Data characteristics of this category
This category regularly produces documents including gameplay design plans, numerical tables, version requirement sheets, and balance test records. Data sources include player behavior data, public competitor materials, battle logs, and version feedback. Data updates follow a weekly or per-version cycle. Numerical tables contain fields such as level, damage coefficient, and resource consumption, with units including gold, diamonds, and seconds. Gameplay design plans include unstructured content such as rule descriptions and trigger conditions. The overall data includes both structured fields and free text.
Constraints on model access and configuration
The mixed format of structured numerical tables and unstructured gameplay descriptions requires model access configuration to support both field extraction and text understanding. Data updates follow a weekly or per-version cycle, so knowledge base synchronization must match this pace to avoid expired data interfering with review results. Data sources include real-time battle logs and version feedback, so context length must be controlled during retrieval to ensure response speed. Compliance review results directly affect gameplay balance and version launch, so recall must cover all core document content to avoid missing key validation items.
Configuration guidelines
The following configurations are based on FastGPT v4.17.0:
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Core documents for this category (gameplay design plans, numerical tables) are mostly 5000-8000 token per file. Full context must be retained to cover all compliance validation related content. |
maxTokens | 4000–6000 token | Security and compliance review requires generating detailed reports including rule validation and numerical deviation analysis. Sufficient output space is needed to carry complete conclusions. |
quoteMaxToken | 2000–3000 token | Sufficient battle logs and version feedback fragments must be recalled as compliance evidence. Control the total length of referenced fragments to avoid context overflow. |
temperature | 0.1–0.3 | Compliance review requires stable, consistent validation conclusions to avoid judgment deviations caused by randomness. |
AIPROXY_API_ENDPOINT | Root address of the AI Proxy service, for example http://aiproxy:3000 (do not append /v1 or /chat/completions, do not use single-model addresses such as VLLM/Ollama/Xinference) | Specify the access address of the AI Proxy service for the App/Admin service. |
AIPROXY_API_TOKEN | Admin token consistent with the AI Proxy server configuration, and cannot be empty | Used for authentication between the App/Admin service and the AI Proxy service. Do not use application API keys, model vendor keys, or other types of tokens. |
Three common configuration errors
- Phenomenon: Knowledge base retrieval response is slow, with the page waiting more than 10 seconds without returning results. Cause: Index sharding rules are not optimized for the category's structured numerical tables, leading to loading too many shard files during retrieval.
- Phenomenon: After uploading a gameplay design plan or numerical table, parsing results miss core fields such as damage coefficient and resource consumption. Cause: Parsing logic for structured documents is not adapted, leading to failure to correctly extract field association information from numerical tables.
- Phenomenon: Logs showing
gpt-4o-mini call failedappear during workflow runtime, and the model call is not actively configured. Cause: Uncleaned model reference configuration remains in workflow nodes, and the system attempts to trigger invalid calls.
How to verify successful configuration
- Upload a typical numerical table document, check if the parsing result completely includes core fields such as level, damage coefficient, and resource consumption.
- Initiate a compliance review request, check if the response time meets business expectations with no obvious timeouts.
- Verify the
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations, initiate a test call to confirm the App/Admin service can normally connect to the AI Proxy service. - Run a workflow including a compliance review node, check that there are no error messages about invalid model calls in the logs.
The values provided 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.