Knowledge Base Retrieval and Recall for Snack Food

What the Data for This Category Entails

Snack food investment research data primarily comes from industry association public reports, brand public financial reports, e-commerce platform terminal sales data, supply chain raw material quotation documents, and new product filing public information.

Update rhythms vary across data types: terminal sales data is updated weekly, new product filing information is updated monthly, industry quarterly reports are released quarterly, and brand financial reports are disclosed per fiscal quarter.

Document structures fall into three categories:

Structured tables (including fields such as SKU code, selling price, distribution volume, etc.)
Semi-structured reports (including market analysis, competitor updates)
Unstructured text (including e-commerce user reviews, industry opinions)

Fields and units include per-box retail price (yuan), raw material procurement cost (yuan/kg), shelf life (days), and others. Some documents include multi-unit conversion annotations.

Constraints on Retrieval and Recall Workflows

The multi-source nature and varied update rhythms of snack food investment research data require retrieval workflows to support time-based data filtering. This prevents outdated sales or filing information from being included in results.

The varied document structure types require retrieval systems to support both structured field matching and unstructured text semantic matching. A single retrieval logic will not suffice.

The varied fields and units require retrieval workflows to support field-level filtering and unit standardization. This avoids matching failures caused by inconsistent units.

The multi-segment category feature requires retrieval workflows to support filtering by category groups. This prevents unrelated cross-category results from appearing in returned data.

Configuration Settings

Configuration Item	Recommended Value Range	Rationale
`maxRetrieve`	Top 15-20 results	Snack food investment research data includes multi-dimensional information such as SKU, sales, and supply chain data. Initial recall of this volume sufficiently covers multi-field association requirements
`similarityThreshold`	0.65-0.75	Snack food data contains numerous similar category descriptions. A threshold that is too low will introduce irrelevant results, while a threshold that is too high will miss relevant SKU information
`chunkSize`	800-1200 characters	Individual sales reports and e-commerce reviews are mostly short paragraphs, while financial report fragments are structured long texts. This segment length balances context completeness and retrieval accuracy
`rerankTopN`	Top 5-8 results	Investment research scenarios require focusing on core data. Reranking retains the most relevant sales, cost, and compliance information
`filterCollections`	Group by document type	Snack food data is divided into three categories: sales data, supply chain data, and industry reports. Filtering by collections allows quick location of target data sources
`PARSE_FILE_TIMEOUT_SECONDS`	300 seconds	Supply chain documents containing multiple SKUs take longer to parse. This duration ensures complete extraction of field information

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

Three Common Configuration Mistakes

After uploading a Markdown format file, the interface displays broken image placeholders and cannot load images normally. The cause is that local image paths were not replaced with publicly accessible addresses hosted by the knowledge base, so retrieval workflows cannot read local file resources.
When creating a new knowledge base, a parsing timeout error pops up with status code 408 returned. The cause is that the PARSE_FILE_TIMEOUT_SECONDS parameter was not adjusted. Parsing time for supply chain documents containing multiple SKUs exceeds the default limit.
After triggering a search plugin retrieval, only web page titles and short summaries are returned, with no complete page body content. The cause is that web page content crawling configuration was not enabled. Only search metadata was retrieved, and complete information from target pages was not extracted synchronously.

How to Verify Proper Configuration

Run a single SKU keyword retrieval test, check if returned results include target field information, and adjust similarityThreshold and maxRetrieve parameters to achieve expected recall volume.
Attempt to retrieve documents of a specified category using collection filtering configuration, confirm results only include content within the target group, to verify that the filterCollections parameter takes effect.
Upload a supply chain table containing multiple SKUs, check if all fields are fully extracted after parsing with no missing or truncated content, to verify that the PARSE_FILE_TIMEOUT_SECONDS configuration matches the file scale.
After triggering a search plugin retrieval, check if returned results include complete web page body content, to confirm that web page content crawling configuration has been properly enabled.

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.