chore: Enabling Milvus for VectorIO CI

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

docs/source/providers/vector_io/inline_chromadb.md

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+# inline::chromadb
+
+## Description
+
+
+[Chroma](https://www.trychroma.com/) is an inline and remote vector
+database provider for Llama Stack. It allows you to store and query vectors directly within a Chroma database.
+That means you're not limited to storing vectors in memory or in a separate service.
+
+## Features
+Chroma supports:
+- Store embeddings and their metadata
+- Vector search
+- Full-text search
+- Document storage
+- Metadata filtering
+- Multi-modal retrieval
+
+## Usage
+
+To use Chrome in your Llama Stack project, follow these steps:
+
+1. Install the necessary dependencies.
+2. Configure your Llama Stack project to use chroma.
+3. Start storing and querying vectors.
+
+## Installation
+
+You can install chroma using pip:
+
+```bash
+pip install chromadb
+```
+
+## Documentation
+See [Chroma's documentation](https://docs.trychroma.com/docs/overview/introduction) for more details about Chroma in general.
+
+
+
+## Configuration
+
+| Field | Type | Required | Default | Description |
+|-------|------|----------|---------|-------------|
+| `db_path` | `<class 'str'>` | No | PydanticUndefined |  |
+
+## Sample Configuration
+
+```yaml
+db_path: ${env.CHROMADB_PATH}
+
+```
+