diff --git a/components/platerecognizer/actions/run-recognition/run-recognition.mjs b/components/platerecognizer/actions/run-recognition/run-recognition.mjs
index 54f0ddbb2da61..e424d3541f8bf 100644
--- a/components/platerecognizer/actions/run-recognition/run-recognition.mjs
+++ b/components/platerecognizer/actions/run-recognition/run-recognition.mjs
@@ -1,5 +1,6 @@
+import fs from "fs";
+import { checkTmp } from "../../common/utils.mjs";
 import platerecognizer from "../../platerecognizer.app.mjs";
-import { axios } from "@pipedream/platform";
 
 export default {
   key: "platerecognizer-run-recognition",
@@ -9,35 +10,55 @@ export default {
   type: "action",
   props: {
     platerecognizer,
-    imageFileOrUrl: platerecognizer.propDefinitions.imageFileOrUrl,
-    regions: platerecognizer.propDefinitions.regions,
-    cameraId: platerecognizer.propDefinitions.cameraId,
-    mmc: platerecognizer.propDefinitions.mmc,
-    config: platerecognizer.propDefinitions.config,
+    imageFileOrUrl: {
+      type: "string",
+      label: "Image File or URL",
+      description: "The image file or URL to be recognized.",
+    },
+    regions: {
+      type: "string[]",
+      label: "Regions",
+      description: "Regions to select specific license plate patterns. [See further details here](https://guides.platerecognizer.com/docs/other/country-codes/#country-codes)",
+      optional: true,
+    },
+    cameraId: {
+      type: "string",
+      label: "Camera ID",
+      description: "The ID of the camera that took the image.",
+      optional: true,
+    },
+    mmc: {
+      type: "boolean",
+      label: "MMC",
+      description: "Whether to detect vehicle make, model, and color.",
+      optional: true,
+    },
+    config: {
+      type: "object",
+      label: "Config",
+      description: "Additional configuration. [See further details here](https://guides.platerecognizer.com/docs/snapshot/api-reference/#engine-configuration)",
+      optional: true,
+    },
   },
   async run({ $ }) {
-    const formData = new FormData();
+    const fileObj = {};
+
     if (this.imageFileOrUrl.startsWith("http")) {
-      formData.append("upload", this.imageFileOrUrl);
+      fileObj.upload_url = this.imageFileOrUrl;
     } else {
-      const fs = require("fs");
-      formData.append("upload", fs.createReadStream(this.imageFileOrUrl));
+      const file = fs.readFileSync(checkTmp(this.imageFileOrUrl));
+      fileObj.upload = Buffer(file).toString("base64");
     }
-    if (this.regions) formData.append("regions", this.regions.join(","));
-    if (this.cameraId) formData.append("camera_id", this.cameraId);
-    if (this.mmc !== undefined) formData.append("mmc", this.mmc);
-    if (this.config) formData.append("config", this.config);
 
-    const response = await axios(this, {
-      method: "POST",
-      url: `${this.platerecognizer._baseUrl()}/plate-reader/`,
-      headers: {
-        "Authorization": `Token ${this.platerecognizer.$auth.api_key}`,
-        "Content-Type": "multipart/form-data",
+    const response = await this.platerecognizer.runRecognition({
+      $,
+      data: {
+        ...fileObj,
+        regions: this.regions,
+        camera_id: this.cameraId,
+        mmc: this.mmc,
+        config: this.config,
       },
-      data: formData,
-      maxContentLength: Infinity,
-      maxBodyLength: Infinity,
     });
 
