Added feature: Download generated files to local session file storage

Mubert_Text_to_Music.ipynb

@@ -1,43 +1,25 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
-    "colab": {
-      "provenance": [],
-      "collapsed_sections": [],
-      "toc_visible": true,
-      "authorship_tag": "ABX9TyNRcUVF3ZzTw+oK4ortpcH+",
-      "include_colab_link": true
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
   "cells": [
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
+        "colab_type": "text",
+        "id": "view-in-github"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/ferluht/Mubert-Text-to-Music/blob/main/Mubert_Text_to_Music.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "gHJPhnu7Lg2v"
+      },
       "source": [
         "# **Mubert Text to Music ✍ ➡ 🎹🎵🔊**\n",
         "\n",
         "A simple notebook demonstrating prompt-based music generation via [Mubert](https://mubert.com) [API](https://mubert2.docs.apiary.io/)"
-      ],
-      "metadata": {
-        "id": "gHJPhnu7Lg2v"
-      }
+      ]
     },
     {
       "cell_type": "code",
@@ -67,12 +49,19 @@
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "cellView": "form",
+        "id": "yW-3aTNYvKM_"
+      },
+      "outputs": [],
       "source": [
         "#@title **Define Mubert methods and pre-compute things**\n",
         "\n",
         "import numpy as np\n",
         "from sentence_transformers import SentenceTransformer\n",
         "minilm = SentenceTransformer('all-MiniLM-L6-v2')\n",
+        "import urllib.request\n",
         "\n",
         "mubert_tags_string = 'tribal,action,kids,neo-classic,run 130,pumped,jazz / funk,ethnic,dubtechno,reggae,acid jazz,liquidfunk,funk,witch house,tech house,underground,artists,mystical,disco,sensorium,r&b,agender,psychedelic trance / psytrance,peaceful,run 140,piano,run 160,setting,meditation,christmas,ambient,horror,cinematic,electro house,idm,bass,minimal,underscore,drums,glitchy,beautiful,technology,tribal house,country pop,jazz & funk,documentary,space,classical,valentines,chillstep,experimental,trap,new jack swing,drama,post-rock,tense,corporate,neutral,happy,analog,funky,spiritual,sberzvuk special,chill hop,dramatic,catchy,holidays,fitness 90,optimistic,orchestra,acid techno,energizing,romantic,minimal house,breaks,hyper pop,warm up,dreamy,dark,urban,microfunk,dub,nu disco,vogue,keys,hardcore,aggressive,indie,electro funk,beauty,relaxing,trance,pop,hiphop,soft,acoustic,chillrave / ethno-house,deep techno,angry,dance,fun,dubstep,tropical,latin pop,heroic,world music,inspirational,uplifting,atmosphere,art,epic,advertising,chillout,scary,spooky,slow ballad,saxophone,summer,erotic,jazzy,energy 100,kara mar,xmas,atmospheric,indie pop,hip-hop,yoga,reggaeton,lounge,travel,running,folk,chillrave & ethno-house,detective,darkambient,chill,fantasy,minimal techno,special,night,tropical house,downtempo,lullaby,meditative,upbeat,glitch hop,fitness,neurofunk,sexual,indie rock,future pop,jazz,cyberpunk,melancholic,happy hardcore,family / kids,synths,electric guitar,comedy,psychedelic trance & psytrance,edm,psychedelic rock,calm,zen,bells,podcast,melodic house,ethnic percussion,nature,heavy,bassline,indie dance,techno,drumnbass,synth pop,vaporwave,sad,8-bit,chillgressive,deep,orchestral,futuristic,hardtechno,nostalgic,big room,sci-fi,tutorial,joyful,pads,minimal 170,drill,ethnic 108,amusing,sleepy ambient,psychill,italo disco,lofi,house,acoustic guitar,bassline house,rock,k-pop,synthwave,deep house,electronica,gabber,nightlife,sport & fitness,road trip,celebration,electro,disco house,electronic'\n",
         "mubert_tags = np.array(mubert_tags_string.split(','))\n",
@@ -82,7 +71,7 @@
         "import httpx\n",
         "import json\n",
         "\n",
-        "def get_track_by_tags(tags, pat, duration, maxit=20, autoplay=False, loop=False):\n",
+        "def get_track_by_tags(tags, pat, duration, prompt, maxit=20, autoplay=False, loop=False):\n",
