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feat: add oci genai service as chat inference provider (#3876)

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# What does this PR do?
Adds OCI GenAI PaaS models for openai chat completion endpoints.

## Test Plan
In an OCI tenancy with access to GenAI PaaS, perform the following
steps:

1. Ensure you have IAM policies in place to use service (check docs
included in this PR)
2. For local development, [setup OCI
cli](https://docs.oracle.com/en-us/iaas/Content/API/SDKDocs/cliinstall.htm)
and configure the CLI with your region, tenancy, and auth
[here](https://docs.oracle.com/en-us/iaas/Content/API/SDKDocs/cliconfigure.htm)
3. Once configured, go through llama-stack setup and run llama-stack
(uses config based auth) like:
```bash
OCI_AUTH_TYPE=config_file \
OCI_CLI_PROFILE=CHICAGO \
OCI_REGION=us-chicago-1 \
OCI_COMPARTMENT_OCID=ocid1.compartment.oc1..aaaaaaaa5...5a \
llama stack run oci
```
4. Hit the `models` endpoint to list models after server is running:
```bash
curl http://localhost:8321/v1/models | jq
...
{
      "identifier": "meta.llama-4-scout-17b-16e-instruct",
      "provider_resource_id": "ocid1.generativeaimodel.oc1.us-chicago-1.am...q",
      "provider_id": "oci",
      "type": "model",
      "metadata": {
        "display_name": "meta.llama-4-scout-17b-16e-instruct",
        "capabilities": [
          "CHAT"
        ],
        "oci_model_id": "ocid1.generativeaimodel.oc1.us-chicago-1.a...q"
      },
      "model_type": "llm"
},
   ...
```
5. Use the "display_name" field to use the model in a
`/chat/completions` request:
```bash
# Streaming result
curl -X POST http://localhost:8321/v1/chat/completions   -H "Content-Type: application/json"   -d '{
        "model": "meta.llama-4-scout-17b-16e-instruct",
       "stream": true,
       "temperature": 0.9,
      "messages": [
         {
           "role": "system",
           "content": "You are a funny comedian. You can be crass."
         },
          {
           "role": "user",
          "content": "Tell me a funny joke about programming."
         }
       ]
}'

# Non-streaming result
curl -X POST http://localhost:8321/v1/chat/completions   -H "Content-Type: application/json"   -d '{
        "model": "meta.llama-4-scout-17b-16e-instruct",
       "stream": false,
       "temperature": 0.9,
      "messages": [
         {
           "role": "system",
           "content": "You are a funny comedian. You can be crass."
         },
          {
           "role": "user",
          "content": "Tell me a funny joke about programming."
         }
       ]
}'
```
6. Try out other models from the `/models` endpoint.
This commit is contained in:
Dennis Kennetz 2025-11-10 15:16:24 -06:00 • committed by GitHub
parent fadf17daf3
commit 209a78b618
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# 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="inline::rag-runtime"),
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(),
)
vector_io_provider = Provider(
provider_id="faiss",
provider_type="inline::faiss",
config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
)
files_provider = Provider(
provider_id="meta-reference-files",
provider_type="inline::localfs",
config=LocalfsFilesImplConfig.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_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",
),
},
)