What the data for this category looks like
Data sources include public industrial and commercial disclosures and public financing announcements from industry investment and financing platforms. Full valid financing entries from the previous day are updated at a fixed daily time slot. Each data document contains six core fields: full enterprise name, main condiment category, financing amount, financing round, investor list, and announcement release date. Financing amount is measured in RMB ten thousand yuan. Announcement release dates use ISO standard date format. The main category field marks specific condiment sub-directions, such as soy sauce, seasoning sauce, compound seasonings, and similar items.
What constraints these characteristics impose on model access and configuration
The daily fixed update feature requires configuration items to adapt to the scheduled pull time window. This prevents exceeding quota limits by calling data source interfaces too frequently. The sub-field for main condiment category requires dedicated field mapping rules during model access. This ensures parsed content matches the condiment classification system in the knowledge base. The fixed unit rule for financing amount requires unit conversion logic for numerical parsing. This prevents unit confusion in model output. The multi-value list format of the investor list requires a multi-field parsing template. This ensures the model can fully extract and display multiple investor information. The fluctuation in daily new entry volume requires dynamic current-limiting parameters. This avoids timeouts in pull tasks caused by sudden increases in data volume.
Configuration Parameters
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DATA_PULL_FREQUENCY | Once daily, during the 02:00-04:00 time window | Matches the daily update rhythm of the condiment financing daily report, avoids peak access periods for industry data interfaces |
FIELD_MAPPING_RULE | Map the "Main Category" field to the "Condiment Sub-Category" classification in the knowledge base | Adapts to the main condiment category field included in the data, achieves precise knowledge base classification matching |
PARSE_AMOUNT_UNIT | Automatically convert the value of the "Financing Amount" field to ten thousand yuan units | Adapts to the field rule that the financing amount in the data is in ten thousand yuan units, avoids unit errors during model parsing |
MAX_PULL_RECORDS_PER_DAY | Calibrated based on actual testing | Adapts to the fluctuation range of the number of daily new financing entries, avoids exceeding the call limit of the data source interface |
CONTEXT_WINDOW_SIZE | 800–1200 characters | Adapts to the length of a single financing daily report entry, ensures the model can fully parse key information of each record |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Configuration Errors
- Phenomenon: A
[FATAL] failed to get-type error occurs when starting the OneAPI container service. Cause: No correct network proxy is configured, or the local deployment environment has no external network access permission. This prevents pulling the data source interface for the condiment financing daily report. - Phenomenon: A large number of meaningless punctuation marks such as
#and*appear in dialogue output results. Cause: TheMARKDOWN_RENDER_MODEparameter is not configured. This leaves format tags generated by the model unfiltered, and fails to adapt to special character escaping rules for some fields in the data source. - Phenomenon: The model cannot correctly output the image URL configured in the knowledge base. Cause: The
IMAGE_URL_PARSE_ENABLEconfiguration item is not enabled, and the data source field corresponding to the image URL is not bound in the field mapping. This prevents the model from recognizing and returning the image link.
How to Confirm Successful Configuration
- Execute a manual data pull task, and check that the number of pulled entries matches the number of financing entries released by the data source on that day.
- View the field parsing results, and confirm that the financing amount unit has been correctly converted, and the main category field has been matched to the corresponding classification.
- Initiate a test dialogue, and verify that there are no extra format punctuation marks in the model output, and that the image URL in the knowledge base can be correctly referenced.
- View the system logs, and confirm that the daily scheduled pull task has not reported timeout or call quota exceeded 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.