What Data for This Category Looks Like
Infrastructure engineering research report data mainly comes from industry association public reports, engineering bidding announcements, cost indicators released by local housing and urban-rural development departments, and internal research documents from leading engineering enterprises. Update rhythm adjusts with project milestones: bidding data updates in real time, while industry special research reports are released quarterly. Document structure includes fields such as project initiation approval, investment budget estimates, material consumption quotas, construction progress plans, and cost details. Most units use standard engineering measurement units including ten thousand yuan, cubic meters, construction days, and square meters.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The multi-source heterogeneous data feature of infrastructure engineering research reports requires multi-turn dialogue to support filtering retrieval scope by data source type. This prevents mixing real-time bidding data with quarterly research reports. Documents contain multiple types of engineering measurement fields. Prompts must clearly define retrieved field dimensions to stop the model from mixing numerical results with different units. The dynamic update attribute linked to project milestones requires multi-turn dialogue context to retain the currently discussed project identifier. This avoids data misalignment across retrieval rounds.
Configuration Settings
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
maxContext | 8000–12000 characters | Individual infrastructure research report documents are lengthy, and multi-turn dialogue needs to retain project keywords and parameter requirements from multiple interaction rounds |
Recall Count | Top 10–15 entries | Infrastructure research reports contain multiple segmented fields, sufficient recall volume can cover retrieval needs across different dimensions |
Similarity Threshold | 0.75–0.85 | Infrastructure engineering data contains many professional terms, requiring a balance between retrieval accuracy and recall coverage |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Individual infrastructure research report documents have large file sizes, leading to longer parsing time |
Reranked Return Count | Top 5–8 entries | The most relevant research report fragments must be retained to supplement context for multi-turn dialogue |
Knowledge Base Chunk Length | 800–1000 characters | Professional paragraphs in infrastructure research reports are lengthy; overly long chunks harm recall accuracy, while overly short chunks break professional term associations |
The parameter values provided on this page are general recommendations used as a starting point for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Errors
- Phenomenon: After calling the API to initiate a dialogue, the generated reply does not associate with infrastructure research report content in the knowledge base. Cause: The prompt fails to clearly specify the retrieval scope for infrastructure engineering documents, or the knowledge base association trigger rules are not configured correctly.
- Phenomenon: When running the AI dialogue component in a private deployment environment, an uncaught exception pop-up appears. Cause: The
FASTGPT_API_KEYor knowledge base association parameters in the configuration file are filled incorrectly, and do not match the actual configuration of the deployment environment. - Phenomenon: When using the platform interface of version 4.8.20, the dialogue page or knowledge base page crashes. Cause: This version has a memory overflow issue related to long document parsing, and the large file size of individual infrastructure research reports easily triggers this exception.
How to Confirm Configuration Is Complete
- Initiate a single-turn dialogue test, input a specific question related to infrastructure engineering, and verify whether the returned results include research report fields and corresponding data in the knowledge base.
- Initiate multiple consecutive dialogue rounds, gradually adjust retrieval keywords, and confirm that the project information associated with the context is not lost, and the retrieval scope always matches the currently discussed infrastructure project.
- Upload a single large-volume infrastructure research report, check whether the parsing task is completed within the set timeout period, and there are no parsing failure errors.
- Call the API interface to initiate a dialogue, and verify whether the returned results include content related to the preset retrieval scope and field requirements.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.