What This Category of Data Looks Like
This category of data typically originates from ERP/WMS systems, barcode or RFID collection devices, purchase work orders, bin ledgers, AGV transport systems, and weighing equipment. Daily documents include receiving slips, putaway slips, material issue and return slips, stock transfer slips, inventory counts, lot ledgers, and expiration date records. Data updates follow three rhythms: real-time (for bin changes, weighing data), daily (for material issue and return statistics), and monthly (for full inventory counts). Core fields include material code, lot number, bin number, inspection status, expiration date, and inventory quantity. Units include pieces, kilograms, cubic meters, and other standard units.
What Constraints These Characteristics Impose on Multi-Turn Dialogue and Prompt Engineering
Data sources for this category are scattered, and update rhythms differ. Multi-turn dialogue must connect ERP batch ledgers and real-time collected bin change data simultaneously. It must use context to track the association between current work orders and lots. Document fields are numerous, and formats are inconsistent. Prompts must clearly define required fields and validation rules to prevent mixing information from different documents. Cross-process material flow management requires dialogue to retain historical inspection and stock transfer records. Excessively long context increases inference workloads. Non-core historical content must be truncated appropriately.
Configuration Setup
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Maximum Context Length | 8000–12000 characters | This category requires coverage of information from multiple historical documents including lot ledgers, bin records, and material issue and return slips. Sufficient context ensures coherent dialogue logic |
chatId Binding Rule | Bind the conversation ID associated with the current work order | This limits dialogue context to only lot and bin data for the current work order, preventing interference from cross-work order information |
variables Loading Scope | Load global variables from the first 3 historical conversations | Core variables for this category are lot number, bin number, and expiration date. A small number of historical variables balances context completeness and inference efficiency |
messages Context Truncation Threshold | Automatically truncate the earliest non-core records when exceeding 10 conversation turns | In-plant logistics data updates frequently. Excessively long conversation history reduces response speed. Truncating non-core documents optimizes performance |
| Prompt Template Field Validation | Calibrate based on actual testing | Must match field formats for different documents such as receiving slips and inventory counts, to ensure extracted information accurately aligns with business requirements |
Three Common Mistakes
- Symptom: MySQL tool call returns 400 status code (no body). Cause: Global variables for ERP/WMS data sources are not correctly bound, leading to missing request parameters.
- Symptom: Users accessing via login-free links delete conversations, and background logs are cleared synchronously. Cause: Conversation log persistence configuration is not enabled, making historical inspection records untraceable.
- Symptom: Historical global variables fail to load during multi-turn dialogue. Cause: The
variablesbinding scope is not limited to the current work order, leading to mixing of lot and bin information across conversations.
How to Verify Successful Configuration
- Initiate a query that includes a specified material code and lot number, confirm that the conversation returns historical records for the corresponding bin, expiration date, and inspection status.
- Test deleting a single conversation entry, check if the background log retains the full operation record for that conversation.
- Call the MySQL tool, confirm that batch ledgers and inventory data from the ERP system can be retrieved normally.
- Initiate multi-turn queries across work orders, confirm that the conversation does not mix material and bin information from different work orders.
The values provided are common starting points and should be evaluated against the reader's own samples.