Knowledge Base Retrieval and Recall for Feed Marketing Content

Feed marketing-related data mainly comes from internal production documents of feed enterprises, raw material quality inspection reports, breeding

What Data Looks Like for This Category

Feed marketing-related data mainly comes from internal production documents of feed enterprises, raw material quality inspection reports, breeding technology manuals, compliance standard documents, and marketing material libraries. Data update rhythm follows raw material price fluctuations, new product launches, and compliance policy adjustments, with no fixed cycle. Core formula documents update at a low frequency, while marketing script templates update regularly alongside promotional campaigns. Documents contain both structured and unstructured content. Structured fields include raw material name, addition ratio, applicable breeding category, and marketing scenario tag. Unstructured content includes breeding case descriptions and product selling point scripts. Units involved include percentage, kg/ton, and month age, among others.

What Constraints Do These Characteristics Impose on Retrieval and Recall?

The structured features and update rhythm of feed marketing data create multiple constraints for the retrieval and recall process. First, structured fields contain precise values and units. Field semantics must be matched. Relying only on keywords may lead to incorrect formula ratio matches. Second, data updates have no fixed cycle. The knowledge base must be incrementally updated on a regular basis. This avoids recalling expired raw material information or non-compliant scripts. Third, script differences across breeding scenarios are significant. Documents must be split into vector chunks by scenario. Otherwise, retrieval results cannot accurately match different user needs. Fourth, compliance data requires high recall precision. Incorrect threshold settings may push out incorrect compliance information.

How to Set Configurations

Configuration ItemRecommended ValueRationale
recall count3–5Feed marketing content often needs to cover multiple needs such as breeding scenarios, compliance reminders, and product selling points. Retrieving more results can match the query intentions of different users
similarity threshold0.72–0.85Feed data contains precise values and compliance requirements. A threshold that is too low may introduce irrelevant content, while a threshold that is too high may miss document segments with acceptable matching degrees
chunk length800–1200 charactersFeed formula tables and technical descriptions often contain long paragraphs. Too long chunking will lose context association, while too short chunking will split field logic
PARSE_FILE_TIMEOUT_SECONDS600 secondsParsing large feed formula documents and quality inspection reports takes a long time. The default timeout duration is insufficient to complete full parsing
rerank return countTop 3The highest-matching marketing scripts and compliance reminders need to be displayed first to avoid users receiving redundant information
maxContext2000–3000 charactersFeed data often contains associated information across paragraphs. A reasonable context length can retain complete formula or script logic

The parameter values provided on this page are common recommended starting points for configuration. Actual values are influenced by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on self-provided samples before finalizing settings.

Three Common Misconfigurations

  • Phenomenon: Embedded feed breeding scenario images in retrieval results fail to load properly. Cause: Images uploaded to the knowledge base do not have public access permissions, or file paths are not correctly replaced with accessible links during parsing.
  • Phenomenon: Only one result is returned per knowledge base retrieval, which cannot cover multi-scenario needs. Cause: The recall count configuration value is set to 1, which does not match the content recall requirements of multi-scenario feed marketing.
  • Phenomenon: Retrieval response speed is too slow after configuring the knowledge base. Cause: Vector index sharding is not performed for large feed raw material libraries, or the maxContext configuration value is too large, leading to increased context loading time.

How to Confirm Proper Configuration

  • Upload one feed formula document and one marketing script, perform a retrieval test, and verify that the number of returned results matches the configured recall count value.
  • Check the image links in the retrieval results. Clicking them opens normally, confirming that image permission configurations are correct.
  • Upload one feed quality inspection report larger than 100 MB, verify that no ETIMEDOUT error occurs during parsing, confirming that the timeout configuration is reasonable.
  • Adjust the similarity threshold and perform multiple retrievals, compare the matching degree changes of returned results, confirming that the threshold configuration takes effect.

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.