What This Category of Data Looks Like
The business data for coal transportation and sales mainly comes from internal transportation and sales scheduling systems, port loading and unloading ledgers, railway/road waybill systems, and contract management modules. Data updates follow two rhythms: real-time and quasi-real-time. Waybill and loading/unloading data are updated in real time alongside shipping and loading operations. Contract and inquiry/quotation data are updated on a natural day basis when businesses are signed or adjusted. Documents are primarily structured forms, including fixed fields such as coal type, calorific value, moisture content, shipping origin, destination, carrier, actual transportation volume (unit: ton), and settlement unit price (unit: yuan/ton). Some attachments are unstructured waybill scans and contract PDFs.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The large number of structured fields with strong business correlation requires multi-turn dialogue to track already collected business parameters, avoiding repeated questions to users. Real-time updated waybill data means dialogue context cannot be overly long, otherwise expired data will lead to inaccurate responses. The coexistence of unstructured attachments and structured fields requires prompt engineering to clearly distinguish field types and formats to be extracted, preventing confusion of business parameters. Cross-system data sources require dialogue flows to guide users step-by-step according to transportation and sales business links. For example, confirm shipping origin first before querying corresponding transportation capacity, otherwise parameter matching errors may occur. Additionally, single interaction cycles for coal transportation and sales service inquiries are usually short. A reasonable expiration time must be set for conversation contexts to avoid invalid data occupying resources.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique identity identifier of the user system, valid for 7200 seconds | Users of coal transportation and sales services are mostly internal enterprise personnel or service applicants. Isolating conversations by user can prevent cross-user data leakage; 7200 seconds matches the typical processing cycle of coal transportation and sales business |
messages | Retain the last 20 dialogue contexts, with a single message length not exceeding 800 characters | Coal transportation and sales business has many fields, and an overly long context will dilute key parameters. 20 contexts can cover 3 to 5 rounds of inquiry processes for typical service requests |
variables | Preset three business variables: coal type, transportation volume range, shipping origin/destination | The core needs of coal transportation and sales service inquiries revolve around these three types of parameters. Pre-binding variables can reduce repeated questions and improve inquiry efficiency |
| Maximum Context Length | 10000 token | Coal transportation and sales contracts and waybill documents are relatively long, requiring sufficient context to carry business details while avoiding exceeding the model's processing limit |
| Conversation Timeout | 600 seconds | The single interaction cycle for coal transportation and sales service inquiries usually does not exceed 10 minutes. Automatically clearing the context after timeout can prevent expired data from affecting responses |
Three Common Misconfigurations
- The phenomenon where different users see the same conversation history after logging in. The cause is failing to correctly bind
chatIdto the unique identity identifier of the user system, resulting in conversations not being isolated by user. - The phenomenon where the system repeatedly asks for repeated information such as coal type and transportation volume during multi-turn inquiries. The cause is failing to preset core business variables through
variablesand failing to track already obtained user input in the dialogue flow. - The phenomenon where all replies from embedded AI dialogue nodes appear in a single chat interface after a workflow is executed, without returning results step-by-step by turn. The cause is failing to split the context by dialogue turn and failing to restrict a single turn to only return the output of the current node, preventing multi-turn question and answer from proceeding according to the process.
How to Verify Proper Configuration
- Invoke the interface using two distinct
chatIds, submit an identical inquiry question for both, and confirm that the conversation histories of the two sessions do not interfere with one another. - Initiate a multi-turn inquiry, enter coal type and transportation volume range in sequence, and confirm that the system does not repeatedly ask for confirmed business parameters.
- Trigger a workflow to execute multi-turn dialogue, and confirm that only the reply of the current node appears in the chat interface, without returning all node outputs simultaneously.
- Wait 600 seconds, then initiate a new conversation, and confirm that the old conversation context has been automatically cleared.
The values provided here are common starting points and should be evaluated against the respective deployment’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.