Urban Water Utility Business Process Guidance: Knowledge Base Retrieval and Recall

What the data for this category looks like

Urban water utility business process data comes from official business manuals, pipeline operation and maintenance archives, offline handling guides, and fee standard documents. The system updates data once per month, synchronized with new business launches or policy adjustments. Documents are organized by handling matter. Each matter includes handling conditions, required materials, process steps, handling time limits, and consultation channels. Fields include matter number, handling time limit (unit: working days), material details, unit fee (unit: yuan/cubic meter), and some data uses structured table formatting.

What constraints these characteristics impose on knowledge base retrieval and recall

Water utility business data has structured features. Retrieval must adapt to both text semantics and table field matching to avoid missing critical numerical information. Business handling process steps are highly correlated. Recalled results must maintain a coherent sequence, or they will mislead users. The fixed update cycle requires knowledge base synchronization to align with official update frequency, to avoid using expired data. Both colloquial consultations and standardized business terms appear together. Retrieval must support both precise matching and semantic expansion, to ensure corresponding content is recalled for any valid query wording.

How to set the configurations

Reference only; verify against the target FastGPT release and deployment documentation.

| limit | Top 8 entries | Individual water utility handling documents have relatively long content. Too many results will exceed the context limit, while too few will miss supplementary material explanations |

| searchMode | hybrid | Balances text semantic matching and keyword matching, adapting to scenarios where water utility documents contain both process text and fixed business keywords |

| usingReRank | Enabled | The step order of water utility handling processes is critical for guidance, and re-ranking corrects deviations in the initial recalled step order |

| datasetSearchUsingExtensionQuery | Enabled | Can automatically expand colloquial user queries, adapting to common colloquial consultation scenarios in water utility business |

| collectionIds | Exclusive collection ID corresponding to the water utility knowledge base | Limits the retrieval scope, avoiding recalling non-water utility knowledge base data, and ensuring retrieval accuracy |

Three Common Misconfigurations

• Phenomenon: Tool flows call the knowledge base and return empty results. Cause: The collectionIds configuration to limit retrieval scope is missing, and the system mistakenly recalls other category knowledge base data.
• Phenomenon: Some field data is lost after uploading a table dataset to the knowledge base. Cause: The structured data parsing configuration is disabled, and the system fails to correctly extract unit fields from tables, resulting in incomplete training data.
• Phenomenon: The AI only calls the knowledge base and does not execute tools in tool flows. Cause: The similarity threshold is set too high. The system uses knowledge base recall results for all query scenarios, and does not trigger tool call logic.

How to confirm the configuration is correct

• Manually enter a water utility business query such as "What materials are required for resident account opening". Check if retrieval results include the corresponding material list and handling steps.
• Verify that the number of retrieval results matches the limit configuration value, and that sorting follows the logical order of business handling.
• Upload a water utility fee standard table, and confirm that structured data is fully extracted and correctly recalled.
• Check knowledge base synchronization logs to confirm that update frequency aligns with official water utility document update rhythms.

The values provided are common starting points and should be measured against the reader's own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.