What the data for this category looks like
Core data for this category originates from cell grading equipment, production MES systems, welding torque tools, BMS software, EOL test benches, and similar equipment. Daily generated documents include grouping rules, BOM lists, welding torque records, BMS flash logs, insulation and voltage withstand reports, EOL test data, and system configuration lists. Data updates occur each time a battery pack or energy storage cabinet finishes production. Updates also trigger when the BMS software version changes. Fields include cell capacity (unit: Ah), internal resistance (unit: mΩ), welding torque (unit: N·m), insulation resistance (unit: MΩ), BMS version number, charge-discharge voltage (unit: V), and similar metrics. The data size of a single process document ranges from 800 to 1200 characters. This page was written based on FastGPT v4.17.0.
What constraints these characteristics impose on HTTP interfaces and external systems
Data sources for this category are scattered, and update frequency is high. HTTP interfaces must support batch pulling and real-time synchronization of data from multiple devices. Business requirements for multiple fields require interfaces to support specifying returned fields, to avoid redundant data transmission. Severe potential error consequences require interfaces to include authentication and retry mechanisms. These mechanisms prevent abnormal data from flowing into process documents and exception reports. For intranet deployment scenarios, some devices cannot directly access the internet. Interfaces must support HTTP proxy configuration with username and password, to adapt to intranet access needs.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {fastgpt_api_token} | Complies with HTTP interface authentication standards, and supports integration with external systems from multiple manufacturers |
variables | {"product_type": "pack", "report_scope": "eol"} | Passes category-specific business parameters, to distinguish between different types of process documents and exception reports |
responseData | include:["torque_value","insulation_resistance","bms_version","related_docs"] | Only returns core fields required for process documents and exception reports, to reduce data transmission volume, and supports returning associated knowledge base document information |
| Request timeout | 300 seconds | Adapts to data collection delays in welding, EOL testing and other links, to avoid interface interruptions |
| HTTP proxy configuration | Proxy address + port + username and password | Adapts to internet access requirements in intranet deployment scenarios, and resolves issues where intranet servers cannot directly access external data sources |
Three common misconfigurations
- Phenomenon: The interface returns the
Data too long for column 'models'error. Cause: The length ofvariablesor custom fields is not limited, causing incoming BOM details or cell parameters to exceed the storage limit of database fields. - Phenomenon: Non-login links cannot load process documents when accessed across devices. Cause: The cross-domain whitelist for the interface is not configured, preventing external devices from calling FastGPT interfaces to obtain data via links.
- Phenomenon: The
responseDatafield returned by the interface is empty. Cause: Required business fields are not specified, so the interface fails to match the cell and test data required for process documents.
How to verify correct configuration
- Call the test interface, check if the
Authorizationauthentication header is correctly carried, and confirm the returned status code is 200. - Pass preset
variablesparameters, check if theresponseDatareturned by the interface includes category-specific business fields. - Test interface calls in an intranet proxy environment, confirm that external data sources can be accessed normally, and no connection timeout errors occur.
- Simulate exception scenarios to trigger the interface, check if field data required for exception reports can be generated correctly.
The values provided here are common starting points and should be evaluated against actual deployment samples.