What This Type of Data Looks Like
Data is primarily sourced from public bidding platforms, internal project ledgers of engineering consulting organizations, and bank credit approval public notices. Updates follow a workday cadence, with one daily report released each workday. Each report covers engineering financing projects finalized during the current week. The document structure includes fixed fields: project ID, client entity name, financing amount, financing term, consulting service scope, and approval status. Amounts use ten thousand yuan as the unit, and terms use natural months or years as the unit.
Constraints for Vector Models and Indexing
The format difference between unstructured text from public data sources and structured text from internal ledgers is significant, requiring vector models to support mixed-format text chunking. The high-frequency update requirement means indexes must use incremental update mode to avoid resource consumption from full reindexing. Fixed fields and unique identifiers require indexes to bind business primary keys to eliminate duplicate entries. The large number of project entries per daily report requires vector splitting by entry granularity to avoid vector confusion across projects. Additionally, structured numeric fields require vector models to have strong encoding capabilities for numeric text.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | The length of project entries in a single daily report mostly falls between 500-1000 characters. This range fully covers core information for individual projects and avoids slicing off critical business fields |
chunk_overlap | 50–80 characters | Retains associated context between adjacent project entries, preventing information gaps in cross-entry vector recall |
vector_model | text-embedding-ada-002 or Chinese vector models of equivalent dimension | Adapts to specialized terminology and structured numeric fields in the engineering consulting domain, with recall accuracy meeting business requirements |
index_type | FAISS IVF index | Adapts to large volumes of frequently updated entries, balancing recall speed and storage efficiency |
top_k | Top 10–15 results | The number of projects per daily report typically falls between 10-20 entries, so this range covers the full target result set |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the file size of single engineering consulting financing daily reports, avoiding file size limit errors during import |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and testing against sample data tailored to the deployment is recommended before finalizing settings.
Three Common Configuration Mistakes
- Symptom: The number of recall results after importing the daily report is far fewer than the actual number of projects. Cause: The
unique_key_fieldis not set to the project ID, resulting in failed deduplication after duplicate indexing of the same project entries. - Symptom: API calls return status code 413 with a file size too large prompt. Cause: The
UPLOAD_FILE_MAX_SIZEparameter is not adjusted, and the file size of a single engineering consulting financing daily report usually exceeds the default limit. - Symptom: Custom index model channels cannot be configured in version V4.14.3. Cause: This version does not offer the custom index model channel configuration entry, so an upgrade to a supported version is required.
How to Verify Correct Configuration
- A single test daily report is imported, then the knowledge base entry list is checked to confirm the number of entries matches the number of projects in the daily report.
- A vector recall test is initiated, and the
project IDfield of the recall results is verified to match the entry range specified in the query conditions. - The financing amount of a single project entry is manually modified to trigger an incremental index update, then the recall results are confirmed to be updated synchronously.
- The index monitoring dashboard is reviewed to confirm the index update frequency matches the workday update schedule of the daily reports.
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.