Citation Sources and Traceability for Dairy Product

Data characteristics of this category

Dairy product due diligence data primarily comes from third-party food testing institution reports, batch testing records of large-scale ranch milk sources, national and local food safety sampling announcements, and supply chain traceability ledgers. Data update frequency aligns with testing batches. Single test reports are archived as independent batches. Most documents are structured tables or PDF files with official seals. Core fields include milk source traceability codes, batch numbers, protein content, total bacterial count, pathogen test results, and compliance determination conclusions. Common units follow general food testing standards, such as g/100g, CFU/g, mg/kg.

Constraints imposed by these characteristics on citation sources and traceability

The multi-source and dispersed nature of dairy product due diligence data requires the traceability link to support precise batch matching across data sources. This prevents recalling test results from non-corresponding batches. Requirements for structured fields and standardized units mean the system must automatically align field names and units during recall. This avoids citation errors caused by mismatched numerical units. Unstructured PDF documents with official seals require the traceability link to support formatted document parsing and seal area localization. This ensures cited test reports are verifiable. The batch-based update rhythm requires the traceability system to automatically update citation sources based on the latest batches. This prevents use of expired test data.

Configuration settings

Configuration Item	Recommended Setting	Rationale
`Recall Count`	`Top 6–8 entries`	Dairy product due diligence reports need to cover data from milk source, production, and sampling links. Too many entries will cause redundant citations, while too few will fail to cover core traceability information
`Similarity Threshold`	`0.75–0.85`	Dairy product test data has a high degree of standardization for fields. A threshold that is too low will recall irrelevant batch data, while a threshold that is too high will miss valid traceability information
`PARSE_FILE_TIMEOUT_SECONDS`	`120 seconds`	Parsing sealed PDF test reports requires additional processing of seal areas and structured extraction. The timeout period must be longer than that for general document parsing
`Chunk Length`	`800–1200 characters`	Most dairy product test reports are structured paragraphs. Chunks that are too long will split associated test items from the same batch, while chunks that are too short will increase recall matching costs
`Citation Source Display Format`	`By batch number + testing institution + document type`	Due diligence reports need to clearly identify the traced batch and issuing party. This format allows quick location of corresponding test data

The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three common configuration errors

Phenomenon: Cited sources are displayed even when the corresponding switch is not enabled, with no clear error prompt. Cause: In version 4.9.4, the global configuration of the citation source switch and knowledge base-level configuration do not have linked validation, causing the switch state to not take effect.
Phenomenon: Recalled citation sources do not match the current due diligence batch, with cross-batch test data appearing. Cause: Precise filtering rules based on batch numbers are not configured, and only similarity-based recall is used, leading to mismatches.
Phenomenon: The custom variable format [{datasetId: xxx}] fails to call the data source normally. Cause: The variable syntax required by FastGPT official standards is not used. The {{dataset.xxx}} format must be used to bind dataset parameters.

How to verify correct configuration

Upload a dairy product test PDF with a batch number, initiate a due diligence question and answer, and check if the citation sources in the returned results include the batch number and testing institution information of this document.
Adjust the similarity threshold to different ranges, compare the number of recalled citation sources, and confirm that the recall results within the configured range meet expectations.
Check the system logs to confirm that no 408 Request Timeout errors appear in parsing requests, indicating that the document parsing configuration meets requirements.
Test the custom variable binding, enter the official required {{dataset.xxx}} format, and confirm that the data source can be called normally with no parameter error prompts.

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.