What the data for this category looks like
The financial scenario data linked to satellite communications marketing content primarily comes from satellite downlink transmission data received by ground gateway stations. This includes business report data from remote financial terminals, satellite orbit and coverage area snapshots, and form submission behavior logs from user terminals. The data updates on a near-real-time cadence, with a single data collection interval of 10 seconds to 1 minute. The data follows a structured time-series format, with fields including satellite ID, terminal IMEI, form submission status, signal SNR, link latency, and business throughput. Field units include dB, ms, Mbps, s, and others. There is no highly nested unstructured content.
What constraints these characteristics impose on the forms and interactions workflow
The near-real-time update cadence of satellite communications data requires form interactions to support fast refresh of query results. The time span of a single query should not exceed 24 hours, otherwise data loading timeout will be triggered, affecting the real-time push effect of financial marketing activities. Structured fixed fields require form input items to have preset unit suffixes, to avoid user confusion of physical quantity units and ensure data accuracy in subsequent financial links such as risk assessment and business application. Multi-dimensional filter fields require forms to support combined condition configuration, along with real-time verification of the legal range of filter parameters. For example, signal SNR must not be lower than -10dB, to ensure that marketing content is only pushed to terminal users with stable signals. In addition, financial marketing content needs to be associated with terminal data from specific coverage areas, so forms must integrate map point-selection components to limit the geographic scope of queries, preventing invalid content from being pushed to users in signal-free coverage areas.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
searchMaxContext | 8000–12000 characters | The length of a single satellite communications data record is short, and the total context of batch recall needs to adapt to multi-dimensional query requirements, avoiding exceeding the model token limit |
similarityThreshold | 0.72–0.85 | The feature similarity of satellite communications signal and link data is relatively high. A threshold that is too low will introduce invalid matches, while a threshold that is too high will filter out valid abnormal records |
rerankTopN | Top 8–12 results | Satellite communications has many filter dimensions. Retaining Top results after reranking can balance query efficiency and result coverage |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | When batch importing satellite terminal historical data, single file parsing takes a long time, so sufficient processing time needs to be reserved |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Satellite communications batch data files usually contain multiple days of terminal report records, so support for large single-file uploads is required |
queryTimeout | 60 seconds | Near-real-time queries need to return results within a user-acceptable waiting time, and a retry prompt should be provided if a timeout occurs |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: After setting
searchMaxContextto 2000, the results returned by a single query exceed the model token limit, triggering a model error and preventing the generation of personalized financial marketing content. Cause: The context upper limit was not adjusted based on the single-record length of satellite communications data, and the default configuration did not adapt to the recall requirements of batch time-series data, resulting in excessive token consumption. - Phenomenon: The deployed GLM series models cannot be selected in the text extraction module, only GPT series models are displayed, and structured extraction of form content cannot be completed. Cause: The model access endpoint dedicated to text extraction was not configured in FastGPT's model management, only the financial marketing dedicated model for the conversation module was configured.
- Phenomenon: When batch uploading form submission history data of satellite communications terminals, a parsing timeout error is triggered, and knowledge base import cannot be completed. Cause:
PARSE_FILE_TIMEOUT_SECONDSwas set to a value lower than 180 seconds, and no parsing time was reserved for batch financial data.
How to Confirm the Configuration Is Correct
- Submit preset financial marketing filter conditions, such as specifying coverage area and signal threshold, and check whether the field units of the returned results match the preset satellite communications financial terminal data fields.
- Adjust the value of
searchMaxContext, verify whether the token consumption of a single query meets the maximum limit of the model, and ensure that compliant financial marketing content can be generated. - Upload a small-volume form submission test data file, confirm that the number of data entries after parsing is consistent with the source file, and ensure that user behavior data for financial marketing is accurately imported.
- Trigger a near-real-time query, confirm that the result refresh interval meets the preset time range requirements, and ensure that real-time pushed marketing content reaches target users in a timely manner.
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.