What the data for this category looks like
Business data for urban water services comes primarily from water operation management systems, offline processing ledgers, and online user declaration portals. Data is divided into three categories: real-time work order data (repair requests, new connection applications, household transfer requests), monthly billing data, and pipe network-related business data. Most documents take the form of structured forms, including fields such as business type, processing nodes, required material list, processing time limit, and applicant user information. The unit for processing time limits is working days. The material list field stores a comma-separated list of item names. Data update frequencies range from real-time (for repair and new connection work orders) to monthly (for water bills).
Constraints Imposed on Model Integration and Configuration
The multi-type and time-staged update characteristics of urban water service business data impose multiple constraints on model integration and configuration. Real-time work order services require low-latency model calls, with a defined single-request timeout limit. The multi-field structure of structured forms requires the model context window to adapt to long-text input containing multi-node processing flows. Different business scenarios (new connections, billing, repairs) have differentiated model call requirements, so multi-API key group management must be supported. Batch processing of monthly billing data requires limiting the maximum token count of model generation to avoid exceeding API call quotas.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to long-text input containing multi-node processing flows and user historical application information, covering the context requirements of the full water service business process |
maxTokens | 1500–2000 token | Limits the length of single model generation responses, adapts to concise guidance output for business processing steps, and avoids exceeding API call quotas |
temperature | 0.2–0.4 | Reduces randomness of generated content, ensures accurate and consistent wording of business processing steps, and meets the rigor requirements of water service processes |
AIPROXY_API_ENDPOINT | Corresponding deployed model gateway address | Adapts to the requirements of multi-key group management, supports directing calls for different business scenarios to gateway nodes corresponding to their respective keys |
quoteMaxToken | 600–800 token | Limits the length of referenced water service business document fragments, ensuring the model only uses process rule data within valid ranges |
toolChoice | auto | Allows the model to automatically choose whether to call tools, adapting to process query requirements across different business scenarios |
Three Common Configuration Mistakes
- Configuring multiple API keys leads to call failures, with an invalid key prompt displayed in the interface. The cause is that keys are not grouped by business scenario, only a single set of key variables is added to docker-compose.yml, and the dynamic call logic for batch keys is not implemented.
- Model call tests return a 404 status code. The cause is that the gateway address configured in
AIPROXY_API_ENDPOINTdoes not correctly point to the deployed model service node, or the gateway configuration path is not updated synchronously after a version upgrade. - Testing returns an error after configuring the Ollama channel, with a field missing prompt. The cause is that the Ollama local deployment address parameter is not supplemented in the page configuration, and only configuration items from the old version config file are relied on, causing the call link to break.
How to Confirm Successful Configuration
- Navigate to the FastGPT model management page, view the configured API key groups, and confirm that each group corresponds to the correct business scenario.
- Initiate a test call for a single business processing flow, check that the returned result context contains complete processing node information, with no truncation or missing content.
- Check the token consumption of single requests in the call logs, confirm that the configured thresholds for
maxTokensandmaxContextare not exceeded. - Test the switching call for multi-key groups, confirm that the keys and gateway addresses used under different business scenarios match correctly.
The values provided are common starting points and should be evaluated 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.