What the data for this category looks like
Data sources for general equipment financing daily reports include financing filing systems of local financial regulatory authorities, business ledgers of cooperating financial leasing institutions, and corporate loan databases of banks. Data is updated on a T+1 daily schedule. Previous day’s business data is collected to form that day’s daily report. The structure of a single data document includes fields such as financing filing number, general equipment category (such as conveying equipment, cutting equipment), equipment model, financing amount (yuan), loan institution, financing party unified social credit code, loan date, repayment period (months), and guarantee form. Amounts are denominated in RMB yuan. Dates use the YYYY-MM-DD standard format.
Constraints on model access and configuration
Multiple heterogeneous data sources require configuring access adaptation rules for each data source. Rules must connect to the API formats and authentication methods of different institutions separately. The daily T+1 update schedule requires configuring scheduled synchronization tasks. Trigger times must align with the daily report update cycle to avoid data lag or duplicate synchronization. Fixed-format dedicated fields require configuring custom field extraction and format verification rules. These rules prevent the model from receiving dirty data. Enumerated equipment categories and uniquely identified filing numbers require configuring tag mapping and deduplication rules. These rules ensure the model can accurately identify specific equipment categories and avoid duplicate data recall. Financially sensitive fields require configuring data desensitization rules. These rules comply with data compliance requirements.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_CUSTOM_FIELD_RULE | Configure a regular expression that matches the 9 preset fields including financing filing number and general equipment category | This category of data has a fixed field format, and regular expression matching can accurately extract dedicated business fields |
SYNC_DATA_FREQUENCY | 1 time per day, triggered at 2:00 AM | General equipment financing daily reports are updated T+1, aligning with business collection rhythm and avoiding occupying peak business bandwidth |
VECTOR_DB_REFRESH_BATCH_SIZE | 500 items per batch | Single data contains multiple business fields. Excessively large batches may trigger third-party interface timeouts. 500 items balances synchronization efficiency and stability |
SENSITIVE_DATA_MASK_RULE | Partially mask unified social credit code and financing amount | Data contains financially sensitive information and must comply with data compliance requirements |
MAX_CONTEXT | 8000–16000 characters | Parsed single daily report data is approximately 200 characters. Context after batch recall must accommodate multi-turn conversations and data content |
RECALL_TOP_N | Top 8 entries | Single batch business data volume for general equipment financing daily reports is moderate. 8 entries covers typical business query scope |
The parameter values provided on this page are all conventional recommendations used as a starting point 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
- Symptom:
Request Timeouterrors occur frequently during dialogue when accessing a locally deployed large model. Cause: TheMAX_CONTEXTparameter value is not adjusted. The volume of context data passed to the model exceeds the carrying limit of the local model, triggering request timeout. - Symptom: Tool calling fails to trigger function call logic. The returned result does not include preset financing data extraction instructions. Cause: The field mapping rules for
PARSE_CUSTOM_FIELD_RULEare not configured. The model cannot recognize the dedicated fields of general equipment financing daily reports, so it cannot trigger corresponding tool calls. - Symptom: Duplicate entries appear in recalled general equipment financing daily report data. Cause: The deduplication function of the
DATA_DEDUPLICATION_ENABLEparameter is not enabled. The deduplication rule using the financing filing number as the unique identifier is not configured, resulting in duplicate data being recalled.
How to Confirm Configuration is Complete
- Manually trigger a data synchronization. Check the synchronization log in the FastGPT knowledge base. Confirm all preset fields are correctly extracted, with no dirty data containing format errors.
- Initiate a query related to general equipment financing. Verify the results returned by the model include correct fields such as equipment category and financing amount, with no duplicate entries.
- Call the local large model interface. Test passing the custom extracted context data. Confirm no request timeout error occurs.
- Check the system scheduled task record. Confirm the daily synchronization task triggered at the configured time has completed.
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.