feat: add oci genai service as chat inference provider

docs/docs/providers/agents/index.mdx

@@ -1,7 +1,7 @@
 ---
 description: "Agents
 
-    APIs for creating and interacting with agentic systems."
+APIs for creating and interacting with agentic systems."
 sidebar_label: Agents
 title: Agents
 ---
@@ -12,6 +12,6 @@ title: Agents
 
 Agents
 
-    APIs for creating and interacting with agentic systems.
+APIs for creating and interacting with agentic systems.
 
 This section contains documentation for all available providers for the **agents** API.

docs/docs/providers/batches/index.mdx

@@ -1,14 +1,14 @@
 ---
 description: "The Batches API enables efficient processing of multiple requests in a single operation,
-    particularly useful for processing large datasets, batch evaluation workflows, and
-    cost-effective inference at scale.
+particularly useful for processing large datasets, batch evaluation workflows, and
+cost-effective inference at scale.
 
-    The API is designed to allow use of openai client libraries for seamless integration.
+The API is designed to allow use of openai client libraries for seamless integration.
 
-    This API provides the following extensions:
-     - idempotent batch creation
+This API provides the following extensions:
+ - idempotent batch creation
 
-    Note: This API is currently under active development and may undergo changes."
+Note: This API is currently under active development and may undergo changes."
 sidebar_label: Batches
 title: Batches
 ---
@@ -18,14 +18,14 @@ title: Batches
 ## Overview
 
 The Batches API enables efficient processing of multiple requests in a single operation,
-    particularly useful for processing large datasets, batch evaluation workflows, and
-    cost-effective inference at scale.
+particularly useful for processing large datasets, batch evaluation workflows, and
+cost-effective inference at scale.
 
-    The API is designed to allow use of openai client libraries for seamless integration.
+The API is designed to allow use of openai client libraries for seamless integration.
 
-    This API provides the following extensions:
-     - idempotent batch creation
+This API provides the following extensions:
+ - idempotent batch creation
 
-    Note: This API is currently under active development and may undergo changes.
+Note: This API is currently under active development and may undergo changes.
 
 This section contains documentation for all available providers for the **batches** API.

docs/docs/providers/eval/index.mdx

@@ -1,7 +1,7 @@
 ---
 description: "Evaluations
 
-    Llama Stack Evaluation API for running evaluations on model and agent candidates."
+Llama Stack Evaluation API for running evaluations on model and agent candidates."
 sidebar_label: Eval
 title: Eval
 ---
@@ -12,6 +12,6 @@ title: Eval
 
 Evaluations
 
-    Llama Stack Evaluation API for running evaluations on model and agent candidates.
+Llama Stack Evaluation API for running evaluations on model and agent candidates.
 
 This section contains documentation for all available providers for the **eval** API.

docs/docs/providers/files/index.mdx

@@ -1,7 +1,7 @@
 ---
 description: "Files
 
-    This API is used to upload documents that can be used with other Llama Stack APIs."
+This API is used to upload documents that can be used with other Llama Stack APIs."
 sidebar_label: Files
 title: Files
 ---
@@ -12,6 +12,6 @@ title: Files
 
 Files
 
-    This API is used to upload documents that can be used with other Llama Stack APIs.
+This API is used to upload documents that can be used with other Llama Stack APIs.
 
 This section contains documentation for all available providers for the **files** API.

docs/docs/providers/inference/index.mdx

@@ -1,11 +1,11 @@
 ---
 description: "Inference
 
-    Llama Stack Inference API for generating completions, chat completions, and embeddings.
+Llama Stack Inference API for generating completions, chat completions, and embeddings.
 
-    This API provides the raw interface to the underlying models. Two kinds of models are supported:
-    - LLM models: these models generate \"raw\" and \"chat\" (conversational) completions.
-    - Embedding models: these models generate embeddings to be used for semantic search."
+This API provides the raw interface to the underlying models. Two kinds of models are supported:
+- LLM models: these models generate \"raw\" and \"chat\" (conversational) completions.
+- Embedding models: these models generate embeddings to be used for semantic search."
 sidebar_label: Inference
 title: Inference
 ---
@@ -16,10 +16,10 @@ title: Inference
 
 Inference
 
-    Llama Stack Inference API for generating completions, chat completions, and embeddings.
+Llama Stack Inference API for generating completions, chat completions, and embeddings.
 
-    This API provides the raw interface to the underlying models. Two kinds of models are supported:
-    - LLM models: these models generate "raw" and "chat" (conversational) completions.
-    - Embedding models: these models generate embeddings to be used for semantic search.
+This API provides the raw interface to the underlying models. Two kinds of models are supported:
+- LLM models: these models generate "raw" and "chat" (conversational) completions.
+- Embedding models: these models generate embeddings to be used for semantic search.
 
 This section contains documentation for all available providers for the **inference** API.

docs/docs/providers/safety/index.mdx

@@ -1,7 +1,7 @@
 ---
 description: "Safety
 
-    OpenAI-compatible Moderations API."
+OpenAI-compatible Moderations API."
 sidebar_label: Safety
 title: Safety
 ---
@@ -12,6 +12,6 @@ title: Safety
 
 Safety
 
-    OpenAI-compatible Moderations API.
+OpenAI-compatible Moderations API.
 
