What Data for This Category Looks Like
Crop farming investment research data draws from multiple sources. These include publicly monitored data from the Ministry of Agriculture and Rural Affairs, crop trial reports from local agricultural academies, on-farm farmer planting logs, agricultural product spot price data, and hourly observational data from meteorological stations. Update cycles vary widely. Meteorological data updates daily or hourly. Crop trial reports update quarterly or annually. Spot price data updates daily. Farmer logs upload on a regular schedule. Document types range from tens of thousands of-word annual planting zoning reports, to thousands of-row crop pest and disease control Excel spreadsheets, to single-page crop planting specification Word documents. Common fields include crop variety, growth stage, mu yield, pest and disease severity, meteorological thresholds, and more. Most units follow standard agricultural production conventions, such as kilograms per mu, millimeters, and degrees Celsius.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
The multi-dimensional structure of crop farming data and differences in update frequencies require multi-turn dialogue to retain core context parameters such as crop variety, planting region, and growth stage. This prevents fuzzy matching across different crop categories. The presence of long documents and large structured spreadsheets requires prompt engineering to explicitly define field formats and units. This stops AI outputs from mixing units or omitting critical data points. Differing update cycles for data require prompts to distinguish between static historical data and dynamic real-time data. This ensures the AI prioritizes access to the latest meteorological and price data. Large file processing increases context window load. This requires limiting the context length of single-turn dialogue to avoid token overflow.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
CORS_ALLOW_ORIGINS | Set to the frontend access domain name (e.g. https://your-agri-platform.com) | Resolves cross-domain request error issues when calling the dialogue interface from the frontend |
maxContext | 8000–12000 characters | Adapts to the context retention needs of crop farming multi-turn dialogue, prevents loss of core planting parameters |
chunk_size | 800–1000 characters | Splits long documents and large Excel spreadsheets, balances information completeness of individual segments and recall accuracy |
top_k | Top 6 entries | Covers recall needs for multi-dimensional data including meteorology, pest and disease control, and yield, avoids omission of critical information |
rerank_top_k | Top 3 entries | Filters redundant identical-type planting solution data, improves dialogue response speed |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports upload and parsing of 100,000-character Chinese documents and 15,000-row Excel spreadsheets |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to parsing time requirements for large structured spreadsheets, prevents parsing failures |
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. Testing on own samples is recommended before finalizing settings.
Three Common Misconfigurations
- Symptom: The frontend calls the
/api/v1/chat/completionsinterface and returns a CORS-related error or 403 status code. Cause: TheCORS_ALLOW_ORIGINSparameter is not configured correctly, or the configured value does not cover the frontend access domain name. - Symptom: Dialogue response time exceeds 30 seconds, or a
504 Gateway Timeoutstatus code appears. Cause: The values oftop_kandrerank_top_kare too high, or thePARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted to fit large file parsing needs. - Symptom: After importing a 100,000-character Chinese document or 15,000-row Excel spreadsheet, recall results fail to match user queries. Cause: The
chunk_sizevalue is unreasonable, or theUPLOAD_FILE_MAX_SIZEconfiguration does not allow large file uploads.
How to Verify Proper Configuration
- Access to the frontend configured domain name is initiated. A test dialogue including "winter wheat mu yield" and "recent precipitation data" is run. No cross-domain errors are detected.
- A 15,000-row structured Excel spreadsheet and a 100,000-character Chinese document are uploaded. Knowledge base parsing logs are checked. No timeout or parsing failure records are confirmed.
- Two linked dialogue turns are initiated. For example, first query "corn planting density", then follow up with "meteorological recommendations for the corresponding region". Context parameters are confirmed to be retained correctly.
- Backend dialogue logs are reviewed. Token consumption for each dialogue is fully recorded. Data can be extracted and calculated via the corresponding interface.
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.