What Data Looks Like for This Category
Research report data for professional services scenarios is sourced from public industry and company research reports published by licensed financial consulting institutions and securities firm research institutes. Update frequency follows the report release cycle: securities firm reports are updated on trading days, while industry special reports are released as needed. Typical document structure includes an abstract, industry fundamental analysis, target company financial models, valuation conclusions, and risk disclosures. Fields covered include report issuing institution, release date, rating, target price, core business data, and more. Common data units are percentage, yuan, 100 million yuan, and other standard financial industry units.
Constraints Imposed on Tool Calling and Plugins
Individual research reports can be lengthy, with some deep reports reaching tens of thousands of characters. Tool calling must support large file parsing and long context processing. Supported data formats include PDF, Word, and Excel/CSV files with embedded financial tables. Tools must support multi-format parsing and structured field extraction. Data updates follow no fixed schedule, so tool calling must support on-demand loading of the latest research report sources, and be compatible with variations in document formatting across different issuing institutions. Research reports also include multi-dimensional financial fields. Tool calling must explicitly specify target extraction fields to avoid returning redundant content.
Configuration Settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing a single deep research report takes significant time, default timeouts may be insufficient |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Research report documents may contain large numbers of charts and data tables, leading to larger individual file sizes |
maxContext | 8000–12000 characters | Research report content is lengthy, sufficient context must be retained to link cross-paragraph industry and financial data |
Recall Count | Top 8–12 results | Professional services scenarios require precise matching of industry and company-specific research report content; excessive results increase filtering costs |
Similarity Threshold | Calibrated via actual testing | Filtering standards must be adjusted based on the granularity of target topics to avoid redundant results or missed content |
Reranked Return Count | Top 3–5 results | Professional services scenarios require focus on core conclusions; excessive results can interfere with decision-making |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test with your own samples before finalizing settings.
Three Common Mistakes
- Issue: A
413 Request Entity Too Largeerror is returned when uploading a research report file via the HTTP API. Cause: TheUPLOAD_FILE_MAX_SIZEconfiguration has not been adjusted, and the default limit is smaller than the size of the uploaded research report file. - Issue: Global variable parameters do not take effect when calling the application via API, and the returned results lack specified fields. Cause: Global variables were not passed in the required parameter format specified in the API documentation, and variable values were not wrapped in the correct request body fields.
- Issue: After upgrading to version
4.8.10, the original application cannot be used as a tool call, triggering atool not founderror. Cause: After the version update, applications must be configured as team plugins and have tool calling permissions enabled; the original application call chain is no longer valid.
How to Verify Correct Configuration
- Upload the largest single research report file, check if the parsing task completes within the preset timeout period, and verify that the timeout configuration is effective.
- Initiate an API call test, pass custom global variables, check if the returned results include the specified content corresponding to the variables, and verify that the parameter passing logic is correct.
- Configure a team plugin and bind the application, call the plugin in the chat interface, check if the application logic is triggered normally, and verify that the post-update plugin configuration is correct.
- Upload CSV research report data containing structured tables, compare the dataset generated in the interface with the fields of the dataset created via API, and verify that the format parsing configuration is effective.
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.