What the data for this category looks like
Data sources for e-commerce due diligence include open APIs from e-commerce platforms, third-party business data interfaces, and public store operation disclosure information. Core business indicators update daily. Inventory and real-time traffic data update hourly. Qualification files sync immediately after submission by merchants. The document structure has two parts: a structured field package and an attachment package. Structured fields include store main body information, product listing, and operating transaction details. Attachments include qualification scans, logistics cooperation agreements, and similar materials. Operating transaction amounts use yuan as the unit. Order volume uses orders as the unit. Qualification numbers and store IDs are unitless strings.
Constraints on Tool Calling and Plugins
Multiple data sources have inconsistent update frequencies. Tool calling must distinguish trigger timing for real-time and T+1 indicators. This prevents retrieving expired or unupdated data due to incorrect call timing. The combined structured and attachment document structure requires plugins to support both structured data pulling and unstructured file parsing. Two separate calling logic configurations are needed. Inconsistent field units require adding unit conversion and labeling rules after tool calling. This prevents mixed currency and quantity units in reports. The large data volume from multiple SKUs and entries requires batch pulling tools to configure pagination parameters. This controls the volume of data returned per batch, avoiding timeouts or overloaded response content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
customToolVars | Bind three variable types: store ID, SKU range, qualification type | E-commerce due diligence requires pulling data by specific store or product dimension to avoid mixing data across entities |
functionCallTriggerMode | Trigger function calls for structured data pulling; parse attachments separately | E-commerce data is split into structured operating transactions and unstructured attachments, requiring separate calling logic |
PARSE_FILE_TIMEOUT | 600 seconds | Attachments such as qualification files and logistics agreements may be large, leading to longer parsing times |
batchPullSize | First 200 entries | E-commerce operating transaction details have many entries. Batch pulling must control per-batch data volume to avoid timeouts |
embeddingModelType | Calibrate based on actual testing | Structured fields and attachment text have different vector representation needs, requiring matching model types |
maxContext | 8000–12000 characters | E-commerce due diligence reports require integrating multi-dimensional data. Context length must cover complete operating details and qualification content |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- The symptom is returning unrelated store business data after tool calling. The cause is failing to configure the target store ID variable in
customToolVars. This causes the tool to pull full data from the default range. - The symptom is the function calling module not appearing in the sidebar. The cause is failing to enable the function calling switch in the application's function configuration, or using an application version that does not support tool calling.
- The symptom is garbled text returned when calling a VL model to parse product qualification images. The cause is configuring the VL model input as a text field instead of an image URL. This prevents the model from correctly parsing image content.
How to Confirm Correct Configuration
- Enter test values for custom tool variables in the application debug panel, trigger tool calling, and check if returned data matches the target store's information.
- After enabling the function calling switch, view the tool module in the sidebar to confirm the feature is enabled.
- Upload an e-commerce qualification attachment, trigger VL model parsing, and check if returned text matches the attachment's content.
- Call the embedding model interface, pass a text snippet of e-commerce operating transaction details, and check if returned vector data matches the expected dimension.
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.