Principle:Intel Ipex llm RAG Chain Assembly

Knowledge Sources	LangChain Documentation IPEX-LLM
Domains	NLP, RAG
Last Updated	2026-02-09 00:00 GMT

Overview

Pattern for composing a Retrieval-Augmented Generation chain using LangChain Expression Language (LCEL) with a retriever, prompt template, LLM, and output parser.

Description

RAG Chain Assembly composes the final inference pipeline that: (1) takes a user question, (2) retrieves relevant document chunks from the vector store, (3) formats them into a prompt template with context and question placeholders, (4) passes the formatted prompt to the LLM, and (5) parses the output. LangChain Expression Language (LCEL) enables declarative chain composition using the pipe operator.

Usage

Use as the final assembly step after creating the retriever and LLM. The chain is invoked with a user question and returns the generated answer grounded in the retrieved context.

Theoretical Basis

# Abstract RAG chain logic (NOT real implementation)
# Given query Q:
# 1. relevant_docs = retriever.invoke(Q) -> List[Document]
# 2. context = "\n\n".join(doc.page_content for doc in relevant_docs)
# 3. prompt = template.format(context=context, question=Q)
# 4. answer = llm.invoke(prompt)
# 5. return parse(answer)

Related Pages

Implemented By

• Implementation:Intel_Ipex_llm_LangChain_RAG_Chain