What Data for This Category Looks Like
Survey and design data primarily comes from project survey reports, official design drawings, change negotiation records, submission and approval documents, and similar official documents. Data updates follow project progress, with synchronized updates after each phase’s deliverables are finalized. Each document includes fields such as project-specific ID, professional chapter divisions, core parameter indicators, approval node records, and similar similar fields. Units include millimeters, megapascals, cubic meters, square meters, and other standard engineering units used in the survey and design industry. Different disciplines such as geotechnical, structural, and mechanical and electrical have distinct field structures for their documents.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
The multi-disciplinary segmentation and project-specific nature of survey and design data requires that multi-turn conversations strictly bind context at the project level, to avoid mixing content across different projects. Documents are lengthy and dense with professional terminology, so prompts must clearly define the response scope to prevent retrieving irrelevant professional documents. Data updates dynamically alongside project progress, so prompts must guide the model to prioritize calling the latest version of documents, to avoid citing outdated content. Multi-turn consultations often involve change tracing, so key node information from previous conversations must be retained to ensure context coherence.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Context Window Size | 8000–12000 token | Adapts to the length of single survey and design documents, avoiding truncation of core professional parameter content |
chatId | Enable and bind to project-specific ID | Differentiates conversation histories for different survey and design projects, preventing cross-project context confusion |
| Prompt Template | Must include "Answer solely based on the current project’s survey and design documents, prioritize content matching the corresponding project ID" | Matches the project-specific data characteristics, limits the response scope |
| Retrieval Top K | Top 6 | Balances retrieval precision and response completeness, adapting to the multi-chapter structure of professional documents |
variables | Pre-set project ID and professional type variables | Enables dynamic prompt matching, reducing manual adjustment workload |
messages | Retain the last 10 rounds of conversation context | Adapts to multi-turn change consultation context needs, ensuring key node information is not lost |
Three Common Misconfigurations
- The symptom is retrieving non-target project survey and design documents. The cause is failure to bind the dedicated
chatIdor failure to explicitly specify the project ID in the prompt, leading to cross-project context confusion. - The symptom is custom prompt templates failing to load or not taking effect after adjustment. The cause is using a FastGPT version lower than v4.17.0; versions prior to v4.17.0 only support basic parameter adjustments.
- The symptom is survey data returned by tool calls not being referenceable in subsequent conversations. The cause is failure to pass tool-returned parameters via the
variablesconfiguration, leading to lost context.
How to Verify Correct Configuration
- Initiate a consultation that includes a project ID, check if the returned results only reference documents related to the corresponding project’s survey and design work.
- View conversation logs, confirm that the
chatIdfield is correctly populated and matches the current project’s dedicated ID. - Adjust the prompt’s variable parameters, verify that the response automatically uses the pre-set project professional type content.
- Initiate consecutive multi-turn consultations, check if design parameters or change content mentioned in earlier conversations are correctly referenced.
The values provided here are common starting points, and should be evaluated against the reader’s own specific 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.