What this category of data looks like
Data sources for this category include enterprise procurement platforms, public resource trading platforms, supplier databases, contract management systems, and audit issue repositories. The update frequency is daily. Daily documents cover procurement plans, requirement specifications, bidding documents, bid evaluation records, contracts, acceptance documents, and supplier complaint materials. Fields include procurement methods, budget basis, scoring methods, supplier qualification requirements, performance clauses, and more. There are no unified fixed units; fields change dynamically based on document type.
Constraints imposed by these characteristics on vector models and indexing
Daily updated data requires indexes to support incremental synchronization, avoiding time consumption and resource usage caused by full reconstruction. Differences in structure across multiple document types require adapting different chunking strategies, ensuring core compliance-related content such as procurement methods and budget basis is not truncated. The wide range of covered fields requires vector model encoding to prioritize alignment with compliance review keyword dimensions, while limiting the volume of data indexed per batch to avoid memory overflow. Inconsistent data formats across cross-platform sources require pre-format standardization processing, otherwise vector retrieval accuracy will be affected.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Covers the complete semantics of a single piece of core compliance-related content, avoiding truncation of key clauses |
| Overlap Length | 100–200 characters | Connects the semantics of adjacent chunks, preventing compliance clauses from being split and losing context |
maxToken | 8192 | Adapts to the context window limit of mainstream large language models, ensuring recalled content can be fully included in Q&A |
| Single Search Limit | Top 10 results | Controls the volume of retrieval returns, avoiding redundant content occupying context space |
defaultToken | 2000 | Limits the maximum number of tokens for a single vector encoding, balancing semantic completeness and indexing efficiency |
| Reranking | Calibrated based on actual testing | Adjusts reranking rules for compliance keyword weights in tendering and procurement, improving accuracy |
Three common configuration errors
- Retrieval response times are excessively long, with request timeouts displayed in the interface. Cause: Incremental indexing strategy is not enabled, and each retrieval triggers a full data scan, occupying large amounts of computing resources.
- The Q&A pair extraction task continuously shows the "Indexing" status and cannot enter the ready state. Cause: Chunk length settings exceed the single-document processing limit, and no chunk timeout threshold is configured, causing task blocking.
- The dataset automatically generates multiple duplicate indexes, with data volume growing abnormally over time. Cause: Document deduplication configuration is not enabled during incremental synchronization, and duplicate content from the same data source is written to the index multiple times.
How to verify correct configuration
- Manually upload a typical bidding document, check whether the chunking results cover core compliance clauses with no obvious truncation.
- Submit a compliance-related query, confirm the number of retrieval return results matches the single search limit configuration.
- Wait for one full daily incremental synchronization cycle, check that index updates only include new data with no duplicate entries.
- View vector model call logs, confirm that the
maxTokenanddefaultTokenconfigurations are correctly loaded.
The values given 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.