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feat: add oci genai service as chat inference provider (#3876)
# 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.
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src/llama_stack/distributions/oci/run.yaml
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src/llama_stack/distributions/oci/run.yaml
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version: 2
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image_name: oci
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apis:
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- agents
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- datasetio
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- eval
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- files
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- inference
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- safety
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- scoring
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- tool_runtime
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- vector_io
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providers:
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inference:
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- provider_id: oci
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provider_type: remote::oci
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config:
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oci_auth_type: ${env.OCI_AUTH_TYPE:=instance_principal}
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oci_config_file_path: ${env.OCI_CONFIG_FILE_PATH:=~/.oci/config}
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oci_config_profile: ${env.OCI_CLI_PROFILE:=DEFAULT}
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oci_region: ${env.OCI_REGION:=us-ashburn-1}
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oci_compartment_id: ${env.OCI_COMPARTMENT_OCID:=}
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vector_io:
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- provider_id: faiss
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provider_type: inline::faiss
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config:
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persistence:
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namespace: vector_io::faiss
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backend: kv_default
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safety:
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- provider_id: llama-guard
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provider_type: inline::llama-guard
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config:
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excluded_categories: []
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agents:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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persistence:
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agent_state:
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namespace: agents
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backend: kv_default
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responses:
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table_name: responses
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backend: sql_default
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max_write_queue_size: 10000
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num_writers: 4
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eval:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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kvstore:
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namespace: eval
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backend: kv_default
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datasetio:
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- provider_id: huggingface
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provider_type: remote::huggingface
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config:
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kvstore:
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namespace: datasetio::huggingface
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backend: kv_default
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- provider_id: localfs
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provider_type: inline::localfs
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config:
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kvstore:
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namespace: datasetio::localfs
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backend: kv_default
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scoring:
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- provider_id: basic
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provider_type: inline::basic
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- provider_id: llm-as-judge
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provider_type: inline::llm-as-judge
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- provider_id: braintrust
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provider_type: inline::braintrust
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config:
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openai_api_key: ${env.OPENAI_API_KEY:=}
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tool_runtime:
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- provider_id: brave-search
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provider_type: remote::brave-search
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config:
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api_key: ${env.BRAVE_SEARCH_API_KEY:=}
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max_results: 3
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- provider_id: tavily-search
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provider_type: remote::tavily-search
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config:
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api_key: ${env.TAVILY_SEARCH_API_KEY:=}
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max_results: 3
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- provider_id: rag-runtime
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provider_type: inline::rag-runtime
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- provider_id: model-context-protocol
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provider_type: remote::model-context-protocol
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files:
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- provider_id: meta-reference-files
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provider_type: inline::localfs
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config:
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storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/oci/files}
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metadata_store:
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table_name: files_metadata
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backend: sql_default
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storage:
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backends:
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kv_default:
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type: kv_sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/oci}/kvstore.db
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sql_default:
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type: sql_sqlite
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db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/oci}/sql_store.db
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stores:
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metadata:
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namespace: registry
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backend: kv_default
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inference:
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table_name: inference_store
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backend: sql_default
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max_write_queue_size: 10000
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num_writers: 4
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conversations:
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table_name: openai_conversations
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backend: sql_default
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prompts:
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namespace: prompts
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backend: kv_default
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registered_resources:
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models: []
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shields: []
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vector_dbs: []
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datasets: []
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scoring_fns: []
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benchmarks: []
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tool_groups:
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- toolgroup_id: builtin::websearch
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provider_id: tavily-search
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server:
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port: 8321
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telemetry:
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enabled: true
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