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# What does this PR do? https://github.com/meta-llama/llama-stack/pull/2490 broke postgres_demo, as the config expected a str but the value was converted to int. This PR: 1. Updates the type of port in sqlstore to be int 2. template generation uses `dict` instead of `StackRunConfig` so as to avoid failing pydantic typechecks. 3. Adds `replace_env_vars` to StackRunConfig instantiation in `configure.py` (not sure why this wasn't needed before). ## Test Plan `llama stack build --template postgres_demo --image-type conda --run`
1.3 KiB
1.3 KiB
inline::faiss
Description
Faiss is an inline vector database provider for Llama Stack. It allows you to store and query vectors directly in memory. That means you'll get fast and efficient vector retrieval.
Features
- Lightweight and easy to use
- Fully integrated with Llama Stack
- GPU support
Usage
To use Faiss in your Llama Stack project, follow these steps:
- Install the necessary dependencies.
- Configure your Llama Stack project to use Faiss.
- Start storing and querying vectors.
Installation
You can install Faiss using pip:
pip install faiss-cpu
Documentation
See Faiss' documentation or the Faiss Wiki for more details about Faiss in general.
Configuration
Field | Type | Required | Default | Description |
---|---|---|---|---|
kvstore |
utils.kvstore.config.RedisKVStoreConfig | utils.kvstore.config.SqliteKVStoreConfig | utils.kvstore.config.PostgresKVStoreConfig | utils.kvstore.config.MongoDBKVStoreConfig |
No | sqlite |
Sample Configuration
kvstore:
type: sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/faiss_store.db