What the data for this category looks like
Financing daily report data for joint-stock banks is sourced from the institution’s credit management system, interbank lending transaction ledger, and the central bank’s financial statistics reporting system. Daily data aggregation and updates complete after 17:30 each day. Each daily report includes multi-dimensional line items. Core fields include same-day interbank borrowing and lending amounts (unit: 100 million yuan), weighted average interbank lending rate (unit: %), number of maturing financing transactions, proportion of financing from core counterparty banks (unit: %), and term structure distribution (1 day / 7 days / 14 days, etc.). Data line items are fixed. The total character count of a single document varies widely. It is recommended to confirm values based on sample statistics or actual testing before finalizing. No randomly added fields exist.
Constraints imposed by these characteristics during model access and configuration
Fixed fields and units require strict matching to the preset input schema when accessing the model, to avoid parsing failures caused by missing fields or unit conversion errors. A fixed daily update schedule requires scheduling configuration to bind a timed trigger rule after 17:30, to ensure timing alignment between data acquisition and model processing. Stable total character count per single document and fixed line items limit the preset context window range, requiring adaptation to medium-length text processing capabilities. Structured counterparty bank and term fields require the model recall step to associate unique identifiers for corresponding fields, to avoid confusion across fields.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
EMBEDDING_MODEL | text-embedding-v3 | Matches vector extraction accuracy for structured financial data, supports joint semantic encoding of multiple fields |
PARSE_CHUNK_SIZE | 800-1000 characters | Matches the total length of a single financing daily report (800-1200 characters), to avoid overly fragmented chunks or semantic breaks |
RETRIEVAL_TOP_K | Top 6 entries | The number of core line items in financing daily reports is fixed. Excessive recall will introduce non-core data to interfere with inference |
SIMILARITY_THRESHOLD | 0.75-0.85 | Meets semantic matching accuracy requirements for structured financial fields, to avoid incorrect recall of non-current or non-bank financing data |
SCHEDULE_CRON_EXPRESSION | 0 18 * * * | Aligns with the daily update schedule of bank financing daily reports after 17:30, to ensure access to the latest aggregated data |
MODEL_PROVIDER | Calibrated via actual testing | Adapts to model invocation permissions for the organization’s channel, to avoid errors from unavailable channels |
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 internal samples before finalizing.
Three common mistakes
- Symptom: A
503 No available channel for model text-embedding-v3 under current group defaulterror is returned when invoking the model. Cause: The dedicated channel for the corresponding model is not configured, or the channel permission is not bound to the default group. - Symptom: A
connection errorerror occurs when invoking the large language model. Cause: A compliant channel configuration is not used, or the channel configuration’s key and interface address do not match. - Symptom: Unit information is missing from parsed financing daily report fields. Cause: Structured field retention configuration is not enabled, or trailing characters related to units are truncated during chunk splitting.
How to confirm the configuration is complete
- View the model channel configuration page, confirm the binding relationship between
EMBEDDING_MODELandMODEL_PROVIDER, and verify the validity of the channel key and interface address. - Trigger a manual data import, check that the parsed document fields include complete unit information with no missing content or garbled text.
- Run a scheduled scheduling test, confirm that the task triggers and completes data processing at the time specified by
SCHEDULE_CRON_EXPRESSION. - Initiate a simulated query, check that the number of recalled financing data line items matches the core fields of the current day’s document, and aligns with business expectations.
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.