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import time
import base64
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(prompt):
try:
pat = get_pat("[email protected]")
_, tags = get_tags_for_prompts(minilm, mubert_tags_embeddings, [prompt, ])[0]
result = get_track_by_tags(tags, pat, int(30), loop=False)
print(result)
return result
except Exception as e:
return str(e)
iface = gr.Interface(fn=generate_track_by_prompt, inputs=["text"], outputs=[gr.Text(label="Result")])
iface.queue(max_size=100, concurrency_count=20)
iface.launch() |