What this category's data looks like
This page addresses the kindergarten health care and meal management scenario. The materials come from daily documents such as recipes, purchase orders, retention sample records, disinfection records, and absence cause registration, with an update cadence that rolls by week and by month. Ingredient names and specifications, retention sample times and batches, disinfection periods, and absence cause classification are the key fields for verification. When entering the model integration and configuration function, these materials serve as text chunks to be retrieved and used in conversation: the language model handles conversation and recognizing documents in images, the index model handles text chunk indexing to support relevant text retrieval, the rerank model optimizes retrieval ranking, and speech synthesis and speech recognition handle voice materials. The unified terminology glossary and comparison draft need to keep the same term consistent throughout multilingual materials and ensure translated names can refer back to the source text. Therefore, after the materials enter the function, they are first bound to the corresponding model by type, and then the terminology glossary and comparison draft are produced through the conversation and retrieval steps.
Configuration and implementation checks
This step is executed by the server-side model channel configuration, outputting model binding relationships and channel responses. The unified terminology glossary and comparison draft are then completed by conversation and retrieval using that model. Models are divided into five categories: language, index, rerank, speech synthesis, and speech recognition, and different steps bind different model types.
| Object | Check | Verification action |
|---|---|---|
| Ingredient name and specification materials | Whether the recipe and purchase categories are consistent | Check the channel configuration and key source, compare against the model name returned by the channel, and confirm that the index model is bound to the retrieval step |
| Retention sample time and batch materials | Whether the documents and retention sample batches match | Check the type annotation in the model configuration, confirm that the language model is bound to the conversation step, and check whether the values of maxContext and maxTokens can accommodate the document text |
| Disinfection record materials | Whether any disinfection period is missing | Confirm that the rerank model is bound to the retrieval result reranking step, and check that the model identifier matches the name listed in the documentation |
| Absence cause classification materials | Whether the cause classification is unified | Confirm that the speech recognition and speech synthesis models are each bound to the corresponding step, and check the model name returned by the channel |
Three common errors
- Symptom: documents and retention sample batches do not match. Cause: when retention sample records enter retrieval, the text chunks are not split by batch, and the index model and rerank model are not bound by material type.
- Symptom: recipes and purchase categories are inconsistent. Cause: ingredient names and specifications are not unified in the terminology glossary, and the language model uses the same model for conversation and retrieval but the type annotation was not checked.
- Symptom: disinfection records are missing periods. Cause: disinfection period materials do not fully enter the index, retrieval reports an index-model-related error, or the answer style changes abruptly after switching models.
How to verify the setup
This function's acceptance: run one conversation and one retrieval, check the model identifier in the response, and confirm that toolChoice and quoteMaxToken take effect in the response according to the configuration; the number of citations is the array length, and quoteMaxToken is the citation content budget. The two are not compared for equality. If a citation upper limit is involved, check the tokens of the cited text, and record the array count separately.
Business test: sample three terms and check whether their spelling is consistent throughout the document.
- In the model configuration, check the type annotation and confirm that the five model categories—language, index, rerank, speech synthesis, and speech recognition—are each bound to the step in which they are to be used.
- Check the channel configuration and key source, compare against the model name returned by the channel, and confirm that the model identifier matches the name listed in the documentation.