Data Profile for This Category
Coal chemical industry service consultation and reply data originates from internal enterprise service guide databases, approval process archives, archived annual consultation work orders, and service specifications published by industry regulatory authorities. Data updates align with regulatory policy adjustments and internal enterprise process optimizations. There is no fixed update cycle, but core document updates occur no more than once every six months. Each document maps to a single service matter, and includes standardized fields: matter name, application conditions, declaration material list, handling process, consultation channel, and processing time limit. Field units follow standard administrative document formats, such as working days, copies, and yuan.
Constraints for Model Access and Configuration
Coal chemical industry service consultation data is split into individual documents per service matter, and includes multi-dimensional administrative fields. Model access must include precise matching of field association logic to avoid cross-matter confusion. Data updates have no fixed cycle, so a knowledge base synchronization mechanism supporting flexible triggering must be configured to adapt to document updates following temporary policy adjustments. Some service matter documents have lengthy text, so model context carrying capacity must be limited to prevent exceptions caused by long texts exceeding model processing thresholds. The dataset also contains dense professional terminology, so model parameters must be adjusted to improve semantic understanding accuracy for industry text, ensuring reply professionalism and accuracy.
Configuration Guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Coal chemical industry service matter documents are mostly 1000-3000 characters long. Combined with context-associated historical consultation work orders, this range covers complete service matters and historical consultation context |
maxTokens | 2000–3000 token | Service replies must be clear and complete. Excessively long output is prone to deviating from core points. This range covers conventional reply lengths |
quoteMaxToken | 3000–5000 token | Complete service material lists and process documents must be recalled to ensure referenced content is not truncated |
temperature | 0.2–0.4 | Service replies must be accurate and rigorous. A lower temperature reduces irrelevant content generation, adapting to the standardization requirements of administrative consultations |
toolChoice | auto | Automatic judgment of whether to call the knowledge base or reply directly is required, adapting to diverse coal chemical industry service consultation scenarios |
AIPROXY_API_ENDPOINT | Fill in the deployed private proxy address | Model requests must be routed to the internal proxy to ensure the security of coal chemical industry business data |
AIPROXY_API_TOKEN | Fill in the actually generated proxy key | Used for identity verification to ensure the legitimacy of model requests |
Three Common Misconfigurations
- Symptom:
Unexpected end of JSON inputerror occurs when calling the model. Cause:AIPROXY_API_TOKENis not configured correctly, or the proxy address format is incorrect, resulting in empty or incomplete JSON responses from requests. - Symptom: The model outputs irrelevant answers when asking questions about long-text service documents. Cause:
maxContextis set too small, failing to cover the complete service document context, causing the model to lose key process and material information. - Symptom: No response after connecting a custom Chat TTS. Cause:
AIPROXY_API_ENDPOINTis not correctly pointed to the TTS service address, resulting in incorrect request routing and failure to complete voice generation and playback.
How to Confirm Proper Configuration
- Submit a single coal chemical industry service consultation, check whether the model output includes accurate service processes and material information, and verify whether the output content matches the knowledge base documents.
- Upload a long-form service document to verify that the
maxContextsetting can fully load the document content without truncation or loading failure errors. - Trigger a knowledge base synchronization operation, check whether the model can recall the latest service specification content after data updates, ensuring the update takes effect.
- Call the test interface to verify that the identity verification of
AIPROXY_API_TOKENworks normally, with no permission-related errors.
The values listed are common starting points and should be evaluated against individual deployment 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.