What the data for this category looks like
Carbon steel financing daily report data comes from three sources: daily financing monitoring from domestic steel industry associations, credit granting submissions for the steel industry from partner banks, and pledged financing filings from the spot market. The update cycle is daily T+1 generation, covering all carbon steel pledged financing transactions from the previous trading day. Each daily report contains multiple structured records, with fields including statistical date, carbon steel grade, pledged cargo volume, single transaction financing amount, financing term, credit granting institution, and financing cost. The unit for pledged cargo volume is tons, financing amount is ten thousand yuan, and financing term is calendar days.
What constraints do these characteristics impose on vector models and indexing
Structured multi-transaction features require splitting documents by individual financing transactions as the smallest unit, to avoid losing business details in long-text vectors. Multiple data sources bring differences in field formats, so standardized processing must be completed before embedding to ensure consistency in vector embeddings. The daily update cycle requires the index to support incremental synchronization, to avoid resource consumption from full index rebuilding. The mixed structure containing numeric and text fields requires adapting to vector models that support multiple field types, or completing text conversion for numeric fields. At the same time, business field filtering requirements require the index to support precise recall based on dimensions such as carbon steel grade and financing term, to improve matching efficiency.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
embedding_model | bge-large-zh-1.5 | Compatible with the embedding interface of FastGPT v4.8.7 and above, supports Chinese structured fields, and the embedding dimension matches the text length of carbon steel financing daily reports |
chunk_size | 200–300 characters | The text description of a single financing transaction mostly falls within this range, to avoid destroying the integrity of business logic when splitting segments |
index_incremental_sync | Enabled | Adapts to the daily update cycle, avoiding resource consumption from full index rebuilding |
filter_field_list | ["carbon steel grade", "financing term", "financing amount"] | Matches common filtering requirements in business scenarios, improving the accuracy of recall results |
embedding_batch_size | 32–64 items/batch | Balances server CPU/GPU resource usage and vector embedding processing efficiency |
max_recall_count | Top 10 entries | Adapts to the scale of business entries in a single daily report, avoiding excessive recall results that increase subsequent processing overhead |
The parameter values provided on this page are 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, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- After generating multiple vector groups from a single carbon steel financing daily report, it is impossible to associate them with business entries. Failing to split document chunks by individual financing transactions, and directly performing vector embedding on the entire daily report, causes vectors to fail to match specific business transactions.
- After uploading the carbon steel financing daily report, the index status continuously shows "indexing" with no progress. Failing to configure the incremental index switch, and a single daily report containing a large number of business entries, triggers full index timeout.
- After uploading a locally generated carbon steel financing vector file to the server, normal recall fails. The vector model used by the server has inconsistent embedding dimensions with the local model, and model parameters were not aligned in advance.
How to confirm the configuration is correct
- Review the chunk data after vector embedding, confirm that each chunk corresponds to the complete fields of a single financing transaction, with no splitting errors.
- Trigger an incremental synchronization task, check that the index logs show no full rebuilding records, only the number of incrementally updated entries.
- Enter a carbon steel grade keyword to test that recall results only include financing transactions for that category, confirming the filtering logic is active.
- Upload a small test daily report, confirm that the index completion time meets the requirements of the business update cycle, with no prolonged hanging.
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.