chore: Enabling Milvus for VectorIO CI

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

docs/source/providers/vector_io/inline_faiss.md

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+# inline::faiss
+
+## Description
+
+
+[Faiss](https://github.com/facebookresearch/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:
+
+1. Install the necessary dependencies.
+2. Configure your Llama Stack project to use Faiss.
+3. Start storing and querying vectors.
+
+## Installation
+
+You can install Faiss using pip:
+
+```bash
+pip install faiss-cpu
+```
+## Documentation
+See [Faiss' documentation](https://faiss.ai/) or the [Faiss Wiki](https://github.com/facebookresearch/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
+
+```yaml
+kvstore:
+  type: sqlite
+  namespace: null
+  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/faiss_store.db
+
+```
+