What the data for this category looks like
Data for this category comes from requirement specifications, test environment configurations, customer business sample data, and defect management systems. Daily produced documents include UAT use cases, acceptance issue tickets, acceptance reports, and signed confirmation forms. Data updates follow project phases or software version cycles, and are maintained jointly by implementation consultants, test managers, and customer business representatives. Data fields include business scenarios, test steps, issue descriptions, reproduction conditions, acceptance conclusions, and associated version numbers. There are no fixed unified units, and values are adjusted based on actual project scenarios.
What constraints these characteristics impose on the context and token workflow
Data sources for this category are scattered, spanning multiple systems including requirement specifications, test environments, and defect systems. Integrating this data requires handling heterogeneous formatted content, which creates adaptation requirements for context stitching token allocation. Data updates follow project phases or software version cycles. Context must dynamically match the current version’s acceptance scope to avoid mixing invalid cross-version content. Daily documents include structured use cases and unstructured issue tickets. Context splitting must accommodate varying content densities. UAT data accumulates gradually as the project progresses. Token consumption increases with each phase. Context total scale must be limited to avoid resource overload. Acceptance-related documents contain customer-confirmed content. Context filtering must accurately distinguish valid business data from redundant information.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Max Context | 8000–12000 token | Adapts to the model hosting limit of FastGPT v4.17.0, accommodates the integration needs of multiple UAT document types, and avoids exceeding resource thresholds during single loading |
| Max Quote Token | 2000–3000 characters | Reserves sufficient token space to retain key details for long-text reproduction content in acceptance issue tickets, and prevents core information from being truncated |
| Chunk Length | 1000–1500 characters | Accommodates structured paragraphs of UAT use cases and unstructured descriptions of issue tickets, balancing splitting efficiency and context coherence |
| Single Search Limit | Top 6 entries | Matches the number of core acceptance documents during the UAT phase, and prevents redundant content from occupying excessive token resources |
| Context Filtering Rules | Filter by version scope | Adapts to the update rhythm of data by phase or version, only loads valid documents from the current acceptance phase, and reduces invalid token consumption |
Three common misconfigurations
- Symptom: Model-generated Markdown tables fail to render correctly, or displayed content is truncated. Cause: The
maxContextandquoteMaxTokenconfigurations are not adjusted for structured table content in UAT acceptance reports, causing table content to exceed the allocated token limit and be truncated. - Symptom: Question-and-answer response speeds slow down, and token consumption continues to rise. Cause: The context loading scope is not limited by project phase, and all UAT use cases and issue tickets from all historical phases are included in the context, causing token occupancy to grow uncontrollably as the project progresses.
- Symptom: Retrieved content is unrelated to the current acceptance phase, or redundant historical issue records appear. Cause: The context filtering rule for filtering by version scope is not configured, causing invalid documents from cross-phase periods to be loaded and additional token resources to be consumed.
How to confirm configurations are set correctly
- Upload a UAT acceptance report and issue ticket from the current phase, and test whether the context loading only includes valid content for the current version, with no cross-phase redundant documents.
- Initiate a query for acceptance issues that include structured tables, and confirm that model-generated tables render correctly with no content truncation.
- Count token consumption values for three consecutive question-and-answer interactions, and confirm that consumption stays within the configured maximum context range with no abnormal increases.
- Test the context filtering rule, and verify that historical documents from cross-version periods are not included in the context for the current question-and-answer session.
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.