What the data for this category looks like
Data sources for textile manufacturing research reports include industry association public reports, specialized research reports from securities firms’ light industry teams, customs import and export textile category statistical data, and regular reports of listed textile enterprises. Update frequencies cover regular weekly, monthly, and quarterly reports, as well as real-time reports for sudden scenarios such as cotton price fluctuations and foreign trade policy adjustments. Document structures typically include abstracts, segmented category supply and demand data, raw material price trends, policy interpretations, corporate dynamics, and risk warnings. Fields include report publishing institution, publishing date, core category production capacity, raw material unit price, import and export volume, and more. Most units use professional measurement standards such as ten thousand tons, ten thousand meters, yuan per ton, and hundred million USD.
What constraints these characteristics impose on tool calling and plugins
The diversity of data sources requires tool calling to connect to multi-source APIs and adapt to different return formats, to avoid missing data. Differences in update rhythms require configuring incremental synchronization trigger rules to avoid repeatedly pulling old data or omitting the latest research reports. The complexity of document structures requires plugins to specify extraction logic for specific fields; generalized recall of full document content will lead to excessive redundant information and reduce answer accuracy. Professional field units require unit verification during tool calling to ensure that the measurement standards of returned data match business requirements.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
rag_recall_top_k | Top 8-12 entries | Single textile manufacturing research report has a relatively large content volume; too many recalled entries will exceed the context window limit and affect answer coherence |
rag_chunk_size | 800-1200 characters | Research reports contain continuous industry supply and demand data and policy interpretation paragraphs; the segment length is adapted to the semantic integrity of such long texts |
rag_chunk_overlap | 150-200 characters | Retain associations of professional terms and data context across segments to avoid losing key logic after splitting |
plugin_timeout | 300 seconds | When connecting to third-party industry data source APIs, some data sources have high response delays; this duration covers most normal requests |
rag_similarity_threshold | 0.72-0.78 | The textile manufacturing field has a high concentration of professional terms; this threshold filters low-relevance general research report content and focuses on segmented category data |
The parameter values provided on this page are conventional 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 errors
- Phenomenon: The response returned by the API does not include uploaded textile manufacturing research report content, while the platform-side test result is normal. Cause: The knowledge base recall is not specified to be enabled in the API request parameters, or the bound knowledge base ID parameter is not passed correctly.
- Phenomenon: Core fields are missing from the research report data returned by tool calling, such as raw material price information. Cause: The target fields to be extracted are not specified in the plugin configuration; the default recall only extracts the abstract content of the research report.
- Phenomenon: The API call returns a
413status code, prompting that the request content is too long. Cause: Therag_chunk_sizeconfiguration item is not adjusted, and the single-segment text length exceeds the platform limit, causing segmentation failure.
How to confirm the configuration is complete
- Initiate a test query targeting a textile manufacturing segmented category on the platform side, verify whether the preset industry data is included in the response to confirm that the knowledge base has been bound normally.
- Call the API to send the same test query, compare the response content from the platform side and the API to confirm that the parameters are passed correctly.
- View the plugin running logs, check the response status codes of the data source and field extraction results to confirm that the configuration items have taken effect.
- Trigger a manual incremental sync, verify whether the updated research reports appear in the recall results to confirm that the sync logic is working properly.
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.