What this category of data looks like
Data sources include new energy project work orders from local government service centers, industry policy documents released by energy authorities, and consultation feedback records submitted by project developers. Updates are synced in real time when work orders are completed. Policy documents are updated based on their release dates. Documents are organized by service matters, and include fields such as unique project ID, land coordinates, installed capacity (unit: megawatt), approval stage nodes, consultation question category, and reply reference document number. Each individual consultation entry includes three core modules: original question text, reply history, and associated project information.
Constraints imposed by these characteristics during model integration and configuration
Numeric fields with units such as geographic coordinates and installed capacity require the model to adapt to standardized numeric parsing formats during integration, to avoid reply errors caused by unit confusion. The non-fixed update schedule of policy documents requires configuring a context synchronization mechanism to ensure that called knowledge base content aligns with the latest policies. The real-time requirement of work orders means model call response delays must match daily service time standards, while supporting accurate classification of multiple service matter types to avoid cross-matter reply deviations. Additionally, the approval stage node field must be bound to the model's tool call logic to ensure reply content accurately links to the corresponding approval step.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | New energy service consultations involve policy texts and work order history, requiring sufficient context to associate past consultation records |
maxTokens | 2000–3000 token | Service replies require clear step-by-step explanations. Overly long output reduces readability |
vision | Enabled | Some service materials include project drawings and on-site photos, requiring image content recognition to assist with replies |
temperature | 0.2–0.4 | Service consultations require rigorous replies, to avoid generating uncertain content |
AIPROXY_API_ENDPOINT | Enterprise-specific proxy address | Ensures data transmission security for state-owned enterprises and public institutions, preventing sensitive information leaks |
AIPROXY_API_TOKEN | Regularly rotated encrypted token | Complies with information security specifications for state-owned enterprises and public institutions, preventing permission risks caused by token leaks |
Three common mistakes
- Symptom: Only the AI chat module outputs dialog box content in the workflow, and custom-processed content cannot be displayed synchronously. Cause: The binding relationship between the output node and the dialog box is not configured in the workflow, and only the default output of the AI chat module is retained.
- Symptom:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations are lost after system restart. Cause: Configurations are not saved to the platform's persistent storage directory, and only exist in local temporary cache. - Symptom: After uploading a PDF document containing images, the model does not recognize the image content. Cause: The
visionparameter is not enabled, or the pre-processing step for PDF image extraction is not configured.
How to confirm configurations are complete
- The FastGPT v4.17.0 test interface is called. A consultation question containing installed capacity and geographic coordinates is input, and the model output is checked for correct parsing of values and units.
- A PDF test file containing project drawings is uploaded, and the model output is checked for descriptive information about image content.
- The platform service is restarted, and the
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations are checked for retention in the settings interface. - Consultation questions for multiple service matter types such as grid connection application and qualification review are input, and the model is checked for correct classification and linking to corresponding policy references.
The values provided here are common starting points and should be measured against the samples relevant to the specific deployment.
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.