Tool Calling and Plugins for Energy Storage Research Report

What the data for this category looks like

Energy storage research report data comes from public statistics from domestic energy storage industry associations, research reports on power equipment subdivisions from securities firms, and technical white papers released by leading energy storage manufacturers. Update cycles are adjusted based on industry policy milestones and monthly installed capacity data release schedules. Core installed capacity and cost data are updated monthly or quarterly. Reports on new energy storage technology iterations are released irregularly. Document structures include core summaries, industrial chain link breakdowns, quantitative indicators, and policy interpretations. Fields include publishing institution, release date, installed capacity unit GW, levelized cost of electricity unit yuan/kWh, cycle life unit times, and more. Long research reports usually include chapter-by-chapter technical details and market size forecasts.

Constraints for Tool Calling and Plugins

Multiple core indicators in energy storage research reports use different units. This requires mandatory unit validation during tool calling, to avoid confusing units of different magnitudes. Non-fixed update cycles require the plugin to use a dynamic pull mechanism. Long-term caching of research report data is prohibited. The latest data source must be confirmed each time the tool is called, to avoid returning outdated installed capacity or cost data. The multi-chapter structure of long documents requires tool calling to support targeted recall by chapter. This avoids redundant content interfering with the large model context window. Specific industrial chain subdivision fields require the tool to have preset matching templates. This ensures extracted indicators align with industry general standards, and improves the accuracy of tool calling.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`tool_call_max_retries`	`2-3 retries`	Most tool call failures stem from temporary network or interface fluctuations. Retrying 2-3 times covers most temporary faults, and avoids excessive retries that consume resources.
`recall_chunk_size`	`800-1200 characters`	Energy storage research reports often contain long paragraphs of technical and market analysis. Segments of 800-1200 characters retain complete indicator context, and avoid breaking logical flow during splitting.
`rag_similarity_threshold`	`0.75-0.85`	Energy storage research reports contain many professional terms. A threshold that is too low introduces irrelevant content, while a threshold that is too high may miss relevant chapters. 0.75-0.85 balances recall precision and coverage.
`parse_file_timeout_seconds`	`600 seconds`	A single energy storage research report can be tens of thousands of characters long. Parsing long documents requires a longer timeout period. 600 seconds covers most complete parsing workflows.
`tool_param_unit_check`	`Enabled`	Energy storage research report indicators carry a risk of mixed units. Enabling this parameter validation ensures that industry standard units are used during tool calling.
`max_recall_results`	`Top 8-12 results`	Core information in energy storage research reports is distributed across multiple chapters. 8-12 recall results cover most relevant content, and avoid excessive content consuming the context window.

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Misconfigurations

Phenomenon: Tool calls return 408 Request Timeout or Connection refused. Cause: Port forwarding rules for intranet penetration are not configured correctly, preventing external tools from accessing the FastGPT interface address.
Phenomenon: No tool parameters are returned when calling the Gemini model, with no tool call triggered. Cause: The function call function is not enabled in the model configuration, or no preset tool call template matching energy storage research reports is configured for the model.
Phenomenon: Mixed units appear in recalled research report data (such as MW labeled as GW). Cause: The tool_param_unit_check configuration is not enabled, and no unit validation is performed on extracted indicator fields.

How to Confirm Correct Configuration

Manually trigger a tool call, check that the returned research report data contains correct industry units, and confirm that the unit validation configuration is active.
View the FastGPT tool call logs, confirm that the number of retries matches the tool_call_max_retries configuration value, and there are no abnormal timeout errors.
Upload an energy storage research report document, check that the parsed segment length matches the recall_chunk_size setting, with no excessive splitting or overly long paragraphs.
Test the tool call function of the Gemini model, confirm that entering energy storage professional terms triggers the targeted recall of research report tool call workflows.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.