What this category of data looks like
Coal transportation and sales ledger data mainly comes from coal loading systems, railway freight platforms, port EDI systems, and purchase and sales contract documents. The data updates immediately after each shipment waybill is generated. Each ledger document uses a structured table format, including fields such as shipping station, destination station, coal type, low heating value, shipment tonnage, settlement amount, and carrier. Most fields combine numerical and text values, with units including kilocalories per kilogram, tons, yuan, and other standard units.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
The structured fields of coal transportation and sales ledgers are numerous and have professional attributes. Multi-turn dialogue must clearly limit extraction to specified fields to avoid irrelevant information interfering with analysis results. Daily updated batch data requires the dialogue context to retain recent shipment waybill identifiers, ensuring accurate cross-turn data association. Data from multiple sources may use different field naming conventions, so multi-turn dialogue must automatically align field names. The data volume of a single batch ledger is large, so the context window range must be limited to avoid redundant information occupying dialogue resources.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Fixed as the unique business number of the current transportation and sales batch | Ensures multi-turn dialogue is bound to the ledger data of the same batch, avoiding confusion across batches |
messages | Retain the latest 12 dialogues and 7 days of shipment waybill data slices | Covers recently associated transportation and sales ledgers, preventing data association errors caused by expired context |
variables | Preset three core variables: coal type, shipping station, settlement cycle | Matches conventional analysis dimensions of coal transportation and sales, simplifying user input procedures |
| Maximum context length | 8000–12000 characters | Accommodates the complete content of multiple structured ledgers in a single batch, avoiding information truncation |
| Question optimization | Calibrated based on actual testing | Adapts to professional terminology and field naming conventions of coal transportation and sales, improving dialogue understanding accuracy |
Three common mistakes
- Phenomenon: When initiating cross-application dialogue using a global general identifier, ledger data from different coal transportation and sales batches is incorrectly associated. Cause: No independent
chatIdis bound to each batch, resulting in globally shared context. - Phenomenon: When importing ledger attachments in Word format, images automatically carry domain names. After conversion to Markdown format for import, image links are lost. Cause: No image domain name replacement rule is configured when importing Markdown, resulting in relative paths not being completed.
- Phenomenon: The content returned after tool calling includes tool execution logs and parameters. Cause: The prompt does not explicitly require filtering the intermediate process of tool calls, only retaining the final organized report content.
How to confirm the configuration is correct
- Initiate a query including coal type and shipment volume, and verify that returned results only extract ledger fields for the currently bound batch.
- Switch the
chatIdof different transportation and sales batches, and confirm that the dialogue context no longer associates data from prior batches. - Import ledger attachments in Markdown format, and check that image links automatically complete the preset domain name.
- Call the tool to generate a transportation and sales report, and confirm that returned content only includes organized report results, with no tool execution logs.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.