What this category of data looks like
The account and report data for survey and design originates primarily from project survey reports, design construction drawing specifications, on-site visa accounts, change notices, and other documents. Data updates are triggered by project progress. Basic account entry is completed in the early project phase. Updates are synchronized with on-site changes during the construction phase. Final report archiving is completed during the completion phase. Individual documents include structured fields such as project number, survey point coordinates, geomechanical parameters, and design load values, with numerical items that include units. Complete survey report documents over 10,000 characters in length per single file are also present.
What constraints these characteristics impose on vector models and indexing
Survey and design data includes large amounts of structured metadata with units and long-text reports. This requires indexing systems to distinguish between vectorization logic for structured metadata fields and main text content. The length of individual documents varies widely. Long reports require a chunking strategy to avoid semantic fragmentation. Update rhythm fluctuates significantly over the project cycle. Incremental indexing is needed to reduce redundant calculations. Multiple types of files are stored together. A unified vector model is required to adapt to text extraction results from different formats.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the semantic integrity of survey report paragraphs, avoids semantic breaks across chapters |
| Overlap Length | 100–150 characters | Retains context continuity between adjacent chunks, prevents semantic loss after chunking long documents |
| Similarity Threshold | 0.72–0.85, calibrated via actual testing | Matches the semantic similarity distribution of parameters in the survey and design field, filters low-relevance results |
| Single Search Limit | Top 15 entries | Covers multi-dimensional associated data of project accounts, avoids missing key associated items |
defaultToken | 4096 | Adapts to input length limits of most open-source vector models, ensures complete semantic input |
maxToken | 8192 | Supports complete context recall for long reports, meets multi-document association requirements for account summary |
Three Common Misconfigurations
- Symptom: Semantic similarity scores of low-relevance documents in retrieval results exceed 0.9, and the issue cannot be fixed by adjusting the threshold. Cause: Vectorization rules are not configured separately for structured fields of survey and design such as geotechnical parameters, causing the general semantic model to misjudge parameter semantic similarity.
- Symptom: Auxiliary account fields are not included in the indexing scope, and associated change records cannot be retrieved during searches. Cause: Metadata fields of auxiliary data are not added to the vector indexing configuration, and only main text content is vectorized.
- Symptom: Multiple sets of vector results appear after uploading data for the same project, or vector data that works correctly in local tests cannot be retrieved on the server. Cause: Vector model versions and chunking configurations are not unified, leading to inconsistent vector generation logic across different environments.
How to Verify the Configuration
- Upload a single survey report over 10,000 characters in length. Check that chunked text fragments retain complete paragraph semantics, with no obvious truncation or semantic breaks.
- Enter a structured query such as "geotechnical bearing capacity parameters of a project". Verify that the field matching degree of retrieval results meets expectations.
- Upload incrementally updated change accounts. Check that the indexing system only performs vector calculations on newly added data, with no full reindexing operations.
- Switch between different vector models. Verify that the consistency of retrieval results meets the requirements of the current scenario.
The values listed here are common starting points, and should be validated against samples from the actual deployment scenario.
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.