Tender Document and Quotation Preparation for Meat Products and Slaughter Processing: Multi-turn Dialogue and Prompt Engineering

Core data for this category comes from animal quarantine information, supplier batch ledgers, production traceability systems, cold chain temperature

What the Data for This Category Looks Like

Core data for this category comes from animal quarantine information, supplier batch ledgers, production traceability systems, cold chain temperature collection equipment, metal detection devices, and laboratory test results. Daily documents include quarantine certificates, slaughter and cutting records, ingredient marinating records, thermal processing records, cold chain temperature logs, and microbial test reports. Each production batch and shift triggers data updates. Systems collect and update cold chain temperature data continuously. Document fields include batch numbers, quarantine numbers, processing parameters, temperature thresholds, test indicators, and some records bind timestamps and operator information to the corresponding production link.

Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering

This category’s data links to production batches and quarantine information. Multi-turn dialogue uses chatId to associate context for the corresponding production batch, avoiding cross-batch data mixing. Systems collect large volumes of continuous cold chain temperature data, so prompts limit the extraction scope to prevent context overflow from harming response accuracy. Document fields differ significantly across production links, so prompts use variables to pass exclusive fields for the corresponding link, ensuring extracted content matches business requirements. Tender documents integrate multiple batches of test and processing data, so multi-turn dialogue retains complete historical records to provide traceable basis for quotations and qualification descriptions.

Configuration Settings

This document follows the configuration logic of FastGPT v4.17.0.

Configuration ItemRecommended SettingRationale
chatIdBind to production batch numberEnsure multi-turn dialogue context associates with quarantine and processing data for the corresponding batch, avoiding cross-batch confusion
messagesRetain the first 10 dialogue history entriesCover multi-round requirement confirmation and data supplementation required for tender quotations, preventing context loss
variablesPass the current batch’s quarantine number and cold chain temperature thresholdProvide category-specific fields for prompts, ensuring extracted content matches production records
Single search limitTop 5 entriesLimit the number of extracted historical documents, preventing redundant data from interfering with prompt processing
Maximum context length800–1200 charactersAdapt to the average length of single-batch documents for this category, avoiding context overflow
Question optimizationCalibrate based on actual testingAdapt to requirement decomposition logic in tender scenarios, optimizing the accuracy of questions in multi-turn dialogue

Three Common Misconfigurations

  • Symptom: After entering the variables parameter in the prompt code block, the extracted result displays empty fields. Cause: The system does not receive exclusive fields for the corresponding batch via variables, so the prompt cannot access category-specific data such as quarantine information and temperature values.
  • Symptom: After deleting a dialogue record, the system log syncs and deletes along with it. Cause: The system does not enable independent storage configuration for dialogue logs, so logs bound to chatId associate with and delete alongside the dialogue context.
  • Symptom: Multi-turn dialogue cannot reference batch information from previous questions. Cause: The system does not retain the batch number field from historical context in messages, so the prompt cannot associate content from historical dialogue.

How to Confirm Proper Configuration

  • Initiate a test dialogue, enter keywords for a batch’s quarantine information, and check if the response associates with the cold chain temperature data for that batch.
  • View the dialogue history and confirm that the batch number bound to chatId matches the current test batch.
  • Check that the fields passed via variables include the category-specific quarantine number and microbial test indicators.
  • Test deleting a single dialogue record and confirm that the system log does not sync and delete.

The values provided here are common starting points and should be measured against the reader's own samples.