What data for this category looks like
Data sources include public financing announcements of publishing enterprises, filing information from local cultural and tourism publishing regulatory platforms, and data disclosed by industry associations. The update rhythm is daily. Financing information disclosed on the same day is entered into the system the same day. The core content is structured tables, with fixed fields including full name of the financing party, financing round, financing amount (unit in ten thousand yuan or hundred million yuan), investor list, disclosure date, publishing sub-sector, and original announcement link. Some entries include a brief description of financing purposes.
What constraints these characteristics impose on model access and configuration
The daily updated data source requires configuring scheduled task scheduling parameters to ensure financing information disclosed on the same day is timely added to the processing workflow. There are many structured fields and a need for amount unit conversion, so field extraction rules and unit standardization logic must be configured to avoid chaotic model output formats that disrupt downstream data use. Announcement originals contain long text segments, so context window parameters must be adjusted to adapt to long text input, while limiting token consumption per single data entry to prevent token length limit exceeded errors. The investor list is a multi-value field, so multi-value extraction parsing rules must be configured to ensure the model accurately identifies and returns complete investor entity information.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
scheduleCron | 0 8 * * * | Adapts to the daily 8 AM update requirement of publishing financing daily reports, ensuring timely processing of same-day disclosed data |
maxContext | 8000–12000 characters | Adapts to the long text input requirement of announcement originals, avoiding truncation of key financing information |
tokenLimitPerRequest | 4096 | Controls token consumption per request, preventing token length limit exceeded errors |
fieldExtractionPrompt | Extract financing party name, financing round, financing amount and unit, investor list, disclosure date from given text, return in standard JSON format | Matches structured field extraction requirements, ensuring output formats meet downstream processing standards |
multiValueParseThreshold | 0.6–0.8 | Sets the similarity threshold when identifying multi-value investor fields, avoiding misjudging unrelated entities as investors |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Adapts to the parsing duration requirement of announcement originals, avoiding long text parsing timeouts |
The parameter values provided on this page are all common recommended starting points for determining configurations. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to conduct tests on your own samples before finalizing settings.
Three common errors
- A 422 status code is returned during calls, with the prompt "Messages token length must". The cause is that the
tokenLimitPerRequestparameter is not configured, and the token consumption of a single data entry exceeds the model interface limit. - The AI chat node continuously outputs chat return content during debugging, and independent task results cannot be obtained separately. The cause is that the chat context retention switch of the node is not turned off, resulting in historical chat content being appended to each call.
- The financing amount field has mixed units, with some entries displaying both ten thousand yuan and hundred million yuan identifiers. The cause is that unit standardization configuration is not enabled, and no unified processing is performed for amount units.
How to confirm configurations are properly set
- Manually upload a single publishing financing announcement original, check the matching degree between the structured fields returned by the model and the original text, adjust field extraction configurations until the extraction results meet expectations.
- Trigger the preset scheduled scheduling task, check the task execution log, confirm there are no errors such as token limit exceeded or parsing timeout, adjust context and timeout parameters until the task runs stably.
- Batch import multiple sets of different types of financing daily report data, check the extraction completeness of multi-value fields, adjust the multi-value parsing threshold to a reasonable range.
- Call the API interface to initiate a test request, confirm the returned result format meets preset requirements, adjust the per-request token limit parameter to ensure the request completes normally.
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.