What the Data for This Category Looks Like
Data for packaging and printing financing daily reports comes from three sources: daily public financing filings of enterprises released by the national packaging and printing industry association, financing announcements in the light manufacturing sector from local industry and information departments, and publicly disclosed financing information of unlisted packaging and printing enterprises. The update rhythm is that full data from the previous day is compiled and released every early morning. The data uses a structured format, with each record containing eight core fields: enterprise name, unified social credit code, financing subject type, financing amount (unit: ten thousand yuan), financing channel, financing purpose, release date, and public source. The financing purpose field often includes packaging-specific business phrases such as carton production equipment procurement and raw material stock preparation.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Multiple data sources lead to inconsistent field formats across different public channels. Some financing amounts are written in Chinese uppercase. The granularity of keywords in financing purposes varies. These factors require prompts to include format standardization rules and category-specific keyword matching logic. The daily update rhythm requires dialogues to default to focusing on same-day or specified single-day data. Multi-turn dialogues must retain historical filter conditions, which creates requirements for context storage capacity. The unified social credit code, as the unique identifier field, requires multi-turn dialogues to associate this field to achieve precise deduplication and matching. Specialized terminology for financing purposes requires prompts to limit query scope only to financing entries related to packaging and printing.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | This category has many fields per record. Multi-turn dialogues need to retain 3-5 rounds of historical query conditions and results. This range covers context storage needs for regular dialogues. |
json_schema | {"type":"object","properties":{"Enterprise Name":{"type":"string"},"Financing Amount":{"type":"number"},"Financing Channel":{"type":"string"}},"required":["Enterprise Name","Financing Amount"]} | Core query needs focus on enterprises and financing amounts. This schema enforces structured results, suitable for subsequent automated data processing. |
recall_top_k | Top 10 entries | Daily data volume is moderate. Recalling 10 entries covers regular query result needs, avoiding excessive redundant information interfering with dialogue. |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Documents are compiled from multi-channel public content. Parsing takes longer. This duration avoids task interruption mid-execution. |
prompt_template | Based on the uploaded packaging and printing financing daily report data, {user question}, only return entries corresponding to financing activities of packaging and printing enterprises | This limits the dialogue scope to the packaging and printing category, filtering out financing data from unrelated industries. |
response_format_type | JSON | Structured replies are suitable for subsequent batch processing and system integration, aligning with the business logic of this scenario. |
The parameter values provided on this page are general recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Analyze specific issues on a case-by-case basis, and testing on applicable samples is recommended before finalizing.
Three Common Configuration Mistakes
- Phenomenon: Subsequent queries in multi-turn dialogues cannot associate historical filter conditions, and returned results do not match the scope of the first query. Cause: The
maxContextconfiguration value is insufficient, not retaining enough historical context, or the dialogue context storage function is not enabled. - Phenomenon: Returned results include financing entries from non-packaging and printing enterprises, and some fields are empty. Cause: The prompt template does not include category-specific filtering rules, and does not limit the keyword matching logic for financing purposes or the enterprise's industry.
- Phenomenon: Dialogue execution times out, and the interface displays status code
504 Gateway Timeout. Cause: ThePARSE_FILE_TIMEOUT_SECONDSconfiguration value is too small, not adapting to the parsing time of multi-channel compiled documents for packaging and printing financing daily reports.
How to Confirm Configuration is Correct
- Upload a single sample of packaging and printing financing daily report, trigger a test dialogue, and verify that returned results only include financing entries from packaging and printing related enterprises.
- Initiate two consecutive dialogues: first filter financing data for a specified date, then query financing entries of a specific type within that date, and verify that subsequent queries retain historical filter conditions.
- View the reply content in the dialogue card, and verify that the returned format conforms to the preset JSON structure with no syntax errors.
- View the task execution log, and verify that the parsing time does not exceed the configured
PARSE_FILE_TIMEOUT_SECONDSvalue, with no timeout-related errors present.
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.