What this category's data looks like
Data sources for this category include purchase orders, drawings and specifications, supplier quality certificates, inspection equipment, historical quality data, and supplier portals. Daily processed documents cover inspection specifications, sampling plans, incoming material reports, supplier audit reports, exception contact sheets, 8D reports, and concession acceptance approval forms. Data updates are triggered by each batch of incoming material inspection, monthly or quarterly supplier evaluations, and ad-hoc special audits. Document structure includes fields such as batch number, inspection items, judgment results, and supplier information. There is no unified fixed unit, and it adjusts dynamically based on the specific inspection type.
What constraints do these characteristics impose on deployment and upgrade
This category has scattered data sources and fluctuating update rhythms. Deployment must adapt to multi-source data access configuration, and support integration with supplier portals and inspection equipment interfaces. Flexible space for document parsing and field mapping configuration must be reserved to accommodate diverse document types and non-fixed field formats. Data is associated with batches, suppliers, and inspection results. Association storage index rules must be configured during deployment to ensure accurate querying. Custom incremental sync trigger cycles must be supported to adapt to different update frequencies such as per-batch incoming material and quarterly evaluations, avoiding excessive system resource usage from full syncs. Strict permission isolation rules must be configured during deployment, as quality data involves production risks, to distinguish access scopes for different roles.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://iqc_user:secure_pass@db-host:27017/fastgpt_iqc?authSource=admin | Stores multiple types of business documents including batch incoming material inspection reports and supplier audit reports, requires a dedicated database instance to ensure high-concurrency read/write performance |
REDIS_URL | redis://iqc_cache:secure_redis_pass@redis-host:6379/1 | Caches frequently accessed data such as batch inspection results and supplier qualification information to reduce database query latency |
DB_MAX_LINK | 20–30 | Adapts to the concurrent connection requirements of batch data import for each incoming material batch, avoids deployment failures caused by exhausted connections |
FE_DOMAIN | https://quality-check.your-enterprise.com | Configures the frontend domain name accessed by inspectors, binds the enterprise's internal SSL certificate to ensure secure transmission of inspection data |
ROOT_KEY | 32-bit random string generated according to enterprise security policies | Configures the system's highest permission key, used to initialize the administrator account and ensure initial access security |
STORAGE_S3_ENDPOINT | https://s3-cn-beijing.aliyuncs.com | Stores large files such as raw data exported by inspection equipment and 8D reports, adapts to the enterprise's existing cloud storage service |
Three common misconfigurations
- Symptom: Unable to retrieve the initial administrator account when logging into the system for the first time, with an invalid username or password prompt. Cause:
ROOT_KEYwas not properly generated and configured, causing the initial administrator credentials to not be correctly written to the database. - Symptom: When configuring a DingTalk robot to push inspection results, the published application prompts "message receiving address verification failed". Cause:
FE_DOMAINwas not configured as a valid publicly accessible address, or SSL certificate verification rules were not correctly configured during deployment. - Symptom: After importing a PDF file of a supplier audit report, the parsed result lacks core fields such as inspection items and batch number. Cause: A custom parsing template was not configured for the fixed fields of incoming material inspection documents, and the general parsing rules cannot match the structure of business documents.
How to confirm successful configuration
- Run the FastGPT v4.17.0 initial administrator account initialization script, verify that the system can be successfully logged in using the corresponding credentials.
- Import a standard incoming material inspection report, check whether the parsed document result includes the core fields required for the business.
- Configure a test supplier data entry, trigger an incremental sync task, verify that the data is successfully written to the database and can be queried via the frontend interface.
- Call the large model to generate a preliminary analysis of an exception contact sheet, verify that the interface call returns no errors and the returned content conforms to inspection business logic.
The values provided are common starting points and should be measured against the reader's own samples.