What the data for this category looks like
Gas marketing data for the financial sector primarily comes from user profile systems of gas operating enterprises, pipe network operation platforms, monthly billing systems, regional promotion activity ledgers, and user credit data from partner financial institutions. Update frequencies vary across sources:
- User basic profiles sync daily
- Monthly usage bills and linked financial account information update after monthly settlement
- Pipe network inspection logs push in real time after each inspection is completed
- Promotion campaign reach feedback data is aggregated after the campaign ends
Document structure primarily uses structured tables, with fields including user ID, usage address, usage type, historical usage peak, payment records, linked financial account identifier, regional subsidy policy text, marketing reach feedback tags, and more. The usage address field includes the corresponding administrative division code. The usage peak field marks the unit of measurement. Policy text is fixed-format official announcement content.
What constraints these characteristics impose on tool calling and plugins
Gas marketing data for the financial sector is dispersed across multiple sources. Tool calling must integrate multiple independent API interfaces from gas operators and partner financial institutions. Plugins must support configuring call timing based on the update frequency of different data sources.
Structured fields have unit and format requirements. Parameter validation must be completed before tool calling to prevent interface errors caused by unit mismatches or incorrect financial account field formats. Unstructured policy text and feedback tags require plugins to support field extraction and association binding, so that marketing content can be linked to corresponding gas users and financial credit data.
Call current limiting rules vary across different data sources. The call interval for real-time inspection data must adapt to interface frequency limits. Monthly bills and financial data can be synced on a fixed cycle. Plugins must configure different call strategies separately.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
TOOL_CALL_TIMEOUT | 600 seconds | Gas marketing data requires integration of multiple sources, single round calls take longer. This setting prevents process interruption from timeouts |
SOURCE_TRACE_ENABLE | Enabled | Marketing content corpus sources must be bound to corresponding gas users and financial data to meet traceability requirements |
API_REQUEST_INTERVAL | 30 seconds | Adapts to current limiting rules for real-time pipe network data interfaces, prevents frequent calls from triggering interface restrictions |
OUTPUT_FIELD_VALIDATION | Enabled | Validates units and formats of gas data, such as cubic meter units for usage peaks, to ensure output data compliance |
DEFAULT_TOOL_MODEL | gpt-4o-mini | Balances logical processing capability and call costs for tool calling, adapts to integration needs for multi-source data |
PARSE_MULTI_SOURCE_DATA | Enabled | Supports integration of multi-source gas marketing data including user profiles, bills, and financial credit data, to produce unified formatted output |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Calling workflow APIs with file upload returns
400 Bad Request. The cause is failure to configure format validation for gas-related documents, and failure to restrict required fields and unit formats for structured tables. - AI responses fail to display the source of marketing content. The cause is failure to enable the
SOURCE_TRACE_ENABLEconfiguration, and failure to bind corpus source fields during tool calling. - Interface current limiting errors occur during tool calling. The cause is failure to set a reasonable
API_REQUEST_INTERVAL, with frequent calls to real-time pipe network data interfaces triggering current limiting rules.
How to confirm configurations are correct
- Initiate a simulated tool call, check if returned gas data includes configured fields, and verify units match expectations.
- View workflow run logs, confirm that call order and interval of multi-source APIs match the
API_REQUEST_INTERVALsetting. - Trigger a traceable AI conversation, check if response content is linked to corresponding corpus source fields.
- Modify the
TOOL_CALL_TIMEOUTvalue, verify that timeout prompts trigger according to the configured threshold.
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.