What the Data for This Category Looks Like
Data for this category comes from internal systems and on-site records of coating, resin, additive, agrochemical intermediate, and specialty chemical enterprises. Daily documents include batch production instructions, feeding verification sheets, reaction process records, cleaning records, test reports, deviation and change orders. Data sources cover formula and process libraries, raw material batch ledgers, reactor DCS data, weighing system records, LIMS systems, and warehouse systems. Data updates are triggered once per production batch or each key process step. Individual documents include clear fields such as feeding parameters, reaction conditions, and test indicators, all linked to batch numbers and reactor numbers.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Multi-batch switching, process confidentiality, and cleaning confirmation requirements for this category impose constraints on multi-turn dialogue context management. Batch-updated data requires dialogue to be linked to the current production batch number to avoid mixing cross-batch data. Multiple scattered on-site records and system data require prompt engineering to explicitly limit the retrieval scope to documents of the current batch, preventing calls to process data from unrelated batches. Frequent step switching and parameter verification requirements require multi-turn dialogue to retain recent process parameters and deviation records, while also limiting context length to avoid answers deviating from the current process due to redundant data. Process confidentiality requirements must explicitly prohibit disclosure of formula details in prompt engineering, with answers generated only based on authorized documents.
Configuration Settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Number of chat history entries | Last 6 entries | This category has dense process steps; retaining the last 6 chat entries covers current process parameter verification and deviation query needs, avoiding context overload |
| Context window size | 800–1200 characters | Key process documents have concentrated fields; 800–1200 characters can fully carry current batch process parameters and historical conversation information |
messages parameter configuration | Sync latest conversation content | Follow standard multi-turn dialogue logic, update context via the messages parameter to ensure each response is based on the latest interaction and process data |
chatId configuration | Bind to current production batch ID | Ensure conversation context for each batch is independent, preventing interference between process data of different batches, aligning with batch-based data management characteristics |
| Prompt template | Limit to current batch documents | Address process confidentiality and multi-batch switching needs, explicitly specify that the prompt only calls authorized documents such as current batch batch production instructions and reaction process records |
Three Common Misconfigurations
- Issue: Using a text content extraction plugin in a workflow to configure the number of chat history entries results in failed multi-turn dialogue. Cause: The workflow node does not correctly bind the
chatIdparameter, leading to independent conversation context for each round, unable to retain historical interaction information. - Issue: Calling a multimodal model to process on-site process images returns incorrect formatting. Cause: The prompt does not explicitly require images to be on-site photos of the current batch’s reactor, and does not limit image format ranges, leading the model to receive invalid input.
- Issue: Search results include process documents from non-current batches. Cause: The current batch number is not bound as a retrieval variable, causing the system to call documents from historical batches, violating batch data isolation requirements.
How to Verify Proper Configuration
- Initiate a first-round query that includes a batch number, confirm that the second-round response is generated based on the batch information from the first round, with no cross-batch data included.
- Check the conversation context display area, confirm that only the last 6 chat entries are retained, with no redundant historical data.
- Upload process documents from non-current batches, verify that the system prompts that such documents cannot be called, ensuring retrieval scope aligns with configuration requirements.
- Call the interface to initiate multi-turn dialogue, check that the
messagesparameter syncs the latest conversation content, ensuring context consistency.
All provided configuration values are common starting points and should be evaluated against the reader’s own samples.