What This Category’s Data Includes
Data for this category comes from cell banks and master seeds, process analytics systems, cleanroom monitoring, Manufacturing Execution Systems (MES), Laboratory Information Management Systems (LIMS), and equipment integrity testing. Daily documents include cell bank or master seed batch records, culture and purification records, aseptic filling records, environmental monitoring data, media fill simulation results, sterility test reports, and batch release documentation. Data is updated per batch, in real time, or per established monitoring schedules. Document fields include batch identifiers, critical process parameters, environmental monitoring readings, test results, and other relevant fields. Associated units of measurement include degrees Celsius, hours, colony-forming units per plate, and other standard units.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering for This Category
This category’s data is multi-source and updated per batch, in real time, or per scheduled plans. Multi-turn dialogue must strictly retain context tied to the current batch to avoid mixing data across batches. Prompts must explicitly limit calls to only cell bank records, process parameters, environmental monitoring data, and test results associated with the current batch, to prevent introduction of irrelevant batch information. Critical parameters and environmental data for aseptic manufacturing directly impact product safety. Context passing for multi-turn dialogue must have controlled scope to avoid accidental calls to unrelated fields. Drafting exception reports requires integrating three categories of multi-dimensional data: environmental, process, and test data. Prompts must guide association with these data points to ensure all necessary judgment bases are covered.
Configuration Settings
These configurations are optimized for FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Context Window | Retain current batch conversation history in messages + bound batch-associated documents | This category requires strict separation of batch contexts to avoid interference from cross-batch data |
| Variable Binding | Link to the variables field for the current batch | Ensures prompts call only process and monitoring data exclusive to the current batch |
| Conversation Identifier Binding | Associate batch numbers via chatId | Prevents cross-interference of conversation history across different batches |
| Prompt Trigger Condition | Activate only when current batch data is submitted | Prevents premature calls to documents and data from unrelated batches |
| Maximum Output Length | 1200–1800 characters | Covers standard drafting length for process documents and exception reports |
| Retrieved Document Limit | Top 5 entries | Ensures necessary data is covered while avoiding interference from redundant information |
Three Common Configuration Mistakes
- Issue: After calling the knowledge base to associate current batch data, the AI’s response is unrelated to the current process or exception issue, and instead references document content from other batches. Cause: The current batch context is not strictly bound via
chatIdorvariables, leading to retrieval of irrelevant cross-batch data. - Issue: In multi-turn dialogue, subsequent AI responses do not reference previously mentioned current batch process parameters, and the generated content lacks necessary associated basis. Cause: The context window is not configured correctly, and batch-associated conversation history in
messagesis not retained. - Issue: Prompts do not explicitly limit data scope. When drafting exception reports, the AI introduces content outside the allowed equipment integrity test data. Cause: Available data fields are not constrained via
variables, leading to calls to unauthorized document content.
How to Verify Proper Configuration
- Manually enter the current batch number, and check that the documents called by the AI only include records for that batch, with no content from other batches.
- Initiate multi-turn dialogue, and check that
messagesretains context information tied to the current batch, with no cross-batch data. - Submit an exception issue, and check that the AI-generated report only uses process, environmental, and test data from the current batch, with no irrelevant content.
- Check that
chatIdis bound to the current batch identifier, to ensure conversations across different batches do not interfere with each other.
The values provided are common starting points and should be measured against the reader's own samples.