What the data for this category looks like
Complaint ticket data primarily comes from enterprise customer service systems, CRM ticket modules, and internal business flow records. Updates occur in real time or near real time. New tickets are created immediately after a user submits a complaint. Archived historical tickets must be retained for reference. Individual ticket documents include structured fields such as ticket ID, customer identity identifier, complaint initiation time, request text, processing progress, and associated business nodes like policy numbers and payment records. They may also include unstructured attachments such as chat screenshots and transcribed text.
What constraints these characteristics impose on knowledge base retrieval and recall
Multi-source heterogeneous data sources require configuring cross-system field mapping rules. This unifies ticket data formats and field names, preventing missing fields or matching errors during retrieval. High-frequency data updates require using incremental synchronization for knowledge base updates, which reduces repeated parsing and indexing overhead. Tickets contain both structured metadata and unstructured request text. This means the retrieval link must support both metadata filtering such as by ticket priority or associated business nodes and semantic recall, to accurately locate relevant historical tickets and solutions. Some tickets include non-text attachments, so corresponding file parsing plugins must be enabled. This extracts valid content from attachments and includes it in the knowledge base index.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_MAX_SIZE | 20 MB | Complaint ticket attachments are mostly chat records and screenshot-transcribed text. Single file size is moderate, which avoids parsing timeouts. |
Incremental Sync Interval | 5 minutes | Complaint tickets have high update frequency. Latest ticket content must be synchronized to the knowledge base in a timely manner. Applies to FastGPT V4.14.3 and later versions. |
Chunk Length | 800–1200 characters | Complaint request text has moderate length. Too long chunks damage semantic coherence, too short chunks lose context information. |
Recall Count | Top 10 entries | Standardized solutions for complaint tickets have a concentrated coverage scope. A small number of recall entries meets customer service query needs. |
Similarity Threshold | 0.75–0.85 | Balances recall precision and coverage, avoids incorrectly recalling irrelevant historical tickets or general solutions. |
UPLOAD_FILE_TIMEOUT_SECONDS | 600 seconds | When importing ticket datasets in batches, single batch data volume is large. Sufficient time is required for upload and parsing. |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. Testing on local samples is recommended before finalizing settings.
Three Common Configuration Mistakes
- A
fail to create post presigned urlerror occurs when uploading a ticket dataset. The cause is that object storage access keys are not configured, or storage bucket permissions are insufficient. This prevents generation of pre-signed URLs for file uploads. - The number of retrieval results does not match the configured
Recall Count. The cause is that the metadata filtering switch is not enabled, or filtering conditions are set incorrectly. This causes some semantically matching tickets to be excluded early. - An error
datasetId is required for S3 filesis displayed when importing CSV-format ticket data. The cause is that the associated knowledge base ID is not specified in the dataset configuration, or the S3 storage path is not bound to the correct dataset identifier.
How to Verify Configurations Are Correct
- Perform an upload test for a single ticket data entry. Check if the interface displays upload success with no error prompts.
- Simulate a retrieval for a typical complaint request. Verify that the number of returned results matches the configured
Recall Count. - View the knowledge base synchronization logs. Confirm that the incremental synchronization task runs on schedule according to the preset
Incremental Sync Interval. - Test setting metadata filtering conditions, such as filtering by ticket priority or associated business nodes. Verify that returned results conform to the filtering rules.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.