What the data for this use case looks like
State-owned capital investment company ledger data sources include state-owned assets supervision and reporting systems, internal group investment management platforms, and financial accounting systems. Updates follow a monthly routine schedule, with immediate updates after key milestones for major investment projects are completed. The document structure uses structured data with multiple table associations, including three sub-tables: project ledger, fund allocation ledger, and performance fulfillment ledger. Fields include project unique code, full name of investment entity, fund in place amount (unit: ten thousand yuan), approval document number, update date, and project progress node, among others. Field association relationships are complex, and there is no redundant content.
What constraints do these characteristics impose on tool calling and plugins
The multi-table association structure requires tool calling to support batch data pulling across multiple data sources. This avoids missing associated content in reports caused by retrieving only single-table information with a single call. The monthly update rhythm requires scheduled tasks for tool calling to match the update cycle. This prevents reports from being generated using outdated data. Strict field specifications require plugin output to map to standard fields required by state-owned assets supervision. Failure to do so will mean reporting requirements cannot be met. The data volume growing with the number of projects requires tool calling to limit the number of single return entries. This prevents context overflow from affecting model responses.
Configuration Settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | "auto" | Adapts automatic tool selection logic for multiple ledger data sources, no manual tool specification required |
functionCall | ["ledgerPull", "reportFormat"] | Matches the needs of ledger pulling and format-compliant report generation for state-owned capital investment companies |
| Tool call timeout | 600 seconds | Pulling state-owned capital ledger data involves multiple system associations, which takes a long time, so sufficient response time must be reserved |
| Single tool call return entry limit | First 20 entries | Avoids excessive data volume in a single return causing context overflow, while covering the main ledger information |
| Data cache duration | 86400 seconds | Matches the monthly ledger update frequency, reducing system load from repeated pulls |
| Report field mapping rule | According to state-owned assets supervision standard fields | Ensures generated reports comply with reporting specifications for state-owned capital investment companies |
Three Common Configuration Mistakes
- A cross-domain error occurs when calling the
api/v1/chat/completionsinterface. The browser console returns CORS-related status codes. The cause is that the allowed frontend domain name whitelist is not configured in the FastGPT backend. - The model returns the "chat:llm-model-response-empty" error. No valid data is returned after tool calling. The cause is that the data source mapping for tool calling is not correctly configured, so ledger data for state-owned capital investment companies cannot be associated.
- The MCP server is mistakenly set as a required configuration. Tool calling cannot start normally. The cause is confusing the usage scenarios of built-in tools and external MCP servers. Some lightweight ledger pulling scenarios do not require enabling the MCP server.
How to Verify Correct Configuration
- Initiate a single tool call test, and check if the returned results include standard field data for the specified ledger.
- Check the FastGPT interface call logs to confirm there are no cross-domain errors, timeouts, or missing field records.
- Generate a test report, and verify that the output content complies with the format and field requirements of state-owned assets supervision.
- Adjust the
toolChoiceparameter to manual specification, and confirm that tool calling can perform corresponding operations according to the preset logic.
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.