Knowledge Base Retrieval and Recall for Internal Policy Compliance

Internal policy data comes from official documents released by enterprise compliance and administrative departments. Update cycles occur irregularly

What data for this category looks like

Internal policy data comes from official documents released by enterprise compliance and administrative departments. Update cycles occur irregularly in line with regulatory policy adjustments or internal process optimizations, and most updates take place after quarter-end or regulatory windows. Most documents use structured formatting, including section numbers, effective dates, release document numbers, applicable scopes, core clauses, violation scenarios and corresponding corrective measures. Some documents include supporting execution tables and approval process templates. Fields include policy numbers, releasing entities, applicable job levels, penalty amount ranges, time limit requirements, and more. Units include workdays, job levels, business amounts, and others.

What constraints these characteristics impose on knowledge base retrieval and recall

The formal nature of internal policies requires that retrieval results match currently active versions. Expired documents must be filtered out using effective dates. Structured section formatting requires that retrieval preserves the contextual logic of clauses, and scattered individual sentences must not be retrieved. Supporting attached tables must have all entries fully extracted, to avoid missing data. Field limitations such as job level and amount require that retrieval uses the user’s business scenario for precise filtering, to avoid retrieving inapplicable clauses. The irregular update cycle also requires full synchronization to be triggered regularly, and incremental updates must use release dates as the core identifier.

How to set configurations

Configuration ItemRecommended ValueRationale
recall counttop 10-15Internal policy clauses are mostly coherent structured content. Too many recalled results lead to redundant context, while too few may miss relevant core clauses
similarity threshold0.75-0.85Internal policy terminology is precise and standardized. This range avoids retrieving irrelevant broad entries while covering policy content with similar phrasing
PARSE_FILE_TIMEOUT_SECONDS120 secondsSome internal policy documents include multi-page supporting tables, which take longer to parse. Sufficient parsing time must be reserved
chunk length800-1000 charactersInternal policy clauses are mostly complete section content. Too long a chunk breaks clause logic, while too short a chunk splits coherent penalty or process explanations
incremental sync trigger conditionupdate by release dateInternal policy updates use effective dates as the core identifier. Triggering updates by release date accurately pulls the latest active policy versions
reranked return counttop 5Users querying compliance issues need to see the most directly relevant core clauses first, to avoid excessive irrelevant content interfering with judgment

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require individual analysis, and it is recommended to test against your own samples before finalizing settings.

Three common mistakes

  • Issue: An error MongoServerError: The dollar ($) p occurs when deploying a knowledge base plugin in FastGPT v4.13.0 and connecting to MongoDB 4.4.29. Cause: A compatibility issue exists between the current version of the plugin and certain query syntax in MongoDB 4.4.29. The plugin dependency version must be adjusted or the database version upgraded.
  • Issue: When exporting the knowledge base, only a single summary file is generated, and the classification structure of multiple policy documents cannot be retained. Cause: The multi-file subdirectory export configuration for the knowledge base is not enabled, or the flag to retain source file structure is not checked during export.
  • Issue: The AI-retrieved policy table content only covers partial entries, and all data cannot be fully extracted. Cause: The chunk length parameter is not adjusted to adapt to long table text, or the row-by-row extraction configuration for table parsing is not enabled, leading to truncation of partial row data.

How to confirm configurations are set correctly

  • Manually upload a latest internal policy document, and check if core fields such as section numbers, effective dates and release document numbers are retained after parsing.
  • Submit a compliance-related business query, and verify that the number of recalled results matches the preset recall count configuration, and that the similarity of each result meets the threshold requirement.
  • Export the current knowledge base, and check if the export files generate multiple independent files sorted by policy, or a single summary file.
  • Connect to the database, and check that the incremental sync task only pulls newly released policy documents and does not include expired versions.

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.