+
+
+
+
+ 
+
+
+
+
+
+
+ Enterprise
+
+
+ Odoo.sh
+
+
+
+
+
+
+
+ 
+
+ + Amazon Forecast Integration +
++ This module helps to create Forecast of our Stock based on Demand. +
+ +
+
+
+
+ 
+
+
+ + Explore This Module
+
+
+
+
+
+
+
+
+
+
+
+ 
+
+
+ + Overview +
+
+
+
+
+
+ This module helps to get the Forecast Report of our Stock based on the
+ historical Time series Data we provide.
+
+
+
+
+ 
+
+
+ + Features +
+
+
+
+
+
+
+
+ 
+ Utilize Amazon Forecast to generate Accurate
+ Demand Forecasts based on historical data from Odoo.
+
+
+ Utilize Amazon Forecast to generate Accurate
+ Demand Forecasts based on historical data from Odoo.
+
+
+ The Forecasts can be used to optimize Inventory
+ levels and plan Procurement.
+
+
+ The Forecasts can be used to optimize Inventory
+ levels and plan Procurement.
+
+
+ Forecasting helps to prevent Stock outs and
+ Overstock situations, reducing holding Costs and improving
+ Customer satisfaction.
+
+
+ Forecasting helps to prevent Stock outs and
+ Overstock situations, reducing holding Costs and improving
+ Customer satisfaction.
+
+
+
+ 
+
+
+ + Screenshots +
+
+
+
+
+
+
+
+ 
+
+ + Login to the Amazon Account and Click on Security + Credentials to Create Access key. +
+
+
+ 
+
+ + Note down the Access Key and the Secret Access Key generated + when Creating the Access Key. +
+
+
+ 
+
+ + Provide these Access Key, Secret Access Key and the AWS region + in Configuration Settings of Inventory. +
+
+
+ 
+
+ + Click on the Menu Item Amazon Forecast and Click on Fetch Data + to Fetch the Data for Forecasting,Note that for Forecasting, a + Historical Data is needed to get the Result. +
+
+
+ 
+
+ + Click on the Fetch Data button for Fetching Data. +
+
+
+ 
+
+ + Now Click on Amazon Forecast and Click on Bucket to Create + Bucket in Amazon S3.Provide a name for the bucket meeting the + naming format allowed in S3. +
+
+
+ 
+
+ + Click on Push to Bucket Button to push the Data to Amazon S3 + Bucket. +
+
+
+ 
+
+ + S3 URI field will be Updated and state is changed to Pushed. +
+
+
+ 
+
+ + Next, Click on Forecast Menu and Create a Table in Dynamodb + and then Table Arn wil be Updated. +
+
+
+ 
+
+ + Create Role by clicking on Create Role Button after providing + the Role Name. +
+
+
+ 
+
+ + Choose the Bucket Name from the Bucket List and Create a KMS + Key by giving KMS Alias Name.KMS Arn will be Updated. +
+
+
+ 
+
+ + Create Policy by giving policy name and Policy Arn will be + Updated. +
+
+
+ 
+
+ + Create Dataset Group and Dataset by Clicking on Create Dataset + after providing the Dataset Group Name and Dataset Name. +
+
+
+ 
+
+ + Import the Dataset from the S3 Bucket by Clicking on Import + Dataset Job After giving the Import Job Name. This requires + some time and ensure that the Data we are using have enough + historical Data. +
+
+
+ 
+
+ + After Importing, now you can Create Predictor function by + giving Predictor Name and then CLicking on Create Predictor + Button. +
+
+
+ 
+
+ + After completing the Predictor function Creation, Create + Forecast by giving the Forecast Name and the Item Id and then + the Forecast Arn will be Updated. +
+
+
+ 
+
+ + Clicking on the Query Forecast Button, you can get the Forecast + Graph. +
+
+
+
+
+ 
+
+
+ + Related Products +
+
+
+
+
+
+
+ 
+ 
+ 
+ 
+ 
+
+
+
+ 
+
+
+ + Our Services
+
+
+
+
+
+
+
+
+
+ 
+
+
+ + Odoo Customization
+
+
+
+ 
+
+
+ + Odoo Implementation
+
+
+
+ 
+
+
+ + Odoo Support
+
+
+
+ 
+
+
+ + Hire Odoo Developer
+
+
+
+ 
+
+
+ + Odoo Integration
+
+
+
+ 
+
+
+ + Odoo Migration
+
+
+
+ 
+
+
+ + Odoo Consultancy
+
+
+
+ 
+
+
+ + Odoo Implementation
+
+
+
+ 
+
+
+ + Odoo Licensing Consultancy
+
+
+
+ 
+
+
+ + Our Industries +
+
+
+
+
+
+
+
+
+
+ 
+
+
+ + Trading
++ Easily procure and sell your products
+
+
+
+ 
+
+
+ + POS
++ Easy configuration and convivial experience
+
+
+
+ 
+
+
+ + Education
++ A platform for educational management
+
+
+
+ 
+
+
+ + Manufacturing
++ Plan, track and schedule your operations
+
+
+
+ 
+
+
+ + E-commerce & Website
++ Mobile friendly, awe-inspiring product pages
+
+
+
+ 
+
+
+ + Service Management
++ Keep track of services and invoice
+
+
+
+ 
+
+
+ + Restaurant
++ Run your bar or restaurant methodically
+
+
+
+ 
+
+
+ + Hotel Management
++ An all-inclusive hotel management application
+
+
+
+ 
+
+
+ + Support +
+
+
+
diff --git a/amazon_forecast_integration/static/src/js/graphView.js b/amazon_forecast_integration/static/src/js/graphView.js
new file mode 100644
index 000000000..e3e530518
--- /dev/null
+++ b/amazon_forecast_integration/static/src/js/graphView.js
@@ -0,0 +1,97 @@
+/** @odoo-module **/
+
+/**
+ * This module defines a custom Odoo web client action 'forecast'.
