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openai-faiss-run.yaml
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# Example llama-stack configuration for OpenAI inference + FAISS (RAG)
#
# Notes:
# - You will need an OpenAI API key
# - You can generate the vector index with the rag-content tool (https://github.com/lightspeed-core/rag-content)
#
version: 2
image_name: openai-faiss-config
apis:
- agents
- inference
- vector_io
- tool_runtime
- safety
models:
- model_id: gpt-test
provider_id: openai # This ID is a reference to 'providers.inference'
model_type: llm
provider_model_id: gpt-4o-mini
- model_id: sentence-transformers/all-mpnet-base-v2
metadata:
embedding_dimension: 768
model_type: embedding
provider_id: sentence-transformers # This ID is a reference to 'providers.inference'
provider_model_id: /home/USER/lightspeed-stack/embedding_models/all-mpnet-base-v2
providers:
inference:
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
config: {}
- provider_id: openai
provider_type: remote::openai
config:
api_key: ${env.OPENAI_API_KEY}
agents:
- provider_id: meta-reference
provider_type: inline::meta-reference
config:
persistence_store:
type: sqlite
db_path: .llama/distributions/ollama/agents_store.db
responses_store:
type: sqlite
db_path: .llama/distributions/ollama/responses_store.db
safety:
- provider_id: llama-guard
provider_type: inline::llama-guard
config:
excluded_categories: []
vector_io:
- provider_id: ocp-docs
provider_type: inline::faiss
config:
kvstore:
type: sqlite
db_path: /home/USER/lightspeed-stack/vector_dbs/ocp_docs/faiss_store.db
namespace: null
tool_runtime:
- provider_id: rag-runtime
provider_type: inline::rag-runtime
config: {}
# Enable the RAG tool
tool_groups:
- provider_id: rag-runtime
toolgroup_id: builtin::rag
args: null
mcp_endpoint: null
vector_dbs:
- embedding_dimension: 768
embedding_model: sentence-transformers/all-mpnet-base-v2
provider_id: ocp-docs # This ID is a reference to 'providers.vector_io'
vector_db_id: openshift-index # This ID was defined during index generation