What the data for this category looks like
Data sources include internal real estate enterprise financing management systems, corporate banking business interfaces of partner banks, and project filing data from local housing and urban-rural development departments. The update rhythm is daily. Documents use structured table format, with fields including: project filing number, full name of development entity, financing type (development loan/trust/supply chain finance), single financing amount (unit: ten thousand yuan), arrival date, remaining credit limit, current repayment amount (unit: ten thousand yuan), fund usage direction. Each entry corresponds to daily financing changes for a single residential development project.
What constraints these characteristics impose on model access and configuration
The structured table format requires adapting to structured text parsing rules during model access, to avoid field loss from unstructured splitting. The daily update rhythm requires configuring scheduled synchronization task trigger intervals to match the data update cycle, to avoid index lag. Unique identifier fields such as project filing number and development entity require configuring index deduplication rules, to prevent repeated import of financing data for the same project. Multi-source data sources require configuring cross-system field mapping rules, to unify field naming differences across different interface returns and ensure data consistency.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
embedding_model | text-embedding-3-large or same-dimensional structured text optimized model | Structured tables have many short fields. High-dimensional models better capture associations between fields. |
chunk_size | 800–1200 characters | Single record length for residential development financing daily reports falls between 300-800 characters. This segment length covers complete single records and avoids cross-field splitting. |
sync_schedule | 0 9 * * * (Cron expression) | Financing data updates follow the T+1 rule. Triggering at 9 AM daily covers all changes from the previous day. |
vector_store_duplicate_check_field | Project Filing Number | This field is the unique identifier for residential development projects. It enables accurate deduplication of financing data for the same project. |
api_qps_limit | 10–15 | Daily synchronized data entry count stays in the hundreds. This QPS range avoids model interface current limiting. |
parse_structured_table | Enabled | Original data uses structured table format. Enabling this setting preserves field hierarchy and association relationships. |
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. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Scenario: After replacing
embedding_model, existing knowledge base recall results do not match expectations, or old data cannot be reused directly. Cause: The vector index rebuild operation was not performed. The original vector library was generated using the old embedding model and was not updated after the model switch. - Scenario: The Docker-deployed FastGPT container restarts frequently after startup. Logs contain the error
dial tcp: lookup oneapi.example.com: no such host. Cause: The model proxy address was not configured correctly, or FastGPT attempted to connect to the oneapi service before it completed startup. - Scenario: Knowledge base recall results lack units for the financing amount field, or numerical calculation errors occur. Cause: The
parse_structured_tableconfiguration was not enabled. The model did not recognize unit annotations for the amount field, leading to separation of numerical values and units.
How to confirm configuration is complete
- Manually trigger a synchronization task. Check that the number of new entries in the synchronization log matches the number of entries updated by the data source on the current day. This confirms scheduled synchronization and field mapping configurations are active.
- Initiate a model call test. Input a structured financing daily report fragment. Check that returned result field integrity matches the original data. This confirms the embedding model and structured parsing configuration are correct.
- View the vector library monitoring panel. Confirm that the number of deduplicated entries matches the unique statistical count of
Project Filing Number. This confirms the deduplication field configuration is active. - Simulate continuous model interface calls. Check whether current limiting errors are triggered. This confirms the QPS limit configuration meets actual call requirements.
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.