What the data for this category looks like
Data for urban gas application materials and case review primarily comes from offline paper materials and online business systems for services such as installation, transfer, and safety inspection. Data updates in real time based on order volume. Each individual material includes structured forms (such as installation address and gas usage scale), identification documents, gas facility drawings, on-site inspection records, and more. Document structures vary: some are plain text forms, while others are scanned documents. Fields include quantified information with units: gas usage scale uses cubic meters or square meters, and approval nodes use dates as units.
Constraints Imposed on Model Access and Configuration
The above data characteristics impose multiple constraints on model access and configuration: First, the data includes unstructured scanned documents and plain text forms, so models must support multimodal input to parse image content. Second, the text length of individual cases varies widely, so a sufficiently large context window must be configured to cover complete review materials. Third, fields include quantified information with units, so models must accurately identify the correspondence between units and numerical values to avoid review errors. Fourth, data sources are scattered and formats are inconsistent, so processing logic adapted to multi-format documents must be configured.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the total text length requirements of individual gas case files (including OCR scan results) and historical approval records |
maxTokens | 2000–3000 token | Controls the output length of single-round review results to avoid exceeding interface return limits |
quoteMaxToken | 1500 characters | Limits the length of referenced case original text fragments to ensure the model focuses on key review nodes |
vision | Enabled | Supports parsing scanned content of gas facility drawings and paper approval forms |
temperature | 0.2–0.4 | Reduces output randomness to ensure consistency and compliance of review results |
AIPROXY_API_ENDPOINT | Fill in the actual address of the deployed proxy service | Adapts to intranet access and interface permission requirements |
AIPROXY_API_TOKEN | Fill in the assigned interface key | Ensures validity of identity verification for interface calls |
Three Common Configuration Mistakes
- Phenomenon: After switching the vector model, the interface shows no progress, and the original model cannot be switched back. Cause: The cache association of the old model was not cleared in the FastGPT v4.17.0 configuration, causing the proxy service to still bind the old model resources.
- Phenomenon: After updating the platform version, the output length of review results becomes significantly shorter, failing to meet complete case review requirements. Cause: The
maxTokensandmaxContextconfiguration parameters were not updated synchronously, and the default parameter thresholds of the new version were adjusted. - Phenomenon: Model calls fail after configuration is completed, returning interface authentication errors. Cause:
AIPROXY_API_TOKENorAIPROXY_API_ENDPOINTwas not filled correctly, leading to failed identity verification.
How to Verify Successful Configuration
- Upload a standard gas installation application material, call the model for testing, and check whether core fields such as installation address and gas usage scale can be correctly extracted.
- View the model call log to confirm that the actual values of configuration parameters such as
maxContextandmaxTokensmatch the set values. - Attempt to switch the configured model, check whether the interface can load and save the new model configuration normally.
- Upload a scanned document with gas facility drawings, check whether the model can correctly parse text and graphic information in the image.
The values given 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.