What this category of data looks like
Agrochemical product research report data primarily comes from industry association monthly operation briefings, securities firm chemical industry special research reports, and production and operation announcements disclosed by enterprises. The update rhythm shifts based on core industry events. Fixed-cycle regular tracked research reports release on a set schedule. Temporary supplementary updates go out during major policy changes or raw material price swings. Each individual document includes title, publishing entity, release date, core category production capacity and raw material cost data, policy summary, risk reminders, and other content. Data fields include production capacity, raw material purchase unit price, export quotas, etc. Corresponding units are ton, yuan/ton, and ton respectively. Some in-depth documents include multi-page structured supplementary tables.
What constraints do these characteristics impose on the vector models and indexing link
Multi-source mixed data in agrochemical research reports requires vector models and indexing to support mixed text and structured numerical retrieval. This prevents loss of professional data associations from single-modal matching. The coexistence of sudden and regular updates requires indexing to support flexible switching between incremental construction and scheduled full reconstruction. This adapts to different update scenarios. Dense professional terminology in text content requires vector models adapted to chemical subdivision domain corpora. This improves the encoding accuracy of professional semantics. Multi-page structured supplementary tables in individual documents require retaining the correspondence between fields and content during segmentation. This avoids semantic fragmentation after splitting.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to the text structure of agrochemical research reports, which are dense with professional terminology and include structured supplementary tables, avoiding semantic fragmentation after splitting |
recall_top_k | Top 10–15 results | Agrochemical research reports have detailed data dimensions. A sufficient number of candidate segments must be recalled to cover core business scenarios |
similarity_threshold | 0.72–0.85 | Filters low-correlation non-professional matching results, retaining research report segments strongly related to agrochemical subdivision categories |
incremental_index_enable | Enabled | Adapts to the event-based update rhythm of research reports, supporting incremental index construction to reduce reconstruction time |
parse_file_timeout_seconds | 600 seconds | Covers the parsing time of in-depth research reports with multi-page supplementary tables, avoiding parsing timeout failures |
mix_index_enable | Enabled | Supports mixed retrieval of text vectors and structured numerical fields, matching data indicators such as production capacity and prices in research reports |
The parameter values provided on this page are common recommendations used 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 misconfigurations
- Phenomenon: The index reconstruction status displayed in the interface continues beyond the preset threshold, index switching operations cannot be triggered, and some nodes return
504 Gateway Timeouterrors. Cause: Incremental index mode is not enabled. Full reconstruction runs even for small data volumes. Although individual agrochemical research reports are long, the overall initial data volume is small. Full reconstruction wastes resources and takes excessive time. - Phenomenon: Retrieval results are scattered or the number of recalled entries is far lower than expected. Cross-document industry association data cannot be obtained. Cause: An independent index creates for each research report. All research report data is not aggregated into a unified index, resulting in retrieval scope limited to a single document index.
- Phenomenon: API batch add index requests return
422 Unprocessable Entityerrors. Cause: The correspondence between thedocument_idsarray andindex_nameis not correctly specified. Batch request parameters are not encapsulated as required, which does not comply with interface format specifications.
How to confirm the configuration is correct
- Perform parsing and index construction tests for a single in-depth research report. Check the semantic integrity of the segmented content after parsing, confirming that the segment length configuration meets professional text splitting requirements.
- Initiate a batch index request, verify the matching between the returned response status code and request parameters, confirming that the batch operation parameter configuration is correct.
- Trigger an incremental index reconstruction, observe the reconstruction time and data synchronization progress, confirming that the incremental index switch is correctly enabled.
- Initiate a mixed retrieval test, input a query term containing professional terminology and numerical indicators. Check whether the retrieval results cover both text content and structured data fields, confirming that the mixed index configuration is effective.
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.