Model extractions update (#5127)

packages/client/hmi-client/src/services/knowledge.ts

@@ -1,11 +1,11 @@
 import API from '@/api/api';
+import { AxiosResponse } from 'axios';
 import { extractionStatusUpdateHandler, subscribe } from '@/services/ClientEventService';
-import type { Code, Dataset, DocumentAsset, Model } from '@/types/Types';
-import { ClientEventType } from '@/types/Types';
+import { type Dataset, type DocumentAsset, type Model, ClientEventType } from '@/types/Types';
 import { logger } from '@/utils/logger';
-import { AxiosResponse } from 'axios';
 
-/** Define the request type
+/**
+ * Define the request type
  * @param equations string[] - list of LaTeX or mathml strings representing a model
  * @param framework string= - the framework to use for the extraction, default to 'petrinet'
  * @param modelId string= - the model id to use for the extraction
@@ -55,70 +55,21 @@ export const profileDataset = async (datasetId: Dataset['id'], documentId: Docum
 
 /** Extract text and artifacts from a PDF document */
 export const extractPDF = async (documentId: DocumentAsset['id']) => {
- console.group('PDF COSMOS Extraction');
  if (documentId) {
  const response = await API.post(`/knowledge/pdf-extractions?document-id=${documentId}`);
  if (response?.status === 202) {
  await subscribe(ClientEventType.Extraction, extractionStatusUpdateHandler);
- } else {
- console.debug('Failed — ', response);
  }
- } else {
- console.debug('Failed — No documentId provided for pdf extraction.');
  }
- console.groupEnd();
 };
 
 /** Extract variables from a text document */
 export const extractVariables = async (documentId: DocumentAsset['id'], modelIds: Array<Model['id']>) => {
- console.group('SKEMA Variable extraction');
  if (documentId) {
  const url = `/knowledge/variable-extractions?document-id=${documentId}&model-ids=${modelIds}`;
  const response = await API.post(url);
  if (response?.status === 202) {
  await subscribe(ClientEventType.Extraction, extractionStatusUpdateHandler);
- } else {
- console.debug('Failed — ', response);
  }
- } else {
- console.debug('Failed — No documentId provided for variable extraction.');
  }
- console.groupEnd();
 };
-
-export async function codeToAMR(
- codeId: string,
- name: string = '',
- description: string = '',
- dynamicsOnly: boolean = false,
- llmAssisted: boolean = false
-): Promise<Model | null> {
- const response = await API.post(
- `/knowledge/code-to-amr?code-id=${codeId}&name=${name}&description=${description}&dynamics-only=${dynamicsOnly}&llm-assisted=${llmAssisted}`
- );
- if (response?.status === 200) {
- return response.data;
- }
- logger.error(`Code to AMR request failed`, { toastTitle: 'Error' });
- return null;
-}
-
-export async function codeBlocksToAmr(code: Code, file: File): Promise<Model | null> {
- const formData = new FormData();
- const blob = new Blob([JSON.stringify(code)], {
- type: 'application/json'
- });
- formData.append('code', blob);
- formData.append('file', file);
- const response = await API.post(`/knowledge/code-blocks-to-model`, formData, {
- headers: {
- Accept: 'application/json',
- 'Content-Type': 'multipart/form-data'
- }
- });
- if (response?.status === 200) {
- return response.data;
- }
- logger.error(`Code to AMR request failed`, { toastTitle: 'Error' });
- return null;
-}

testing/manual/model-extraction.md → testing/manual/model-from-equations.md

@@ -1,4 +1,4 @@
-## Model extraction
+## Model from equations
 Please go through __every__ step of the test scenario.\
 Report any issues into GitHub: [open an issue](https://github.com/DARPA-ASKEM/terarium/issues/new?assignees=&labels=bug%2C+Q%26A&template=qa-issue.md&title=%5BBUG%5D%3A+).
 
@@ -13,18 +13,20 @@ Report any issues into GitHub: [open an issue](https://github.com/DARPA-ASKEM/te
 ### 2. Upload a PDF
 1. Upload _the Document_ [SIR.pdf](../data/SIR.pdf)
 2. Wait for final notification of document extraction
-3. Open _the Document_ and check that extractions are visible
 
 ### 3. Extract model from document
-1. Create a new workflow named `Extract model from document`
+1. Create a new workflow named `Model from equations`
 2. Drag and drop _the Document_ onto the workflow
 3. Add the operator `Create model from equations`
 4. Link _the Document_ and open the operator
 5. Select the equations `S`, `I` and `R` and create model
-6. Save model and name as `SIR`
+6. Save the model for re-use and name it `SIR`
+7. Make sure that the name has been updated:
+ a. Operator drilldown output dropdown
+ b. Operator node output label
+8. The model is available in the resource panel
 
 ### 4. Check extractions from document
-1. Open model `SIR`
-2. Is the TA1 _model card_, extracted with `mit-tr` available?
-3. Is the TA4 _model card_, extracted from `gollm-taskrunner` available?
-4. Are the _variables extractions_ available in the `Other` accordion?
+1. Wait for the notification that the model enrichment has been completed
+2. Is the model description been filled with relevant information from the document?
+3. Are the variables description been filled with relevant information from the document?