Merge branch 'main' of https://github.com/tharoosha/Depresio into emo…

…tion-graph

backend/.cache

@@ -0,0 +1 @@
+{"access_token": "BQBKpbTXdZc6mRoi0aGViqe7TdAV9IvGkfZ1Ojhuz0bQnWZ2bjldoumaP28Ir2SIW0G7ps78Cf4lZj55LIZszkpRDgarAHESTz3n6MOB61Mvzy32DGgHZJxKmKQpTwL3VcTAiAVJyKcprTA-bPrRBAKvl2BAWCaF_ogpPcpBuUqn3NlD68qCQtaOZs51mZF0DWREsIbZyKp2OAsq2HwCxudVDRAR3lWKUrzrAQ", "token_type": "Bearer", "expires_in": 3600, "refresh_token": "AQAZep769iD4hcCGDeW0u_x-yl_3Xw3acR6CDQprtHSE9mVXjGrf6k0dTeQRHpreSM5Zt1AbruOjF2uCS2Tnd5570TLexln-4QsW4wAobc4SYDMthKkNf1_kwGhegBGJ5Qw", "scope": "playlist-read-private user-library-read user-read-recently-played user-top-read", "expires_at": 1698724236}

backend/controllers/mlController.js

@@ -242,29 +242,29 @@ export async function youtube_lists(req, res) {
 // Define the controller function to execute the Python script
 export async function spotify_recommend(req, res) {
   try {
-    const { mood } = req.body;
+    const { emotion } = req.body;
 
     // Spawn the Python script as a child process
     // const pythonProcess = spawn("/usr/src/app/venv/bin/python3", ["/usr/src/app/ml_models/spotify_recommendation/spotifyRecommendExecution.py", mood,]);
-    const pythonProcess = spawn("python3", [ "../backend/ml_models/spotify_recommendation/spotifyRecommendExecution.py", mood,]);
+    const pythonProcess = spawn("python3", [ "../backend/ml_models/spotify_recommendation/spotifyRecommendExecution.py", emotion,]);
 
     let output = "";
     // let output = [];
 
     // Listen for data events from the Python script's stdout
     pythonProcess.stdout.on("data", (data) => {
-      console.log(data.toString())
+      // console.log(data.toString())
       output += data.toString();
     });
 
     // Listen for the 'close' event to handle the completion of the Python script
     pythonProcess.on("close", (code) => {
       if (code === 0) {
         try {
-          const result = JSON.parse(output);
+          // const result = JSON.parse(output);
           // res.status(200).json(result);
           // const result = JSON.parse(output);  // Parse the output string to JSON
-          res.status(200).json(result);
+          res.status(200).send(output);
           // res.status(200).json({"result":output});
         } catch (error) {
           res.status(500).json({ error: "Failed to parse JSON response" });

backend/controllers/testing/test.js

@@ -0,0 +1,5 @@
+console.log(typeof {"result": ["1HNkqx9Ahdgi1Ixy2xkKkL", "1ei3hzQmrgealgRKFxIcWn", "7eJMfftS33KTjuF7lTsMCx"]})
+
+type = {"result": ["1HNkqx9Ahdgi1Ixy2xkKkL", "1ei3hzQmrgealgRKFxIcWn", "7eJMfftS33KTjuF7lTsMCx"]}
+
+console.log(type.result)

backend/controllers/testing/test.py

@@ -0,0 +1,29 @@
+import json 
+import sys
+
+def script_run():
+    try:
+        result = ['1HNkqx9Ahdgi1Ixy2xkKkL', '1ei3hzQmrgealgRKFxIcWn', '7eJMfftS33KTjuF7lTsMCx']
+
+        output = {"result": result}
+
+        output_json = json.dumps(output)
+        print(json.decode(output))
+
+
+        print(output_json)
+
+    except Exception as e:
+        error_message = str(e)
+        output = {"error2011": error_message}
+
+        output_json = json.dumps(output)
+        print(output_json)
+        sys.stdout.flush()
+
+
+if __name__ == "__main__":
+
+    # input_mood = sys.argv[1]
+
+    script_run()

backend/ml_models/spotify_recommendation/spotifyRecommendExecution.py

@@ -26,25 +26,30 @@
 def script_run(input_mood):
     try:
 
