What the Data for This Category Looks Like
Agrochemical product investment research data mainly comes from industry association public reports, listed company periodic announcements, pesticide registration information platforms, and raw pesticide price monitoring databases. Update rhythms vary widely. Industry supply and demand reports are updated monthly or quarterly. Registration certificate information is adjusted dynamically with approval progress. Raw pesticide prices are updated daily.
Documents include structured product parameters, semi-structured research report analyses, and unstructured field trial records. Fields use specialized units: active ingredient percentage is marked as % or g/L, and production capacity is measured in tons/year.
What Constraints Do These Characteristics Impose on the Knowledge Base Retrieval and Recall Process?
The heterogeneous sources, differentiated update rhythms, and specialized field units of agrochemical investment research data create multiple constraints for the retrieval and recall link.
Multi-source heterogeneous data requires the parsing module to support multiple formats including Excel, PDF tables, and structured APIs, to avoid data loss. Differentiated update rhythms require configuring corresponding synchronization cycles based on data types, to ensure timely ingestion of the latest prices, industry reports, and other data. Specialized units and fields require enabling field-level matching logic during retrieval, to avoid invalid recall caused by unit ambiguity. A large number of table documents require support for structured extraction of table content, to ensure accurate recall of table information.
How to Set the Configurations
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
PARSE_TABLE_ENABLE | Enabled | Agrochemical investment research documents contain a large number of structured product parameter tables and dosage tables. Enabling table parsing fully extracts all content |
EMBEDDING_MODEL | text-embedding-ada-002 | Agrochemical specialized fields and units require stable semantic matching capabilities. This model supports professional term recognition and avoids model incompatibility errors |
RECALL_TOP_N | Top 8-12 entries | Agrochemical investment research requires coverage of multi-dimensional information. This range balances recall breadth and context length limits |
SIMILARITY_THRESHOLD | 0.75-0.85 | Agrochemical professional field matching requires a relatively high similarity threshold to filter irrelevant content and ensure recall accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large Excel datasets and multi-page industry research reports take longer to parse. Extending the timeout period avoids parsing interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports importing single large industry report collections and batch product data tables, adapting to investment research data import requirements |
The parameter values provided on this page are all conventional recommendations, used as a starting point for determining configurations. 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: Uploading an .xlsx agrochemical data file results in knowledge base retrieval failing to match field content such as active ingredient content and registered crops in the table. Cause: The
PARSE_TABLE_ENABLEconfiguration is disabled. The parsing module does not extract structured table content, only retaining meaningless plain text fragments. - Phenomenon: Replacing the
EMBEDDING_MODELwith another compatible model causes the interface to return theundefined model must match "^(texterror. Cause: The selected model has not been configured in the deployment environment, or the model name violates the platform's naming verification rules. - Phenomenon: Retrieving graphic and text materials for agrochemical products fails to recall effective ingredient annotation information from images. Cause: Graphic and text parsing configuration is disabled, and professional terms in images are not extracted and retrieved via OCR.
How to Verify Correct Configuration
- Upload an agrochemical data file containing structured tables, and confirm that the knowledge base parsing result completely extracts all fields and content from the table.
- Replace the embedding model with a compatible model other than ada-002, and verify that the embedding task completes normally without error returns.
- Submit a retrieval request for agrochemical specialized terms, and confirm that the number and similarity of recall results align with the preset configuration adjustments.
- After submitting a retrieval, check the reference display option in the conversation interface, and confirm that the source display status is configured as required.
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.