What this category of data looks like
Data originates from project declaration systems, marketing business application platforms, and case archiving modules of power grid enterprises. Data updates align with project timelines or monthly archiving cycles. Single batches include a large number of uploaded materials. Documents are split into two categories: declaration materials and case files. Declaration materials include project application forms, scanned qualification certificates, site inspection records, and power usage plans. Case files include review process sheets, rectification notices, and acceptance reports. Fields cover project number, voltage level, power consumption capacity, approval node, rectification time limit, and other relevant items. Units include kilovolts, kilowatt-hours, working days, and other relevant units.
Constraints on model access and configuration from these characteristics
Bulk document sets require configuration to support batch processing, to avoid timeouts when handling individual materials. Documents with both scanned images and structured fields require models to have visual parsing capabilities, and accurately identify power grid-specific fields and units. Multi-batch archived data updates require configuration context length to hold the full content of a single document, to avoid truncation of critical information. Data security requirements for state-owned enterprises and public institutions mandate configuring dedicated keys and API endpoints for model calls, to isolate data access across different business scenarios.
How to Configure the Parameters
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
vision | Enabled | A large number of scanned qualification certificates and inspection photos are included in declaration materials and case files, requiring visual models to parse non-text content |
maxContext | 8000–12000 token | The text length of a single case file or declaration material can reach thousands of characters, requiring full context to be accommodated to ensure review completeness |
maxTokens | 2000–3000 token | Review results need to cover multi-dimensional judgments, and output length must meet detailed feedback requirements |
temperature | 0.1–0.3 | Review must strictly follow power grid business specifications, reducing randomness to ensure consistent judgments |
AIPROXY_API_TOKEN | Bound to power grid-specific keys | Complies with data security requirements for state-owned enterprises and public institutions, isolating model calls across different business scenarios |
toolChoice | Automatic | Automatically call tools to handle structured field extraction, reducing manual intervention and improving field recognition accuracy |
Three Common Configuration Pitfalls
- Phenomenon: Model detection fails after configuration in FastGPT v4.17.0. The interface prompts "model unavailable" or returns an interface error. Cause:
AIPROXY_API_TOKENis not filled in correctly, or the usedAIPROXY_API_ENDPOINTdoes not match the current deployment environment. - Phenomenon: Scanned drawings or photos in declaration materials cannot be parsed after enabling the
visionfunction. Cause: Visual support is not enabled in the model access configuration, or the uploaded file format does not match the types supported by the model. - Phenomenon: Key matching confusion occurs during calls when multiple models with the same name but different keys are configured. Cause: Independent identification parameters are not configured for each model, causing the system to fail to accurately distinguish model instances with different keys.
How to Confirm the Configuration Is Successful
- Upload a single declaration material containing scanned images, trigger model review, and check whether qualification information and structured fields in the scanned images can be correctly extracted.
- Call the model interface, pass in test case data, and check whether the returned results include review judgments and field extraction content that comply with power grid specifications.
- Configure multiple models with different keys, initiate calls separately, and confirm that each call matches the corresponding model instance without key confusion.
- View the model call logs, confirm that the
maxContextandmaxTokensparameters are correctly applied, and no context truncation or output overrun prompts appear.
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.