What Data for This Category Looks Like
Daily data for level content creation teams comes primarily from level editors, art resource libraries, player test data, and defect tracking systems. Daily documentation includes level design documents, resource requirement sheets, test feedback forms, and version submission records. Level design documents mark path node coordinates and resource placement positions. Resource requirement sheets include resource IDs and capacity units. Test feedback logs record stuck level nodes and debugging times. Version submission records associate submitters with version numbers. Data is updated weekly or with each version iteration. Document structures vary across different levels. Some data uses structured fields, while other data uses free-text descriptions.
Constraints Imposed on Knowledge Base Retrieval and Recall Workflows
First, the high data update frequency requires the retrieval system to support incremental synchronization and fast index updates. This prevents content deviations caused by outdated data. Second, data types include structured fields such as resource IDs and level coordinates, and free text such as debugging records. The system must support both semantic matching and precise field matching retrieval logic. Third, errors in level content directly lead to stuck gameplay or delayed launches. Retrieval results must have high precision to avoid irrelevant data interfering with core tasks. Fourth, the multi-data-source nature requires precise control over the retrieval scope. This prevents cross-level document confusion.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the precision requirements for level design. Filters low-relevance general documents to avoid interference from irrelevant resources during level debugging |
limit | Top 8 entries | Adapts to multi-dimensional associated data for level content. Covers multiple types of information including paths, resources, and feedback, while preventing excessive context from impairing inference |
searchMode | hybrid | Supports both text semantic matching and structured field matching. Covers free text in level design documents and structured IDs in resource requirement sheets |
usingReRank | Enabled | Raises the ranking priority of highly relevant results. Reduces false recalls for stuck-level issues, ensuring core debugging information is displayed first |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands synonyms related to levels. For example, matches "waypoint" to "navigation point" to cover terminology differences across planners |
collectionIds | Configured per single level | Precise control over the retrieval scope. Avoids interference from cross-level irrelevant documents for current tasks. Adapts to parallel development scenarios for multiple levels |
Three Common Misconfigurations
- Phenomenon: Manually inserted knowledge base indexes disappear automatically after several hours. Cause: Incremental synchronization rules are not configured. Batch version updates overwrite temporarily inserted non-periodic index data.
- Phenomenon: Target level documents are not recalled during the first query, but are successfully recalled during the second query. Cause: The
similaritythreshold is set too high. The first retrieval round does not include target data. The system automatically optimizes the query term during the second query to complete the match. - Phenomenon: Multimodal resources such as level screenshots cannot be retrieved. Cause: Multimodal embedding configuration is not enabled. Only text-based documents are processed for recall, so visual level resources cannot be matched.
How to Verify Proper Configuration
Based on the configuration logic of FastGPT v4.17.0, submit a test query that includes specific level coordinates. Check whether the returned results include corresponding level design details and resource information. Adjust the similarity threshold to 0.7 and 0.85. Verify whether the filtering effect for low-relevance results meets expectations. Switch the collectionIds configuration for different levels. Confirm that the retrieval scope is limited to documents for the current level, with no cross-level irrelevant data. Trigger a single batch version data update. Verify that indexes do not disappear automatically. Confirm that the incremental synchronization logic works correctly.
The values given 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 2026-10-19.