Data Characteristics for This Category
The data for this category originates from national public resource trading platforms, local trading platforms, engineering approval systems, and bidding supervision systems, with a daily update frequency. Daily documents include tender notices, qualification prequalification documents, bidding documents, bid submission documents, bid evaluation reports, successful bid candidate announcements, and successful bid result announcements. Fields covered include qualification requirements, performance requirements, bill of quantities, construction period, and others. The structure varies based on section type and project scale.
Constraints for Vector Models and Indexing
Daily updated data sources require indexes to support incremental synchronization, avoiding full reconstruction that consumes excessive computing resources. Multi-type document structures require chunking strategies adapted to different content characteristics. Expert records in bid evaluation reports must be split by entry. Bill of quantities in bid submission documents must retain unit associations, to avoid breaking the integrity of professional content during splitting. The need for precise matching of professional fields such as qualifications and bills of quantities requires vector models adapted to professional terminology in the engineering construction field, reducing the probability of mismatches for non-professional terms. Data from multiple sources must first undergo format standardization. Otherwise, index confusion will occur, affecting the accuracy of subsequent ledger summary and report generation.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the paragraph length of documents such as tender notices and bid submission documents, avoiding splitting that damages the integrity of professional content |
| Overlap Length | 100–150 characters | Retain contextual association between chunks, ensuring the accuracy of vector matching for continuous content such as bills of quantities and qualification requirements |
maxToken | 4096 | Adapt to the input upper limit of the text-embedding-ada-002 model, avoiding vector generation failures |
| Similarity Threshold | 0.75–0.85 | Distinguish qualification and performance requirements for different sections, reducing mismatch probability, and meeting the strict requirements of the bidding scenario |
| Single Search Limit | Top 10 entries | Cover frequently associated documents such as bid evaluation reports and successful bid announcements, balancing search speed and recall completeness |
defaultToken | Calibrated based on actual measurements | Adapt to resource restrictions of different deployment environments, avoiding excessive memory usage |
Three Common Misconfigurations
- Symptom: A prompt stating "no retrievable content" appears when using the knowledge base, or the index status remains unchanged for a long time. Cause: The vector model channel is not configured correctly, or the model is not added to the system's available list, resulting in an interruption of the vector generation process.
- Symptom: Search speed is too slow, with a single query taking more than 30 seconds. Cause: The chunk length and single search limit parameters are not adjusted, resulting in too many redundant documents being recalled, or incremental indexing is not enabled to synchronize daily updated bidding data.
- Symptom: After connecting a local m3e vector model, the interface continuously displays the "indexing" status. Cause: The model's call timeout parameter is not configured, or the response delay of the locally deployed model exceeds the system's default threshold, causing the indexing process to hang.
How to Confirm Proper Configuration
- Upload a single tender notice document to trigger the vector generation process. Confirm that no errors appear in the system logs of FastGPT v4.17.0 and that corresponding vector entries are generated.
- Enter a query containing qualification requirements or a bill of quantities, check the number and relevance of recalled documents, and confirm that they meet the preset matching rules.
- Trigger an incremental synchronization operation to verify whether daily updated bidding data has been successfully added to the index library, with no progress hangs.
- Check the vector model channel information in the configuration panel, confirm that the correct key and address configuration has been completed.
The values provided here 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.