What the data for this category looks like
Paper industry investment research data originates from public reports from industry associations, periodic announcements from listed companies, customs import and export statistics, raw material spot and futures market quotes, and environmental protection regulatory announcements. Update frequencies vary: Monthly production capacity and import/export data updates occur each month. Annual industry analysis reports are released quarterly or annually. Raw material spot quotes update daily. Document formats include structured tables (such as regional production capacity statistics, raw material proportion breakdowns), long-text analysis reports, and PDF-format regulatory documents. Field units mostly follow industrial standard specifications such as ten thousand tons per year, yuan per ton, mg/m³, and others.
Constraints Imposed on Knowledge Base Retrieval and Recall
The multi-source update rhythm of paper industry investment research data requires the retrieval system to support batch incremental synchronization, to avoid excessive resource occupation from full updates. Discrepancies in structured fields and cross-data source calibers require retrieval configurations to support precise multi-field matching and caliber alignment preprocessing. The high proportion of long-text analysis reports requires that contextual associations of industry terminology be retained after segmentation, to avoid disrupting professional expression logic during splitting. Segmented data for different categories (such as packaging paper, cultural paper) is scattered, requiring expansion of the initial recall candidate set to cover segmented investment research needs.
How to Configure the Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Matches the typical paragraph length of paper industry analysis reports, retains contextual associations for terminology such as "wood pulp self-sufficiency rate" and "capacity utilization rate" |
chunk_overlap | 150–200 characters | Connects professional expressions in adjacent segments, avoids disrupting coherent information such as "2024 cultural paper production capacity" during splitting |
recall_top_k | Top 8-12 results | Covers investment research data for segmented categories including packaging paper, cultural paper, and wood pulp, avoids missed recalls caused by insufficient candidate sets |
similarity_threshold | 0.72–0.78 | Adapts to the semantic similarity characteristics of paper industry terminology, filters low-relevance general industry data |
rerank_top_n | Top 3-5 results | Focuses on core investment research basis, reduces interference from redundant information on AI-generated results |
parse_file_timeout | 300 seconds | Adapts to the parsing time required for large annual report PDF files, avoids upload timeout interruptions |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material formats, 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 Misconfigurations
- Returned results from conversation interface calls do not reference knowledge base data, and the
rag_contextfield in logs is empty. Cause: Thekb_idsparameter specifying the paper industry knowledge base ID was not included in the interface request, or the parameter format does not meet requirements. - The number of retrieved results is far lower than the configured
recall_top_k. Cause: Thesimilarity_thresholdwas set too high, filtering out paper industry segmented data that is semantically relevant but has different expressions. - A
504 Gateway Timeouterror is returned after uploading a large industry annual report. Cause: Theparse_file_timeoutconfiguration value is too short, and does not match the parsing time required for large documents.
How to Verify Proper Configuration
- Upload a single monthly paper industry report, check if the parsed segments retain core professional terminology, and verify the configuration effect of
chunk_sizeandchunk_overlap. - Initiate a retrieval request, enter segmented investment research keywords, check if the returned contextual data includes statistical information for the corresponding category, and verify the configuration rationality of
recall_top_kandsimilarity_threshold. - Trigger an incremental update task, check if the update log only synchronizes data from data sources updated on the current day or current week, and verify the configuration of
incremental_update_interval. - Call the conversation interface with the specified knowledge base ID, check if the returned results reference paper industry data within the knowledge base, and verify the correctness of the knowledge base association configuration.
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.