What this category's data looks like
For multilingual materials and terminology processing in kindergarten play activity organization, the materials come from observation records, area plans, material placement lists, activity objectives, and reflections converted into next week's plans. The update cadence follows the weekly activity schedule and teaching research reviews, and the fields include activity name, area, material quantity, observation points, objective achievement description, and reflection entries. When entering the model integration and configuration stage, the correspondence between observation records and area plans serves as retrieval corpus, the material placement quantity serves as the source of glossary entries, the activity objective achievement description serves as the comparison draft field, and reflections converted into next week's plans serve as the trigger basis for updates. Multilingual materials must first form a unified glossary and comparison draft before being released externally.
Configuration and implementation checks
This step is executed by the server-side model channel configuration, outputting model binding relationships and channel responses. The unified glossary and comparison draft are then completed by subsequent AI nodes, code nodes, or manual work. Models are divided into five categories: language, indexing, reranking, speech synthesis, and speech recognition. Different stages bind different model types, and during configuration it is necessary to verify the type labels and the model names returned by the channel.
| Object | Check | Verification action |
|---|---|---|
| Materials corresponding to observation records and area plans | The same terminology is consistent throughout, and translated names can refer back to the original text; observation records correspond to area plans | In the model configuration, verify the type labels of the language model and indexing model, confirm that the retrieval side uses the indexing model and the dialogue side uses the language model, and check whether the values of maxContext and maxTokens match the material length |
| Material placement quantity list | The material placement quantity is consistent with the activity objective achievement description, and terminology translated names can refer back to the original text | Check the model identifier against the model name returned by the channel, confirm that the reranking model is used for reranking retrieval results, check whether quoteMaxToken covers the tokens of the quoted text, and record the number of array entries separately |
| Comparison draft of activity objectives and observation descriptions | Objectives match observations, plans are updated with reflections, and translated names are consistent throughout | Verify the channel configuration and key source, confirm that authentication passes, and check whether the value of toolChoice in the dialogue stage is consistent with the tool-calling scenario |
| Reflections converted into next week's plan entries | When the plan is not updated, it can be traced back to the reflection entries, and terminology usage is consistent | In the model configuration, verify the type labels of the speech synthesis and speech recognition models, and confirm that multilingual speech materials enter the corresponding stages |
Three common errors
- Symptom: Retrieval reports an indexing model-related error. Cause: The retrieval stage is bound to the language model, and the indexing model is not correctly matched, so text chunks cannot be indexed and retrieved.
- Symptom: Objectives do not match observations. Cause: The activity objective achievement description and observation records are not updated synchronously, glossary entries are not adjusted with area plans, and the comparison draft contains two versions.
- Symptom: Insufficient materials. Cause: The material placement quantity list is not updated with reflections converted into next week's plans, and the plan not being updated causes the next round's activity material quantity to mismatch the objectives.
How to verify the setup
Acceptance for this feature: run one dialogue and one retrieval, check the model identifiers in the responses, confirm that the language model and indexing model correspond respectively, and check whether the values of maxContext, maxTokens, and quoteMaxToken in the responses are consistent with the configuration.
Business test: sample three terms and check whether their usage is consistent throughout, confirm that translated names can refer back to the original text, that observation records correspond to area plans, and that material placement quantity is consistent with the objective achievement description.
- In the model configuration, check item by item the type labels of the five model categories: language, indexing, reranking, speech synthesis, and speech recognition, and confirm that they correspond to the stages to be used.
- Check the model identifier against the model name returned by the channel, verify the channel configuration and key source, and confirm that authentication passes and the model identifier is consistent with the names listed in the documentation.