What this category of data looks like
Data sources for this category include approved formulation processes, MES electronic batch records, equipment and environmental monitoring data, LIMS systems, and quality management systems. Data is updated for each production batch, key process step execution, and monitoring plan updates. Daily documents include master production files, batch production records, batch packaging records, cleaning records, inspection records, deviation/CAPA/change documents, and batch release review forms. Data fields include material batch numbers, weighing and feeding values, process parameters, deviation descriptions, test results, and other relevant fields. Associated units include kilograms, degrees Celsius, hours, and similar units.
Constraints on multi-turn dialogue and prompt engineering
Each independent production batch requires dialogue context to bind a specified batch identifier, to avoid cross-batch data confusion. Multiple types of professional documents and fields require prompts to clearly limit called document types and field ranges. This ensures returned content matches the compliant format of production ledgers. The data update rhythm tied to steps and batches requires multi-turn dialogue to retain historical interaction records, to support retrospective review. Strict compliance requirements require dialogue tools to verify data source relevance before report generation, to avoid omitting deviation or test records.
Configuration Settings
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| chatId | Bind the unique ID of the current production batch | Isolate dialogue contexts for different batches to prevent data cross-use |
| messages | Use "batch identifier + specified document type + task instruction" as the fixed opening | Standardize input format to ensure the model accurately matches the ledger scope |
| variables | Preset core parameters such as material batch numbers and deviation types | Simplify repetitive input steps for multi-turn dialogue |
| Maximum single reply token count | 8000–12000 token | Adapt to long-text output requirements for single-batch batch record summaries |
| Context retention rounds | Last 3 interactions + full documents for the current batch | Cover historical operations and all associated data required for the current task |
| File upload verification rules | Filter batch record documents by file type | Ensure only compliant production ledger files are imported |
Three Common Configuration Errors
- Symptom: An error "fail to create post presigned url" is displayed when uploading batch record files, and attachment loading cannot be completed. Cause: The signature parameters of the S3 storage configuration have not completed synchronous migration, leading to pre-signed URL generation failure.
- Symptom: Reports generated via multi-turn dialogue do not follow the required format, with missing fields or disorganized structure. Cause: The prompt fails to clearly specify output fields and format constraints, and does not guide the model to adhere to compliant document structures.
- Symptom: Ledger data called during dialogue does not match the current production batch, with incorrect cross-batch content appearing. Cause: The chatId is not bound, or the chatId is not associated with the current production batch, leading to context cross-use of data from different batches.
How to Confirm Successful Configuration
- A test dialogue containing the target production batch identifier is initiated, and returned ledger data is checked to confirm it only associates documents from the specified batch.
- A test batch record file is uploaded, and the system confirms the file loads normally with no format errors.
- A report generation task is triggered, and output content is checked to confirm it matches the preset document structure and field requirements.
- Multi-turn interaction context retention is tested, and historical dialogue parameters and instructions are confirmed to be correctly invoked.
The values provided here are common starting points, and should be measured against the reader's own samples.