+ * The action generates a scatter chart to display forecast data from the
+ 'amazon.dataset' model.
+ * The chart represents forecast data for three points: p10, p50, and p90.
+ */
+import { registry } from '@web/core/registry';
+const actionRegistry = registry.category("actions");
+const { useRef, onMounted, useState } = owl;
+import rpc from 'web.rpc';
+import { browser } from '@web/core/browser/browser';
+const { Component } = owl;
+
+class ForecastReport extends Component{
+ /**
+ * It is responsible for initializing the component and its state.
+ */
+ setup(){
+ super.setup(...arguments);
+ this.forecastBarGraph = useRef("bubble-chart");
+ this.FinalData = useState({
+ ForecastData:[],
+ })
+ onMounted(async () =>{
+ await this.forecastGraph();
+ });
+ }
+ /**
+ * The 'forecastGraph' function asynchronously retrieves forecast data from the 'amazon.dataset' model using RPC.
+ * It then generates a scatter chart using the Chart.js library to visualize the data.
+ */
+ async forecastGraph(){
+ let abc = await rpc.query({
+ model:'amazon.dataset',
+ method:'get_query_result',
+ }).then(val => {
+ this.FinalData.ForecastData = val
+ });
+ const { p10, p50, p90 } = this.FinalData.ForecastData
+ function getMonthNameFromDate(dateString) {
+ const date = new Date(dateString);
+ const monthName = date.toLocaleString('default', { month: 'long' });
+ return monthName;
+ }
+ const userDate = p10[0].Timestamp;
+ const monthName = getMonthNameFromDate(userDate);
+ let scatterChart = this.forecastBarGraph.el
+ new Chart(scatterChart, {
+ type: 'scatter',
+ data: {
+ datasets: [{
+ label: 'Forecast in '+ monthName,
+ data: [
+ { 'date': p10[0].Timestamp, 'demand': p10[0].Value },
+ { 'date': p50[0].Timestamp, 'demand': p50[0].Value},
+ { 'date': p90[0].Timestamp, 'demand': p90[0].Value}
+ ],
+ borderColor: 'rgb(0, 0, 255)',
+ backgroundColor: 'rgba(0, 0, 255, 0.5)'
+ }]
+ },
+ options: {
+ parsing: {
+ xAxisKey: 'date',
+ yAxisKey: 'demand'
+ },
+ scales: {
+ y: {
+ ticks: {
+ stepSize: 1
+ }
+ },
+ x: {
+ type: 'time',
+ time: {
+ unit: 'day',
+ },
+ ticks: {
+ autoSkip: false,
+ stepSize: 1,
+ }
+ }
+ }
+ }
+ });
+ }
+ goBack() {
+// this.trigger('back');
+browser.history.go(-1)
+
+
+ }
+}
+ForecastReport.template = "ForecastReport"
+actionRegistry.add('forecast', ForecastReport);
diff --git a/amazon_forecast_integration/static/src/xml/graph_view.xml b/amazon_forecast_integration/static/src/xml/graph_view.xml
new file mode 100644
index 000000000..cdff37ce0
--- /dev/null
+++ b/amazon_forecast_integration/static/src/xml/graph_view.xml
@@ -0,0 +1,27 @@
+
+
+
+
+
+
+
+
+
+ 
+
+
+
+
+
+
+
+
+ 
+
+
+
+
+
+
+ 
+
+
+
+
+
+
+
+ + Forecast Report +
++
+
+
+
+ +
+ Forecast Result
+ X axis: Demand + Y Axis: Date ++ +
+
+ Forecast
+
+
+
+
+
+
+
+
+
+
+
+ Forecast helps to predict stock and maintain
+ inventory correctly
+
+
+
+
+ Access Key:
+
+
+
+
+ Secret Access Key:
+
+
+
+
+ Region:
+
+