 This section contains documentation for all available providers for the **safety** API.

llama_stack/distributions/oci/__init__.py

@@ -0,0 +1,9 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .oci import get_distribution_template
+
+__all__ = ["get_distribution_template"]

llama_stack/distributions/oci/build.yaml

@@ -0,0 +1,34 @@
+version: 2
+distribution_spec:
+  description: Use Oracle Cloud Infrastructure (OCI) Generative AI for running LLM
+    inference with scalable cloud services
+  providers:
+    inference:
+    - provider_type: remote::oci
+    vector_io:
+    - provider_type: inline::faiss
+    - provider_type: remote::chromadb
+    - provider_type: remote::pgvector
+    safety:
+    - provider_type: inline::llama-guard
+    agents:
+    - provider_type: inline::meta-reference
+    eval:
+    - provider_type: inline::meta-reference
+    datasetio:
+    - provider_type: remote::huggingface
+    - provider_type: inline::localfs
+    scoring:
+    - provider_type: inline::basic
+    - provider_type: inline::llm-as-judge
+    - provider_type: inline::braintrust
+    tool_runtime:
+    - provider_type: remote::brave-search
+    - provider_type: remote::tavily-search
+    - provider_type: remote::model-context-protocol
+    files:
+    - provider_type: inline::localfs
+image_type: venv
+additional_pip_packages:
+- aiosqlite
+- sqlalchemy[asyncio]

llama_stack/distributions/oci/oci.py

@@ -0,0 +1,123 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from pathlib import Path
+
+from llama_stack.core.datatypes import BuildProvider, Provider, ToolGroupInput
+from llama_stack.distributions.template import DistributionTemplate, RunConfigSettings
+from llama_stack.providers.inline.files.localfs.config import LocalfsFilesImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
+from llama_stack.providers.remote.inference.oci.config import OCIConfig
+
+
+def get_distribution_template(name: str = "oci") -> DistributionTemplate:
+    providers = {
+        "inference": [BuildProvider(provider_type="remote::oci")],
+        "vector_io": [
+            BuildProvider(provider_type="inline::faiss"),
+            BuildProvider(provider_type="remote::chromadb"),
+            BuildProvider(provider_type="remote::pgvector"),
+        ],
+        "safety": [BuildProvider(provider_type="inline::llama-guard")],
+        "agents": [BuildProvider(provider_type="inline::meta-reference")],
+        "eval": [BuildProvider(provider_type="inline::meta-reference")],
+        "datasetio": [
+            BuildProvider(provider_type="remote::huggingface"),
+            BuildProvider(provider_type="inline::localfs"),
+        ],
+        "scoring": [
+            BuildProvider(provider_type="inline::basic"),
+            BuildProvider(provider_type="inline::llm-as-judge"),
+            BuildProvider(provider_type="inline::braintrust"),
+        ],
+        "tool_runtime": [
+            BuildProvider(provider_type="remote::brave-search"),
+            BuildProvider(provider_type="remote::tavily-search"),
+            BuildProvider(provider_type="remote::model-context-protocol"),
+        ],
+        "files": [BuildProvider(provider_type="inline::localfs")],
+    }
+
+    inference_provider = Provider(
+        provider_id="oci",
+        provider_type="remote::oci",
+        config=OCIConfig.sample_run_config(),
+    )
+
+    files_provider = Provider(
+        provider_id="meta-reference-files",
+        provider_type="inline::localfs",
+        config=LocalfsFilesImplConfig.sample_run_config(f"~/.llama/distributions/{name}"),
+    )
+    vector_io_provider = Provider(
+        provider_id="faiss",
+        provider_type="inline::faiss",
+        config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
+    )
+
+    default_tool_groups = [
+        ToolGroupInput(
+            toolgroup_id="builtin::websearch",
+            provider_id="tavily-search",
+        ),
+    ]
+
+    return DistributionTemplate(
+        name=name,
+        distro_type="remote_hosted",
+        description="Use Oracle Cloud Infrastructure (OCI) Generative AI for running LLM inference with scalable cloud services",
+        container_image=None,
+        template_path=Path(__file__).parent / "doc_template.md",
+        providers=providers,
+        run_configs={
+            "run.yaml": RunConfigSettings(
+                provider_overrides={
+                    "inference": [inference_provider],
+                    "vector_io": [vector_io_provider],
+                    "files": [files_provider],
+                },
+                default_tool_groups=default_tool_groups,
+            ),
+        },
+        run_config_env_vars={
+            "OCI_AUTH_TYPE": (
+                "instance_principal",
+                "OCI authentication type (instance_principal or config_file)",
+            ),
+            "OCI_USER_OCID": (
+                "",
+                "OCI user OCID for authentication",
+            ),
+            "OCI_TENANCY_OCID": (
+                "",
+                "OCI tenancy OCID for authentication",
+            ),
+            "OCI_FINGERPRINT": (
+                "",
+                "OCI API key fingerprint for authentication",
+            ),
+            "OCI_PRIVATE_KEY": (
+                "",
+                "OCI private key for authentication",
+            ),
+            "OCI_REGION": (
+                "",
+                "OCI region (e.g., us-ashburn-1, us-chicago-1, us-phoenix-1, eu-frankfurt-1)",
+            ),
+            "OCI_COMPARTMENT_OCID": (
+                "",
+                "OCI compartment ID for the Generative AI service",
+            ),
+            "OCI_CONFIG_FILE_PATH": (
+                "~/.oci/config",
+                "OCI config file path (required if OCI_AUTH_TYPE is config_file)",
+            ),
+            "OCI_CLI_PROFILE": (
+                "DEFAULT",
+                "OCI CLI profile name to use from config file",
+            ),
+        },
+    )