What the data for this category looks like
Typically, daily documents for game design and numerical design include gameplay design docs, structured numerical tables, version requirement lists, and balance test records. Teams source data from internal player behavior data, public competitive product materials, battle logs, and version feedback. Document update frequency follows weekly or per-version iteration cycles. Numerical tables contain fields with units such as character attributes, skill coefficients, and level thresholds. Gameplay design docs primarily consist of rule description text. Overall data includes both structured numerical and unstructured text formats.
What constraints do these characteristics impose on vector models and indexing workflows
The update rhythm of category data requires indexes to support incremental trigger logic. This avoids wasting excessive computing resources on repeated full-index runs. The coexistence of structured numerical tables and unstructured rule text means vector models must adapt to both professional term embedding and semantic capture of numerical association logic. Failure to do this may lose critical coefficient associations. The high risk of error requires index recall accuracy to align with business requirements. This prevents gameplay imbalance or version rework caused by recall bias. Additionally, single-document length varies widely. Proper chunking rules must balance semantic completeness and indexing efficiency.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the single-rule length of gameplay design docs and numerical tables, avoiding semantic fragmentation |
| Overlap Length | 100–200 characters | Preserves cross-chunk numerical association logic, preventing loss of coefficient associations after splitting |
maxToken | 4096 token | Adapts to the embedding upper limit for long text, covering the full content of version requirement lists |
| Similarity Threshold | 0.75–0.85 | Filters low-match irrelevant numerical rules, reducing the risk of gameplay imbalance |
| Single Search Limit | Top 5 entries | Controls context length, avoiding exceeding model input limits |
defaultToken | Calibrated via actual testing | Adapts to the embedding accuracy of professional terms in the category, matching semantic requirements for game numerical scenarios |
Three Common Mistakes
- Symptom: Knowledge base index progress stalls, with unprocessed files remaining in a processing state for long periods. Cause: No incremental index trigger rule is configured, using full-index execution to match weekly or per-version update frequencies, leading to excessive resource usage.
- Symptom: Unable to retrieve index completion status after calling the file upload API. Cause: The index status callback interface of FastGPT v4.17.0 is not enabled, and trigger conditions for status polling are not configured.
- Symptom: Vector embedding results have low matching accuracy with numerical rules. Cause: A generic text vector model is used, without adapting to the semantic characteristics of game numerical and professional rule text.
How to Verify Correct Configuration
- Upload a typical numerical table document, confirm that chunked text fragments retain complete key information such as coefficients and thresholds.
- Submit a query about "character armor penetration coefficient", check that returned context includes relevant document fragments for the corresponding numerical rules.
- Review index task logs, confirm that incremental indexes only trigger after weekly or version updates, with no repeated full-index execution.
- After switching the vector model, re-embed the test document, compare whether semantic similarity of embedding results changes as expected.
The values provided here are common starting points, and should be evaluated against local test samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.