What the data for this category looks like
Oil and gas exploration and development ledger data mainly comes from well logging data collection systems, logging interpretation platforms, oil and gas production IoT platforms, and development plan management systems. Real-time production data refreshes every 15 minutes. Basic well-level ledgers are updated quarterly. Monthly development reports are generated each month. Well-level ledgers include fields such as well ID, well depth, lithology, daily oil production, and water cut. Units include meters, cubic meters, tons, and percentage. Block-level summary ledgers include fields such as cumulative oil production, newly proven reserves, and per-well production capacity. Data structures are categorized by exploration and development stage.
What constraints these characteristics impose on the tool calling and plugin workflow
Scattered data sources require the tool calling process to orchestrate multi-source HTTP plugins, triggering pull requests by data type. Data sources with different update frequencies require differentiated polling intervals. This avoids frequent calls to real-time systems or missed static ledger updates. Inconsistent field units require built-in unit conversion logic in plugins to ensure consistency of summarized data. Long document structures require tool calling context configuration to adapt to large text processing, preventing truncation of critical ledger information.
How to set up the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Multi-source plugin trigger order | Sort by data update priority, pull real-time data first | Aligns with real-time data requirements for oil and gas exploration and development |
toolChoice | Auto | Adapts to multi-tool calling scenarios, no manual tool specification required |
functionCall | Enabled in bulk | Supports calling multiple data pull plugins simultaneously |
| Plugin timeout duration | 600 seconds | Accommodates time required for long document reading and cross-system data summarization |
| Unit conversion switch | Enabled | Unifies field units across different systems |
| Context length | 8000–12000 token | Meets processing requirements for long ledger documents |
Three common mistakes
- Empty fields are returned after calling an external API. The cause is that no authentication key for the oil and gas production system was added in the plugin configuration, so the request was not authorized.
- Tool calling results are output directly, not saved as context data passed to the large model. The cause is that no result transfer node was added to the workflow, and the ledger data returned by the tool was not saved as usable data.
- Plugin execution times out. The cause is that the plugin timeout duration was not adjusted, and the time required for reading and summarizing long ledger documents exceeded the default threshold.
How to confirm the configuration is complete
- Navigate to the FastGPT plugin management page, check the authentication status of each data source plugin, and confirm that a successful connection is displayed.
- Run a test workflow, view the tool calling logs, and confirm that all configured plugins successfully pulled ledger data from the corresponding systems.
- Initiate an API call, check that the returned response body includes summarized ledger fields and that units have been uniformly converted.
- View the output results of workflow nodes, confirm that tool calling results are correctly saved as context data and not directly output externally.
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.