What data for this category looks like
Data for database operations requirements and design documents typically comes from database monitoring, audit logs, SQL execution plans, and ticketing systems. Daily produced documents include database change orders, slow SQL reports, backup records, and permission application forms. Each document contains fields such as instance name, SQL statement, change time, permission level, and backup path. Update frequency is mostly daily or after each database change.
What constraints these characteristics impose on context and token handling
Data sources for this category are scattered and have varying formats. Token consumption differs significantly across documents. Long text content such as slow SQL reports may use large amounts of tokens. Uncertain update frequencies require context to support dynamic loading of recent data, to avoid interference from expired information. Associated queries across multiple document types need to retain cross-document context associations. Unreasonable token allocation may lead to key information being truncated. Ticketing systems also have many associated entries. The volume of content recalled in a single request may easily exceed the token limit, affecting query accuracy.
How to set configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the typical paragraph length of database change orders and slow SQL reports, avoids exceeding token limits for single chunks |
| Overlap Length | 100–200 characters | Retains context for cross-chunk SQL statements and change steps, prevents logical breaks |
maxContext | 8000–12000 tokens | Adapts to associated query needs for multiple tickets and monitoring logs, covers the total token volume of typical operation and maintenance documents |
quoteMaxToken | 2000–3000 tokens | Limits token consumption for a single recalled content piece, avoids context overload |
| Single Recall Limit | Top 6 entries | Matches the number of associated entries in database operation and maintenance tickets, balances recall precision and token consumption |
| Reranking Priority | Sorted by change time in descending order | Prioritizes recalling recent permission applications and backup records, aligns with daily operation and maintenance troubleshooting logic |
Three common configuration errors
- Setting
maxContextto 2000 tokens, which prevents the complete execution plan of a slow SQL report from being read fully. The system prompts that the context length is insufficient. This occurs because parameters are not adjusted based on the long text characteristics of database operation and maintenance documents, and default values are insufficient to cover the token requirements of a single long report. - Using default configuration without adjusting chunk length, which causes slow SQL reports in Excel format to be split into overly small chunks, leading to duplicate matching and overly coarse granularity issues. This occurs because chunking rules are not adjusted for structured table documents in this category, meaning data chunks cannot fully correspond to single slow SQL entries.
- Incorrect configuration of
AIPROXY_API_ENDPOINT(the root address of the AI Proxy service, for example http://aiproxy:3000, do not append paths such as /v1 or /chat/completions) andAIPROXY_API_TOKEN(the AI Proxy administrator token, must match the AI Proxy server configuration and cannot be empty). This causes App/Admin service startup verification failures, or API calls returning 401 unauthorized or connection timeout errors. This occurs because required environment variables are not configured during App/Admin service deployment, or an incorrect proxy root address or administrator token that does not match the server is used.
How to confirm configurations are correct
- Upload a typical slow SQL report, check the chunk preview interface, and confirm that the length of each data chunk falls within the set chunk length range.
- Initiate an associated query for a permission application form, and check that the number of recalled results matches the set single recall limit.
- View system logs, and confirm that the App/Admin service loads the correct
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENenvironment variables during startup, with no startup verification failures, 401 API call errors, or timeout errors. - Test context associated queries for change orders, and confirm that the total token volume of recalled related tickets and monitoring data does not exceed the set
maxContextvalue.
Note: The configuration values listed above are common starting points. Adjustments should be made based on specific samples and use cases.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.