What this category of data looks like
Satellite communications investment research data primarily comes from publicly available orbital parameter documents from satellite operators, ground station network monitoring reports, and communication frequency allocation documents released by industry regulators. Update cycles include quarterly updates for orbital position parameters, monthly updates for payload operation data, and real-time updates for link status logs. Document structures include structured Excel spreadsheets (with fields such as orbital inclination, downlink frequency), industry analysis whitepapers in PDF format, and real-time link data in structured JSON format. Field units include degrees (orbital inclination), GHz (downlink frequency), MHz (communication bandwidth), square kilometers (coverage area), and some documents include both coordinate fields and administrative region mapping fields.
What constraints these characteristics impose on multi-turn dialogue and prompting workflows
Structured multi-field tabular data requires multi-turn dialogue to accurately match field dimensions, avoiding generalized responses. Frequently updated real-time data requires prompts to specify prioritizing recall of newly uploaded knowledge base entries, to avoid using outdated data. Long documents and multi-field combinations create contextual redundancy, so the number of recalled entries per round must be limited to prevent the model from confusing parameters of different satellites. Fields with unified units require prompts to clearly mark units, avoiding missing or confused units in responses. Multi-turn context must retain the satellite identifiers specified by the user, to ensure accurate parameter association during consecutive questions.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Satellite communications investment research documents are mostly structured tables paired with long text; overly long contexts will interfere with accurate recall |
RECALL_TOP_K | Top 6–8 entries | A single satellite parameter document contains multiple types of fields; enough entries must be recalled to cover different dimensions of user questions |
SIMILARITY_THRESHOLD | 0.75–0.85 | Satellite parameter fields have high similarity; low-match redundant data must be filtered to avoid confusing parameters of different satellites |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large satellite orbital Excel files contain tens of thousands of entries, resulting in long parsing times |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Bulk orbital data files in the satellite communications industry are large in size, requiring support for large file uploads |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and testing against local samples before finalizing settings is recommended.
Three common mistakes
- Symptom: The system reports that the uploaded XLSX file cannot be read. Cause: The
PARSE_EXCEL_ENABLEconfiguration item is not enabled, or the uploaded file exceeds theUPLOAD_FILE_MAX_SIZElimit. - Symptom: After multiple consecutive questions, the model confuses the orbital parameters of different satellites. Cause: The
maxContextvalue is insufficient, failing to retain sufficient contextual memory, or theRECALL_TOP_Kvalue is too high, leading to overly mixed recalled entries. - Symptom: The response does not include parameter units, only returning pure numerical values. Cause: The prompt does not explicitly require marking field units, or the parsed document fragments do not carry unit information.
How to confirm the configuration is correct
- Upload an XLSX file containing orbital inclination and downlink frequency fields, initiate a query asking "What is the downlink frequency of XX satellite", and confirm the model returns the corresponding parameters and units.
- Initiate three consecutive rounds of parameter queries for different satellites, and confirm the model can distinguish the corresponding data of different satellites without parameter confusion.
- Upload a satellite industry whitepaper PDF larger than 100 MB, initiate a query related to long text, and confirm the parsing and recall processes complete normally.
- View the knowledge base parsing logs to confirm all fields of the XLSX file are correctly extracted, with no records of field loss or parsing failure.
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.