Service Consultation and Response for Investment Project Approval and Post-Evaluation: Multi-turn Dialogue and Prompt Engineering

Service Consultation and Response for Investment Project Approval and Post-Evaluation: Multi-turn Dialogue and Prompt Engineering

What Data for This Category Includes

Data for this category comes from State-owned Assets Supervision and Administration Commission investment supervision systems, enterprise ERP and project management systems, industry market data, audit and financial statements. Update frequency is quarterly. Daily documents include annual investment plans, project proposals, feasibility study reports, due diligence reports, asset evaluation reports, and post-investment evaluation reports. Data fields include project unique identifiers, investment scale, approval nodes, core post-evaluation indicators, and more. Documents are archived across three stages of the full project lifecycle: approval preparation, implementation, and post-evaluation.

Constraints Imposed on Multi-turn Dialogue and Prompt Engineering

Data sources span multiple systems, with inconsistent field calibers. Teams use multi-turn dialogue to gradually align field formats and units across systems. Quarterly updated datasets require regular context refreshes to prevent use of outdated project data. The stage-based document archive structure requires prompts to guide users to provide materials for the relevant project phase. Business involving state-owned assets requires retaining full dialogue context for regulatory traceability. For scenarios with multiple parallel projects, unique identifiers distinguish conversation contexts to avoid cross-project confusion.

Configuration Settings

Configuration ItemRecommended ApproachRationale
Maximum context lengthFirst 8000–12000 charactersMatches total length of single-project documents archived in one quarter, avoids truncating critical approval and post-evaluation materials
chatId binding ruleBind to project unique identifiersEnsures multi-turn dialogue context for the same project is not confused, adapts to cross-departmental collaborative dialogue scenarios
Question optimization switchEnable and limit to state-owned asset investment scenariosAutomatically optimizes prompts for investment project professional terms, improves accuracy of consultations on feasibility studies and post-evaluations
variables initialization configurationPreset project type and affiliated supervision level variablesQuickly aligns with field specifications from state-owned asset supervision systems, reduces repeated confirmations during multi-turn dialogue
Single tool call limitTop 3 recall resultsMatches scale of quarterly updated datasets, avoids excessive redundant information interfering with dialogue logic

Three Common Misconfigurations

  • Tool call results are not displayed in the dialogue interface. Results can only be viewed after re-entering the session, but are not returned with dialogue responses. The cause is that chatId is not bound to the current tool call's conversation context, so results are not attached to the correct dialogue chain.
  • Frequent Request Time errors occur during dialogue. The cause is that the context length of a single call exceeds the system's processing limit, and parameters have not been adjusted to match the scale of quarterly archived documents.
  • No messages parameter content is retrieved for the dialogue, making cross-session data synchronization impossible. The cause is that storage and extraction rules for messages have not been correctly configured, resulting in missing parameters.

How to Verify Successful Configuration

  • Initiate a multi-turn consultation for a single project's approval preparation. Check if the context includes document fragments from the corresponding phase, and confirm that the project identifier bound to chatId matches the current session.
  • Trigger a tool call. Check if the dialogue interface returns fragments of the corresponding feasibility study report or post-evaluation report, and confirm that the number of single call results matches the preset limit.
  • When calling a locally deployed large model, verify that no timeout errors occur during the dialogue. Confirm that the context length matches the actual scale of the current project's documents.
  • Check if the language of the iframe-integrated interface is Chinese, confirming that the localized configuration has taken effect.

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

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.