granitelib rag r1.0 EU AI Act Compliance Profile

Granite RAG Library

The Granite RAG Library includes six adapters implemented as LoRA adapters for ibm-granite/granite-4.0-micro, each of which expects as input a (single-turn or multi-turn) conversation between a user and an AI assistant, and most of which also expect a set of grounding passages. Each adapter has been developed for a specific task that is likely to be useful in Agentic RAG pipelines. We give a brief overview of the functionality of each adapter, as the details can be found in each individual adapter's README.

Capabilities implemented as LoRA adapters

The six adapters that have been implemented as LoRA adapters for ibm-granite/granite-4.0-micro and made available in this HF repository are:

Query Rewrite (QR): Given a conversation ending with a user query, QR will decontextualize that last user query by rewriting it (whenever necessary) into an equivalent version that is standalone and can be understood by itself. While this adapter is general purpose for any multi-turn conversation, it is especially effective in RAG settings where its ability to rewrite a user query into a standalone version directly improves the retriever performance, which in turn improves the answer generation performance. This is a pre-retrieval adapter since its suggested use is before invoking retrieval.

Query Clarification (QC): Given a conversation ending with a user query, (and optionally relevant content such as RAG documents), QC will detect whether the last user query is underspecified (no clear interpretation or multiple valid interpretations) and, if so, formulate an appropriate clarification request back to the user. QR will decontextualize that last user query by rewriting it (whenever necessary) into an equivalent version that is standalone and can be understood by itself. The adapter is designed for conversational use cases where user queries may be ill-formed, unclear, or have multiple valid interpretations based on the underlying sys

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