What the Data for This Category Looks Like
Coal chemical industry policy and regulatory basis data is mainly sourced from publicly released regulatory documents and industry standards issued by the National Energy Administration, the Ministry of Emergency Management, and the Coal Chemical Industry Standardization Technical Committee. Data updates dynamically with new policy releases, with no fixed cycle. A single document has five core fields: issuing document number, issuing authority, effective date, original clause text, and applicable scenario. The document number format is "Fagai Energy [Year] XX No.", the effective date uses the YYYY-MM-DD format, and the character count of single documents varies widely.
What Constraints These Characteristics Impose on Tool Calling and Plugins
Structured official policy data requires tool calling to only connect to compliant public data sources, avoiding non-authoritative information. The multi-field structure requires tool calling nodes to accurately extract three core fields: issuing document number, effective date, and core clauses, and filter redundant content. The wide range of document character counts requires tool calling to support long text parsing, and also requires validating the format of the effective date field to ensure accurate matching of policy timeliness during Q&A. Dynamically updated data requires syncing the knowledge base indexes linked to plugins to avoid policy version mismatches.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool calling trigger method | Trigger based on knowledge base matching threshold | Coal chemical policy data requires first retrieving and matching relevant clauses before calling tools for verification, to avoid invalid calls |
| Maximum tool calling times | 3 times | Single-round policy Q&A does not require multiple file calls, to avoid context overload |
| Tool return result limit | Top 3 entries | The number of public policy documents in the coal chemical industry is limited; returning too many will increase context burden |
| Context window length | 8000–12000 characters | Adapts to the full clause length of a single policy document |
toolChoice | auto | Allow the model to independently decide whether to call tools for policy queries, adapting to questions of varying complexity |
functionCall | Enabled | Force the model to return results using the tool calling format, ensuring output can be parsed by the system |
Three Common Mistakes
- Phenomenon: Enabling tool calling prevents knowledge base queries, returning empty results. Cause: Incorrect execution order configuration between the tool calling node and knowledge base retrieval node. Tool calling occupies context first, leaving no resources reserved for knowledge base retrieval.
- Phenomenon: Two thinking processes appear when debugging the workflow, with chaotic output format. Cause: The
functionCallparameter is not configured correctly, causing the model to generate both natural language responses and tool calling instructions, leading to duplicate thinking. - Phenomenon: Missing fields when calling MCP tools to obtain policy data. Cause: Core fields to be extracted are not specified in the tool configuration, resulting in returned policy data containing redundant content or missing key information such as document number and effective date.
How to Confirm the Configuration Is Correct
- Initiate a specific coal chemical policy query, such as "What are the capacity control policies for the coal chemical industry in 2024", and check if the returned results include matching policy document numbers and effective dates.
- View workflow logs to confirm that the tool calling node only triggers the specified number of times, with no repeated or invalid calls.
- Debug the workflow to check if the tool calling output fields include the three core contents: document number, effective date, and core clauses, with no redundant irrelevant information.
- Test timeout scenarios: intentionally extend tool calling duration, confirm that the system terminates the request and returns an error prompt according to the configured timeout period.
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.