🚀 Describe the new functionality needed

Extend the Llama Stack Batches API to support the /v1/embeddings endpoint, enabling efficient batch processing of embedding requests alongside the existing /v1/chat/completions support.

💡 Why is this needed? What if we don't build it?

The current Batches API implementation only supports /v1/chat/completions requests, limiting batch processing to chat completions. However, many use cases require processing large datasets for embeddings, such as:

1. Document Indexing: Processing thousands of documents for vector search systems
2. Similarity Analysis: Computing embeddings for large text corpora
3. RAG Preprocessing: Batch embedding generation for retrieval-augmented generation pipelines
4. Semantic Clustering: Large-scale text clustering and categorization
5. Content Analysis: Bulk processing of user-generated content for recommendations

Other thoughts

No response