What the data for this category looks like
The data sources for building engineering general contracting service consultation include official approval guidelines published by housing and urban-rural development authorities, internal enterprise project archives, construction logs and acceptance documents. Data update rhythm follows project milestones: update approval materials and handling requirements during the project approval stage, and update progress-related consultation content during the construction stage. The document structure includes structured approval forms, unstructured construction specifications and frequently asked questions. Fields cover project number, approval item name, handling time limit, required material list and other items. Units include standard engineering industry units such as working days, copies, square meters.
What constraints do these characteristics impose on deployment and upgrade
The service consultation data for building engineering general contracting is multi-source and heterogeneous, scattered across external public documents and internal project archives. During deployment, multi-data source adaptation capabilities must be configured. The rhythm of updates following project milestones requires that upgrades support adjusting data synchronization frequency according to project cycles, to avoid excessive resource occupation from full synchronization. Coexistence of structured approval forms and unstructured construction specifications requires distinguishing retrieval and chunking rules for different data types during deployment. Fields such as project-specific handling time limits and material lists require configuring association logic that filters search results by project identifier, to ensure consultation replies match the specific requirements of the corresponding project.
How to configure
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://fastgpt:xxx@mongodb-host:27017/fangjian?authSource=admin | Stores structured data such as project approval forms and historical consultation records, requires specifying the corresponding business database |
PG_URL | postgresql://postgres:xxx@pg-host:5432/fastgpt?search_path=fbzg | Stores unstructured associated data such as construction specifications and Q&A classification tags, matches the schema naming for building engineering business |
REDIS_URL | redis://:redis-pass@redis-host:6379/1 | Caches high-frequency consultation replies, uses database 1 to isolate business data |
DB_MAX_LINK | 8–12 connections | Adapts to the consultation access pressure of multiple parallel building engineering projects, avoids connection pool exhaustion |
STORAGE_S3_ENDPOINT | https://s3-enterprise.com | Connects to the enterprise's internal object storage for storing consultation attachments and document chunks |
FE_DOMAIN | https://fbzg-fastgpt.xxx.com | Configures the frontend access domain name for generating valid consultation interaction links |
Three common misconfigurations
- Symptom: The login-free consultation window cannot verify user identities, and submitted consultations are not associated with the corresponding building engineering project. Cause: The deployed FastGPT version does not integrate project-level identity verification functions, upgrade to v4.17.0 or later is required.
- Symptom: Question classification results across multiple knowledge bases always match the default fallback category, and cannot be associated with historical context records. Cause: Retrieval filtering rules based on project fields are not configured, causing the classification model to only read the current question text without associating historical consultation content of the project.
- Symptom: FastGPT deployed locally via Docker cannot be called via third-party platforms, and the interface returns a 403 status code. Cause:
FE_DOMAINis not correctly configured as the access domain name allowed by the third-party platform, resulting in cross-origin request interception.
How to verify successful configuration
- The FastGPT backend is accessed, and the data source management page is navigated to. Connection test results for
MONGODB_URIandPG_URLare reviewed, and normal status is confirmed. - A test consultation is submitted, the Redis cache page is reviewed, a corresponding cache record is confirmed to be generated, and the
REDIS_URLcaching function is verified to operate correctly. - A building engineering construction specification document is uploaded, keyword retrieval is performed, matching content fragments are confirmed to be returned, and the storage and retrieval logic of
STORAGE_S3_ENDPOINTis verified to operate correctly. - System operation logs are reviewed, exhaustion alerts for the
DB_MAX_LINKconnection count are confirmed to be absent, and the connection pool configuration is verified to take effect.
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.