What this category’s data looks like
General equipment financial report data comes from public periodic reports and temporary announcements of listed companies, as well as public industry research data. Update schedules follow disclosure timelines: periodic reports are released quarterly and annually, while temporary announcements are updated in real time for major operational changes. Document structures are primarily mixed format, including structured revenue composition tables, capacity data tables, long paragraphs of operational analysis and order explanations. Fields include product classification, revenue scale, production capacity scale, unit cost, order amount, delivery cycle, and more. Units cover RMB, units, yuan, and other relevant units.
Constraints imposed on vector models and indexing
The mixed format of general equipment financial reports requires vector models to adapt to both structured tables and long text passages. Splitting solely by character count will lose associated semantic meaning within tables. The multi-field, multi-unit characteristic requires indexes to support multi-dimensional semantic retrieval, avoiding information omission caused by relying only on keyword matching. The real-time or near-real-time update schedule requires indexes to support incremental updates; full index reconstruction consumes excessive resources. Individual documents have relatively long length, so segmentation granularity must be controlled reasonably to avoid context breaks that impact subsequent analysis.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | General equipment financial reports include structured tables and long text passages. This range balances the integrity of individual table blocks and context |
chunk_overlap | 100–150 characters | Prevents cross-paragraph equipment capacity, revenue, and related information in financial reports from being truncated by segmentation |
embedding_batch_size | 8–12 | Reduces the volume of single-batch vectorization requests to mitigate rate limit issues |
retrieve_top_k | Top 10–15 results | General equipment financial reports have many fields. A sufficient number of retrieved segments is needed to cover multi-dimensional metrics |
index_refresh_interval | Every hour | Matches the non-periodic update schedule of temporary announcements, ensuring newly disclosed data is available for retrieval within the set interval |
parse_table_enable | Enabled | Structured tables containing equipment capacity, cost, and other data in financial reports must be parsed separately to avoid losing structured semantic meaning in vectors |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Each scenario requires specific analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- A
rate limit exceedederror appears during vectorization, with logs indicating request rate limits have been hit. The cause is failure to adjust theembedding_batch_sizeparameter, where the number of documents submitted in a single batch exceeds the vector model’s request limit. - Knowledge base retrieval takes an extended period, while other scenarios using the same model respond faster. The cause is failure to enable the
parse_table_enableconfiguration, so structured tables in financial reports are not parsed separately. This leads to redundant long text segmentation and loading of excessive invalid segments during retrieval. - The dataset index status remains stuck on "Indexing" indefinitely without becoming ready. The cause is failure to configure the
skip_existed_chunkparameter. During incremental updates, existing document chunks are not verified, creating a repeated indexing loop.
How to verify correct configuration
- Upload a single general equipment financial report document, review the parsed segmentation results, and confirm that table content is fully split into independent segments.
- Submit a vectorization task, monitor request logs, and confirm that the number of single-batch requests stays within the preset
embedding_batch_sizerange. - Run a search for keywords related to equipment capacity and revenue, check the number and relevance of retrieval results, and adjust
retrieve_top_kto a range that meets business requirements. - Upload a new temporary announcement document, check the index update progress, and confirm that new data completes indexing within the set
index_refresh_interval.
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.