Dataset Fundamentals for Controlled Q&A
A Dataset in FastGPT is designed for scenarios where answers must be strictly tied to provided reference materials, including policy Q&A, product manual support, legal document retrieval, and customer service knowledge bases. Without a connected Dataset, the AI relies exclusively on its base model’s inherent general knowledge. When a Dataset is linked to a conversational agent, the AI first executes a targeted search across the uploaded materials, then synthesizes a structured answer using only the retrieved results. This framework eliminates unvetted, potentially inaccurate responses that can occur when the model draws solely on its built-in memory.
Step-by-Step Civil Code Q&A Assistant Setup
This workflow follows the official FastGPT quick start guidelines for dataset-backed agents:
- Curate the reference dataset: Compile the full official text of the Civil Code of the People's Republic of China as the target knowledge base.
- Create a new Dataset instance within the FastGPT platform, and upload the curated Civil Code materials to the instance.
- Launch a new Conversational Agent application, and associate the newly created Civil Code Dataset with the agent.
- Enable the response grounding setting to require the agent to prioritize citing original uploaded document text when generating answers, reducing fabricated content.
- Validate the agent by submitting natural language questions about Civil Code provisions, confirming that all responses draw directly from the uploaded reference materials.
Critical Control Benefits
Think of the Dataset as a dedicated reference room configured for the AI. The base model possesses broad general knowledge, but has no inherent access to internal company policies, product specifications, internal workflows, or specific regulatory versions like the official Civil Code. The Dataset converts these static materials into searchable, retrievable content, allowing the AI to look up precise, up-to-date information before organizing its final answer. For legal, policy, customer service, and after-sales scenarios, this approach delivers far greater operational control than relying solely on the model’s inherent memory, ensuring all outputs align with official reference materials.
Source: FastGPT official source
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