What is Functionality of rlm/rag-prompt

In Retrieval-Augmented Generation (RAG) tasks, rlm/rag-prompt is a prompt specifically designed for use with the LangChain framework. It serves the purpose of guiding a Large Language Model (LLM) during question answering or similar tasks that leverage retrieved information.

Here's a breakdown of its functionality:

Functionality:

Context and Question Integration: rlm/rag-prompt incorporates both the retrieved context (relevant information for the task) and the user's question seamlessly. It structures the prompt in a way that effectively conveys both elements to the LLM.

Focus on Answer Brevity: This prompt is designed to encourage the LLM to provide concise and informative answers, typically aiming for a maximum of three sentences. This helps with readability and avoids overly verbose responses.

Knowledge Base Reference: While the specific implementation details might vary, rlm/rag-prompt often references a knowledge base or corpus of information that the LLM can access during the retrieval stage. This retrieved context is then used to answer the question.

Benefits:

Improved Answer Quality: By providing context and focusing on brevity, rlm/rag-prompt can lead to more accurate and succinct answers compared to generic prompts that lack context or guidance on answer length.

Enhanced Reusability: This prompt template is generally reusable across various question answering tasks within the LangChain framework, simplifying development and promoting consistency.

Here's an illustrative example (assuming the retrieved context is about different types of birds):

rlm/rag-prompt

You are an assistant for question-answering tasks. Use the following pieces of retrieved context to answer the question. If you don't know the answer, just say that you don't know. Use three sentences maximum and keep the answer concise.

**Retrieved Context:**

* Birds are warm-blooded vertebrates with feathers.

* They lay eggs and have wings.

* There are over 10,000 different bird species in the world.

**Question:** What are some characteristics of birds?

In this example, the rlm/rag-prompt incorporates the retrieved context about birds and presents the question. The LLM, guided by this prompt, would ideally respond with something like:

Birds are warm-blooded animals with feathers. They lay eggs and come in a vast variety, with over 10,000 known species.

In summary, rlm/rag-prompt is a valuable tool within the LangChain framework for guiding LLMs in question answering tasks, promoting context-aware, concise, and informative responses.