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version: 2
distro_name: azure-configuration
apis:
- responses
- batches
- files
- inference
- tool_runtime
- conversations
- vector_io
# external_providers_dir: /opt/app-root/src/.llama/providers.d
providers:
inference:
- provider_id: azure
provider_type: remote::azure
config:
base_url: https://ols-test.openai.azure.com/openai/v1
api_version: 2024-02-15-preview
model_validation: false
- provider_id: openai
provider_type: remote::openai
config:
api_key: ${env.OPENAI_API_KEY}
- config: {}
provider_id: sentence-transformers
provider_type: inline::sentence-transformers
files:
- config:
metadata_store:
table_name: files_metadata
backend: sql_default
storage_dir: ~/.llama/storage/files
provider_id: meta-reference-files
provider_type: inline::localfs
tool_runtime:
- config: {} # Enable the RAG tool
provider_id: file-search
provider_type: inline::file-search
- config: {} # Enable MCP (Model Context Protocol) support
provider_id: model-context-protocol
provider_type: remote::model-context-protocol
vector_io:
- config:
persistence:
namespace: vector_io::faiss
backend: kv_rag
provider_id: faiss
provider_type: inline::faiss
responses:
- config:
persistence:
responses:
table_name: agents_responses
backend: sql_default
provider_id: builtin
provider_type: inline::builtin
batches:
- config:
sqlstore:
table_name: batches
backend: sql_default
provider_id: reference
provider_type: inline::reference
server:
port: 8321
storage:
backends:
kv_default:
type: kv_sqlite
db_path: ${env.KV_STORE_PATH:=~/.llama/storage/kv_store.db}
kv_rag: # Define the storage backend type for RAG
type: kv_sqlite
db_path: ${env.KV_RAG_PATH:=~/.llama/storage/rag/kv_store.db}
sql_default:
type: sql_sqlite
db_path: ${env.SQL_STORE_PATH:=~/.llama/storage/sql_store.db}
stores:
metadata:
namespace: registry
backend: kv_default
inference:
table_name: inference_store
backend: sql_default
max_write_queue_size: 10000
num_writers: 4
conversations:
table_name: openai_conversations
backend: sql_default
prompts:
table_name: prompts
backend: sql_default
connectors:
table_name: connectors
backend: sql_default
registered_resources:
models:
- model_id: gpt-4o-mini
provider_id: azure
model_type: llm
provider_model_id: gpt-4o-mini
- model_id: all-mpnet-base-v2
model_type: embedding
provider_id: sentence-transformers
provider_model_id: all-mpnet-base-v2
metadata:
embedding_dimension: 768
vector_stores:
- embedding_dimension: 768
embedding_model: sentence-transformers/all-mpnet-base-v2
provider_id: faiss
vector_store_id: ${env.FAISS_VECTOR_STORE_ID}
vector_stores:
default_provider_id: faiss
default_embedding_model:
provider_id: sentence-transformers
model_id: all-mpnet-base-v2