What the data for this category looks like
The data for this category primarily comes from customer-submitted warranty work orders, system operation logs, contract warranty terms, and version update records. Four types of documents are processed daily: warranty work orders, defect confirmation sheets, repair records, and customer confirmation sheets. The data structure includes structured fields such as work order number and responsibility judgment items, as well as unstructured text such as defect descriptions and repair plans. Data updates occur daily or per order, with new content added in real time as defect repair progress advances.
Constraints on Context and Token Processing Imposed by These Characteristics
The diverse data sources and frequent updates for this category require context retrieval to cover recent related documents, and avoid introducing outdated historical information. Differences in document structures require context processing to balance the integrity of structured fields and unstructured text, preventing key defect information from being split. The content length of individual documents and the number of related documents determine the upper limit of context token usage. Without proper configuration, token overflow or loss of key information is likely to occur. Additionally, responsibility boundary judgment requires associating context from multiple documents, which places high requirements on the accuracy and scope of retrieval.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 10000–12000 token | Adapts to the average context token usage of single-round requests for this category, balancing retrieval scope and model load capacity |
quoteMaxToken | 2000–2500 token | Limits the maximum token usage of a single related document, preventing context overflow caused by overly long individual documents |
| Chunk Length | 800–1000 characters | Matches the average paragraph length of daily documents for this category, balancing retrieval accuracy and token utilization |
| Overlap Length | 150–200 characters | Retains cross-chunk defect description association information, preventing context breaks |
| Single Search Limit | Top 6 entries | Matches the average number of related documents per day for this category, balancing retrieval scope and response speed |
Three Common Misconfigurations
- Phenomenon: When calling the FastGPT workflow API, returned results cannot associate historical questions, and answers become irrelevant during consecutive questioning. Cause: Context binding rules are not configured in workflow nodes, only single-round request parameters are passed, and token and related document information from historical sessions are not included.
- Phenomenon: After uploading warranty work order documents, the content retrieved by the model has missing fragments, and the complete defect repair process cannot be described. Cause: The chunk overlap length is set too small, causing cross-paragraph defect association information to be split, and a coherent context cannot be formed.
- Phenomenon: The number of documents returned by retrieval exceeds expectations, and some documents are irrelevant to the current question. Cause: The single search limit is set too large, introducing unrelated historical work orders and interfering with the accuracy of context retrieval.
How to Verify Correct Configuration
- Upload a single complete warranty work order document, initiate a query in the knowledge base of FastGPT v4.17.0, and verify that the model can retrieve all key defect descriptions and repair records in the document.
- Initiate 3 consecutive related queries, and verify that each round of answers can associate defect information from previous questions, with no irrelevant answers.
- Call the workflow API, pass request parameters that include a historical session ID, and verify that the returned results can associate historical context content.
- Check the system operation logs, confirm that the number of retrieved documents matches the
maxContextparameter setting, and there are no token overflow error messages.
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.