What the data for this category looks like
Data for this category primarily originates from communications tower operation and maintenance management systems, base station inspection logs, and supporting infrastructure archives. Two data update cycles apply: routine daily inspection records are synchronized and updated each day, and basic facility archives are updated monthly alongside maintenance activities. Each individual document contains fields including base station unique identifier, installation location coordinates, tower height, supporting machine room area, recent fault type, and processing status. Field units include meters, square meters, hours, status codes, and others. The overall structure is straightforward with no complex nested layers.
What constraints these characteristics impose on model access and configuration
The daily updated inspection records and monthly updated basic archives for this category require a short-cycle data synchronization mechanism to be configured during model access, to avoid use of expired facility status information. Fixed fields and units require clear mapping rules to be established between data fields and model inputs during configuration, to prevent query deviations caused by unit mismatches. The simple structure of individual documents, which includes a unique identifier field, requires recall processes to prioritize matching base station IDs. The total token count of recalled documents per single request must also be controlled, to avoid exceeding model context limits.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | This category has a low token count per individual document. After batch recalling hundreds of inspection and archive records, this value range prevents critical information from being truncated |
maxTokens | 2000–3000 token | Responses to service inquiries require precise matching of user questions. Overly long generated content reduces inquiry response efficiency |
quoteMaxToken | 1500 token | The token count for a single base station archive is approximately 100–200. This value range can cover around 10 associated documents, meeting the reference needs of service inquiries |
toolChoice | auto | Facility query tools must be triggered automatically based on user inquiry type, to adapt to different service inquiry scenarios |
temperature | 0.3–0.5 | Service inquiry responses must maintain accuracy and rigor. This parameter range avoids generating irrelevant or uncertain content |
AIPROXY_API_ENDPOINT | Fill in the official access address of the corresponding model | Official endpoints ensure interface stability and avoid compatibility issues with third-party proxies |
AIPROXY_API_TOKEN | Fill in the valid key obtained from the model service provider | Legal identity verification is a necessary prerequisite for model access |
Three common errors
- Symptom: A prompt indicating no available model appears after model access. Cause: The
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENparameters are not configured correctly, or the selected model is not included in the supported list for FastGPT v4.17.0. - Symptom: A configured One API channel shows as unavailable, even if local testing of One API succeeds. Cause: FastGPT's
AIPROXY_API_ENDPOINTparameter does not align with the forwarding request format of One API, resulting in a mismatched request path. - Symptom: Facility data with mixed units appears in generated responses. Cause: No mapping rules between data fields and model inputs were established during configuration, and field unit formats were not unified, leading to abnormal model parsing.
How to confirm configurations are complete
- Run a model interface test to verify that identity verification for
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENpasses, and check if the returned model list includes the configured model. - Submit a test service inquiry, such as "Query the current maintenance status of a specified base station", and confirm whether the model correctly calls tools and returns matching facility data.
- Review the values of context configuration items, and confirm that the covered token count does not exceed the maximum context length supported by the current model. Adjust values based on truncation observed in test responses.
- Review the field mapping results for recalled documents, and confirm that returned facility data field names match preset rules, with no unit or format deviations.
The values provided here are common starting points, and should be evaluated against 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.