# Standard RAG LMRP

The Standard RAG pipeline uses **6 primary LMRPs** across preprocessing, retrieval, and generation stages. Some of the LMRP&#x20;

#### Summary LMRP Table

| LMRP Name                               | Pipeline Stage      | Purpose                                              | Model        | Conditional                                         |
| --------------------------------------- | ------------------- | ---------------------------------------------------- | ------------ | --------------------------------------------------- |
| **build\_standalone\_query**            | Preprocessing       | Transforms query with history into standalone query  | gpt-4.1-nano | ✓ History exists **AND** context < 32K chars        |
| **standard\_rag\_transform\_query**     | Retrieval           | Optimizes query for retrieval (intent clarification) | gpt-4o-mini  | ✓ NOT Smart Search **AND** context < 32K chars      |
| **generate\_conversation\_title**       | Concurrent/Parallel | Generates conversation title from first message      | gpt-4.1-mini | ✗ Always runs                                       |
| **generate\_related\_query**            | Generation          | Suggests 2-3 related follow-up queries               | gpt-4.1-mini | ✓ Smart Search enabled                              |
| **standard\_rag\_reference\_formatter** | Generation          | Filters retrieved chunks to only referenced content  | gpt-5-mini   | ✓ Chunks exist AND reference\_formatter\_type="llm" |
| **time\_extractor**                     | Preprocessing       | Extracts temporal metadata for memory retrieval      | gpt-4.1-nano | ✓ Memory enabled                                    |

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