Citation Sources and Traceability for Decoration and

What the Data for This Category Looks Like

The data for decoration and renovation intelligent due diligence reports mainly comes from decoration qualification documents filed by housing and urban-rural development authorities, project construction contracts, material procurement ledgers, on-site supervision logs, and owner acceptance records. Data updates synchronize with project progress. Due diligence data for individual projects enters a static archiving cycle after completion and filing. Enterprise qualification data is updated annually through annual inspections. Most documents combine structured tables and unstructured attachments. Core fields include project number, decoration construction scope, material brand and model, construction period, acceptance milestones, and qualification certificate number. Units involved include square meters, cubic meters, ten thousand yuan, and calendar days.

Constraints on Citation Sources and Traceability

The mixed structured and unstructured combination of decoration due diligence data requires the traceability link to support associated tagging for multi-format data sources. The dynamic update feature of project-level data requires binding a unique project number as the traceability anchor to avoid cross-project reference confusion. The multi-field attributes of material details require precise field matching during recall to avoid deviations caused by relying only on keyword matching. The presence of long-text attachments such as supervision logs requires configuring reasonable segmentation rules, while retaining paragraph anchors from original documents for traceability.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`Recall Count`	`Top 15-20 entries`	Decoration due diligence data covers multiple dimensions including materials, qualifications, and construction. Excessive recall causes context overload, while insufficient recall fails to cover all necessary information
`Segment Length`	`800-1200 characters`	Documents such as supervision logs and material ledgers are mostly long texts. This segment length preserves complete business descriptions while adapting to large model context windows
`Similarity Threshold`	`0.75-0.85`	Matching decoration-related fields such as material brands and qualification numbers requires high accuracy. A low threshold introduces irrelevant data, while a high threshold misses valid citation sources
`Rearranged Return Count`	`Top 8-10 entries`	Prioritize returning content most relevant to core due diligence requirements such as compliance and material authenticity, to reduce redundant interference
`Maximum Character Count for Citation Sources`	`3000 characters`	Some procurement ledger details have long content. This value preserves complete cited content while complying with general context limits
`Anchor Field`	`Project Number`	Decoration projects have unique identifiers. Binding this field ensures precise association with all data for the corresponding project during traceability, avoiding cross-project confusion

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volume, and business rules. Specific issues require individual analysis. Testing on local samples is recommended before finalizing settings.

Three Common Misconfigurations

Scenario: After setting Maximum Character Count for Citation Sources to 3000, the large model does not receive context content. Cause: Some large models have a default context window smaller than 3000 characters. Cited sources exceeding the limit cannot be included in processing scope.
Scenario: After uploading raw data returned by an HTTP interface as a knowledge base citation, retrieval results are empty. Cause: The response data was not converted to the structured format supported by FastGPT. The platform cannot complete content indexing and matching.
Scenario: After configuring knowledge base recall, the generated answer does not include decoration material compliance information from the knowledge base. Cause: The similarity threshold is set too high, filtering valid recall results, or the recall count is set too low, failing to cover target content.

How to Confirm Configuration is Successfully Applied

The knowledge base management interface is reviewed to check the values of configuration items such as Recall Count and Segment Length, and confirm alignment with preset rules.
A query related to decoration due diligence is initiated, and the recall count and field matching degree of retrieval results are reviewed to confirm compliance with configuration requirements.
Citation traceability markers in generated answers are reviewed to confirm each cited content is bound to corresponding anchor field information.
One configuration parameter is adjusted, and changes to retrieval results are observed to confirm the configuration takes effect normally.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.