mirror of
https://github.com/meta-llama/llama-stack.git
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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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7
src/llama_stack/distributions/oci/__init__.py
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7
src/llama_stack/distributions/oci/__init__.py
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from .oci import get_distribution_template # noqa: F401
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35
src/llama_stack/distributions/oci/build.yaml
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src/llama_stack/distributions/oci/build.yaml
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version: 2
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distribution_spec:
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description: Use Oracle Cloud Infrastructure (OCI) Generative AI for running LLM
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inference with scalable cloud services
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providers:
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inference:
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- provider_type: remote::oci
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vector_io:
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- provider_type: inline::faiss
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- provider_type: remote::chromadb
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- provider_type: remote::pgvector
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safety:
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- provider_type: inline::llama-guard
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agents:
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- provider_type: inline::meta-reference
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eval:
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- provider_type: inline::meta-reference
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datasetio:
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- provider_type: remote::huggingface
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- provider_type: inline::localfs
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scoring:
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- provider_type: inline::basic
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- provider_type: inline::llm-as-judge
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- provider_type: inline::braintrust
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tool_runtime:
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- provider_type: remote::brave-search
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- provider_type: remote::tavily-search
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- provider_type: inline::rag-runtime
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- provider_type: remote::model-context-protocol
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files:
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- provider_type: inline::localfs
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image_type: venv
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additional_pip_packages:
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- aiosqlite
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- sqlalchemy[asyncio]
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140
src/llama_stack/distributions/oci/doc_template.md
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140
src/llama_stack/distributions/oci/doc_template.md
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@ -0,0 +1,140 @@
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---
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orphan: true
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---
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# OCI Distribution
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The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations.
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{{ providers_table }}
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{% if run_config_env_vars %}
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### Environment Variables
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The following environment variables can be configured:
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{% for var, (default_value, description) in run_config_env_vars.items() %}
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- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
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{% endfor %}
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{% endif %}
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{% if default_models %}
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### Models
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The following models are available by default:
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{% for model in default_models %}
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- `{{ model.model_id }} {{ model.doc_string }}`
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{% endfor %}
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{% endif %}
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## Prerequisites
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### Oracle Cloud Infrastructure Setup
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Before using the OCI Generative AI distribution, ensure you have:
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1. **Oracle Cloud Infrastructure Account**: Sign up at [Oracle Cloud Infrastructure](https://cloud.oracle.com/)
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2. **Generative AI Service Access**: Enable the Generative AI service in your OCI tenancy
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3. **Compartment**: Create or identify a compartment where you'll deploy Generative AI models
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4. **Authentication**: Configure authentication using either:
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- **Instance Principal** (recommended for cloud-hosted deployments)
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- **API Key** (for on-premises or development environments)
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### Authentication Methods
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#### Instance Principal Authentication (Recommended)
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Instance Principal authentication allows OCI resources to authenticate using the identity of the compute instance they're running on. This is the most secure method for production deployments.
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Requirements:
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- Instance must be running in an Oracle Cloud Infrastructure compartment
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- Instance must have appropriate IAM policies to access Generative AI services
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#### API Key Authentication
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For development or on-premises deployments, follow [this doc](https://docs.oracle.com/en-us/iaas/Content/API/Concepts/apisigningkey.htm) to learn how to create your API signing key for your config file.
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### Required IAM Policies
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Ensure your OCI user or instance has the following policy statements:
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```
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Allow group <group_name> to use generative-ai-inference-endpoints in compartment <compartment_name>
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Allow group <group_name> to manage generative-ai-inference-endpoints in compartment <compartment_name>
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```
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## Supported Services
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### Inference: OCI Generative AI
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Oracle Cloud Infrastructure Generative AI provides access to high-performance AI models through OCI's Platform-as-a-Service offering. The service supports:
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- **Chat Completions**: Conversational AI with context awareness
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- **Text Generation**: Complete prompts and generate text content
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#### Available Models
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Common OCI Generative AI models include access to Meta, Cohere, OpenAI, Grok, and more models.
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### Safety: Llama Guard
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For content safety and moderation, this distribution uses Meta's LlamaGuard model through the OCI Generative AI service to provide:
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- Content filtering and moderation
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- Policy compliance checking
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- Harmful content detection
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### Vector Storage: Multiple Options
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The distribution supports several vector storage providers:
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- **FAISS**: Local in-memory vector search
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- **ChromaDB**: Distributed vector database
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- **PGVector**: PostgreSQL with vector extensions
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### Additional Services
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- **Dataset I/O**: Local filesystem and Hugging Face integration
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- **Tool Runtime**: Web search (Brave, Tavily) and RAG capabilities
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- **Evaluation**: Meta reference evaluation framework
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## Running Llama Stack with OCI
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You can run the OCI distribution via Docker or local virtual environment.
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### Via venv
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If you've set up your local development environment, you can also build the image using your local virtual environment.
