What the data for this category looks like
The business data for batch fine chemical synthesis comes from formula and process libraries, raw material batch ledgers, reactor DCS systems, weighing systems, LIMS laboratory management systems, and warehouse systems. The system triggers data updates once per production batch and each critical step. Daily documents include batch production instructions, feeding review slips, reaction process records, cleaning records, inspection reports, and deviation and change orders. Data fields include batch number, feeding quantity, reaction temperature, reaction duration, cleaning confirmation records, and others. Formula parameters are classified as confidential content, and access scope must be strictly restricted.
Constraints on Multi-turn Dialogue and Prompt Engineering for This Category
Batch production switching for this category requires multi-turn dialogue to lock context data for a single batch, to avoid mixing process parameters across batches. The dialogue system pulls the latest feeding and reaction records in real time for frequently updated production data. Prompts restrict calls to only document content for the current batch. The dialogue guides users through multi-stage production processes including feeding review, reaction end point judgment, and cleaning confirmation. Prompts embed verification rules for each stage. The dialogue system applies permission filtering to sensitive fields for confidential formula parameters, to prevent unauthorized access.
Configuration Settings
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind the batch number, raw material batch ID, and cleaning record ID corresponding to the current bid project | Data for this category is associated by batch, so single-batch production documents must be locked to avoid calling incorrect historical data |
messages | Retain the first 10 rounds of dialogue context, truncate historical content exceeding 8000 tokens | Bid communication requires retaining historical dialogue records of quotations and technical parameters, while controlling context length to ensure response speed |
| Maximum context | 6000–10000 tokens | Single-batch process documents and inspection report data for this category have large volume, so long context processing needs must be accommodated |
| Question optimization | Enabled, calibrated based on actual testing | Bid documents need to accurately match the technical parameter requirements of the tenderer, and optimized prompts can improve content accuracy and compliance |
chatId | Bind the unique identifier of the current bid project | Dialogue histories for different bid projects must be distinguished to avoid mixing and interference of cross-project data |
Three Common Misconfigurations
- The symptom is that the dialogue return result ends with a fixed-format trace display symbol similar to "Reference Documents: XXX". The cause is that the system default prompt trace display switch is not turned off.
- The symptom is that some dialogue returns empty results during high-concurrency calls. The cause is that the concurrent request limit for a single
chatIdis not set, leading to context resource preemption. - The symptom is that the generated bid document does not include the exclusive process parameters of the current batch. The cause is that the batch identifier in
variablesis not correctly bound, leading to the calling of incorrect historical documents.
How to Verify Correct Configuration
- Initiate a single-turn test dialogue, check that no trace display symbol similar to "Reference Documents: XXX" appears at the end of the return result.
- Initiate more than 3 rounds of multi-turn dialogue, verify that the
messagescontext is correctly retained, and that historical data from other bid projects is not mixed in. - Call the batch identifier bound in
variables, check that the generated bid document includes exclusive content such as feeding quantity and reaction parameters for the corresponding batch. - Initiate concurrent test requests at 2-3 times per second, verify that no empty result returns occur for requests under a single
chatId.
The values provided are common starting points and should be measured against the reader's own samples.