What does data for this category look like
Due diligence data for the optical and optoelectronics industry comes from public statistics released by the China Optical and Optoelectronics Industry Association, regular disclosure documents of listed entities, public quotation sheets of upstream wafer and panel manufacturers, and terminal equipment test reports. Update cycles cover monthly supply chain quotation data, quarterly industry prosperity reports, and annual industry white papers. Most documents are structured tables paired with text explanations, including fields such as core product parameters, capacity utilization rate, raw material purchase prices, and patent application volume. Field units include cd/m², Hz, mm, ten thousand yuan/ton and other category-specific identifiers.
What constraints do these characteristics impose on tool calling and plugins
Multi-source heterogeneous data sources require tool calling plugins to support cross-format parsing, adapting to mixed input of structured tables and unstructured text. Differentiated update cycles require configuring layered scheduled pull rules to match the release cycles of different data sources. Category-specific field units require the tool to add unit conversion logic before parameter matching, to avoid confusion of cross-category data. Longer industry report documents require limiting the document slice length per tool call, to adapt to the platform's token calculation rules.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Optical and optoelectronics industry report slices have a relatively long average length, need to cover core parameters and supply chain data to avoid context truncation and loss of key information |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Industry white papers are mostly multi-page structured documents, parsing time is longer than general documents, need to extend the timeout threshold to prevent parsing failures |
MCP_SERVER_PORT | 8080 | Standard plugin service port, avoids conflicts with local other service ports, suitable for rapid deployment |
Recall count | Top 8–10 entries | Optical and optoelectronics due diligence reports need to cover multi-dimensional data such as production capacity, prices, and patents, appropriate recall to ensure comprehensive information |
Similarity threshold | 0.75–0.85 | There are many category-specific parameter units, need to balance recall accuracy and coverage, avoid missing relevant data across units |
UPLOAD_FILE_MAX_SIZE | 200 MB | Industry supply chain data mostly includes batch quotation sheets and test reports, need to support large file uploads |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: After deploying the MCP server version 4.9.6, tool calling has no response and returns a
503 Service Unavailablestatus code. Cause: The access address and port of the MCP service are not configured in the FastGPT workflow, causing the plugin to fail to establish a connection. - Phenomenon: The AI only returns knowledge base recall content and does not trigger the preset due diligence data pull tool call. Cause: The tool call trigger condition is not clearly specified in the system prompt, or the tool node is not connected to the correct execution branch of the workflow.
- Phenomenon: After uploading a jpg-format terminal test report, the AI cannot extract parameters such as brightness and refresh rate. Cause: The image OCR parsing plugin is not configured, or the image input support of the AI module in the workflow is not enabled.
How to confirm correct configuration
- Initiate a query covering panel brightness and supply chain costs, check whether the tool call returns the latest data from the corresponding data source.
- View the workflow running log, confirm that the request status code of the MCP service is
200 OK, and there are no timeout or connection failure records. - Upload jpg-format test reports and structured financial reports, check whether the parsed fields include category-specific units and parameters.
- Adjust the context length parameter, verify that the token consumption of a single round of conversation conforms to the platform's calculation rules, and there is no abnormal truncation.
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.