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```bash
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OCI_AUTH=$OCI_AUTH_TYPE OCI_REGION=$OCI_REGION OCI_COMPARTMENT_OCID=$OCI_COMPARTMENT_OCID llama stack run --port 8321 oci
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```
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### Configuration Examples
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#### Using Instance Principal (Recommended for Production)
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```bash
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export OCI_AUTH_TYPE=instance_principal
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export OCI_REGION=us-chicago-1
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export OCI_COMPARTMENT_OCID=ocid1.compartment.oc1..<your-compartment-id>
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```
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#### Using API Key Authentication (Development)
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```bash
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export OCI_AUTH_TYPE=config_file
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export OCI_CONFIG_FILE_PATH=~/.oci/config
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export OCI_CLI_PROFILE=DEFAULT
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export OCI_REGION=us-chicago-1
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export OCI_COMPARTMENT_OCID=ocid1.compartment.oc1..your-compartment-id
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```
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## Regional Endpoints
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OCI Generative AI is available in multiple regions. The service automatically routes to the appropriate regional endpoint based on your configuration. For a full list of regional model availability, visit:
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https://docs.oracle.com/en-us/iaas/Content/generative-ai/overview.htm#regions
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## Troubleshooting
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### Common Issues
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1. **Authentication Errors**: Verify your OCI credentials and IAM policies
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2. **Model Not Found**: Ensure the model OCID is correct and the model is available in your region
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3. **Permission Denied**: Check compartment permissions and Generative AI service access
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4. **Region Unavailable**: Verify the specified region supports Generative AI services
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### Getting Help
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For additional support:
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- [OCI Generative AI Documentation](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm)
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- [Llama Stack Issues](https://github.com/meta-llama/llama-stack/issues)
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108
src/llama_stack/distributions/oci/oci.py
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108
src/llama_stack/distributions/oci/oci.py
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from pathlib import Path
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from llama_stack.core.datatypes import BuildProvider, Provider, ToolGroupInput
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from llama_stack.distributions.template import DistributionTemplate, RunConfigSettings
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from llama_stack.providers.inline.files.localfs.config import LocalfsFilesImplConfig
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from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
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from llama_stack.providers.remote.inference.oci.config import OCIConfig
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def get_distribution_template(name: str = "oci") -> DistributionTemplate:
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providers = {
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"inference": [BuildProvider(provider_type="remote::oci")],
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"vector_io": [
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BuildProvider(provider_type="inline::faiss"),
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BuildProvider(provider_type="remote::chromadb"),
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BuildProvider(provider_type="remote::pgvector"),
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],
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"safety": [BuildProvider(provider_type="inline::llama-guard")],
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"agents": [BuildProvider(provider_type="inline::meta-reference")],
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"eval": [BuildProvider(provider_type="inline::meta-reference")],
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"datasetio": [
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BuildProvider(provider_type="remote::huggingface"),
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BuildProvider(provider_type="inline::localfs"),
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],
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"scoring": [
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BuildProvider(provider_type="inline::basic"),
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BuildProvider(provider_type="inline::llm-as-judge"),
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BuildProvider(provider_type="inline::braintrust"),
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],
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"tool_runtime": [
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BuildProvider(provider_type="remote::brave-search"),
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BuildProvider(provider_type="remote::tavily-search"),
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BuildProvider(provider_type="inline::rag-runtime"),
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BuildProvider(provider_type="remote::model-context-protocol"),
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],
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"files": [BuildProvider(provider_type="inline::localfs")],
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}
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inference_provider = Provider(
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provider_id="oci",
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provider_type="remote::oci",
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config=OCIConfig.sample_run_config(),
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)
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vector_io_provider = Provider(
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provider_id="faiss",
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provider_type="inline::faiss",
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config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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)
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files_provider = Provider(
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provider_id="meta-reference-files",
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provider_type="inline::localfs",
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config=LocalfsFilesImplConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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)
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default_tool_groups = [
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ToolGroupInput(
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toolgroup_id="builtin::websearch",
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provider_id="tavily-search",
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),
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]
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return DistributionTemplate(
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name=name,
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distro_type="remote_hosted",
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description="Use Oracle Cloud Infrastructure (OCI) Generative AI for running LLM inference with scalable cloud services",
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container_image=None,
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template_path=Path(__file__).parent / "doc_template.md",
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providers=providers,
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run_configs={
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"run.yaml": RunConfigSettings(
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provider_overrides={
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"inference": [inference_provider],
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"vector_io": [vector_io_provider],
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"files": [files_provider],
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},
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default_tool_groups=default_tool_groups,
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),
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},
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run_config_env_vars={
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"OCI_AUTH_TYPE": (
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"instance_principal",
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"OCI authentication type (instance_principal or config_file)",
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),
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"OCI_REGION": (
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"",
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"OCI region (e.g., us-ashburn-1, us-chicago-1, us-phoenix-1, eu-frankfurt-1)",
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),
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"OCI_COMPARTMENT_OCID": (
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"",
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"OCI compartment ID for the Generative AI service",
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),
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"OCI_CONFIG_FILE_PATH": (
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"~/.oci/config",
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"OCI config file path (required if OCI_AUTH_TYPE is config_file)",
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),
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"OCI_CLI_PROFILE": (
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"DEFAULT",
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"OCI CLI profile name to use from config file",
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),
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},
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)
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136
src/llama_stack/distributions/oci/run.yaml
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136
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: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
server:
|
||||
port: 8321
|
||||
telemetry:
|
||||
enabled: true
|
||||
Loading…
Add table
Add a link
Reference in a new issue