Reference only; verify against the target FastGPT release and deployment documentation.
What Data for This Category Looks Like
Coal chemical business process data is sourced from internal enterprise business process manuals, on-site operation guides, safety supervision filing documents, and approval node ledgers. Data updates occur monthly or quarterly, synchronized with business process adjustments. Documents are categorized by business lines such as gasification, purification, and synthesis. Each process entry includes fields including node number, operation steps, responsible position, time limit requirements, and safety specifications. Field units include professional operation parameters such as hours, person-times, and tons.
What Constraints Do These Characteristics Impose on the "Multi-turn Dialogue and Prompt Engineering" Link
The document structure categorized by business line requires multi-turn dialogue to guide progress by node, and cross-business line jumps are prohibited to avoid confusion between different operation processes. Fields that include responsible positions require prompts to clearly correspond to post operation permissions, filtering out operation guidance that exceeds permissions. Time limit requirement fields require prompts to embed compliance verification logic, reminding of compliant time limits for operations. The feature with a large number of professional terms requires unified term explanations in multi-turn dialogue to avoid ambiguity. The monthly update rhythm requires the knowledge base synchronization cycle to match the business update frequency, keeping prompts consistent with the latest rules.
How to Configure Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Generate a unique value based on the business handling order number | Distinguish dialogue contexts for different business processes to avoid context interference |
messages | Retain the last 10 rounds of dialogue content | Coal chemical business handling has numerous steps, requiring retention of previous node operation information |
variables | Bind business line and operation node variables | Business data is organized by business line and node, accurately matching user query scenarios |
| Maximum context length | 6000–8000 token | Coal chemical business documents contain many professional terms and step details, requiring sufficient context support |
| Prompt update cycle | Synchronize once per month | Business data update frequency is monthly, keeping prompts consistent with business rules |
Three Common Misconfigurations
- Uploading documents to the dialogue page triggers a 503 error, and backend logs show the file upload was successful. The cause is that the file upload interface for the dialogue scenario is not bound to the coal chemical business file verification rules, resulting in abnormal traffic threshold triggering.
- When using a strict question-and-answer template, after retrieving the image address in the knowledge base, a prompt indicates that no answer was found. The cause is that the prompt does not configure the adaptation logic for image addresses, only matching text-based knowledge base content.
- Sending consecutive dialogue requests in a short period causes subsequent requests to wait for previous generation to complete. The cause is that different dialogue sessions are not isolated via
chatId, resulting in request queue blocking.
How to Confirm Proper Configuration
- Initiate a new business handling dialogue, check if
chatIdupdates with the handling order to ensure isolation between different session contexts. - Enter a cross-business line query, check if the dialogue correctly binds
variablesto match the rules of the corresponding business. - Send multiple consecutive dialogue requests, check that generation processes for different sessions do not interfere with each other, with no queue waiting.
- After uploading business documents, check that the knowledge base synchronization status matches the prompt update cycle, with no content lag.
The values provided 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.