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app.py

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+import time
+
+import gradio as gr
+from sentence_transformers import SentenceTransformer
+
+import httpx
+import json
+
+from utils import get_tags_for_prompts, get_mubert_tags_embeddings, get_pat
+
+minilm = SentenceTransformer('all-MiniLM-L6-v2')
+mubert_tags_embeddings = get_mubert_tags_embeddings(minilm)
+
+
+def get_track_by_tags(tags, pat, duration, maxit=20, loop=False):
+    if loop:
+        mode = "loop"
+    else:
+        mode = "track"
+    r = httpx.post('https://api-b2b.mubert.com/v2/RecordTrackTTM',
+                   json={
+                       "method": "RecordTrackTTM",
+                       "params": {
+                           "pat": pat,
+                           "duration": duration,
+                           "tags": tags,
+                           "mode": mode
+                       }
+                   })
+
+    rdata = json.loads(r.text)
+    assert rdata['status'] == 1, rdata['error']['text']
+    trackurl = rdata['data']['tasks'][0]['download_link']
+
+    print('Generating track ', end='')
+    for i in range(maxit):
+        r = httpx.get(trackurl)
+        if r.status_code == 200:
+            return trackurl
+        time.sleep(1)
+
+
+def generate_track_by_prompt(email, prompt, duration, loop=False):
+    try:
+        pat = get_pat(email)
+        _, tags = get_tags_for_prompts(minilm, mubert_tags_embeddings, [prompt, ])[0]
+        return get_track_by_tags(tags, pat, int(duration), loop=loop), "Success", ",".join(tags)
+    except Exception as e:
+        return None, str(e), ""
+
+
+block = gr.Blocks()
+
+with block:
+    gr.HTML(
+        """
+            <div style="text-align: center; max-width: 700px; margin: 0 auto;">
+              <div
+                style="
+                  display: inline-flex;
+                  align-items: center;
+                  gap: 0.8rem;
+                  font-size: 1.75rem;
+                "
+              >
+                <h1 style="font-weight: 900; margin-bottom: 7px;">
+                  TTM By Satwik 
+                </h1>
+              </div>
+              <            </div>
+        """
+    )
+    with gr.Group():
+        with gr.Box():
+            email = gr.Textbox(label="email")
+            #email="oneafterlif3@gmail.com"
+            prompt = gr.Textbox(label="prompt")
+            duration = gr.Slider(label="duration (seconds)", value=60, maximum=300)
+            is_loop = gr.Checkbox(label="Generate loop")
+            out = gr.Audio()
+            result_msg = gr.Text(label="Result message")
+            tags = gr.Text(label="Tags")
+            btn = gr.Button("Submit").style(full_width=True)
+        
+        btn.click(fn=generate_track_by_prompt, inputs=[email, prompt, duration, is_loop], outputs=[out, result_msg, tags])
+       
+        gr.HTML('''
+        <div class="footer" style="text-align: center; max-width: 700px; margin: 0 auto;">
+        </div>
+        </div>
+              <p style="margin-bottom: 10px; font-size: 94%">
+                if you put anything over 250 seconds, you will need to wait 10 or 30 second after it is done processing.
+            </div>
+        ''')
+
+block.launch()

constants.py

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+import numpy as np
+
+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'
+MUBERT_TAGS = np.array(MUBERT_TAGS_STRING.split(','))
+MUBERT_LICENSE = "ttmmubertlicense#f0acYBenRcfeFpNT4wpYGaTQIyDI4mJGv5MfIhBFz97NXDwDNFHmMRsBSzmGsJwbTpP1A6i07AXcIeAHo5"
+MUBERT_MODE = "loop"
+MUBERT_TOKEN = "4951f6428e83172a4f39de05d5b3ab10d58560b8"

requirements.txt

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+httpx
+sentence-transformers

utils.py

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+import json
+import numpy as np
+import httpx
+
+from constants import MUBERT_TAGS, MUBERT_LICENSE, MUBERT_MODE, MUBERT_TOKEN
+
+
+def get_mubert_tags_embeddings(w2v_model):
+    return w2v_model.encode(MUBERT_TAGS)
+
+
+def get_pat(email: str):
+    r = httpx.post('https://api-b2b.mubert.com/v2/GetServiceAccess',
+                   json={
+                       "method": "GetServiceAccess",
+                       "params": {
+                           "email": email,
+                           "license": MUBERT_LICENSE,
+                           "token": MUBERT_TOKEN,
+                           "mode": MUBERT_MODE,
+                       }
+                   })
+
+    rdata = json.loads(r.text)
+    assert rdata['status'] == 1, "probably incorrect e-mail"
+    pat = rdata['data']['pat']
+    return pat
+
+
+def find_similar(em, embeddings, method='cosine'):
+    scores = []
+    for ref in embeddings:
+        if method == 'cosine':
+            scores.append(1 - np.dot(ref, em) / (np.linalg.norm(ref) * np.linalg.norm(em)))
+        if method == 'norm':
+            scores.append(np.linalg.norm(ref - em))
+    return np.array(scores), np.argsort(scores)
+
+
+def get_tags_for_prompts(w2v_model, mubert_tags_embeddings, prompts, top_n=3, debug=False):
+    prompts_embeddings = w2v_model.encode(prompts)
+    ret = []
+    for i, pe in enumerate(prompts_embeddings):
+        scores, idxs = find_similar(pe, mubert_tags_embeddings)
+        top_tags = MUBERT_TAGS[idxs[:top_n]]
+        top_prob = 1 - scores[idxs[:top_n]]
+        if debug:
+            print(f"Prompt: {prompts[i]}\nTags: {', '.join(top_tags)}\nScores: {top_prob}\n\n\n")
+        ret.append((prompts[i], list(top_tags)))
+    return ret