What this category of data looks like
Data related to document and material drafting for urban investment platforms mainly comes from internal project management systems, official documents pushed by finance departments, and OA approval archive content. Document types include project approval reports, debt financing plans, monthly operation reports, government approval documents, and more. The length of single documents varies widely, with some annual audit reports being lengthy. Each document has standardized fields, including document number, project name, responsible entity, involved amount, approving authority, effective date, and others. Amount fields mostly use ten thousand yuan as the unit, while time fields use Gregorian dates or workdays. Data updates have no fixed cycle, and are triggered by project progress, report submission, or policy adjustments.
What constraints these characteristics impose on the model access and configuration link
The document data for urban investment platforms has four core characteristics: high proportion of long documents, fixed field formats, strict compliance requirements, and no fixed update cycle. The long document feature requires the model access link to adapt to large context windows to avoid truncating core information. Fixed field formats require clear extraction rules to be defined during configuration, ensuring generated documents include all required content. Compliance requirements demand access channels bound to exclusive permissions to prevent data leaks. No fixed update cycle requires the knowledge base recall strategy to be flexibly adjusted to adapt to document timeliness needs across different scenarios. Reference only; verify against the target FastGPT release and deployment documentation.
How to set configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 12000–16000 token | Urban investment platform documents often include multiple related documents, requiring space for complete project background and approval content |
maxTokens | 2000–3000 token | A single drafted document must cover core project information to avoid truncation of generated content |
temperature | 0.3–0.5 | Urban investment documents must maintain an official and rigorous style, with no excessive divergence |
AIPROXY_API_ENDPOINT | Fill in the exclusive access address assigned by the platform | Ensure compliance and security of data transmission for urban investment platforms |
AIPROXY_API_TOKEN | Use a token bound to exclusive scenario permissions | Comply with state-owned asset supervision requirements and avoid cross-category data access risks |
toolChoice | auto | Automatically call document retrieval tools based on document type to supplement missing project data |
Three common configuration errors
- A 403 error indicating the token does not have permission to use the model occurs when calling the model. The cause is failing to bind exclusive model permissions for the urban investment platform scenario to the token, or failing to configure the access scope of the corresponding model in the access platform.
- Generated documents lack core project fields. The cause is failing to explicitly require extraction of required fields such as document numbers and responsible entities from urban investment documents in the prompt, leading the model to omit key information.
- Knowledge base recall results are incomplete. The cause is failing to adjust context parameters based on the characteristics of long urban investment documents, with recalled content truncated after exceeding the
maxContextthreshold.
How to confirm correct configuration
- Run a model access test to verify there are no permission-related error messages in the returned results, confirming that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare configured correctly. - Import a typical urban investment project document to trigger the drafting process, and check whether the generated content includes core fields and data from the original document.
- Adjust the
temperatureparameter, compare document styles across different values, and confirm compliance with the rigorous style required for the scenario. - View the knowledge base recall log to confirm that the number and type of recalled documents match the needs of the current drafting task.
The values provided here 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.