What the data for this category looks like
Follow-up record summary data comes from two sources: speech-to-text transcripts from hotline call centers, and fields from follow-up forms linked to ticket systems. Data is synchronized to the knowledge base within 10 minutes after a single follow-up is completed. The structure of each document includes fields such as follow-up subject ID, follow-up time period, verified problem list, rectification conclusion, follow-up requirements, and more. The follow-up time period field uses minutes as the unit. The verified problem list is multi-paragraph text. The rectification conclusion uses a mixed format of fixed options plus supplementary notes. All fields are text type.
What constraints these characteristics impose on deployment and upgrade
Since the data sources include two heterogeneous sources: call center speech-to-text transcripts and ticket follow-up forms, deployment requires configuring interface authentication and format conversion rules for both data sources to ensure both types of data can be uniformly stored in the database. Because follow-up records are generated in real time and have a high update frequency, upgrade steps need to adjust the synchronization trigger logic to avoid duplicate entry of the same follow-up data. Since documents include multi-paragraph verified lists and unstructured supplementary notes, field mapping rules must be predefined to ensure semantic association during vector database import meets retrieval requirements. Because some transcribed text contains noise, basic text cleaning parameters must be configured during the deployment phase to improve the accuracy of subsequent retrieval.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:password@localhost:27017/fastgpt?authSource=admin | Used to store original follow-up record text and structured fields, matching the storage requirements of dual data sources |
REDIS_URL | redis://:redis_password@localhost:6379/0 | Caches real-time synchronized follow-up task queues to avoid repeated synchronization triggers |
DB_MAX_LINK | 20–30 connections | Adapts to database concurrent connection requirements during batch follow-up record synchronization |
STORAGE_S3_ENDPOINT | https://s3.cn-north-1.amazonaws.com.cn | Stores audio attachments from original recorded speech transcripts, matching the storage requirements of multi-source data |
ROOT_KEY | custom 32-character strong secret string | Used for authentication of internal synchronization interfaces, ensuring the security of follow-up data synchronization |
Three common mistakes
- Symptom: No results are returned when the workflow calls follow-up data. Cause: Access permissions for
MONGODB_URIwere not configured correctly, making it impossible to read original follow-up record data. - Symptom: Real-time synchronization tasks frequently time out. Cause: The value of
DB_MAX_LINKis too low, failing to support concurrent synchronization requests for batch follow-up records. - Symptom: Uploaded follow-up recorded speech transcription attachments cannot be parsed. Cause: Read/write permissions for the storage bucket corresponding to
STORAGE_S3_ENDPOINTwere not configured, making it impossible to obtain the transcription text source file.
How to confirm the configuration is complete
- Execute the built-in interface test script provided by FastGPT, call the follow-up data synchronization interface, and check whether the returned results include preset fields such as follow-up time period and rectification conclusion.
- Log in to the Redis monitoring panel, check the queue length corresponding to
REDIS_URL, and confirm that real-time synchronization tasks have no backlog and the count increases normally. - Access the knowledge base management page of FastGPT v4.17.0, verify that the vector database index for follow-up record summaries has been generated and can be retrieved normally.
- Trigger a synchronization operation for a simulated follow-up ticket, and check whether a corresponding data entry has been created in the target database.
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 2026-09-28.