What the Data for This Category Looks Like
Data sources include public tender announcement platforms, official purchaser announcements, and internal post-tender project review documents. Updates are triggered based on tender project milestones, and generated in a concentrated batch after a single bid opening. There is no fixed batch update cycle. Most documents use a structure combining structured fields and free text descriptions. Fields include project ID, failed bid reason, original judgment basis, associated bidder name, failed bid time, and more. Text length per data entry has no unified standard.
Constraints on Vector Models and Indexing
The mixed structured and unstructured data structure requires indexes to support both semantic vector recall and structured metadata filtering. The non-fixed update cycle requires indexes to support incremental writes and on-demand refreshes. Full scheduled index rebuilding cannot be used as a fixed process. Free text in failed bid judgment basis exhibits significant semantic variation across similar cases. This requires vector models to adapt to professional terminology understanding in the tender and bidding domain. The wide variation in text length per data entry requires a dynamic chunking strategy to adapt to different input text lengths, avoiding truncation of core judgment information.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Text Chunk Length | 800–1200 characters | The original judgment basis for failed bids mostly consists of tender clause snippets. This chunk length covers most single judgment text lengths and avoids truncating core judgment information |
Vector Model | bge-large-zh-v1.5 | This model performs well in understanding professional terminology semantics in the tender and bidding domain, and adapts to the text characteristics of failed bid judgment basis |
Recall Count | Top 8–12 results | Failed bid judgment basis usually relates to a small number of relevant tender clauses. Too many recall results introduce irrelevant information |
Similarity Threshold | 0.75–0.85 | This range filters out non-relevant failed bid items with large semantic differences, while retaining similar judgment scenarios with close semantics |
Index Incremental Update Toggle | Enabled | Failed bid item data updates non-fixedly based on project milestones. Incremental updates reduce resource consumption from index rebuilding |
Metadata Filter Fields | project ID, failed bid time | Recall failed bids must be associated by tender project dimension to avoid interference from irrelevant data across projects |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on applicable samples before finalizing settings.
Three Common Misconfigurations
- Issue: Index creation fails when calling a vector model connected via One API, returning a
401 Unauthorizederror. Cause: The One API proxy address and custom secret key are not correctly filled in the vector model configuration, leading to authentication failure. - Issue: Key information is truncated when parsing the original failed bid judgment basis, resulting in loss of core judgment logic in vector recall. Cause: The
text chunk lengthis set too small, truncating tender text snippets exceeding the chunk length and losing complete basis for failed bid judgment. - Issue: The number of index recall results does not match the set
recall count, with either too many or too few results. Cause: The matching relationship betweensimilarity thresholdandrecall countis not adjusted synchronously. A threshold set too high filters out valid results, while a threshold set too low recalls irrelevant results.
How to Confirm Proper Configuration
- The vector model configuration interface can be reviewed to confirm that
vector model, proxy address, andAPI keymatch the actual service in use. - A single failed bid test data entry can be uploaded to trigger index creation, and the index log can be checked for successful incremental writes with no prompts for truncation or parsing errors.
- A semantic recall test can be initiated, with a relevant description of a tender document input, and the
project IDof the recall results can be verified to match the project identifier of the test data to confirm that metadata filtering is operational. - The value of
text chunk lengthcan be adjusted, a long-text failed bid judgment basis can be uploaded, and the parsed chunks can be checked to cover the full text with no loss of key content.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.