What the Data for This Category Looks Like
Glass is a segmented construction material category. Financial report-related data for the sector mainly comes from the National Bureau of Statistics Building Materials Industry Statistical Monthly Report, public periodic reports of listed glass manufacturing enterprises, and third-party building material supply chain data platforms. Two data update cycles apply: Listed enterprise financial reports are released as fixed disclosures on a quarterly and annual basis, with temporary announcements issued alongside market fluctuations. Industry monitoring data updates production and circulation data on a monthly basis. The data structure is split into three sections: production end, cost end, and market end. Core fields include float glass thickness specification, ex-factory unit price, inventory volume, and raw material procurement cost. Corresponding units are millimeters, yuan per square meter, ten thousand tons, and yuan per ton respectively.
Constraints for Tool Calling and Plugin Workflows
The scattered distribution of multiple data sources requires tool calling to connect financial report APIs, industry data APIs, and bulk commodity price APIs simultaneously. Multiple sets of authentication parameters must be configured for this integration. The wide range of segmented glass specifications requires plugin return results to support field filtering by thickness specification. This eliminates irrelevant data that could disrupt analysis. Fixed update cycles require plugins to use scheduled synchronization tasks. These tasks must align with the update frequencies of different data sources to maintain data timeliness. Cross-section data splicing requires tool calling to resolve field name differences across data sources. Field mapping rules must be configured to standardize data formats for follow-up analysis.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
plugin_request_timeout | 120–180 seconds | Glass financial report data requires splicing across three data sources. A single request needs to cover multiple types of fields to avoid truncated return results due to timeout |
parse_field_whitelist | ["thickness specification", "ex-factory unit price", "inventory volume", "raw material cost"] | Filters non-core fields to reduce large language model context usage, and matches the core requirements of glass financial report analysis |
sync_cron_expression | 0 0 2 * | Matches the daily early morning update rhythm of industry data, while avoiding peak periods for listed enterprise financial report disclosures |
api_auth_type | Multi-key rotation | Connecting multiple data sources requires separate configuration of authentication keys, to avoid triggering current-limiting restrictions with a single key |
result_filter_condition | Specification matches the current analysis category | Only returns glass data for the corresponding thickness, to avoid irrelevant specification data interfering with analysis logic |
max_context_tokens | 8000–12000 | Glass financial report analysis requires splicing long-text data from multiple data sources, adapting to the context window requirements of large language models |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Common Misconfigurations
- Calling the
/api/v1/chat/completionsAPI returns aninvalid_prompterror. The cause is failure to pass glass financial report-specific field filtering rules in the request body, which prevents the large language model from recognizing the analysis scope. - A
429 Too Many Requestsstatus code is returned during high-concurrency calls. The cause is failure to configure API current-limiting parameters for multiple data sources and enable the key rotation policy, resulting in call restrictions being triggered for a single key. - Directly writing glass data acquisition logic into the workflow without encapsulating it as a plugin. This prevents cross-session reuse of the tool calling configuration, requiring repeated configuration of data source parameters for each session.
How to Verify Successful Configuration
- Initiate a simulated call, and check whether the return result only includes the configured whitelist fields and matches the specified glass thickness specification.
- View plugin call logs to confirm that the request timeout configuration is in effect, with no request interruptions or result truncations.
- Test multiple concurrent requests to confirm that no current-limiting errors are triggered and the authentication key rotation logic runs normally.
- View scheduled task execution records to confirm that the data source update frequency matches the configured cron expression.
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.