add: roboflow, salesforce_rest_api

Author: GTFalcao

components/roboflow/actions/classify-image/classify-image.mjs

@@ -1,11 +1,11 @@
 import roboflow from "../../roboflow.app.mjs";
-import { getFileStream } from "@pipedream/platform";
+import utils from "../../common/utils.mjs";
 
 export default {
   key: "roboflow-classify-image",
   name: "Classify Image",
   description: "Run inference on classification models hosted on Roboflow. [See the documentation](https://docs.roboflow.com/deploy/hosted-api/classification).",
-  version: "0.1.0",
+  version: "1.0.0",
   type: "action",
   props: {
     roboflow,
@@ -32,23 +32,14 @@ export default {
     },
   },
   async run({ $ }) {
-    const stream = getFileStream(this.filePath);
-    const chunks = [];
-    for await (const chunk of stream) {
-      chunks.push(chunk);
-    }
-    const data = Buffer.concat(chunks).toString("base64");
-
-    const args = {
+    const response = await this.roboflow.classifyImage({
       datasetId: this.datasetId,
       $,
-      data,
+      data: await utils.getBase64File(this.filePath),
       headers: {
         "Content-Type": "application/x-www-form-urlencoded",
       },
-    };
-
-    const response = await this.roboflow.classifyImage(args);
+    });
 
     if (!response?.error) {
       $.export("$summary", "Successfully classified image.");

components/roboflow/actions/detect-object-from-image/detect-object-from-image.mjs

@@ -1,11 +1,11 @@
 import roboflow from "../../roboflow.app.mjs";
-import { getFileStream } from "@pipedream/platform";
+import utils from "../../common/utils.mjs";
 
 export default {
   key: "roboflow-detect-object-from-image",
   name: "Detect Object From Image",
   description: "Run inference on your object detection models hosted on Roboflow. [See the documentation](https://docs.roboflow.com/deploy/hosted-api/object-detection).",
-  version: "0.1.0",
+  version: "1.0.0",
   type: "action",
   props: {
     roboflow,
@@ -32,23 +32,14 @@ export default {
     },
   },
   async run({ $ }) {
-    const stream = getFileStream(this.filePath);
-    const chunks = [];
-    for await (const chunk of stream) {
-      chunks.push(chunk);
-    }
-    const data = Buffer.concat(chunks).toString("base64");
-
-    const args = {
+    const response = await this.roboflow.detectObject({
       datasetId: this.datasetId,
       $,
-      data,
+      data: await utils.getBase64File(this.filePath),
       headers: {
         "Content-Type": "application/x-www-form-urlencoded",
       },
-    };
-
-    const response = await this.roboflow.detectObject(args);
+    });
 
     if (!response?.error) {
       $.export("$summary", "Successfully ran object detection inference model on image.");

components/roboflow/actions/upload-image/upload-image.mjs

@@ -1,5 +1,5 @@
 import roboflow from "../../roboflow.app.mjs";
-import { getFileStream } from "@pipedream/platform";
+import { getFileStreamAndMetadata } from "@pipedream/platform";
 import utils from "../../common/utils.mjs";
 import FormData from "form-data";
 
@@ -31,29 +31,26 @@ export default {
     },
   },
   async run({ $ }) {
-    const args = {
-      projectId: utils.extractSubstringAfterSlash(this.projectId),
-      $,
-    };
-
     const formData = new FormData();
     if (this.name) {
       formData.append("name", this.name);
     }
 
-    if (this.filePath.startsWith("http")) {
-      args.params = {
-        image: this.filePath,
-        name: this.name,
-      };
-    } else {
-      const stream = getFileStream(this.filePath);
-      formData.append("file", stream);
-      args.data = formData;
-      args.headers = formData.getHeaders();
-    }
+    const {
+      stream, metadata,
+    } = await getFileStreamAndMetadata(this.filePath);
+    formData.append("file", stream, {
+      contentType: metadata.contentType,
+      knownLength: metadata.size,
+      filename: metadata.name,
+    });
 
-    const response = await this.roboflow.uploadImage(args);
+    const response = await this.roboflow.uploadImage({
+      $,
+      projectId: utils.extractSubstringAfterSlash(this.projectId),
+      data: formData,
+      headers: formData.getHeaders(),
+    });
 
     if (!response?.error) {
       $.export("$summary", "Successfully uploaded image.");

components/roboflow/common/utils.mjs

@@ -1,3 +1,5 @@
+import { getFileStream } from "@pipedream/platform";
+
 function extractSubstringAfterSlash(str) {
   const match = str.match(/\/(.*)/);
   if (match && match[1]) {
@@ -7,6 +9,16 @@ function extractSubstringAfterSlash(str) {
   }
 }
 
+async function getBase64File(filePath) {
+  const stream = await getFileStream(filePath);
+  const chunks = [];
+  for await (const chunk of stream) {
+    chunks.push(chunk);
+  }
+  return Buffer.concat(chunks).toString("base64");
+}
+
 export default {
   extractSubstringAfterSlash,
+  getBase64File,
 };

components/roboflow/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@pipedream/roboflow",
-  "version": "0.2.0",
+  "version": "1.0.0",
   "description": "Pipedream Roboflow  Components",
   "main": "roboflow.app.mjs",
   "keywords": [

components/salesforce_rest_api/common/sobjects/attachment.mjs

@@ -9,7 +9,7 @@ export default {
     },
     filePathOrContent: {
       type: "string",
-      label: "File Path or URL",
+      label: "File Path, URL or Content",
       description: "The file to attach. Provide either a file URL, a path to a file in the `/tmp` directory (for example, `/tmp/myFile.txt`), or base64-encoded file data.",
     },
     ContentType: {