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huggingartists

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AlekseyKorshuk commited on Aug 19, 2021

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5739196

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1 Parent(s): df81345

Update app.py

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app.py +133 -1

app.py CHANGED Viewed

@@ -4,6 +4,9 @@ import random
 import os
 import streamlit as st
 import lyricsgenius
 st.set_page_config(page_title="HuggingArtists")
@@ -122,11 +125,140 @@ model_html = """
 </div>
 """
 if st.button("Run"):
-    with st.spinner(text=f"Downloading the model by {artist_name }..."):
         artist = genius.search_artist(artist_name, max_songs=0, get_full_info=False)
         if artist is not None:
             artist_dict = genius.artist(artist.id)['artist']
             artist_url = str(artist_dict['url'])
             model_name = artist_url[artist_url.rfind('/') + 1:].lower()
             st.markdown(model_html.replace("USER_PROFILE",artist.image_url).replace("USER_NAME",artist.name).replace("USER_HANDLE",model_name), unsafe_allow_html=True)

 import os
 import streamlit as st
 import lyricsgenius
+import transformers
+from transformers import AutoTokenizer, AutoModelForCausalLM
 st.set_page_config(page_title="HuggingArtists")
 </div>
 """
+def post_process(output_sequences):
+    predictions = []
+    generated_sequences = []
+    max_repeat = 2
+    # decode prediction
+    for generated_sequence_idx, generated_sequence in enumerate(output_sequences):
+        generated_sequence = generated_sequence.tolist()
+        text = tokenizer.decode(generated_sequence, clean_up_tokenization_spaces=True, skip_special_tokens=True)
+        generated_sequences.append(text.strip())
+    for i, g in enumerate(generated_sequences):
+        res = str(g).replace('\n\n\n', '\n').replace('\n\n', '\n')
+        lines = res.split('\n')
+        # print(lines)
+        # i = max_repeat
+        # while i != len(lines):
+        #   remove_count = 0
+        #   for index in range(0, max_repeat):
+        #     # print(i - index - 1, i - index)
+        #     if lines[i - index - 1] == lines[i - index]:
+        #       remove_count += 1
+        #   if remove_count == max_repeat:
+        #     lines.pop(i)
+        #     i -= 1
+        #   else:
+        #     i += 1
+        predictions.append('\n'.join(lines))
+    return predictions
+def get_table(table_data):
+  html = ("</head>\r\n"
+    "<body>\r\n\r\n"
+    "<h2></h2>"
+    "\r\n\r\n"
+    "<table>\r\n"
+    "    <colgroup>\r\n"
+    "       <col span=\"1"
+    "\" style=\"width: 10"
+    "%;\">\r\n"
+    "       <col span=\"1"
+    "\" style=\"width: 10"
+    "0%;\">\r\n"
+    "    </colgroup>\r\n"
+    f"{' '.join(table_data)}"
+    "</table>\r\n\r\n"
+    "</body>\r\n"
+    "</html>")
+  return html
+def get_share_button(url):
+    return f'''
+            <div style="width: 76px;">
+                <a target="_blank" href="{url}" style='background-color:rgb(27, 149, 224);border-bottom-left-radius:4px;border-bottom-right-radius:4px;border-top-left-radius:4px;border-top-right-radius:4px;box-sizing:border-box;color:rgb(255, 255, 255);cursor:pointer;display:inline-block;font-family:"Helvetica Neue", Arial, sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:28px;line-height:26px;outline-color:rgb(255, 255, 255);outline-style:none;outline-width:0px;padding-bottom:1px;padding-left:9px;padding-right:10px;padding-top:1px;position:relative;text-align:left;text-decoration-color:rgb(255, 255, 255);text-decoration-line:none;text-decoration-style:solid;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>
+                <i style='background-attachment:scroll;background-clip:border-box;background-color:rgba(0,0,0,0);background-image:url(data:image/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%2072%2072%22%3E%3Cpath%20fill%3D%22none%22%20d%3D%22M0%200h72v72H0z%22%2F%3E%3Cpath%20class%3D%22icon%22%20fill%3D%22%23fff%22%20d%3D%22M68.812%2015.14c-2.348%201.04-4.87%201.744-7.52%202.06%202.704-1.62%204.78-4.186%205.757-7.243-2.53%201.5-5.33%202.592-8.314%203.176C56.35%2010.59%2052.948%209%2049.182%209c-7.23%200-13.092%205.86-13.092%2013.093%200%201.026.118%202.02.338%202.98C25.543%2024.527%2015.9%2019.318%209.44%2011.396c-1.125%201.936-1.77%204.184-1.77%206.58%200%204.543%202.312%208.552%205.824%2010.9-2.146-.07-4.165-.658-5.93-1.64-.002.056-.002.11-.002.163%200%206.345%204.513%2011.638%2010.504%2012.84-1.1.298-2.256.457-3.45.457-.845%200-1.666-.078-2.464-.23%201.667%205.2%206.5%208.985%2012.23%209.09-4.482%203.51-10.13%205.605-16.26%205.605-1.055%200-2.096-.06-3.122-.184%205.794%203.717%2012.676%205.882%2020.067%205.882%2024.083%200%2037.25-19.95%2037.25-37.25%200-.565-.013-1.133-.038-1.693%202.558-1.847%204.778-4.15%206.532-6.774z%22%2F%3E%3C%2Fsvg%3E);background-origin:padding-box;background-position-x:0px;background-position-y:0px;background-repeat-x;background-repeat-y;background-size:auto;color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:"Helvetica Neue",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:italic;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;height:18px;line-height:26px;position:relative;text-align:left;text-decoration-thickness:auto;top:4px;user-select:none;white-space:nowrap;width:18px;'></i>
