:
+  - provider_id: huggingface
+    provider_type: remote::huggingface
+    config:
+      kvstore:
+        type: sqlite
+        namespace: null
+        db_path: /opt/app-root/src/.llama/distributions/rh/huggingface_datasetio.db
+  - provider_id: localfs
+    provider_type: inline::localfs
+    config:
+      kvstore:
+        type: sqlite
+        namespace: null
+        db_path: /opt/app-root/src/.llama/distributions/rh/localfs_datasetio.db
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+    config: {}
+  - provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+    config: {}
+  - provider_id: braintrust
+    provider_type: inline::braintrust
+    config:
+      openai_api_key: ${env.OPENAI_API_KEY:=}
+  telemetry:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      service_name: "${env.OTEL_SERVICE_NAME:=\u200b}"
+      sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
+      sqlite_db_path: /opt/app-root/src/.llama/distributions/rh/trace_store.db
+      otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
+  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
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
+    config: {}
+metadata_store:
+  type: sqlite
+  db_path: /opt/app-root/src/.llama/distributions/rh/registry.db
+inference_store:
+  type: sqlite
+  db_path: /opt/app-root/src/.llama/distributions/rh/inference_store.db
+models:
+- metadata: {}
+  model_id: /mnt/models
+  provider_id: vllm-inference
+  model_type: llm
+- metadata:
+    embedding_dimension: 768
+  model_id: granite-embedding-125m
+  provider_id: sentence-transformers
+  provider_model_id: ibm-granite/granite-embedding-125m-english
+  model_type: embedding
+shields: []
+vector_dbs: []
+datasets: []
+scoring_fns: []
+benchmarks: []
+tool_groups:
+- toolgroup_id: builtin::websearch
+  provider_id: tavily-search
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
+server:
+  port: 8321
+external_providers_dir: /opt/app-root/src/.llama/providers.d"""
+        },
+    ) as config_map:
+        yield config_map
+
+
 @pytest.fixture(scope="class")
 def llama_stack_distribution(
     admin_client: DynamicClient,
     model_namespace: Namespace,
     enabled_llama_stack_operator: DataScienceCluster,
     llama_stack_server_config: Dict[str, Any],
+    llama_stack_config_map: ConfigMap,
 ) -> Generator[LlamaStackDistribution, None, None]:
     with create_llama_stack_distribution(
         client=admin_client,