What the Data for This Category Looks Like
Data sources for condiment industry research reports include broker food and beverage industry research reports, specialized analysis documents for condiment sub-categories, and public statistical materials from industry associations. Updates are scheduled irregularly, tied to listed company earnings report cycles and fluctuations in industry raw material prices, with no fixed cycle. Document structures typically include modules such as industry supply and demand scale, leading enterprise operating data, cost composition, channel layout, and market competition landscape. Fields include revenue, production capacity, sales volume, market share, and more. Units use physical and monetary units like tons, ten thousand yuan, and kiloliters.
Constraints Imposed on Knowledge Base Retrieval and Recall
Multi-source heterogeneous data sources lead to inconsistent document formats and field standards. Field alignment and unified vectorization adaptation are required before retrieval. Irregular update cycles require incremental document synchronization to avoid resource waste from full scans. Documents contain both long-form industry trend analysis and short-form operating data, which demands adaptive text segmentation granularity. Mixed use of physical and monetary units requires retaining unit-associated matching during the recall phase to avoid unit deviations in numerical retrieval results.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
segment length | 800–1200 characters | Condiment research reports include both long-form industry analysis and short-form operating data. This range balances complete semantics and recall accuracy |
recall count | Top 8–12 results | Condiment sub-category information has high density. Too many recalled results introduce irrelevant content, while too few fail to cover core arguments |
embedding thread count | 2–4 threads | Reducing the thread count avoids rate limit errors during vectorization, and adapts to the document length and volume characteristics of condiment research reports |
maxContext | 4000–6000 characters | Research report content requires sufficient contextual association to avoid key logic breaks that affect retrieval result accuracy |
similarity threshold | 0.75–0.85 | Filters low-similarity irrelevant recall results, adapting to the high number of industry-specific terms in the condiment sector |
folder filter toggle | Enabled | Allows users to limit retrieval scope to condiment research reports in specified folders, matching retrieval needs precisely |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Errors
- Phenomenon: Setting
segment lengthto 3000 characters results in partial document chunks being lost. Cause: Long paragraphs of industry trend analysis exist in condiment research reports. Text chunks exceeding 3000 characters are truncated or skipped during parsing, preventing key information from being recalled. - Phenomenon: Retrieval results do not return the preset Q&A pair original text from the knowledge base. Cause: The
force return knowledge base original textconfiguration item is not enabled, or Q&A pair documents are not marked as core recall sources. - Phenomenon: Embedding rate limit errors occur during vectorization. Cause: The
embedding thread countis not adjusted to a reasonable range, or the total document size of a single batch of vectorization is not limited.
How to Verify Proper Configuration
- Upload a test condiment research report document, view the parsed text chunk list, and confirm that the segment length configuration matches the preset value.
- Initiate a retrieval by selecting a research report in a specified folder, verify that retrieval results only include documents within that folder.
- Enter the query keywords of a preset Q&A pair, confirm that the retrieval results directly return the preset original text response.
- View the running logs of the vectorization task, confirm that no embedding rate limit error messages appear.
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.