What this category of data looks like
Telecommunications service market and yield data is sourced from dedicated industry segment APIs of mainstream domestic financial market data providers. There are two update frequencies: real-time market data refreshes every 5 seconds, and daily yield reports are updated within 1 hour after the close of each trading day. Data is packaged in structured JSON format, including segment ID, segment name, daily opening price, daily closing price, daily price change, daily trading volume, total daily transaction amount, and daily turnover rate. Unit specifications: prices are in Chinese yuan, trading volume is in ten thousand shares, total transaction amount is in ten thousand yuan, and turnover rate is a dimensionless ratio.
Constraints on conversation logging and auditing workflows
The characteristics of telecommunications service data impose multiple constraints on the conversation logging and auditing workflow. First, with two update frequencies (real-time and daily reports), logs must accurately record request timestamps to match the corresponding data update cycle and avoid returning expired data. Second, the data includes multiple structured fields. The auditing workflow must verify the presence and format validity of each field. For example, prices must not be negative, and trading volume must not be a non-positive value. Third, the data relies on third-party market data APIs. Logs must fully record API call return codes, request latency, and return content summaries for troubleshooting. Fourth, telecommunications service segment IDs have a fixed allowed range. Auditing must verify that requested segment IDs are within the allowed list to prevent invalid requests.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
LOG_LEVEL | info | Covers core logs for API calls, request parameters, and return results, balances troubleshooting needs and log storage costs |
API_REQUEST_TIMEOUT | 10 seconds | Telecommunications market API responses are typically fast. An overly long timeout will block conversation workflows, while an overly short timeout will cause normal requests to fail |
MAX_RETRY_TIMES | 2 retries | Market APIs occasionally experience fluctuations. Retries can reduce failure rates, while too many retries will extend user wait times |
AUDIT_FIELD_WHITELIST | ["segment ID","opening price","closing price","trading volume","total transaction amount"] | Core fields for telecommunications service market data, ensures returned content is complete and format-compliant |
LOG_RETENTION_DAYS | 30 days | Auditing needs typically cover 30 days of conversation and API call records. Excessive retention will consume excessive storage resources |
VECTOR_DIMENSION | 2560 | Matches the vector dimension of text embeddings generated from telecommunications industry market data, ensuring retrieval matching accuracy |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by data type, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Issue: Unable to view FastGPT runtime logs after Docker deployment. Cause: The log directory inside the container was not mounted to the host machine. Default logs are only stored inside the container, and logs will be deleted when the container restarts.
- Issue: Vector dimension mismatch error when calling the telecommunications market API. Cause: The
VECTOR_DIMENSIONconfiguration was not set to 2560, which does not match the vector dimension generated by the embedding model, causing retrieval workflow errors. - Issue: Unable to find the corresponding entry in the interface after configuring the plugin. Cause: The plugin package was not placed in the FastGPT-specified plugin directory, or the service was not restarted to load the new plugin, so the system cannot recognize the added plugin.
How to Verify Successful Configuration
- Log in to the log management panel in the FastGPT backend, confirm that the log level matches the configured setting, and that calls to the telecommunications market API, their parameters, and return results are captured.
- Manually initiate a test request for telecommunications segment market data, check that the returned result fields include all items in the audit field whitelist, and that the format is normal.
- Restart the FastGPT service, check the system startup logs for no configuration loading failure error messages, and confirm that the added audit rules and external interface configurations have taken effect.
- Verify the log storage logic, confirm that old logs exceeding the configured retention period have been automatically cleaned up according to the rules, with no redundant log accumulation.
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.