Block train start if either the dataset or the model is not downloaded, and then download them

src/renderer/components/Experiment/Train/LoRATrainingRunButton.tsx

@@ -21,20 +21,131 @@ export default function LoRATrainingRunButton({
       color="primary"
       endDecorator={<PlayIcon size="14px" />}
       onClick={async () => {
-        // Use fetch API to call endpoint
-        await fetch(
-          chatAPI.Endpoints.Jobs.Create(
-            experimentId,
-            'TRAIN',
-            'QUEUED',
-            JSON.stringify(job_data)
+        const model = job_data.model_name;
+        console.log(job_data)
+        const dataset = job_data.dataset;
+
+        const models_downloaded = await fetch(
+          chatAPI.Endpoints.Models.LocalList()
+        ).then((response) => {
+          // First check that the API responded correctly
+          if (response.ok) {
+            return response.json();
+          } else {
+            const error_msg = `${response.statusText}`;
+            throw new Error(error_msg);
+          }
+        })
+        .then((data) => {
+          // Then check the API responose to see if there was an error.
+          console.log('Server response:', data);
+          if (data?.status == "error") {
+            throw new Error(data.message);
+          }
+          return data;
+        })
+        .catch((error) => {
+          alert(error);
+          return false;
+        });
+        let modelInLocalList = false;
+        models_downloaded.forEach(modelData => {
+          if (modelData.model_id == model) {
+            modelInLocalList = true;
+          }
+        });
+
+        const datasets_downloaded = await fetch(
+          chatAPI.Endpoints.Dataset.LocalList()
+        ).then((response) => {
+          // First check that the API responded correctly
+          if (response.ok) {
+            return response.json();
+          } else {
+            const error_msg = `${response.statusText}`;
+            throw new Error(error_msg);
+          }
+        })
+        .then((data) => {
+          // Then check the API responose to see if there was an error.
+          console.log('Server response:', data);
+          if (data?.status == "error") {
+            throw new Error(data.message);
+          }
+          return data;
+        })
+        .catch((error) => {
+          alert(error);
+          return false;
+        });
+
+        let datasetInLocalList = false;
+        datasets_downloaded.forEach(datasetData => {
+          if (datasetData.dataset_id == dataset) {
+            datasetInLocalList = true;
+          }
+        });
+        
+        if(modelInLocalList && datasetInLocalList){
+          // Use fetch API to call endpoint
+          await fetch(
+            chatAPI.Endpoints.Jobs.Create(
+              experimentId,
+              'TRAIN',
+              'QUEUED',
+              JSON.stringify(job_data)
+            )
           )
-        )
-          .then((response) => response.json())
-          .then((data) => console.log(data))
-          .catch((error) => console.log(error));
-        jobsMutate();
-      }}
+            .then((response) => response.json())
+            .then((data) => console.log(data))
+            .catch((error) => console.log(error));
+          jobsMutate();
+        }
+        else{
+          let msg = "Warning: To use this recipe you will need to download the following:";
+          let shouldDownload = false;
+
+          if (!datasetInLocalList) {
+            msg += "\n- Dataset: " + dataset;
+          }
+          if (!modelInLocalList) {
+            msg += "\n- Model: " + model;
+          }
+          msg += "\n\nDo you want to download these now?";
+          if (confirm(msg)) { // Use confirm() to get Accept/Cancel
+            if (!datasetInLocalList) {
+              fetch(chatAPI.Endpoints.Dataset.Download(dataset))
+                .then((response) => {
+                  if (!response.ok) {
+                    console.log(response);
+                    throw new Error(`HTTP Status: ${response.status}`);
+                  }
+                  return response.json();
+                })
+                .catch((error) => {
+                  alert('Dataset download failed:\n' + error);
+                });
+            }
+            if (!modelInLocalList) {
+              chatAPI.downloadModelFromHuggingFace(model)
+                .then((response) => {
+                  if (response.status == "error") {
+                    console.log(response);
+                    throw new Error(`${response.message}`);
+                  }
+                  return response;
+                })
+                .catch((error) => {
+                  alert('Model download failed:\n' + error);
+                });
+            }
+          } else {
+            // User pressed Cancel
+            alert("Downloads cancelled. This recipe might not work correctly.");
+          }
+        }
+        }
+      }
     >
       {initialMessage}
     </Button>