What the data for this category looks like
Data related to communication equipment revenue covers mainstream categories including base stations, optical modules, communication terminals, and others. Sources include vendor unit price ledgers, public industry bidding quotes, public market price APIs, and core component market quotes. Data updates are divided into two types: daily report data is fully updated at fixed times each day, while real-time market data is refreshed at fixed intervals. The document structure combines structured fields and unstructured notes. Structured fields include device model, affiliated category, current quote, cost benchmark, and market change value, with corresponding units of yuan per unit, category classification, yuan per unit, yuan per unit, and point. Unstructured fields include temporary price adjustment notices, winning bid project notes, and more. The length of individual data entries varies widely.
What constraints these characteristics impose on multi-turn dialogue and prompting
Data sources for the communication equipment category are scattered and the structure is mixed. Multi-turn dialogue must explicitly specify the device sub-category to be processed before each call to avoid confusion across category data. Real-time market data is refreshed at fixed intervals, so multi-turn dialogue must set a fixed context refresh timing to prevent the use of expired market data. The length of individual data entries varies widely, so the prompt must adapt to input content of different lengths, while limiting the maximum character count of the context window to avoid exceeding the model's processing limits. Structured and unstructured fields coexist, so the prompt must explicitly require the model to first extract structured field content, then integrate unstructured notes, to avoid chaotic output logic.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | The length of individual communication equipment data entries varies widely. This range covers most single-round input lengths while adapting to the context processing limits of general large models |
contextRefreshInterval | 300 seconds | Real-time market data is refreshed at fixed intervals. This interval ensures that market data used in conversations remains synchronized with public data sources |
PROMPT_TEMPLATE | Fixed specification: "Only process revenue rate and market trend data for the communication equipment category, first extract structured fields, then integrate unstructured notes" | Data contains both structured and unstructured fields. A clear template prevents the model from confusing data from other categories |
UPLOAD_FILE_MAX_SIZE | 100 MB | Communication equipment price ledgers and bidding documents are usually batch structured tables. This size covers most upload requirements |
maxHistoryTurns | First 3 turns | Early category specification information can be reused in subsequent conversations. Excessive turns increase context redundancy and reduce model response efficiency |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large equipment bidding documents contain many entries. This duration ensures complete parsing of all content |
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 specific analysis, and it is recommended to test on independent samples before finalizing settings.
Three Common Mistakes
- Phenomenon: After uploading a communication equipment-related price ledger file via the dialogue interface, no parsing result is returned and no error logs appear in the background. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration was not adjusted to match the document size, or the structured table parsing switch was not enabled, causing the file to not be correctly identified. - Phenomenon: After calling the API to stop the current dialogue, the model continues to generate content. Cause: The
conversation_stop_triggerparameter was not configured correctly, or the correct session identifier was not included in the API call, causing the stop command to not be received by the system. - Phenomenon: Results from multiple AI dialogue nodes in a workflow are all displayed, instead of only retaining the output of the last node. Cause: No result truncation configuration was added to the workflow, or the
workflow_output_filterparameter was not set to only retain the content of the last node, causing redundant results to be output.
How to Verify Proper Configuration
- Upload a standard communication equipment price document, check that the parsing result includes preset structured fields such as device model and quote, and confirm that the parsing configuration matches the file size.
- Initiate more than two rounds of dialogue, specify different communication equipment sub-categories in sequence, check that the model always focuses on the currently specified category, and confirm that the context refresh and history turn configurations are effective.
- Call the stop dialogue API, check that the model immediately terminates the current generation process, and confirm that the session identifier and stop trigger parameters are configured correctly.
- Run a workflow containing multiple AI dialogue nodes, check that the final output only retains the content of the last node, and confirm that the workflow output filter configuration is correct.
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.