What this category of data looks like
Data for infrastructure construction declaration materials and file review primarily comes from project approval declaration documents, construction drawing design materials, budget preparation lists, completion acceptance files, and similar sources. Data updates fall into two categories: centralized batch updates and ad-hoc updates. Centralized batch uploads occur during project declaration and archiving stages. Sporadic content modifications happen during approval and circulation processes.
Documents include two types: structured declaration forms and unstructured long texts. Structured forms have fixed fields including project number, declaring unit, total investment, construction duration, and more. Units are mostly ten thousand yuan and days. Unstructured texts are mostly OCR-transcribed feasibility study reports, construction plans, and other similar content.
Constraints on Vector Models and Indexing
The data characteristics of infrastructure construction declaration materials and files create clear constraints for the vector models and indexing workflow. Fixed fields in structured forms must be linked to business identifiers. Indexing must support filtering and recall by project number and file number. Unstructured long texts vary widely in length. Use a flexible chunking strategy to avoid semantic breaks. The mix of centralized batch uploads and ad-hoc updates requires indexing to support incremental synchronization. This reduces the overhead of full index reconstruction. OCR-transcribed texts have recognition errors. Vector models must have strong semantic fault tolerance.
Configuration Recommendations
These configuration recommendations are formulated for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the semantic integrity of unstructured long texts such as feasibility study reports and construction plans. Balances storage and retrieval efficiency for vector indexes. |
| Overlap Length | 100–150 characters | Prevents semantic breaks after long text chunking. Adapts to the paragraph logic of engineering documents. |
maxToken | 4096 token | Adapts to the vector encoding limit for long documents. Prevents truncation of critical engineering parameters and professional terminology content. |
defaultToken | 256 token | Used for vector encoding of structured form fields. Balances field semantic expression and index storage costs. |
| Similarity Threshold | 0.72–0.78, calibrated via actual testing | Engineering documents contain many professional terms. Balances recall accuracy and coverage. Adapts to semantic matching logic within the field. |
| Single Search Limit | Top 10 results | Covers the retrieval needs of multiple associated materials during file review. Avoids returning excessive redundant results. |
Three Common Misconfigurations
- Symptom: The index status continuously displays "indexing", but no matching results return after querying. Cause: Incremental synchronization trigger logic is not configured. Batched completed files and declaration materials are not automatically added to the indexing queue. Manual full synchronization tasks are not executed.
- Symptom: When using the bge-m3 vector model, semantic retrieval returns similarity scores that are consistently too high, exceeding the preset threshold range. Cause: No preprocessing is applied to engineering professional terms or OCR recognition noise. This causes abnormal vector embedding norm lengths, amplifying semantic similarity calculation results.
- Symptom: The database only stores vector data. Original declaration materials cannot be linked via project number. Cause: Metadata binding rules are not configured. Only text content is passed to the vectorization workflow. Key associated fields such as project code and file archiving number are not stored synchronously.
How to Verify Correct Configuration
- Upload a typical feasibility study report. Confirm the number of chunked text blocks matches expectations. No excessive truncation or overly long blocks appear.
- Initiate a retrieval targeting engineering professional terms. Check that the similarity score range of returned results aligns with preset rules.
- View the vector index's metadata binding fields. Confirm business identifiers such as project number and file archiving number are already linked.
- Trigger an incremental synchronization task. Verify newly added declaration materials are indexed and retrievable within a reasonable time frame.
The values listed above are common starting points. They should be evaluated 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.