Handling Consultation and Response for Urban Investment Platforms: Multi-turn Dialogue and Prompt Engineering

Handling Consultation and Response for Urban Investment Platforms: Multi-turn Dialogue and Prompt Engineering This document is written based on FastGPT v4.17.0.

Reference only; verify against the target FastGPT release and deployment documentation.

What Data for This Category Looks Like

Consultation data for urban investment platforms mainly comes from public service guidelines, project operation ledgers, government public service item lists, and historical user consultation records. The data update rhythm varies by item type. Project progress data is updated monthly. Policy data is synchronized quarterly. Service guidelines are adjusted according to local government service requirements. Most documents use structured formats, containing fields such as item code, handling entity, handling time limit, application material list, and consultation contact information. Units mostly adopt general government service standards such as working days, copies, and yuan.

What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering

The clear fields of structured data require prompts for multi-turn dialogue to fixedly extract core fields such as item code and handling entity to avoid vague responses. The difference in update rhythms of different data types requires prompts to prioritize calling recently updated policy data and filter out expired items. In cross-item consultation scenarios, multi-turn dialogue retains the item identifiers mentioned by users through the messages context to reduce repeated inquiries. The fields in historical user consultation records must match the current dialogue’s item type. Otherwise, response content will deviate from service requirements.

How to Configure Settings

Configuration ItemRecommended SettingRationale
Maximum Context LengthFirst 8 turns of dialogue + 1200 characters of knowledge base contentUrban investment platform service consultations mostly follow single-item, multi-step processes. 8 turns cover complete dialogue logic, and 1200 characters can hold core service guideline text
Dialogue Retention Period30 daysMost urban investment platform user service cycles range from 15 to 30 days. 30 days covers traceability needs for complete processes
Knowledge Base Permission ControlBind corresponding knowledge bases by item categoryData permission differences across urban investment platform items are significant. Category binding prevents unauthorized access
Prompt Variable BindingBind item code fields via variablesStructured data requires clear field matching to avoid confusing different service items in responses
Dialogue Log RetrievalRetrieve by chatIdUrban investment platforms mostly aggregate service consultation records by conversation ID. Retrieving by chatId allows quick location of a single user’s complete dialogue chain
Retrieval Matching Threshold0.75–0.85Service guideline text requires high similarity matching. This range filters irrelevant content while retaining core information

Three Common Misconfigurations

  • Symptom: Dialogue logs are empty or only retain content for 1 day. Cause: The dialogue retention period parameter was not configured correctly, and the default value does not adapt to the traceability needs of urban investment platform service processes.
  • Symptom: Response content includes expired service policies. Cause: The prompt did not prioritize calling recently updated knowledge base data, and outdated service guideline content was used by mistake.
  • Symptom: When a user consults across items, the response confuses the application materials of different items. Cause: Multi-turn dialogue did not retain the item identifiers mentioned by the user through the messages context, leading to matching incorrect knowledge base content.

How to Verify Proper Configuration

  • Initiate a multi-turn consultation for a single item, and check whether the dialogue context retains the previously mentioned item code and handling requirements.
  • View the dialogue log storage path, and confirm that logs are aggregated according to the preset classification rules.
  • Test cross-item consultation, and check whether the response matches the current consultation’s item type and does not associate irrelevant knowledge base content.
  • Modify the dialogue retention period configuration, and verify whether the log retention duration matches the configured value.

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.