Optimize Retriever queryset with select_related and only to reduce DB load

### **A. Is your feature request related to a problem? Please describe.**
File to be updated: `backend/appa/ai/agent/tools/rag/retriever.py`

Currently, the `retrieve()` method loads entire Chunk objects and related models, which can cause unnecessary database load and higher memory usage when only a few fields are required.
```
chunks = queryset.select_related("context__entity_type").order_by("-similarity")[:limit]
```

* This pulls all fields for Chunk, the related context, and the related entity (because later you access chunk.context.entity in get_additional_context).
* That means: a lot of unused DB columns and full ORM objects are hydrated into memory.
* If your Chunk or entity tables are large (with big text/blob fields), this is wasteful — both in query size (more bytes over the wire) and in Python object construction.

### **B. Describe the solution you'd like**
* Narrow down the fields to only those you actually need for the retrieval result:
```
chunks = (
queryset
.select_related("context__entity_type")
.only("id", "text", "context_id", "context__entity_id", "context__entity_type")
.order_by("-similarity")[:limit]
)
````
* This way, Django fetches only the minimal set of columns for Chunk and context

### **C. Describe alternatives you've considered**
- Keeping the current implementation, which works but is less efficient.
- Fetching all related entities lazily, which increases the number of queries (N+1 problem).

### **D. Are you going to work on implementing this?**

- [x] Yes
- [ ] No

**Additional context**
This change will reduce query time and memory footprint, especially when dealing with large datasets of chunks. It also prepares the codebase for scaling to larger corpora.

Start in backend/appa/ai/agent/tools/rag/retriever.py by reading retrieve() and get_additional_context(). Check which Chunk and related context/entity fields the retrieval result accesses, then verify the narrowed queryset avoids loading unused columns and does not introduce extra queries. Done means retrieval still returns the required result and related context without the current unnecessary database load.

Written by the indexing model from the issue text.