What data for this category looks like
Advanced chemical materials internal office data mainly comes from an enterprise's internal LIMS laboratory information management system, ERP production management system, process manuals and compliance documents. Data update schedules are adjusted based on production batches and technical transformation projects. Raw material batch data is updated upon completion of each production batch, and process parameters are updated every 1-3 months along with equipment technical transformations. Document structures primarily consist of structured tables, containing fields such as material grade, density, tensile strength, elongation at break, production batch number, quality inspection date, compliance level and other fields. Most field units use standard chemical measurement units such as g/cm³, MPa. A single document covers full-dimensional performance and production-related information for a single material category.
What constraints these characteristics impose on tool calling and plugins
Structured multi-field data requires tool calling to accurately match specified fields, avoiding invalid results caused by fuzzy retrieval. Dynamically updated batch data requires plugins to support real-time pulling of the latest data. Static caching cannot adapt to high-frequency updated production scenarios. The presence of compliance fields requires tool calling to verify the compliance level of returned results, preventing output that does not meet safety standards. Multi-dimensional parameters in a single document require tool calling to limit the number of returned entries, preventing context window overload which would affect model responses. Tools used in chemical scenarios mostly connect to internal dedicated systems, requiring adaptation to enterprise intranet access permissions and response delays.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | ["auto"] or specified as ["get_material_performance", "check_batch_compliance"] | The advanced chemical materials scenario requires precise calling of specified tools. Auto mode can automatically match tools, and specifying tools can avoid irrelevant calls, adapted to FastGPT v4.17.0 |
functionCall | Set according to actual measurements | Needs to adapt to the input parameter format of internal enterprise tools to avoid call failures caused by parameter mismatches |
| Tool call timeout period | 30–60 seconds | Querying chemical data requires connecting to internal LIMS or ERP systems, and response delays are generally higher than general-purpose interfaces |
| Number of entries returned by a single tool call | First 3 entries | There are many performance parameters for a single material category, limiting the number of returned entries can avoid context overload |
| Tool result cache duration | 12 hours | The update frequency for raw material batches is typically weekly, caching can reduce repeated requests and balance data timeliness and system load |
Three common mistakes
- Phenomenon: A cross-origin error is returned when calling the
api/v1/chat/completionsinterface, and the front-end console displays CORS-related status codes. Cause: No cross-domain allowed domain whitelist is configured in the FastGPT backend, or the response headers are not set correctly. - Phenomenon: The error "chat：llm—model—response-empty" is returned during tool calling. Cause: The
toolChoiceparameter is not configured correctly, or the result format returned by the tool does not meet the model requirements, causing the model to fail to generate a valid reply. - Phenomenon: The MCP server cannot be properly connected by FastGPT after startup. Cause: The port of the MCP server is not opened to the enterprise intranet, or the correct service address is not filled in the FastGPT plugin configuration.
How to confirm the configuration is complete
- Enter the FastGPT tool call test page, enter a command to query chemical material performance, and check whether the returned results contain the specified material fields.
- View the FastGPT plugin logs to confirm that the parameters of the tool call request are consistent with the configuration items, and there are no format errors.
- Simulate a cross-origin request, check whether the browser console still displays CORS-related errors, and confirm that the cross-domain configuration takes effect.
- Wait for the cache duration to expire, call the tool again, and confirm that the returned data is the latest updated data.
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.