What the data for this category looks like
Agrochemical product research report data comes from public monitoring data from basic chemical industry associations, regular financial reports of listed agrochemical enterprises, pesticide and fertilizer supply and demand monitoring reports from the Ministry of Agriculture and Rural Affairs, and third-party specialized sector consulting research reports. Update frequencies vary: corporate financial reports are updated quarterly, industry monitoring data is updated monthly, and specialized production capacity and price research reports are released per project cycle.
Single document lengths vary widely, ranging from thousands of words of industry briefings to tens of thousands of words of full industrial chain analysis. Document structures typically include core indicators, policy interpretations, upstream and downstream industrial chain data, and corporate dynamics. Fields include product name (e.g., glyphosate, compound fertilizer), unit (ton, yuan/kg, hectare), time dimension, regional distribution, and more.
What constraints do these characteristics impose on HTTP interfaces and external systems
The multi-source nature, varied document lengths, and specific field units of agrochemical product research reports create multiple constraints for HTTP interface and external system integration.
Connect to multiple interfaces including industry associations and corporate financial reports for multi-source data. Configure independent authentication parameters to adapt to the verification rules of each data source. The wide span of document lengths requires adjusting the interface’s segment parsing threshold for long-text retrieval, to avoid truncating core content. Interface return fields must include unit identifiers to meet specific unit requirements. External systems must add unit verification logic to prevent data misuse. For retrieval needs organized by product category, preset classification filter parameters such as product_category in the interface to support precise retrieval of specific product segments.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | A single longest agrochemical research report can reach tens of thousands of words, requiring sufficient time to complete full-text parsing |
maxContext | 8000–12000 characters | Adapt to context recall for long documents, covering complete industry analysis paragraphs |
| Number of recalled entries | Top 8–12 entries | Agrochemical research reports have multiple specialized dimensions, requiring a sufficient number of related documents to support precise question answering |
| Similarity threshold | 0.72–0.80 | Balance retrieval accuracy and recall coverage, avoiding missing relevant research reports for specific product segments |
UPLOAD_FILE_MAX_SIZE | 500 MB | Single long research report files have large volume, so the upload limit needs to be relaxed |
external_api_auth_type | Configured per data source | When connecting to multi-source external data, adapt to the authentication rules of different interfaces, such as API Key, OAuth2 |
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 specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common errors
- Phenomenon: Calling the HTTP interface returns
401 Unauthorizedwith a prompt about conflicting authentication information. Cause: Duplicate model parameter configuration inconfig.json, failing to distinguish between global model binding and independent configuration of external data sources, resulting in overwritten authentication logic. - Phenomenon: Triggering
504 Gateway Timeoutwhen executing a local curl test command, or TSX project compilation failure. Cause: Failure to adjustPARSE_FILE_TIMEOUT_SECONDSto adapt to long research report parsing, or incorrect configuration of local development environment variable paths, leading to abnormal dependency loading. - Phenomenon: Values with mixed units appear in retrieval results after external systems sync research reports. Cause: Failure to enable unit verification logic in the interface configuration, and failure to bind the unique unit field rules for agrochemical products, resulting in lost or incorrect units during data parsing.
How to verify correct configuration
- Execute a local curl test command, check if the research report data returned by the interface includes unique product names and unit fields for agrochemical products, and verify field completeness.
- View the synchronization logs of the external system, confirm that the authentication status of multi-source data interfaces is normal, with no connection timeout or permission denied errors.
- Trigger a retrieval request, verify the matching logic between the number of recalled research reports and the similarity threshold, and adjust parameters to the range that meets business requirements.
- Upload a single long research report file, confirm that the upload progress is normal, with no file size limit exceeded prompts.
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.