What the Data for This Category Looks Like
Data for power generation group document and material drafting is primarily sourced from internal production and operation documents, contract templates, safety regulations, annual work reports, unit maintenance records, and similar materials. Data update rhythms include fixed cycle updates and ad-hoc updates. Fixed cycle updates cover monthly business analysis documents, quarterly summary reports, and annual official documents. Ad-hoc updates include emergency notices, temporary maintenance applications, and similar materials. Document structures are divided into fixed field template type and free text type. Fixed fields include unit number, power generation, coal consumption rate, and similar items, with corresponding units of megawatt-hours and tons of standard coal. Free text type has no fixed format requirements.
What Constraints Do These Characteristics Impose on the Multi-turn Dialogue and Prompt Engineering Link
Fixed field template documents require output to strictly match preset fields and units. During multi-turn dialogue, continuous verification of field completeness is needed to avoid missing key production information. Free text documents are often lengthy, so multi-turn dialogue must retain sufficient messages context to prevent key production data from being truncated. Real-time updated power generation data requires calling the latest variables each time a dialogue is initiated to ensure the timeliness of data referenced in documents. For scenarios with many power generation-specific terms, prompt engineering must clearly define term definitions to avoid biased understanding of professional concepts, and standardize output format to meet official document requirements.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context | Previous 20 turns of dialogue + latest 8000 characters | Matches the characteristic that power generation group documents are mostly long texts, prevents key data from being truncated during multi-turn interactions |
| Question Optimization | Enabled, calibrated based on actual testing | Adapts to scenarios with many power generation-specific terms, reduces term understanding bias |
| Variable Call | Synchronously updated with each dialogue | Adapts to the real-time update characteristic of power generation data, ensures accurate information such as unit data and power generation referenced in documents |
| Output Format Control | Markdown syntax disabled | Meets the standardized typesetting requirements of power generation group official documents, avoids unexpected formatting symbols |
| Dialogue Branch Trigger | Direct jump to question classification nodes, distinguish sessions via chatId | Adapts to one-to-many dialogue scenarios, avoids repeated triggering of classification links in the workflow |
Three Common Misconfigurations
- Dialogue output contains Markdown syntax symbols such as # and *. The cause is that Markdown syntax was not disabled in the output format control configuration, resulting in the AI using formatted output by default.
- Repeated entry into the question classification node after one-to-many dialogue is completed. The cause is that the workflow was not configured to end the branch directly after the dialogue is completed, resulting in repeated triggering of the classification link in a loop.
- Dialogue response times out without returning results. The cause is that the timeout setting was not adjusted based on the generation requirements of long-text documents, resulting in interruption of the content generation process.
How to Verify Correct Configuration
- Initiate a draft request for a unit maintenance application form, and verify that the output content strictly matches preset fields and contains no Markdown formatting symbols.
- After configuring the one-to-many dialogue branch, initiate multiple requests of different classifications, and confirm that the workflow directly enters the corresponding knowledge base and AI dialogue link, without repeatedly triggering the classification node.
- Initiate a draft request for an annual work report, and verify that the dialogue context retains key production data from multi-turn interactions, with no content truncation.
- Test the variable call function, and confirm that the latest unit operation data fields are synchronously updated with each dialogue.
The values provided here are common starting points, and should be evaluated against applicable 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.