What Data for This Category Looks Like
Data related to processes and exceptions for pharmaceutical preparations production comes from approved formulation processes, material batch information, MES electronic batch records, equipment and environmental monitoring data, LIMS test results, and quality management system records. Data update frequency follows every production batch, each critical process step, and as per established monitoring plans. Daily documents include master production files, batch production records, batch packaging records, cleaning records, test records, deviation/CAPA/change documents, and batch release review forms. Fields include material batch numbers, process parameter values, deviation descriptions, test results and release status. Units include degrees Celsius, hours, batch numbers and other standardized production parameters.
What Constraints These Characteristics Impose on Deployment and Upgrade
The characteristics of process and exception data for pharmaceutical preparations production impose clear constraints on FastGPT deployment and upgrade. Multiple heterogeneous data sources require configuring multiple database and system connection parameters during deployment, to ensure data synchronization accuracy and real-time performance. High-frequency batch-wise updates require sufficient concurrent connections and storage capacity to avoid data backlog. Fixed GMP document structures and field requirements need preset parsing rules during deployment, to ensure generated process documents and exception reports meet compliance requirements. Production data abnormalities may lead to serious consequences, so a complete failure retry and alert mechanism must be configured during deployment to ensure system stability. FastGPT v4.17.0 includes optimizations for multi-data source connection and compliance document parsing, which can meet the deployment needs of this category.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 10–15 个 | Address concurrent connection requirements for multi-system data synchronization, matching multi-data source calls per production batch |
MONGODB_URI | 按企业LIMS与质量管理系统的部署地址填写 | Store unstructured documents such as batch records and deviation reports, meeting GMP-compliant document retention requirements |
PG_URL | 按企业MES系统的数据库地址填写 | Store structured production data such as process parameters and material batches, ensuring data query efficiency |
REDIS_URL | 按企业内部缓存服务地址填写 | Cache frequently called process templates and release rules to shorten the response time for exception report drafting |
STORAGE_S3_ENDPOINT | 按企业合规存储服务地址填写 | Retain complete electronic batch records and cleaning records to meet data traceability requirements |
FILE_TOKEN_KEY | 按实测标定 | Ensure permission security for file upload and parsing, adapting to document access control under GMP |
Three Common Misconfigurations
- Phenomenon: After deployment, when calling the MCP service, the parameter type of custom fields is fixed to string. Cause: No corresponding field type mapping rule was added in the configuration, and the fixed field format requirements in GMP documents were not matched.
- Phenomenon: After uploading a batch production record file, the system displays parsing timeout and request failure. Cause: The
REDIS_URLconfiguration is incorrect, causing the cache service to fail to work properly, unable to quickly load predefined process templates, and extending file parsing time. - Phenomenon: The content of the inference-generated exception report is incomplete and fails to cover associated equipment monitoring and test data. Cause: The
DB_MAX_LINKconfiguration value is too low, causing the system to fail to pull all associated production data, and the context length is insufficient to support complete content generation.
How to Verify Proper Configuration
- Test the connections for
MONGODB_URIandPG_URL, verify that structured process data and unstructured batch record files from historical batches can be pulled. - Upload a simulated deviation report file, confirm that parsing time meets the expected requirements of production rhythm.
- Call the MCP service, verify that the parameter type of custom fields can be dynamically adjusted according to document fields, and is not fixed to string.
- Check system operation logs, confirm that the concurrent connection count of
DB_MAX_LINKdoes not trigger upper limit alerts.
The values provided are common starting points and should be measured against the reader's own samples.