What this category of data looks like
Process and standard data for welded structural component manufacturing originates from design drawings, material quality certificates, welding equipment parameters, filler metal inventory, non-destructive testing systems, and personnel qualification ledgers. Data is updated per weld seam, per batch of workpieces, or per shift of operations. It includes exclusive documents such as welding procedure qualification reports, welding procedure specifications, filler metal usage records, welder qualification records, weld inspection reports, and repair orders. Fields cover base metal grade, filler metal model, welder qualification number, welding parameters, flaw detection results, repair times, and more.
Constraints Imposed by These Characteristics on the Multi-turn Dialogue and Prompt Engineering Link
The discrete nature and strong interconnectedness of this category of data requires multi-turn dialogue to bind chatId, ensuring conversation context only relates to documents for the corresponding weld seam or batch. The high-frequency update feature requires the dialogue link to pull the latest data from the filler metal inventory and personnel qualification ledgers in real time, avoiding use of outdated static information. With numerous professional fields and strict business logic, prompts must limit retrieval scope to process and inspection documents for the specified workpiece, while guiding users to gradually provide positioning information such as weld seam numbers and flaw detection results to narrow retrieval scope and improve matching accuracy.
Configuration Settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
messages | Retain the first 10 rounds of conversation content in the current session | Welding structure process consulting mostly involves coherent questions about a single batch of workpieces; the first 10 rounds cover complete logic and avoid context overflow |
variables | Bind the weld seam number and batch number of the current workpiece | Match the data update feature of this category per weld seam or batch, and accurately locate corresponding process and inspection documents |
chatId | Bind the unique identifier of a single batch of workpieces | Isolate conversation contexts across different batches to prevent cross-batch data confusion |
| Single search limit | Top 6 matching results | Aligns with the conventional scope of single-batch retrieval data for this category, reducing redundant information interference |
| Question optimization | Enable and limit to welding professional terminology | Adapt to the professional vocabulary of welding processes, and optimize retrieval matching rate for user questions |
| Maximum context | 8000 characters | Accommodate complete process and inspection data for a single batch of workpieces, avoiding truncation of critical information |
Three Common Misconfiguration Issues
- Chaotic conversation output splicing: Multi-turn conversation results displayed in the interface show misaligned filler metal models and base metal grades. This occurs because
variablesare not used to bind the weld seam number of the current workpiece, leading to mixed retrieval of process data across batches. - Inability to retrieve full conversation records: The returned conversation log after calling the interface only includes the last 5 rounds of content, with no data export option. This occurs because the complete context retention rule for
messagesis not configured, and the conversation log export permission is not enabled. - No interpretation result after image upload: After uploading a weld flaw detection image, the system does not return corresponding defect judgment content. This occurs because the multimodal dialogue configuration is not enabled, and the image analysis interface of the non-destructive testing system is not associated.
How to Verify Successful Configuration
- Initiate a query that includes a specific weld seam number, and check whether the returned process data only relates to the workpiece corresponding to that number.
- Initiate 10 consecutive queries about the same batch of workpieces, and confirm that the conversation context is not truncated and the logic is consistent across the exchange.
- Attempt to export the conversation log, and confirm that it includes all session content.
- Upload a flaw detection image and submit an interpretation request, and confirm that the system returns professional analysis content for that image.
The values provided here are common starting points and should be measured against the reader's own samples.