What this category’s data looks like
Survey and design work consulting and response data mainly comes from project survey reports, construction drawing design documents, industry specification clauses, project ledgers, and other sources. Data update frequency changes with project phases: weekly updates during the preliminary design phase, and daily updates during the construction drawing design phase. Document structures include long text paragraphs, professional tables, and drawing annotation text. Fields include project number, survey point coordinates, design load, specification number, and more. Units include millimeters, megapascals, cubic meters, and other professional engineering units.
Constraints these characteristics impose on model access and configuration
The long text and professional attributes of survey and design data require sufficient context capacity when connecting the model, to avoid truncating professional logic. The accuracy requirements for professional fields and units require adding targeted system prompts in the model configuration, to ensure output content complies with engineering specifications. The high-frequency update feature of data requires the model configuration’s knowledge base synchronization mechanism and update rhythm to match, to avoid returning outdated content. The presence of drawing annotation text requires enabling visual processing capabilities to adapt to the parsing needs of multimodal data.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Survey and design documents often contain long paragraphs of specification clauses and drawing descriptions, requiring sufficient context to maintain professional logic coherence |
maxTokens | 2000–3000 token | Consulting response work requires complete output of professional solutions, avoiding truncation of key parameters and specification references |
quoteMaxToken | 1500 token | Accurate reference to specific fields in survey reports and design documents is required, limiting the length of single references to ensure reference accuracy |
temperature | 0.1–0.3 | Professional consulting requires strict answers, avoiding randomly divergent generated content |
vision | Enabled | Some survey and design documents contain drawing annotation text, requiring visual processing capabilities to recognize text information in drawings |
AIPROXY_API_ENDPOINT | Fill in according to the deployment environment | Adapt to model access paths for local or cloud deployments, ensuring model call connectivity |
Three common configuration errors
- Phenomenon: When calling a locally deployed model, custom professional system prompts do not take effect, and the returned content does not include expected engineering specification constraints. Cause: No targeted constraints are added to the system prompt module in the model access configuration, and the prompt mounting position does not comply with FastGPT configuration rules.
- Phenomenon: After configuring domain name access, the model configuration page displays as empty, and knowledge base data is inconsistent with that accessed via IP. Cause: The API proxy endpoint corresponding to the domain name is not correctly configured, causing domain name requests to fail to connect to the locally deployed model service.
- Phenomenon: After enabling the image recognition function, annotation text in survey drawings cannot be parsed. Cause: The
visionconfiguration item is not enabled, or the model backend adapted to multimodal tasks is not selected.
How to confirm the configuration is complete
- Submit a consulting query containing professional terms, and check whether the model's returned content includes accurate survey and design professional terms and specification references.
- View the model call log to confirm that the actual call values of configuration items such as
maxContextandmaxTokensmatch the configured values. - Test both domain name and IP access methods to confirm that model configuration items and knowledge base data are synchronized and consistent.
- Upload a survey drawing with text annotations, and check whether the model can correctly recognize the annotation information in the drawing.
The values provided are common starting points and should be measured 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.