         "  if loop:\n",
         "    mode = \"loop\"\n",
         "  else:\n",
@@ -107,6 +96,9 @@
         "      r = httpx.get(trackurl)\n",
         "      if r.status_code == 200:\n",
         "          display(Audio(trackurl, autoplay=autoplay))\n",
+        "          urllib.request.urlretrieve(trackurl, str(prompt)+\".mp3\")\n",
+        "          print('All generated files will save in this sessions \"Files\" on the left, please download if you wish to keep them. \\n (May take 30sec-2min to appear)')\n",
+        "          print('\\n')\n",
         "          break\n",
         "      time.sleep(1)\n",
         "      print('.', end='')\n",
@@ -131,16 +123,16 @@
         "            print(f\"Prompt: {prompts[i]}\\nTags: {', '.join(top_tags)}\\nScores: {top_prob}\\n\\n\\n\")\n",
         "        ret.append((prompts[i], list(top_tags)))\n",
         "    return ret"
-      ],
-      "metadata": {
-        "cellView": "form",
-        "id": "yW-3aTNYvKM_"
-      },
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "cellView": "form",
+        "id": "a4ACdvWLRJ5U"
+      },
+      "outputs": [],
       "source": [
         "#@markdown **Get personal access token in Mubert and define API methods**\n",
         "email = \"your e-mail here\" #@param {type:\"string\"}\n",
@@ -160,16 +152,16 @@
         "assert rdata['status'] == 1, \"probably incorrect e-mail\"\n",
         "pat = rdata['data']['pat']\n",
         "print(f'Got token: {pat}')"
-      ],
-      "metadata": {
-        "cellView": "form",
-        "id": "a4ACdvWLRJ5U"
-      },
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "cellView": "form",
+        "id": "hTf7sZcfbI0K"
+      },
+      "outputs": [],
       "source": [
         "#@title **Generate some music 🎵**\n",
         "\n",
@@ -180,31 +172,32 @@
         "def generate_track_by_prompt(prompt, duration, loop=False):\n",
         "  _, tags = get_tags_for_prompts([prompt,])[0]\n",
         "  try:\n",
-        "    get_track_by_tags(tags, pat, duration, autoplay=True, loop=loop)\n",
+        "    get_track_by_tags(tags, pat, duration, prompt, autoplay=True, loop=loop)\n",
         "  except Exception as e:\n",
         "    print(str(e))\n",
+        "  print('Prompt:', prompt)\n",
+        "  print(tags)\n",
         "  print('\\n')\n",
         "\n",
         "generate_track_by_prompt(prompt, duration, loop)\n"
-      ],
-      "metadata": {
-        "cellView": "form",
-        "id": "hTf7sZcfbI0K"
-      },
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
-      "source": [
-        "### **Batch generation 🎶**"
-      ],
       "metadata": {
         "id": "wSKTfub-bitp"
-      }
+      },
+      "source": [
+        "### **Batch generation 🎶**"
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "BzrhcwIHXlg0"
+      },
+      "outputs": [],
       "source": [
         "duration = 60\n",
         "\n",
@@ -229,21 +222,49 @@
         "  except Exception as e:\n",
         "    print(str(e))\n",
         "  print('\\n')"
-      ],
-      "metadata": {
-        "id": "BzrhcwIHXlg0"
-      },
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "code",
-      "source": [],
+      "execution_count": null,
       "metadata": {
         "id": "JieLk6kjZFai"
       },
-      "execution_count": null,
-      "outputs": []
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "authorship_tag": "ABX9TyNRcUVF3ZzTw+oK4ortpcH+",
+      "collapsed_sections": [],
+      "include_colab_link": true,
+      "provenance": [],
+      "toc_visible": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3.9.7 64-bit",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.9.7"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "81794d4967e6c3204c66dcd87b604927b115b27c00565d3d43f05ba2f3a2cb0d"
+      }
     }
-  ]
-}
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}