-        file_path = '/usr/src/app/ml_models/spotify_recommendation/tokenizer.pkl'
+        # file_path = '/usr/src/app/ml_models/spotify_recommendation/tokenizer.pkl'
         # file_path = '../backend/ml_models/spotify_recommendation/tokenizer.pkl'
-        if os.path.exists(file_path):
-            with open('/usr/src/app/ml_models/spotify_recommendation/tokenizer.pkl', 'rb') as f:
+        # if os.path.exists(file_path):
+            # with open('/usr/src/app/ml_models/spotify_recommendation/tokenizer.pkl', 'rb') as f:
             # with open('../backend/ml_models/spotify_recommendation/tokenizer.pkl', 'rb') as f:
-                scaler = pickle.load(f)
+                # scaler = pickle.load(f)
 
-        model = tf.keras.models.load_model('/usr/src/app/ml_models/spotify_recommendation/spotify_model')
+        # model = tf.keras.models.load_model('/usr/src/app/ml_models/spotify_recommendation/spotify_model')
         # model = tf.keras.models.load_model('../backend/ml_models/spotify_recommendation/spotify_model')
 
-        result = spotifyRecommendScript.getRecommendation(input_mood, model, scaler)
-        result = json.dumps(result)
+        # result = spotifyRecommendScript.getRecommendation(input_mood, model, scaler)
+
+        # print({input_mood})
+        # result = '["1HNkqx9Ahdgi1Ixy2xkKkL", "1ei3hzQmrgealgRKFxIcWn", "7eJMfftS33KTjuF7lTsMCx"]'
+        # result = '["1bzsi0xA8MxBZICdtB23pO", "6XSCLKQcavtn1PaLAhmo1x", "0sfCRhw6gS3b1WepmTVPZE", "6u8KnNnGthVY4PaWiH2mgt", "4FIGOj3O3cyIf6Dg2TDoVv", "0FSk1OsGWoTCS8lA74x5lF", "55eUtE9v3uatR0y0NijM6N", "1bzsi0xA8MxBZICdtB23pO", "6XSCLKQcavtn1PaLAhmo1x", "0sfCRhw6gS3b1WepmTVPZE"]'
+        result = '["0wjno8lHmDep5uhLVowoSA", "42maX10SkL9u6KM2dCdgPm", "0ABeQP5ffDRiZTe3aorRGn", "3QPFWCPWmL7fed8jCQ8jty", "59s47nDkFz1UNXujnpzEPt", "4c2JHXheN3t6Wh13lqj91s", "6eABugchKfRPyrzUpv7UzJ", "42maX10SkL9u6KM2dCdgPm", "6PJrnbdGmbiXjFceEFlnaR", "4cFm2ZZcb4mQMXwKCeJgzs"]'
+        # result = json.dumps(result)
         # response = str(result)
         output = {"result": result}
 
-        # output_json = json.dumps(output)
+        output_json = json.dumps(output)
         # sys.stdout.flush()
         # print(result)
-        print(output)
+        print(output_json)
 
     except Exception as e:
         error_message = str(e)
@@ -87,6 +92,7 @@ def script_run(input_mood):
 
     # Call the function with the received input_mood
     script_run(input_mood)
+    # print({input_mood})
 
     #     # script_run("happiness")
 

frontend/src/pages/MusicTherapy.js

@@ -29,77 +29,143 @@ import { useEffect, useState } from 'react';
 import { Buffer } from 'buffer';
 import { getUsername } from '../helper/helper'
 import { getRecommendation } from '../helper/helper'
+import useFetch from '../hooks/fetch.hook';
+import { useAuthStore } from '../store/store';
 
