What the data for this category looks like
Baijiu intelligent due diligence report data comes from publicly available sampling inspection data of national and local food and drug inspection and testing institutions, monthly and quarterly production area data updated by baijiu-producing region industry associations, annual public reports of listed liquor companies, and third-party compliance audit documents. Single report document lengths vary widely, ranging from hundreds-of-word batch sampling inspection summaries to tens of thousands-of-word full-chain traceability reports. Document fields include alcohol content (unit: %vol), total acid and total ester content (unit: g/L), raw material ratio, brewing cycle, compliance inspection item results, batch number and production date. Some traceability documents also include logistics links and terminal sales data. Update frequencies differ by data source: sampling inspection data is released by batch, production area industry data is updated monthly, and enterprise annual reports are synchronized annually.
What constraints these characteristics impose on tool calling and plugins
The multi-source and decentralized nature of baijiu due diligence data requires plugins to be configured with multiple data source adapters, to connect separately with sampling inspection institution interfaces, production area association APIs, and enterprise annual report databases. The wide range of document lengths requires adjusting the context truncation threshold for tool calling, to avoid losing key fields such as physical and chemical indicators. The special nature of field units requires plugins to include built-in unit verification logic, to automatically identify and convert dedicated units such as %vol and g/L, and prevent parameter parsing failures. Differences in update frequencies across multiple data sources require configuring differentiated scheduling rules for scheduled pull tasks, to ensure synchronization of the latest sampling inspection data and annual reports. Some compliance fields require permission verification, so plugins must integrate role-based permission filtering logic, to return complete data only to authorized callers.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
TOOL_CONTEXT_TRUNCATE_LENGTH | 800–1200 characters | Core fields of baijiu due diligence reports (physical and chemical indicators, compliance inspection items) usually fall within this length range, to avoid truncating critical information |
UNIT_VALIDATION_ENABLE | Enabled | Baijiu data includes dedicated units such as %vol and g/L. Enabling this setting automatically verifies and standardizes parameter units, to prevent parsing errors |
PLUGIN_DATA_SOURCE_ADAPTERS | Sampling inspection interface, production area API, enterprise annual report database | Covers the three core sources of baijiu due diligence data, to ensure the plugin can pull full-chain data |
SCHEDULE_INTERVAL | 3600 seconds, 86400 seconds | Adapts to the update rhythms of different data sources: pull new batch sampling inspection data hourly, and synchronize production area monthly data daily |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large full-chain traceability documents takes longer, to avoid task interruption due to timeout |
PLUGIN_PERMISSION_FILTER | Compliant field visibility scope | Filters sensitive data such as unpublicized production capacity and inventory of enterprises, to open complete fields only to authorized nodes |
The parameter values provided on this page are common recommended starting points 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 mistakes
- Scenario: When calling an MCP plugin packaged with the SSE protocol, the interface prompts "Only stdio process calls are supported". Cause: The plugin runtime environment of FastGPT 4.9.6 only enables stdio communication by default, and does not open SSE protocol support.
- Scenario: When the
streamparameter is set totrue, complete final tool call results cannot be obtained, only segmented data streams are returned. Cause: The result aggregation logic for tool calls is not configured, and segmented data streams are not merged into a complete output. - Scenario: When deploying FastGPT V4.14.1 privately, importing a custom plugin prompts "internal server error". Cause: The interface address in the plugin configuration has not been added to the deployment environment's allowlist, or there is a port mapping conflict.
How to confirm the configuration is correct
- Upload a baijiu batch sampling inspection report, check whether the physical and chemical indicator fields extracted after tool calling include correct units, and verify whether
UNIT_VALIDATION_ENABLEtakes effect. - After configuring multiple data source adapters, manually trigger the plugin to pull data, and check whether sampling inspection data, production area data and enterprise annual report information are obtained simultaneously.
- View the plugin runtime logs, confirm that the
SCHEDULE_INTERVALscheduled tasks execute according to the preset cycle, and there are no timeout errors. - Switch between different permission roles to call the plugin, check whether compliance fields are filtered according to the configuration, and unauthorized roles cannot view sensitive data.
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.