What the data for this category looks like
Ledger data for telecommunications engineering construction is primarily sourced from on-site construction logs, material incoming acceptance receipts, progress approval forms, supervision rectification receipts, and similar documents. It covers specialized fields such as optical cable laying length, base station antenna model, and equipment installation location.
The data update rhythm follows: daily construction log updates for each project, weekly summary of progress ledgers, and monthly archiving of acceptance documents. Each individual document includes fields such as project number, construction section, material model, incoming quantity, acceptance date, and supervision signature. Field types cover character, numeric, and date formats. Some documents also include unstructured attachments such as drawing photos and scanned files.
How these characteristics impose constraints on vector models and indexing
The diversity of specialized fields requires indexing to support both structured field association and unstructured text vector matching. High-frequency updated data requires adaptation to incremental indexing processes to avoid performance losses caused by full reconstruction. Unstructured attachments must first undergo OCR conversion to text, otherwise valid vectors cannot be generated. Unique field identifiers such as project number + construction section require deduplication rules in index configuration to avoid duplicate recall of the same ledger record. Long text content from construction logs requires retaining contextual associations during chunking to prevent loss of key construction details after splitting.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the typical content length of single telecommunications engineering construction logs, avoids splitting that breaks associations between fields such as optical cable laying records and base station parameters |
| Overlap Length | 100–150 characters | Retains context for cross-chunk construction progress descriptions, ensures recalled content is coherent and complete |
| Similarity Threshold | 0.75–0.85 | Adapts to the precise matching requirements of ledger data, reduces false recall probability across projects and construction sections |
| Single Search Limit | Top 10 entries | Covers the volume of ledger data updated daily for a single project, avoids redundant results interfering with report generation |
| defaultToken | 8192 | Adapts to the context length requirements for indexing and recalling long documents, meets text needs after splicing multiple fields |
| Maximum Context | Calibrated via actual testing | Matches the long text processing limit of FastGPT v4.17.0 |
Three Common Misconfigurations
- Phenomenon: Vector model connection displays an error, and the console returns a timeout error. Cause: The
defaultTokenparameter is not configured to adapt to long text requests, and the batch recall request format for telecommunications engineering ledgers is not adapted. - Phenomenon: Recall results include ledger records from non-target projects. Cause: Index filtering rules are not set based on the project number field, resulting in cross-project data being included in the recall range.
- Phenomenon: Key field information such as material model and incoming quantity is lost after chunking long documents. Cause: Field metadata is not retained during chunking, making it impossible to associate complete structured information of the corresponding ledger after vector recall.
How to Confirm Proper Configuration
- Upload a single construction log document containing optical cable laying records, check that the index generation progress bar advances normally with no error prompts.
- Enter a query statement containing a project number and base station construction section, verify that the recall results include specialized fields such as optical cable length and antenna model of the corresponding ledger, as well as complete text content.
- Add a newly updated base station acceptance ledger document for the current day, check that the system automatically triggers incremental indexing with no prompt for full index reconstruction.
- Adjust the similarity threshold, verify that the number of recall results changes as expected with the threshold, with no abnormal fluctuations.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.