What This Category’s Data Looks Like
The category mainly covers factories producing carbonated drinks, fruit juices, tea drinks, functional beverages, and packaged drinking water. Daily documents include formula sheets, water treatment records, mixing records, sterilization or aseptic filling records, packaging material inspection records, and finished product inspection records. Data sources include water source and raw material testing systems, formula management systems, online sugar and acidity monitoring equipment, filling equipment, visual inspection equipment, and LIMS systems. Data is updated per batch, per shift, or via continuous collection. Documents are associated with corresponding testing, mixing, and filling data by production batch. Fields include specific production parameters and test results.
Constraints for Multi-turn Dialogue and Prompt Engineering From This Category’s Characteristics
Data for this category is associated by production batch and has a high update frequency. Multi-turn dialogue must support specifying batch numbers to accurately call corresponding documents, avoiding confusion between formulas and inspection records of different batches. Data sources cover online monitoring equipment and laboratory systems, so prompts must clearly guide the distinction between real-time collected parameters and offline test results. Additionally, this category has prominent compliance requirements for water treatment and aseptic filling links. Multi-turn dialogue must continuously verify the matching degree between feeding parameters and aseptic records, without omitting details of key production links.
Configuration Settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | A variable group including batch numbers, water treatment parameters, and filling batch records | Data for this category is updated per batch, so it must be bound to production documents associated with the batch to ensure accurate data for the called batch during dialogue |
messages | The first 10 dialogue history entries | Multi-turn dialogue needs to retain context from bidding requirements and data verification to avoid repeatedly asking for basic production information |
| Maximum Context | 8000–12000 tokens | Needs to accommodate batch references of multiple formulas and inspection records, adapting to the long-content generation requirements of bid documents |
| Question Optimization | Calibrated based on actual testing | Needs to adapt to format requirements of different bidding documents, avoiding generated content that deviates from compliant production data reference rules |
| Single Search Limit | Top 6 recall results | Documents for this category are mostly categorized by batch, so precise matching of production data for the corresponding batch is needed to avoid recalling records from unrelated batches |
chatId | Bound to the exclusive dataset ID of the corresponding bidding project | Ensures the dialogue only calls production documents associated with the current bidding project, avoiding data confusion across projects |
Three Common Misconfigurations
- Phenomenon: The dialogue page crashes when loading multi-batch production data. Cause: The number of
messageshistory entries is not restricted, leading to context overflow that exceeds the system's carrying limit. - Phenomenon: The guiding prompt does not take effect, and the generated bid quotation does not associate production data for the corresponding batch. Cause:
variablesare not bound to the formula and water treatment record fields for the corresponding batch, so the prompt cannot call exclusive production parameters. - Phenomenon: The plugin that calls associated production data returns empty results. Cause:
chatIdis not specified in the dialogue configuration to bind the exclusive dataset of the current bidding project, leading to incorrect data call scope.
How to Verify Proper Configuration
- Initiate a test query that includes a specified batch number, and check whether the generated bid document automatically associates data such as the corresponding batch's formula and water treatment records.
- View the
messagesfield in the dialogue history to confirm that recent valid context is retained, and no redundant invalid dialogue content appears. - Call the plugin that associates production data, and check whether the returned results include packaging material inspection and finished product inspection data corresponding to the current bidding project.
- Adjust the parameter range in
variables, and verify whether the generated bid document automatically updates the corresponding content based on the adjusted parameters.
The values provided are common starting points and should be evaluated against the reader's own samples.