What data for this category looks like
This category of data originates from requirement specification documents, test environment configurations, client business sample materials, and defect management systems. Core daily deliverables include UAT test cases, acceptance issue tickets, acceptance reports, and signed confirmation forms. Document fields include scenario identifiers, expected results, actual operation steps, defect severity levels, acceptance conclusions, and additional relevant fields. Data is updated synchronously per project phase or software version, and is maintained jointly by implementation consultants, test managers, and client business representatives.
What constraints these characteristics impose on the model integration and configuration workflow
The multi-source nature of this category’s data requires model integration to support custom business term mapping, to adapt to exclusive business expressions of different clients. The phase- or version-based update rhythm requires configurations to support rapid iterative adjustments, without requiring redeployment to adapt to new UAT phase data. Core documents include traceable content such as signed confirmation forms, so model output associated context parameters must retain complete link information. The requirement to interface with defect systems and client business samples requires configuration items to explicitly specify API access endpoints and verification tokens.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
AIPROXY_API_ENDPOINT | Root address of the AI Proxy service, for example http://aiproxy:3000. Do not append /v1 or /chat/completions paths. Do not use single-model service addresses such as VLLM/Ollama/Xinference | Complies with official configuration requirements for AI Proxy dependencies, ensuring service startup verification passes |
AIPROXY_API_TOKEN | Administrator token consistent with the AI Proxy server configuration, cannot be empty | Complies with authentication requirements for the AI Proxy service, ensuring service startup verification passes. Do not use application API keys, model vendor secrets, or tokens issued per application |
maxContext | 8000–12000 token | Covers the full context of single-phase UAT test cases and acceptance issue tickets, avoiding truncation of critical information |
maxTokens | 2000–3000 token | Controls output length for single-round defect analysis or test case generation, adapting to typesetting specifications for acceptance documents |
quoteMaxToken | 1500 token | Limits the length of quoted UAT test case or defect ticket content, ensuring output focuses on core conclusions |
temperature | 0.3–0.5 | Reduces output randomness, ensuring consistency of acceptance conclusions and defect categorization |
Three common configuration mistakes
- The symptom is that the defect categorization output by the model does not match the business scenario of the actual acceptance issue ticket. The cause is that custom term mapping is not configured, and client-specific business expressions are not adapted to.
- The symptom is that interface requests return a 401 Unauthorized error. Troubleshooting items include whether
AIPROXY_API_ENDPOINTcomplies with official requirements, or whetherAIPROXY_API_TOKENis a valid non-empty administrator token consistent with the AI Proxy server configuration. - The symptom is that test case generation results output by the model truncate critical steps. The cause is that the
maxContextconfiguration value is too low, failing to cover complete UAT phase context information.
How to confirm configurations are properly applied
The following verification actions must be performed based on FastGPT v4.17.0.
- Initiate a test case generation request, verify that the returned result includes the current phase’s UAT test case fields, and confirm that the
maxContextconfiguration adapts to the current data length. - Submit an acceptance issue ticket, check whether the defect categorization result output by the model matches the business scenario, and confirm that the custom term mapping configuration is effective.
- Check interface request logs, confirm that
AIPROXY_API_ENDPOINTis the root address of the AI Proxy service, and thatAIPROXY_API_TOKENis a valid non-empty administrator token consistent with the AI Proxy server configuration. - Verify that multi-turn conversation context is fully retained, and confirm that the
maxContextconfiguration meets link traceability requirements.
The values listed are common starting points, and should be evaluated against the reader’s own sample data.
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.