What this category of data looks like
Data comes primarily from public industry monitoring platforms, brand supply chain disclosure information, and payment collection records from offline retail terminals. Full data for the previous day is updated daily. Deliverables are structured CSV or Excel files. Files include fields such as brand name, device model, SKU code, shipment volume, terminal selling price, channel financing amount, and payment collection cycle. Shipment volume is measured in units. Selling price and financing amount are measured in yuan. Payment collection cycle is measured in calendar days.
Constraints imposed by these characteristics during model access and configuration
The daily full update feature requires scheduled trigger task configuration during model access, to avoid redundant overhead from frequent calls. Structured fields and fixed unit requirements require enabling structured data parsing mode in model configuration, and presetting field mapping rules to ensure extracted values match their units. Using SKU code as the unique identifier requires configuring a recall matching primary key rule to prevent cross-device data confusion. Fixed units for numeric fields require clear unit validation logic in the model prompt to avoid unit deviations in extraction results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
structured_parse_mode | Force structured parsing | Consumer electronics financing daily reports use structured format, requiring strict matching of preset fields and units |
RECALL_PRIMARY_KEY | SKU code | This field is the unique identifier for consumer electronics financing daily reports, preventing cross-device data confusion |
system_prompt | Only extract fields including SKU code, shipment volume, financing amount, and payment collection cycle. Retain original units for numerical values, and use calendar days as the unit for payment collection cycle | Matches field and unit requirements for this category of data, and clarifies extraction rules |
max_context | 800–1200 characters | Structured content length of a single consumer electronics financing daily report is moderate, and this range covers all field information |
similarity_threshold | 0.85–0.9 | Precise matching of SKU codes is required to avoid recall of irrelevant data with low similarity |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Full consumer electronics financing daily report data has a large volume, requiring sufficient parsing time |
temperature | 0.1 | Ensures accuracy of field extraction, avoiding random deviations |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: Model calls throw errors. OneAPI logs display the request token as "fastgpt". Cause: The token parameter in FastGPT model access configuration was not properly filled, or was overwritten by the default placeholder.
- Phenomenon: Model extracts text content correctly, but cannot assign extracted values to target fields. Cause: Structured field mapping rules were not configured, or the system prompt did not clarify field assignment logic.
- Phenomenon: Scheduled model parsing tasks time out and fail. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted, and the default timeout duration is insufficient for processing full consumer electronics financing daily report data.
How to Confirm Proper Configuration
- Manually upload a single structured consumer electronics financing daily report file, and check if the parsing result fully extracts the preset fields and matches the original data units.
- Initiate a single model call to verify that extracted field values exactly match the numbers in the original document, with no unit deviations.
- Check call logs to confirm that the request token matches the configured token, with no abnormal placeholders.
- Run a scheduled task once to check if the task completes within the preset time, with no timeout errors.
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.