What Data for This Category Looks Like
Data sources for agrochemical product research reports include public statistics from domestic agricultural input industry associations, securities firm industry research reports, regular operating announcements from agrochemical enterprises, and industry analysis documents from international agrochemical organizations.
Core data update cadence is divided into multiple tiers:
- Raw material and product ex-factory prices are updated weekly
- Supply and demand capacity data is updated monthly
- Enterprise operating data is updated quarterly
- Annual in-depth research reports are released per project
Typical document structure includes sections such as industry overview, segmented category capacity/output, price trends, policy impacts, and competitive landscape. Fields include active ingredient content (unit: %), capacity (unit: 10,000 tons/year), ex-factory price (unit: yuan/ton), month-on-month growth rate (unit: %). Some documents include structured charts and policy document number citations.
Constraints Imposed on Multi-turn Conversation and Prompt Engineering
The multi-tier update cadence of agrochemical research reports requires multi-turn conversations to support retrieval limited by time ranges. For example, when a user asks about recent prices, the system automatically filters data sources from the last 7 days.
The diversity of professional fields and units requires prompt engineering to explicitly require returned results to label corresponding units and statistical periods. This avoids data confusion.
The large number of professional terms and structured charts in documents requires multi-turn conversations to support user follow-up questions about term definitions or extraction of specific values from charts. It also requires retaining professional contextual association information to avoid logical breaks caused by truncation.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single agrochemical research report is typically 5000-8000 characters long. Multi-turn conversations need to retain contextual professional terms and data associations to avoid truncating critical information |
recallTopK | Top 8–12 results | There are many segmented categories in agrochemical research reports. Sufficient recall is needed to cover relevant content across segmented tracks, while avoiding redundant information interference |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Single agrochemical research report contains multiple charts and structured tables, which take longer to parse. Sufficient time must be reserved for complete parsing |
similarityThreshold | 0.75–0.85 | Professional term matching for agrochemical research reports has high requirements. A threshold that is too low will introduce content from unrelated tracks, while a threshold that is too high will miss relevant segmented reports |
promptTemplate | Add fixed rules to the base prompt: clearly label units and statistical periods for all data, and add brief definitions for involved professional terms | Agrochemical data has strong professional units and terms, to avoid user misunderstanding due to missing information |
toolCallEnable | Enabled | Support users to call data extraction and chart generation tools to meet personalized needs of multi-turn follow-up questions |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific scenarios require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: Conversation response times out, returns 504 status code. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted. Chart parsing for agrochemical research reports takes longer than the default threshold, causing overall conversation timeout. - Issue: Generated charts are empty after calling the chart tool. Cause: The prompt does not explicitly require extraction of structured values corresponding to charts. Only text-image mixed research report content is recalled, and no chart data is available for visualization generation.
- Issue: The large language model returns empty content or an error, and the frontend displays a blank page. Cause: No fallback logic is configured for
toolCallErrorHandler. When no matching results are found or tool calls fail, no clear prompt information is returned, and empty content is sent directly.
How to Verify Proper Configuration
- Upload a single agrochemical research report longer than 6000 characters, check that no timeout errors occur during parsing, and confirm parsing time falls within the range set by
PARSE_FILE_TIMEOUT_SECONDS. - Initiate a multi-turn conversation: first ask about the current ex-factory price of a specific agrochemical product, then follow up to ask about the unit and statistical period. Check that the returned results clearly label the corresponding information, with no ambiguous statements.
- Enable the tool call function, initiate a query that requires extraction of chart data, and check that visualization content containing the corresponding values is generated with no empty results.
- Initiate a conversation in the team version scenario, check that complete conversation history and retrieval data sources can be exported, and confirm the export function works properly.
- Create a query scenario with no matching data sources, check that a clear prompt message is returned, with no empty content or error messages.
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.