What the Data for This Category Looks Like
The business data for game client performance optimization comes from engine Profiler, crash platforms, real-device testing, and frame rate data collection tools. Daily output documents include performance test reports, device adaptation lists, optimization records, and crash analysis reports. Data updates occur daily or per release cycle. Fields across documents include device model, frame rate threshold, resource occupancy ratio, crash log ID, and more. Units include frames per second (fps), memory occupancy in megabytes (MB), time consumption in milliseconds, and others. Participants include client engineers, engine engineers, and performance testing teams. Most documents focus on performance metrics for single devices or all supported devices.
Constraints for Multi-turn Dialogue and Prompt Engineering
Most data is structured content exported from tools. Dialogue prompts must adapt to professional field formats related to performance optimization, to avoid failure to recognize technical terms. Data updates occur daily or per release cycle. Older documents have limited reference value. Dialogue context must limit the retained range, to prevent redundant data from interfering with analysis. Core performance optimization steps take a long time. Prompts must focus on key steps such as low-end device reproduction, resource occupancy analysis, and optimization effect regression, to reduce invalid information. Multiple segmented documents exist. Multi-turn dialogue must support associating information across multiple documents, to ensure the completeness of requirements and design documents.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
messages | Segment by single-round tasks not exceeding 8000 characters, retain the most recent 15 turns of content for multi-turn dialogue | Game performance document update frequency is daily or per release cycle. Older data has low reference value. Excessively long context reduces processing efficiency |
variables | Inject preset business variables such as frame rate thresholds, device parameters, and crash log IDs | Daily documents contain structured performance test data. Preset variables enable quick association with professional fields |
| Maximum context length | 10000–12000 token | Matches the total character count of single-version performance documents, avoids truncating key optimization records |
| Maximum single-turn document count | Top 5 core documents | The most time-consuming steps are low-end device reproduction and resource analysis. Focusing on core documents improves dialogue accuracy |
chatId | Bind optimization task IDs for each version | Differentiates performance optimization requirements across versions, prevents cross-version context confusion |
Three Common Misconfigurations
- When analyzing long-text performance documents, the error "The value of 'offset' is out of range" is returned. The cause is failure to segment long documents by fixed length, leading the model to exceed the text offset threshold during processing.
- After uploading multiple performance documents, the dialogue cannot associate content across different documents. The cause is failure to add clear role and content identifiers for each document in the format specified by the
messagesparameter. - Performance data and configurations must be reloaded each time a dialogue starts. The cause is failure to bind
chatIdto lock task context, and failure to reuse configured document resources.
How to Verify Proper Configuration
- Input raw data exported from engine Profiler, verify whether the dialogue automatically associates preset device adaptation parameters.
- Launch a cross-version performance optimization dialogue, verify whether the task identifier correctly binds the optimization requirements of the corresponding version.
- Input a document segment exceeding the preset length, verify whether processing follows the set segmentation rules.
- Upload multiple performance documents, verify whether the dialogue can retrieve the set number of core document contents.
The values provided here are common starting points, and should be evaluated 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.