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System Prompt

System Prompt

AI

A system prompt is the set of instructions that define an LLM’s role, behavior, and constraints before user messages are added. In RAG chat, the system prompt typically tells the model to answer only from provided excerpts and to cite sources. In extraction, high-level instructions can act like a system prompt for the extraction task.

In DocLD

Chat — System prompt enforces grounding in retrieved chunks and citation format.
Extraction — Schema instructions guide the model on how to fill fields and handle edge cases.

Prompt engineering often focuses on refining the system prompt to reduce hallucination and improve consistency.

Related Concepts

System prompt is part of prompting and prompt engineering. It affects completion and RAG behavior; temperature and top-p control randomness given that prompt.

Related terms

Prompting
Prompt Engineering
RAG
LLM

Frequently Asked Questions

A system prompt sets the LLM’s role, behavior, and constraints before user messages. In RAG chat, it typically tells the model to answer only from provided excerpts and to cite sources.

DocLD may allow system prompt customization for chat (e.g., tone, citation format). For extraction, schema instructions act like a system prompt. Check the dashboard and API for configurable options.

Instructions to answer only from the provided chunks, cite sources, and say "I don't know" when the answer is not in the context. DocLD sets this by default.

It shares the context window with chunks and conversation. Keep it concise so there is room for retrieved content.

Check if DocLD supports per-knowledge-base or per-session system prompts. Useful for different tones or domains.

Extraction uses schema instructions rather than a single system prompt. Instructions play a similar role for the extraction model.

Run sample queries and check answer quality and citation behavior. A/B test if you have enough traffic.

No. The system prompt is set by the app or DocLD. Users send messages; they do not set the system prompt.

System sets behavior (role, rules); user is the actual question or input. The model sees both but treats them differently.

See the DocLD documentation and glossary for details, and check the API reference for related endpoints and options.

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