What the data for this category looks like
The declaration materials and file review data for building construction engineering general contracting mainly originate from project winning bid notices, construction permit approval documents, cost accounting lists, sub-item acceptance reports, and completion archives. Data updates align with project milestones: declaration materials are updated after winning a bid, and complete file materials are supplemented during the completion phase. Documents contain structured fields including project number, section scope, cost amount, and construction period, alongside unstructured construction logs and material test reports. Field units include square meters, ten thousand yuan, and calendar days. Individual document lengths vary widely, ranging from a few pages of declaration forms to hundreds of pages of completion files.
Constraints imposed on vector models and indexing by these characteristics
The declaration and file data for building construction engineering general contracting has both structured and unstructured attributes, with significant variation in individual document lengths. This requires vector modeling to balance field relevance and text integrity. Data updates occur on an irregular schedule, so incremental indexing support is required, and index real-time performance is a priority. Multiple fields mean chunking must retain field context to avoid losing key associated information after splitting. As document volume grows with project scale, batch vectorization is needed. Adapt batch processing logic to reduce the number of text slices per request and avoid timeouts.
How to set configurations
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the average text density of building construction declaration materials, retains complete key information such as approval nodes and section scope in a single chunk |
| Overlap Length | 100–150 characters | Prevents context breakage after chunking, and prevents associated fields such as project number and construction period from being split into different chunks |
defaultToken | 1024 | Matches the average token proportion of a single chunk of building construction documents, adapting to the parameter requirements of basic vectorization requests |
| Similarity Threshold | 0.75–0.85 | Filters low-match irrelevant files, ensuring that review results only associate with materials of the target project |
| Single Search Limit | Top 8 entries | Controls the number of returned results, balancing sufficient recall of project-related declaration and file content |
maxToken | 4096 | Limits the total token amount of a single round of context, adapting to the model input limit of FastGPT v4.17.0 |
Three Common Mistakes
- Phenomenon: Vectorization tasks take too long, and the console log shows that only a single text slice is submitted each time. Cause: The batch vectorization switch is not configured, and requests are only initiated for single pieces of text.
- Phenomenon: Search results have low matching accuracy, returning irrelevant non-project-specific file materials. Cause: The chunk length is set to more than 1500 characters, causing the association information between project number and section to be lost after splitting.
- Phenomenon: Index update is delayed, and newly submitted declaration materials cannot be retrieved. Cause: The incremental index trigger rule is not set, and only full index reconstruction is performed.
How to confirm the configuration is correct
- View the index construction logs in FastGPT v4.17.0 to confirm that vectorization requests include batch-submitted text slices.
- Test searching for declaration materials with a specific project number, confirming that returned results include associated information such as the corresponding section and cost.
- Enter the configuration panel to verify that parameters such as chunk length and overlap length match the preset values.
- Submit a single completion file, confirming that the index can be retrieved within the preset duration after update.
The values provided here are common starting points and should be evaluated against your 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.