Reference only; verify against the target FastGPT release and deployment documentation.
What This Category of Data Looks Like
Internal office data for telecommunications engineering construction primarily originates from construction logs, equipment operation and maintenance ledgers, project progress documents, employee work orders, and site disclosure records. Update rhythms vary widely: construction logs and operation work orders are updated in real time, while equipment ledgers and project budget documents are updated weekly or monthly. Individual documents follow a fixed structure, including fields such as project number, construction area, GPS coordinates, equipment model, and processing result. Some documents include audio-transcribed site disclosure content, with units including engineering-specific measures such as man-days, sets, and kilometers.
Constraints on Vector Models and Indexing
The varied update rhythms, specialized fields, and diverse document types of telecommunications engineering construction internal office data create multiple constraints for the vector model and indexing workflow. Real-time construction logs and operation work orders require incremental indexing to eliminate resource consumption from full reindexing. Documents with structured fields like GPS coordinates and project numbers need combined text vector and metadata filtering to enable precise recall. Long audio-transcribed site disclosure content requires indexing support for long text splitting and overlapping segments to prevent key information loss. Documents with different update cycles must use classified indexing to avoid high-frequency updated data overwriting low-frequency static data.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the effective information length per segment of documents such as construction logs and work orders, avoiding overloading single chunk content |
| Overlap Length | 100–150 characters | Covers key information such as construction steps and equipment problem descriptions across chunks, preventing segment breaks |
defaultToken | 8192 token | Adapts to the input upper limit of most open-source vector models, meeting the embedding requirements of long transcribed text |
| Similarity Threshold | 0.72–0.85 | Distinguishes similar records of the same construction issue and different teams, avoiding false recalls |
| Single Search Limit | Top 20 entries | Matches the standard recall volume for work orders and logs in telecommunications engineering construction, balancing recall efficiency and accuracy |
| Maximum Context | 4000 characters | Adapts to the effective information length of internal office Q&A, avoiding redundant content interfering with model understanding |
Three Common Configuration Errors
- Phenomenon: After custom document splitting, duplicate index entries appear in the knowledge base, and the index order does not match the original document. Cause: The unique identifier field of the document is not retained during the splitting process, so the original document order cannot be associated during indexing, and the automatic deduplication configuration is not enabled.
- Phenomenon: A 401 status code is returned when calling the vector model. Cause: The API key of the vector model is not configured correctly, or the dedicated vector model interface is not correctly bound when using the OneAPI channel, resulting in authentication failure.
- Phenomenon: The index merging component does not take effect after running, and no deduplication results are generated. Cause: The deduplication switch for index merging is not enabled, or the merging rule does not match unique fields such as the document's project number.
How to Verify Correct Configuration
- Upload a test document that includes project number and GPS coordinates, check if metadata fields such as project number and GPS coordinates are retained after indexing.
- Trigger an incremental indexing task, compare the number of index entries before and after the update to confirm that real-time data is correctly added.
- Input a test question containing construction area keywords, check if the recall results include documents from the corresponding area.
- View the vector model call logs, confirm that the returned embedding results have no format errors and the status code is 200.
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.