Reference only; verify against the target FastGPT release and deployment documentation.
What this category's data looks like
Data for communication towers and infrastructure comes from operation and maintenance logs, local communications administration bureau filing databases, and daily inspection reporting systems. Filing data updates once per month. Operation and maintenance inspection data syncs daily. Fault alarm data is accessed in real time.
Documents use structured JSON format. Each entry includes fields such as unique site code, longitude and latitude (decimal degrees, retained to 6 decimal places), tower height (meters), supported frequency band (MHz), last inspection date, and current operating status. All fields have clear units and business definitions.
What constraints do these characteristics impose on the multi-turn dialogue and prompt engineering link
The multi-timeliness dimension of the data requires multi-turn dialogue to distinguish the call priority of different data. Prompts must explicitly prioritize real-time alarm and same-day inspection data, with old filing data only used as supplementary reference.
Fields with units require prompts to strictly retain units in output to avoid parameter confusion. The unique site code requires multi-turn dialogue to bind unique identifiers to avoid cross-interference of consultation contexts from different sites.
The structured field structure requires prompts to guide users to input clear site codes, otherwise accurate recall of corresponding data is impossible. It also requires limiting the context length to avoid redundant data interfering with core information extraction.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | { "target_site_code": "", "consult_scene": "standard" } | Binds the site code and consultation scene to allow prompts to accurately match structured data for this category |
messages | First 10 turns of dialogue context | Consultations for communication towers often involve multi-dimensional questions for a single site; retaining 10 turns covers complete consultation workflows |
chatId | Unique identifier automatically generated when a session is created | Associates multi-turn consultations from the same user, avoiding confusion between consultation contexts of different sites |
| Maximum context length | 800–1200 characters | Communication tower data fields are concise; overly long contexts will interfere with prompt extraction of core information |
| Prompt template | Calibrated based on actual testing | Adapts to exclusive prompt requirements for different scenarios such as fault troubleshooting, filing queries, and operation and maintenance consultation |
Three common mistakes
- Symptom: The AI dialogue node returns an empty string, triggering the
chat:LLM_model_response_emptyerror. Cause: The prompt fails to correctly bind the target site code invariables, resulting in inability to recall structured data for this category. - Symptom: Unclosed half-width quotation marks appear at the end of output content, followed by automatic completion to standard quotation marks. Cause: The prompt fails to clearly restrict output punctuation format, and does not require the use of full-width quotation marks or unified output specifications.
- Symptom: Global variables in the workflow do not take effect, and the prompt cannot obtain the specified site parameters. Cause: The
variablesand session input parameters are not correctly associated in the workflow node, resulting in failed variable transfer.
How to confirm the configuration is correct
- Initiate a consultation for a known communication tower site, check if the context retains the previously entered site code, and confirm that
chatIdis correctly associated with the current session. - Trigger a large model call, check if the returned result includes parameters with units such as tower height and frequency band, to confirm that the prompt's format constraints are in effect.
- Simulate consecutive consultations for two different sites, check if the contexts of the two sessions are independent, to confirm that the context truncation logic for
messagesis correct. - View the workflow run logs to confirm that the site code and consultation scene parameters in
variablesare correctly passed to the prompt.
The values provided here are common starting points and should be evaluated 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.