What the data for this category looks like
Gas utility financial report data primarily comes from periodic reports of listed public utility companies and public industry operation data released by local energy regulatory authorities. Quarterly reports are released within 30 days after the end of each quarter. Annual reports are disclosed by the end of April of the following year. Document structures include modules such as revenue breakdown, procurement costs, total gas supply, pipeline network mileage, and number of end users. Core field units are: revenue in ten thousand yuan, total gas supply in ten thousand cubic meters, pipeline length in kilometers, and number of users in ten thousand households. Most data fields cross-reference physical operation indicators and financial indicators.
Constraints on tool calling and plugins
The characteristics of gas utility financial report data impose multiple constraints on the tool calling and plugins link. Multiple data sources require tools to adapt to both public regulatory APIs and permission verification logic for internal enterprise reports. Asynchronous update schedules require tools to support triggering data pulls on quarterly or annual cycles, to avoid calling outdated information. Multiple fields with differing units require built-in standardized mapping rules to ensure correct matching of units and fields during parameter matching. The long document structure requires configuring long context processing thresholds to prevent content truncation during parsing.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
TOOL_CALL_MAX_RETRIES | 2-3 times | Financial report data pulls may fail due to API rate limiting. Retrying 2-3 times improves call success rates without triggering rate limits |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Full annual financial report documents typically contain dozens of pages. 600 seconds covers the full parsing process and prevents mid-process timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 500 MB | Full annual report documents for listed gas enterprises typically do not exceed this threshold, covering conventional upload requirements |
DATA_SOURCE_WHITELIST | ["energy_supervision.gov", "listed_disclosure_platform"] | Restricts the scope of legitimate data sources to avoid invalid data or permission errors from calling non-compliant APIs |
TOOL_PARAM_MATCH_THRESHOLD | 0.75 | Financial report fields are numerous and have similar naming conventions. A threshold of 0.75 balances matching precision and recall |
CONTEXT_WINDOW_SIZE | 8192-16384 tokens | Long financial report parsing requires a sufficient context window to prevent loss of cross-segment associated information during segmented parsing |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common errors
- The symptom is empty output or no valid visual content after calling the chart generation tool. The cause is that unit standardized mapping for fields such as total gas supply and revenue in gas financial reports has not been completed, so the tool cannot recognize correct numerical parameters for plotting.
- The symptom is a 400 Bad Request error returned when selecting a tool. The cause is that the
DATA_SOURCE_WHITELISTparameter is not configured, or the incoming data source address is not within the whitelist range, triggering API permission verification interception. - The symptom is that only the Tongyi Qianwen model can execute normally when calling the tool, while other models return errors. The cause is that some models do not adapt to the standard function definition format for tool calling, and cannot correctly parse the mapping rules for financial report fields.
How to confirm the configuration is complete
- Upload a simulated gas financial report document, trigger the tool calling process, and check whether the identified core fields match the document content to confirm that the field mapping logic is effective.
- Call the data source pull API, check whether the returned data source address is within the pre-configured whitelist range to confirm that the permission verification rule is operating normally.
- Simulate an API rate limiting scenario, trigger a tool call, and check whether automatic retries are initiated according to the configured retry count without abnormal errors.
- Upload a full-length financial report document, check whether the parsing result covers all content without segment truncation or information loss.
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.