What Data Is Included in This Category?
The data for hotline knowledge base maintenance mainly comes from government hotline call transcription texts, closed ticket archive content, latest policy documents, and offline-sorted common question lists. Data updates are initiated by policy adjustments, ticket closure, or new user requests, with no fixed schedule. Each single document includes fields such as problem classification tags, standard reply text, associated ticket ID, applicable scenario description, effective end date, and more. Fields primarily use text, date, and classification enumeration types, with no complex nested structures.
What Constraints Do These Characteristics Impose on Tool Calling and Plugins?
Since data originates from unstructured or semi-structured sources like call transcriptions and ticket archives, tool calling must support long text segment processing to avoid exceeding single-input limits. The non-fixed update schedule requires plugins to support incremental sync configurations, only pulling updated documents. Multi-classification fields and enumeration attributes let users specify classification tags as recall filtering conditions during tool calling, ensuring returned content aligns with hotline scenario request scopes. Tools must support filtering by date ranges using the effective date field, to prevent returning expired reply content. The associated ticket ID field also requires tool calling to sync the processing status of the corresponding ticket after execution, to support ticket closure workflows.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool calling mode | Trigger via functionCall | Adapts to the structured reply extraction needs of hotline knowledge bases, ensuring returned content conforms to the standardized format required for ticket assistance |
| Recall filtering rules | Filter by problem classification + effective date | Matches the classification and date fields of knowledge base documents, filtering out expired or irrelevant content |
| Incremental sync cycle | Every 6 hours | Adapts to the non-fixed update rhythm, balancing data timeliness and call resource consumption |
| Field extraction scope | Only extract standard reply text, associated ticket ID | Focuses on core business fields for hotline scenarios, reducing invalid data transmission |
| Call timeout | 30 seconds | Adapts to the real-time response requirements of hotline scenarios, avoiding excessive wait times that impact ticket processing efficiency |
| Maximum recall count | Top 3 entries | Controls the scale of knowledge base content returned per call, complying with the length limits of conversation context |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Misconfigurations
- Phenomenon: A "context length exceeded" error appears after tool calling. Cause: No reasonable maximum recall count is configured, causing the total knowledge base content in a single input to exceed the context threshold supported by the model.
- Phenomenon: A connection failure error returns when calling a locally deployed large model. Cause: Correct local model address and port parameters are not configured, preventing the tool from connecting to the model normally.
- Phenomenon: Imported knowledge base documents have abnormal formatting, and content cannot be extracted properly. Cause: No compatible document conversion tool is used to process original call transcriptions or ticket materials, leading to text segmentation or field extraction errors.
How to Verify Successful Configuration
- Manually trigger a tool call for a common user request, and check if the returned knowledge base content includes currently active reply texts.
- Review the plugin's sync logs to confirm that the incremental sync task runs on the set schedule and only pulls updated documents.
- Test user requests across different classifications, and confirm that tool calling only recalls knowledge base content matching the specified classification.
- Simulate a high-frequency call scenario, and verify that the tool's response time stays within the preset timeout threshold.
The values listed here 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 2026-09-28.