What Data for This Category Looks Like
The data for coal-electric integration declaration materials and case review mainly comes from project approval documents, monthly production ledgers, safety supervision law enforcement cases, and compliance rectification records. Data updates fall into two categories: batch import of historical materials during the project declaration phase, and daily case updates aligned with law enforcement and rectification progress. Each individual document has a fixed structure, including fields such as project overview, capacity parameters, environmental protection indicators, approval document numbers, and rectification records. The unit for capacity is ten thousand tons per year, the unit for energy consumption is tons of standard coal, and cases include unified law enforcement numbers and responsible party information.
Constraints Imposed by These Characteristics on Model Access and Configuration
Fixed-structure long documents consume more context quota. Limit the text length processed per round to avoid exceeding the model's supported range. The precise identification requirement for numerical fields requires stable model output, so adjust the temperature parameter to control randomness. Batch-imported declaration materials and dynamically updated cases require the knowledge base synchronization frequency to match business rhythm, to avoid data lag or repeated loading. The unique case numbers and structured fields require the model to accurately match keywords during the recall phase, so adjust thresholds for retrieval-related configurations.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the average length of a single declaration material, avoiding truncation of core approval fields and capacity parameters |
temperature | 0.1–0.3 | Ensures accurate identification of numerical fields and structured information, reducing the probability of irrelevant output |
quoteMaxToken | 1500–2000 characters | Matches the typical length of rectification records in cases, ensuring recalled law enforcement content is fully transmitted |
AIPROXY_API_ENDPOINT | Official access address of the corresponding model service provider | Adapts to the large model computing power specifications and interface specifications required for the coal-electric integration scenario |
AIPROXY_API_TOKEN | Exclusive key obtained from the service provider console | Ensures identity verification security for model access, preventing unauthorized access |
maxTokens | 2000–3000 token | Controls the output length of single-round review results, complying with case review document specifications |
Three Common Configuration Errors
- Phenomenon: The knowledge base can retrieve data, but the model outputs empty or unrelated content. Cause: The
maxContextparameter is not configured correctly, causing recalled case content to exceed the context quota and be truncated, so it cannot be passed to the model. - Phenomenon: The model access channel shows an error, and the corresponding supplier cannot be selected. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare not filled in correctly, and identity verification fails, causing the channel to fail to enable. - Phenomenon: An error is prompted when reconfiguring the model offline, and loading fails. Cause: The model's token quota parameter is not matched, causing the context required for model reconfiguration to exceed the preset limit, so it cannot be loaded normally.
How to Verify Successful Configuration
- Navigate to the model management page of FastGPT v4.17.0, and check whether the status of the corresponding supplier channel shows normal.
- Upload a typical coal-electric integration declaration material, trigger the model review, and confirm whether the recalled case content appears completely in the context preview.
- Submit a test case containing capacity values, and verify that the model output accurately identifies unit fields such as ten thousand tons per year and tons of standard coal.
- Trigger the knowledge base synchronization operation, wait for synchronization to complete, retrieve the law enforcement number of the test case, and confirm that the number of recalled results meets expectations.
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.