 // import 'dotenv/config';
 
 import axios from 'axios';
 const qs = require('qs');
 
-// const client_id = '07f4d94fc95d4955ad32cdf68dbefa0c'; // Your client id
-// const client_secret = 'cd95a4c259a94411b20b6929270c8ab8'; // Your secret
-const client_id = process.env.SPOTIFY_CLIENT_ID; // Your client id
-const client_secret = process.env.SPOTIFY_CLIENT_SECRET; // Your secret
+const client_id = '85828d1937e346c8a174c74766c1bb89'; // Your client id
+const client_secret = 'de99228ea35a4287bd2f1e25d35dec36'; // Your secret
+// const client_id = process.env.SPOTIFY_CLIENT_ID; // Your client id
+// const client_secret = process.env.SPOTIFY_CLIENT_SECRET; // Your secret
 const redirect_uri = process.env.SPOTIFY_REDIRECT_URI;
 const auth_token = Buffer.from(`${client_id}:${client_secret}`, 'utf-8').toString('base64');
 
 const MusicTherapy = () => {
+   // const { username } = useAuthStore((state) => state.auth);
+   // const [{ isLoading, apiData, serverError }] = useFetch(`/user/${username}`);
+
    const [accessToken, setAccessToken] = useState('');
    const [username, setUsername] = useState(''); // State for the username
    const [emotion, setEmotion] = useState('');
    const [recommendations, setRecommendations] = useState('');
 
 
    useEffect(() => {
+      getUsernameAndFetchData();
+      // getRecommendation(apiData.username)
+   }, []);
 
-      const getUsernameAndFetchData = async () => {
+   const getUsernameAndFetchData = async () => {
+      try {
+         // Fetch the username
+         // const userData = await getUsername();
+         const { username } = await getUsername();
+         // const fetchedUsername = userData.username;
+         // setUsername(fetchedUsername); // Update the username state
+         console.log(username)
+
+         const emotionData = await getRecommendation({username});
+         const emotion = emotionData.data;
+         setEmotion(emotion)
+         console.log(emotion)
+
+      } catch (error) {
+         console.error('Error fetching username', error);
+      }       
+   };
+
+   // useEffect(() => {
 
-         try {
-            // Fetch the username
-            const userData = await getUsername();
-            const fetchedUsername = userData.username;
-            setUsername(fetchedUsername); // Update the username state
+   //    const getUsernameAndFetchData = async () => {
 
-            const emotionData = await getRecommendation({username});
-            const emotion = emotionData.data;
-            setEmotion(emotion)
+   //       try {
+   //          // Fetch the username
+   //          const userData = await getUsername();
+   //          const fetchedUsername = userData.username;
+   //          setUsername(fetchedUsername); // Update the username state
+   //          console.log(username)
 
-         } catch (error) {
-            console.error('Error fetching username', error);
-         }
+   //          const emotionData = await getRecommendation({username});
+   //          const emotion = emotionData.data;
+   //          setEmotion(emotion)
+   //          console.log(emotion)
+
+   //       } catch (error) {
+   //          console.error('Error fetching username', error);
+   //       }
 
-      };
+   //    };
 
-      getUsernameAndFetchData();
-   }, []);
+   //    getUsernameAndFetchData();
+   // }, []);
 
 
 
 
 
-   // const handleSubmit = (e) => {
-
-   //    console.log(emotion)
-   //    console.log("get the emotion done...")
-   // }
+
 
 
 
    // const [trackData, setTrackData] = useState(null);
-   const [trackIds, setTrackIds] = useState(['1HNkqx9Ahdgi1Ixy2xkKkL', '1ei3hzQmrgealgRKFxIcWn', '7eJMfftS33KTjuF7lTsMCx']);
+   const [trackIds, setTrackIds] = useState(['1ei3hzQmrgealgRKFxIcWn', '7eJMfftS33KTjuF7lTsMCx']);
+   // const [trackIds, setTrackIds] = useState([]);
    const [trackData, setTrackData] = useState([]);
 
