You can generate context-aware embeddings for legal document indexing in LlamaIndex by integrating a domain-specific embedding model with metadata-aware chunking and indexing.
Here is the code snippet below:

In the above code we are using the following key points:
- 
Custom metadata is embedded within Document objects to retain legal context. 
- 
legal-bert is used for generating semantically rich, domain-specific embeddings. 
- 
SentenceSplitter ensures intelligent chunking for better context preservation. 
- 
Nodes are generated from parsed documents before being indexed. 
Hence, this workflow enables accurate and context-rich legal document retrieval using LlamaIndex and specialized embedding models.