Multi-turn Dialogue and Prompt Engineering for Electronic

What the Data for This Category Looks Like

This category’s data mainly comes from public periodic reports of listed companies disclosed by domestic and overseas stock exchanges, and industrial operation data released by third-party industry research institutions. Quarterly reports are disclosed within 30 days after the end of each quarter. Annual reports are disclosed before April 30 of the following year. Document structures include revenue details of business segments, production capacity and shipment data, cost composition, R&D investment, and downstream application proportions. Fields include revenue amount, shipment volume, cost proportion, and other metrics for specific product categories. Units include electronic component-exclusive measurement methods such as ten thousand RMB, million units, and similar units. Some enterprises with a high proportion of overseas sales also include data related to exchange gains and losses.

Constraints for Multi-turn Dialogue and Prompt Engineering

The multi-source data feature of electronic component financial reports requires multi-turn dialogue to support context association across data sources, ensuring coherent responses to questions that cross financial reports and industry data. Exclusive measurement units require prompt engineering to specify unified unit conversion rules, avoiding unit confusion for fields such as shipment volume and revenue. The high-frequency disclosure rhythm requires the dialogue system to support context locking for specified report periods, preventing use of expired data. The diverse segmented product category structure requires prompt engineering to guide users to specify specific component types, reducing result deviations caused by vague questions. Multi-turn dialogue must also support step-by-step follow-up inquiries for detailed data on segmented dimensions.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Electronic component financial report PDFs usually contain multiple sets of segmented category charts, and a single file can reach hundreds of MB in size, requiring adaptation to large file upload requirements
`UPLOAD_S3_PRE_SIGN_EXPIRE`	`300 seconds`	Large file uploads require a longer pre-signed validity period to avoid pre-signed expiration errors during upload
`maxContext`	`8000–12000 characters`	Multi-turn follow-up inquiries need to retain context information for multiple product categories and periods, preventing information loss caused by context overflow
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Text parsing of large annual reports requires a longer processing time to avoid interrupting the parsing process due to timeout
`Recall Count`	`Top 8–10 entries`	Segmented category information in electronic component financial reports is scattered, requiring recall of a sufficient number of relevant fragments to cover multi-dimensional data
`Similarity Threshold`	`0.75–0.85`	A large number of professional segmented terms exist in electronic components, requiring balance between recall accuracy and coverage to avoid missing relevant fragments

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 specific analysis, and it is recommended to test on local samples before finalizing.

Three Common Misconfigurations

Symptom: After upgrading to version 4.14.3, the error fail to create post presigned url triggers when uploading financial report files or text datasets, and the template import function can upload files normally. Cause: The UPLOAD_S3_PRE_SIGN_EXPIRE parameter configuration value is too small, or the interface path does not adapt to the S3 upload logic of the new version, leading to failed pre-signed URL generation.
Symptom: When following up on segmented category data in multi-turn dialogue, returned results do not clearly specify the corresponding measurement unit, causing unit confusion. Cause: Prompt engineering does not clearly require unified conversion of electronic component-exclusive measurement methods, and does not mark unit rules in the context.
Symptom: After parsing large annual reports, the number of recalled relevant fragments is insufficient to cover the revenue data of segmented categories. Cause: The Recall Count configuration value is too low, or the Similarity Threshold is set too high, filtering out relevant fragments of some segmented categories.

How to Verify Correct Configuration

Upload a typical electronic component annual report PDF, confirm the upload process has no errors, and check the upload log to verify normal pre-signed URL generation.
Initiate a multi-turn dialogue: first ask about total revenue, then follow up on revenue data for a specific segmented category, confirm the context is correctly retained, and the returned results include clear category and period information.
Adjust the Recall Count and Similarity Threshold configurations, test the number of recalled fragments under different values, and confirm all required segmented category data is covered.
Trigger the file parsing task, check the parsing duration, and confirm the timeout limit specified by PARSE_FILE_TIMEOUT_SECONDS is not exceeded.

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.