-   useEffect(() =>  {
-      axios.get('${process.env.SERVER_ENDPOINT}/api/spotify_recommend', { mood: emotion })
+   const handleSubmit = (e) => {
+      console.log(emotion)
+      console.log("get the emotion done...")
+      // const emo = JSON.parse(emotion)
+      console.log(typeof emotion)
+      // const data = {"mood": emotion}
+
+      axios.get(`${process.env.REACT_APP_SERVER_ENDPOINT}/api/spotify_recommend`, { emotion: emotion } )
       .then((response) => {
-         const trackIds = response.data;
-         console.log(response.data);
-         // Store the track IDs in the trackData state
-         setTrackData(trackIds);
+         // const ytTrackIds = response.data.result;
+         console.log(response.data.result);
+         setTrackIds(JSON.parse(response.data.result));
+         // const parsedArray = JSON.parse(ytTrackIds);
+         // console.log(typeof parsedArray)
+         // trackIds.forEach(function(item) {
+         //    console.log(item.id);
+         //    // item = JSON.parse(item)
+         //    setTrackData((prevTrackData) => [...prevTrackData, item.id])
+         //  });
+
+         // trackData.map((track, index) =>{
+         //    console.log(typeof track.id)
+         // })
+         //  console.log(newList)
+         //  newList.forEach(function(item2){
+         //    setTrackData((prevTrackData) => [...prevTrackData, ...ytTrackIds])
+         //  })
+         // setTrackData([ytTrackIds])
+         // console.log(trackIds)
+   //       // Store the track IDs in the trackData state
+   //       setTrackData(trackIds);
+   //       console.log(trackIds)
       })
       .catch((error) => {
          console.error(error);
       });
-   });
+   }
+
+   // useEffect(() =>  {
+   //    axios.get(`${process.env.SERVER_ENDPOINT}/api/spotify_recommend`, { mood: emotion })
+   //    .then((response) => {
+   //       const trackIds = response.data;
+   //       console.log(response.data);
+   //       // Store the track IDs in the trackData state
+   //       setTrackData(trackIds);
+   //    })
+   //    .catch((error) => {
+   //       console.error(error);
+   //    });
+   // });
 
    const getTrackData = async (accessToken, trackIds) => {
       try {
@@ -121,6 +187,8 @@ const MusicTherapy = () => {
    };
 
    useEffect(() => {
+      getUsernameAndFetchData();
+
       // Retrieve access token from Spotify
       axios('https://accounts.spotify.com/api/token', {
          headers: {
@@ -132,10 +200,15 @@ const MusicTherapy = () => {
       })
          .then((tokenResponse) => {
             setAccessToken(tokenResponse.data.access_token);
+            // console.log(client_id)
+            // console.log(client_secret)
+
          })
          .catch((error) => {
             console.error('Error retrieving access token:', error);
          });
+
+
    }, []);
 
    useEffect(() => {
@@ -158,8 +231,8 @@ const MusicTherapy = () => {
             <div className="mt-main-container mt--24 mb--48">
                <div className="mt-second-col">
                   <div>
+
                      <h2 className="mb--16">Music recommended for you based on your emotions.</h2>
-                     {/* <button className='btn' onClick={handleSubmit}>View your current emotion</button> */}
                      <div className="music-flex-cont">
                         {trackData.length > 0 ? (
                            trackData.map((track, index) => (
@@ -171,6 +244,9 @@ const MusicTherapy = () => {
                            <p>No recommended songs...</p>
                         )}
                      </div>
+
+                     <button className='btn' onClick={handleSubmit}>View your recommendations</button>
+
                      {/*
                         {getAudioFeatures_Track('1HNkqx9Ahdgi1Ixy2xkKkL') ? (
                            <div>