What the Data for This Category Looks Like
Snack food research report data mainly comes from public industry monitoring reports, public disclosures from leading brands, and retail monitoring data from offline supermarkets and online e-commerce channels. Industry-wide research reports are released on a quarterly cycle. Channel sales trends and price fluctuation data are updated monthly. New product-related reports are updated alongside product launch timelines. Document structures typically include modules such as overall industry scale, segmented category share, channel sales structure, operating data of leading enterprises, consumer preference surveys, and supply chain cost analysis. Fields include monthly sales volume, per-box ex-factory price, number of new SKUs, unit supply chain cost, with units of ten thousand yuan, yuan, count, and yuan per kilogram respectively.
Constraints on Multi-turn Dialogue and Prompt Engineering
The characteristics of high-frequency updates, numerous segmented categories, and clear quantified fields in snack food research reports create multiple constraints for multi-turn dialogue and prompt engineering. First, the mixed quarterly and monthly update rhythm requires multi-turn dialogue to support dynamic restriction of retrieval time ranges. Prompts must embed time interval parameters to avoid returning outdated data. Second, segmented categories cover multiple branches such as puffed snacks, candies, and nuts. Multi-turn dialogue must guide users to gradually clarify the specific segmented category. Prompts must include category restriction rules. Third, quantified fields require matching clear units. Prompts must require retrieval results to return original numerical values with units to avoid vague descriptions. Fourth, channel data is finely split. Multi-turn dialogue must support users to switch query dimensions between online and offline channels. Prompts must reserve channel parameter positions.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8 turns of conversation context | Snack food research report retrieval involves continuous follow-up questions. 8 rounds of context fully retain the user's previous category and channel restriction conditions, avoiding dialogue logic breakdown |
Recall count | Top 15 entries | There are many segmented categories of snack foods. Sufficient research report fragments must be retrieved to cover different segmented directions and ensure comprehensive retrieval scope |
Similarity threshold | 0.78–0.85 | Quantified field retrieval requires high matching accuracy to avoid introducing irrelevant research report fragments that interfere with data accuracy |
Rerank result count | Top 6 entries | Filter high-match research report content to ensure information returned by multi-turn dialogue is accurate and not redundant |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | A single snack food research report usually contains multiple pages of data and charts. Sufficient time is required to complete document parsing and field extraction |
UPLOAD_FILE_MAX_SIZE | 600 MB | Some large-scale industry research reports include high-definition data charts. Large file upload support is required to fully load all content |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: API calls return research report data that does not match results from the platform test interface. Cause: Context and prompt configurations consistent with the platform are not included in API call parameters. The API call uses default parameters that do not match the custom settings of the platform test.
- Phenomenon: A 422 error is returned when starting a conversation. Cause: The uploaded research report file exceeds the
UPLOAD_FILE_MAX_SIZElimit, or thePARSE_FILE_TIMEOUT_SECONDSsetting is too short, causing incomplete document parsing and triggering parameter verification failure. - Phenomenon: Multi-turn dialogue fails to accurately return channel-specific sales data. Cause: The prompt does not embed channel restriction parameters, or the
Recall countsetting is too low, missing research report fragments containing channel segmented data.
How to Verify Proper Configuration
- Initiate a single-turn query targeting a specific segmented category. Confirm that returned results only include research report data for that category, and adjust the
Similarity thresholdto the required range. - Initiate more than 3 consecutive follow-up questions, such as first asking about industry scale, then asking about the share of online channels, and finally asking about the per-box ex-factory price of leading brands. Confirm that previous restriction conditions are retained during the dialogue process, and adjust the number of rounds set for
maxContext. - Upload a snack food research report with more than 200 pages. Wait for parsing to complete, then initiate a query. Confirm that parsed field data can be returned normally, and adjust the duration set for
PARSE_FILE_TIMEOUT_SECONDS. - Call the API to initiate a query exactly matching the platform test. Confirm that returned results match those from the platform test interface, and check that API parameters fully match the platform configuration.
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.