What the Data for This Category Looks Like
Computer equipment financial report data comes primarily from publicly disclosed stock exchange platforms and official announcements from listed companies. Updates follow a quarterly and annual report cycle, with temporary announcements released irregularly. Documents are structured around tables, including consolidated balance sheets, income statements, and cash flow statements, plus written notes on items such as R&D investment and revenue composition. Fields include original fixed assets, revenue scale, R&D investment amount, and more. Most units are RMB yuan and RMB ten thousand yuan. Some fields cover metrics like equipment count and depreciation period.
Constraints Imposed on Multi-turn Dialogue and Prompting
The mixed structured and unstructured nature of financial reports requires multi-turn dialogue to differentiate between structured field queries and natural language follow-up questions, to avoid context confusion. The periodic update schedule requires prompts to clearly state data cutoff times, to prevent expired data from being used in responses. The highly professional and varied set of fields requires built-in term mapping rules, to ensure consistent understanding of fields such as fixed assets and R&D expenses across multi-turn dialogue. The long length of single documents requires limiting total context length or chunking financial report data during recall, to avoid exceeding model processing limits.
How to Configure Parameters
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Core structured data of a single computer equipment financial report is approximately 5000 characters. Multi-turn dialogue needs to retain 3 rounds of context to avoid context overflow |
similarityThreshold | 0.75–0.85 | Financial report fields for computer equipment have high professional requirements. A higher similarity threshold is needed to filter irrelevant recalled content |
recallCount | Top 6–8 entries | Financial reports cover multiple categories of fields such as revenue, assets, and R&D. A sufficient number of entries must be recalled to support multi-turn follow-up questions |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | A single annual financial report PDF contains multiple tables, which takes a long time to parse. This avoids mid-process timeouts |
UPLOAD_FILE_MAX_SIZE | 50 MB | Single encrypted financial report PDF with charts usually does not exceed 20 MB. This reserves redundant space |
promptPrefix | Built-in computer equipment financial report term mapping rules, clearly mark data cutoff times | Avoid ambiguity of professional terms, and ensure consistent understanding of financial report fields across multi-turn dialogue |
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 case-by-case analysis. It is recommended to perform testing with custom samples before finalizing settings.
Three Common Mistakes
- Symptom: An invalid token error is returned when calling the dialogue API. The log shows the token field value is
fastgpt. Cause: The model call token parameter was not configured correctly, causing the token to be incorrectly filled with the default value. - Symptom: Subfields of financial reports cannot be accurately matched during multi-turn dialogue, and the returned results do not match the actual financial report content. Cause: No built-in term mapping rules for computer equipment financial reports were included in the prompt, leading to deviations in understanding of professional fields.
- Symptom: After uploading a financial report, it cannot be associated with the specified knowledge base, and dialogue cannot recall financial report data. Cause: The binding parameters between the knowledge base and the application were not configured, causing the parsed financial report data to not be included in the application's recall scope.
How to Verify Proper Configuration
- Invoke the model call verification interface to confirm that the incoming token parameter matches the configured value.
- Upload a single test computer equipment financial report, and check whether the corresponding structured index is generated in the knowledge base.
- Initiate two consecutive follow-up questions, and confirm that the dialogue context is correctly retained and used for generating responses.
- Trigger the knowledge base update operation, and confirm that the parsed financial report data is correctly synchronized to the knowledge base associated with the application.
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.