+                <span style='color:rgb(255,255,255);cursor:pointer;display:inline-block;font-family:"Helvetica Neue",Arial,sans-serif;font-size:13px;font-stretch:100%;font-style:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-weight:500;line-height:26px;margin-left:4px;text-align:left;text-decoration-thickness:auto;user-select:none;vertical-align:top;white-space:nowrap;zoom:1;'>Tweet</span>
+            </a>
+            </div>
+            '''
+def share_model_table(artist_name, model_name):
+  url = f"https://twitter.com/intent/tweet?text=I created an AI bot of {artist_name} with %23huggingartists!%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/{model_name}"
+  share_button = get_share_button(url)
+  table_data = [
+        f'<tr><td>{share_button}</td><td>🎉 Share {artist_name} model: <a href="https://huggingface.co/huggingartists/{model_name}">https://huggingface.co/huggingartists/{model_name}</a></td></tr>'
+  ]
+  return get_table(table_data)
+def get_share_lyrics_url(artist_name, model_name, lyrics):
+    return "https://twitter.com/intent/tweet?text=I created an AI bot of " + artist_name + " with %23huggingartists!%0A%0ABrand new song:%0A" + lyrics.replace('\n', '%0A').replace('"', '%22') + "%0A%0APlay with my model or create your own! &url=https://huggingface.co/huggingartists/" + model_name
 if st.button("Run"):
+    model_name = None
+    with st.spinner(text=f"Searching for {artist_name } in Genius..."):
         artist = genius.search_artist(artist_name, max_songs=0, get_full_info=False)
         if artist is not None:
             artist_dict = genius.artist(artist.id)['artist']
             artist_url = str(artist_dict['url'])
             model_name = artist_url[artist_url.rfind('/') + 1:].lower()
             st.markdown(model_html.replace("USER_PROFILE",artist.image_url).replace("USER_NAME",artist.name).replace("USER_HANDLE",model_name), unsafe_allow_html=True)
+        else:
+            st.markdown(f"Could not find {artist_name}! Be sure that he/she exists in [Genius](https://genius.com/).")
+    if model_name is not None:
+        with st.spinner(text=f"Downloading the model of {artist_name }..."):
+            model = None
+            tokenizer = None
+            try:
+                tokenizer = AutoTokenizer.from_pretrained(f"huggingartists/{model_name}")
+                model = AutoModelForCausalLM.from_pretrained(f"huggingartists/{model_name}")
+            except:
+                st.markdown(f"Model for this artist does not exist yet. Create it in just 5 min with [Colab Notebook](https://colab.research.google.com/github/AlekseyKorshuk/huggingartists/blob/master/huggingartists-demo.ipynb):")
+                st.markdown(
+                        """
+                    <style>
+                    .aligncenter {
+                        text-align: center;
+                    }
+                    </style>
+                    <p class="aligncenter">
+                      <a href="https://colab.research.google.com/github/AlekseyKorshuk/huggingartists/blob/master/huggingartists-demo.ipynb" target="_blank">
+                            <img src="https://colab.research.google.com/assets/colab-badge.svg"/>
+                        </a>
+                    </p>
+                        """,
+                        unsafe_allow_html=True,
+                    )
+    if model is not None:
+        with st.spinner(text=f"Generating lyrics..."):
+            encoded_prompt = tokenizer(start, add_special_tokens=False, return_tensors="pt").input_ids
+            encoded_prompt = encoded_prompt.to(trainer.model.device)
+            # prediction
+            output_sequences = trainer.model.generate(
+                                    input_ids=encoded_prompt,
+                                    max_length=max_length,
+                                    min_length=min_length,
+                                    temperature=float(temperature),
+                                    top_p=float(top_p),
+                                    top_k=int(top_k),
+                                    do_sample=True,
+                                    repetition_penalty=1.0,
+                                    num_return_sequences=num_sequences
+                                    )
+            # Post-processing
+            predictions = post_process(output_sequences)
+            table_data = []
+            for result in predictions:
+              table_data.append('<tr><td>' + get_share_button(get_share_lyrics_url(artist.name, model_name, result)) + '</td><td>' + result.replace("\n", "<br>") + '</td></tr>')
+            st.markdown(share_model_table(artist.name, model_name),
+                        unsafe_allow_html=True)
+            st.markdown(get_table(table_data),
+                        unsafe_allow_html=True)