     $.export("$summary", "Recognition process triggered successfully");
diff --git a/components/platerecognizer/common/utils.mjs b/components/platerecognizer/common/utils.mjs
new file mode 100644
index 0000000000000..1a5e36f32a603
--- /dev/null
+++ b/components/platerecognizer/common/utils.mjs
@@ -0,0 +1,6 @@
+export const checkTmp = (filename) => {
+  if (!filename.startsWith("/tmp")) {
+    return `/tmp/${filename}`;
+  }
+  return filename;
+};
diff --git a/components/platerecognizer/package.json b/components/platerecognizer/package.json
index 137711b33dcfb..763385296dc5f 100644
--- a/components/platerecognizer/package.json
+++ b/components/platerecognizer/package.json
@@ -1,6 +1,6 @@
 {
   "name": "@pipedream/platerecognizer",
-  "version": "0.0.1",
+  "version": "0.1.0",
   "description": "Pipedream Plate Recognizer Components",
   "main": "platerecognizer.app.mjs",
   "keywords": [
@@ -11,5 +11,9 @@
   "author": "Pipedream <support@pipedream.com> (https://pipedream.com/)",
   "publishConfig": {
     "access": "public"
+  },
+  "dependencies": {
+    "@pipedream/platform": "^1.6.5"
   }
 }
+
diff --git a/components/platerecognizer/platerecognizer.app.mjs b/components/platerecognizer/platerecognizer.app.mjs
index 55739ef9964f1..5c83ad58b5f5e 100644
--- a/components/platerecognizer/platerecognizer.app.mjs
+++ b/components/platerecognizer/platerecognizer.app.mjs
@@ -3,71 +3,30 @@ import { axios } from "@pipedream/platform";
 export default {
   type: "app",
   app: "platerecognizer",
-  propDefinitions: {
-    imageFileOrUrl: {
-      type: "string",
-      label: "Image File or URL",
-      description: "The image file or URL to be recognized.",
-    },
-    regions: {
-      type: "string[]",
-      label: "Regions",
-      description: "Regions to select specific license plate patterns. Use comma-separated values for multiple regions (e.g., us-ca,us-ny).",
-      optional: true,
-    },
-    cameraId: {
-      type: "string",
-      label: "Camera ID",
-      description: "The ID of the camera that took the image.",
-      optional: true,
-    },
-    mmc: {
-      type: "boolean",
-      label: "MMC",
-      description: "Whether to detect vehicle make, model, and color.",
-      optional: true,
-    },
-    config: {
-      type: "string",
-      label: "Config",
-      description: "Additional configuration in JSON format.",
-      optional: true,
-    },
-  },
   methods: {
-    authKeys() {
-      console.log(Object.keys(this.$auth));
-    },
     _baseUrl() {
       return "https://api.platerecognizer.com/v1";
     },
-    async triggerRecognition({
-      imageFileOrUrl, regions, cameraId, mmc, config,
+    _headers(headers) {
+      return {
+        "Authorization": `Token ${this.$auth.api_token}`,
+        ...headers,
+      };
+    },
+    _makeRequest({
+      $ = this, path, headers = {}, ...opts
     }) {
-      const formData = new FormData();
-      if (imageFileOrUrl.startsWith("http")) {
-        formData.append("upload", imageFileOrUrl);
-      } else {
-        // Assuming the use of Node.js environment, fs should be used for local files
-        // And since the file needs to be read as a stream, ensure fs is properly imported
-        const fs = require("fs");
-        formData.append("upload", fs.createReadStream(imageFileOrUrl));
-      }
-      if (regions) formData.append("regions", regions.join(","));
-      if (cameraId) formData.append("camera_id", cameraId);
-      if (mmc !== undefined) formData.append("mmc", mmc);
-      if (config) formData.append("config", config);
-
-      return axios(this, {
+      return axios($, {
+        url: `${this._baseUrl()}${path}`,
+        headers: this._headers(headers),
+        ...opts,
+      });
+    },
+    runRecognition(opts = {}) {
+      return this._makeRequest({
         method: "POST",
-        url: `${this._baseUrl()}/plate-reader/`,
-        headers: {
-          "Authorization": `Token ${this.$auth.api_key}`,
-          "Content-Type": "multipart/form-data",
-        },
-        data: formData,
-        maxContentLength: Infinity,
-        maxBodyLength: Infinity,
+        path: "/plate-reader/",
+        ...opts,
       });
     },
   },
diff --git a/components/platerecognizer/sources/new-recognition-instant/new-recognition-instant.mjs b/components/platerecognizer/sources/new-recognition-instant/new-recognition-instant.mjs
deleted file mode 100644
index dc1e853bc1c55..0000000000000
--- a/components/platerecognizer/sources/new-recognition-instant/new-recognition-instant.mjs
+++ /dev/null
@@ -1,56 +0,0 @@
-import { axios } from "@pipedream/platform";
-import platerecognizer from "../../platerecognizer.app.mjs";
-
-export default {
-  key: "platerecognizer-new-recognition-instant",
-  name: "New Recognition Instant",
-  description: "Emits new event when a cloud webhook event is broadcasted.",
-  version: "0.0.{{ts}}",
-  type: "source",
-  dedupe: "unique",
-  props: {
-    platerecognizer,
-    db: "$.service.db",
-    http: {
-      type: "$.interface.http",
-      customResponse: true,
-    },
-  },
-  hooks: {
-    async deploy() {
-      console.log("Deploying new recognition instant source");
-    },
-    async activate() {
-      console.log("Activating new recognition instant source");
-    },
-    async deactivate() {
-      console.log("Deactivating new recognition instant source");
-    },
-  },
-  async run(event) {
-    const body = event.body;
-    if (!body) {
-      this.http.respond({
-        status: 400,
-        body: "No data received",
-      });
-      return;
-    }
-
-    this.http.respond({
-      status: 200,
-      body: "Success",
-    });
-
-    const eventData = {
-      hook: body.hook,
-      data: body.data,
-    };
-
-    this.$emit(eventData, {
-      id: eventData.data.timestamp,
-      summary: `New Recognition: ${eventData.data.results.map((result) => result.plate).join(", ")}`,
-      ts: Date.parse(eventData.data.timestamp),
-    });
-  },
-};