V1 florian

unlock gradio

README.md

@@ -4,7 +4,7 @@ emoji: 🌍
 colorFrom: blue
 colorTo: red
 sdk: gradio
-sdk_version: 3.41.0
+sdk_version: 4.16.0
 app_file: app.py
 pinned: false
 python_version: 3.8

app.py

@@ -8,118 +8,199 @@ import datetime
 from huggingface_hub import hf_hub_download
 
 # NO GPU
-os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
 
 max_results = 100
 max_output = 50
 
 
 # Cacher le nom du repo
-python_path = hf_hub_download(repo_id=os.environ['REPO_ID'], repo_type="space", filename=os.environ['MODEL_FILE'],
-                                use_auth_token=os.environ['TOKEN'])
+python_path = hf_hub_download(
+    repo_id=os.environ["REPO_ID"],
+    repo_type="space",
+    filename=os.environ["MODEL_FILE"],
+    use_auth_token=os.environ["TOKEN"],
+)
 print(python_path)
-sys.path.append(os.environ['PRIVATE_DIR'])
+sys.path.append(os.environ["PRIVATE_DIR"])
 from models import *
+
 preprocess_model, model = get_models()
 url_dict = get_durl_myma()
 dict_catalog = get_dict_catalog()
-#audio_names = get_audio_names()
+# audio_names = get_audio_names()
 audio_names = get_audio_names_pickle()
 index = get_index()
-#encoder_text = get_encoder_text() #Error ??
-encoder_text = tf.keras.models.load_model("encoder_text_retrievaltext_bmg_221022_54_clean")
+# encoder_text = get_encoder_text() #Error ??
+encoder_text = tf.keras.models.load_model(
+    "encoder_text_retrievaltext_bmg_221022_54_clean"
+)
+
 
 def process(prompt, lang):
     now = datetime.datetime.now()
-    
+
     print()
-    print('*************')
+    print("*************")
     print("Current Time: ", str(now))
     print("Text input : ", prompt)
-    print('*************')
+    print("*************")
     print()
-    a=time.time()
+    a = time.time()
 
-    embed_query  = get_predict(encoder_text, prompt, preprocess_model, model)
+    embed_query = get_predict(encoder_text, prompt, preprocess_model, model)
     print("Embed time : ", time.time() - a)
     do_normalize(embed_query)
     D, I = get_distance(index, embed_query, max_output)
     print("Search + Embed time : ", time.time() - a)
-    
-    #print(I)
-    #print(D)
-    #print("----")
-    #for i in range(len(I[0])):
+
+    # print(I)
+    # print(D)
+    # print("----")
+    # for i in range(len(I[0])):
     #    print(audio_names[I[0][i]], " with distance ", D[0][i])
     #    print("    url : ", get_url_myma(I[0][i], audio_names, url_dict))
 
-    formated = []
+    formated = [{"f": "Choose a result to play", "t": ""}]
     output_csv = f"prompt_{prompt}_results.csv"
-    out = [output_csv]
-    
     with open(output_csv, "w") as w:
         writer = csv.writer(w)
         header = False
-        count = 0
-        for top in I[0]:
-            if count > max_output:
+        for position, top in enumerate(I[0]):
+            if len(formated) / 2 >= max_output:
                 break
-    
-            #formated.append(get_url_myma(top, audio_names, url_dict)
-            #formated.append(audio_names[top].split('.')[0])
-            file = os.path.splitext(os.path.basename(audio_names[top]))[0]   
-            try :
+
+            file = os.path.splitext(os.path.basename(audio_names[top]))[0]
+            if file in dict_catalog:
                 if not header:
                     writer.writerow(list(dict_catalog[file].keys()))
                     header = True
                 writer.writerow(dict_catalog[file].values())
-            except KeyError:
+            else:
                 writer.writerow([file, "no metadata provided"])
-            count += 1
 
-            out.append(file)
-            out.append(get_url_myma(top, audio_names, url_dict))
+            formated.append(
+                {
+                    "f": f"{position+1} - {file}",
+                    "t": get_url_myma(top, audio_names, url_dict),
+                }
+            )
 
     print("Total time : ", time.time() - a)
-    return out
-    
-    '''return [output_csv,
-            audio_names[I[0][0]].split('.')[0], get_url_myma(I[0][0], audio_names, url_dict), 
-    '''
-inputs = [gr.Textbox(label="Input", value="type your description", max_lines=2), 
-            gr.Radio(label="Language", choices=["en"], value="en")]
-
-poc_examples = [
-          ["Mysterious filmscore with Arabic influenced instruments","en"],
-          ["Let's go on a magical adventure with wizzards, dragons and castles","en"],
-          ["Creepy piano opening evolves and speeds up into a cinematic orchestral piece","en"],
-          ["Chilled electronic","en"],
-          #["","en"],
-          ["Relax piano","en"],
-          ["Halloween rock with creepy organ","en"],
-          ["Rhythmic electro dance track for sport, motivation and sweating","en"],
-          ["soundtrack for an action movie from the eighties in a retro synth wave style","en"],
-          ["Choral female singing is rhythmically accompanied in a church with medieval instruments","en"],
-          ["Christmas","en"],
-          ["love romantic with piano, strings and vocals","en"],
-          ["Electronic soundscapes for chilling and relaxing","en"],
-          ["Minimal, emotional, melancholic piano","en"],
-          ["A calm and romantic acoustic guitar melody","en"],
-          ["horror suspense piano","en"],
-          ["Big Band","en"],
-          ["90 eurodance beat","en"],
-]
-
-outputs = [gr.File(label="Results CSV file : ready for download", show_label=True)]
-for i in range(max_output):
-    outputs.append(gr.Textbox(label=f"top{i+1} track name", show_label=True))
-    outputs.append(gr.Audio(label=f"top{i+1}", show_label=False))
-
-'''outputs = [gr.File(),
-           gr.Textbox(label="Track name 1"), gr.Audio(label="Track 1", show_label=False), 
-'''
-demo1 = gr.Interface(fn=process, inputs=inputs, outputs=outputs, examples=poc_examples, cache_examples=False, examples_per_page=20)
-
-demo1.launch(debug=False)
- 
+    return output_csv, formated
+
+    """return [output_csv,
+            audio_names[I[0][0]].split('.')[0], get_url_myma(I[0][0], audio_names, url_dict),
+    """
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            with gr.Row():
+                with gr.Column():
+                    input_search = gr.Textbox(
+                        label="Input", value="type your description", max_lines=2
+                    )
+
+                    input_search_lang = gr.Radio(
+                        label="Language", choices=["en"], value="en"
+                    )
+
+                    analyze_btn = gr.Button("Search")
+
+                with gr.Column():
+                    csv_results = gr.File(
+                        label="Results CSV file : ready for download", show_label=True
+                    )
+                    results = gr.JSON(visible=False)
+                    select_results = gr.Dropdown(label="Results", choices=[])
+                    audio_player = gr.Audio(None, label="Results player")
+
+                    @select_results.select(inputs=select_results, outputs=audio_player)
+                    def change_audio(value):
+                        if value:
+                            return gr.Audio(value, label="Results player")
+                        return gr.Audio(None, label="Results player")
+
+                    @results.change(
+                        inputs=results,
+                        outputs=select_results,
+                    )
+                    def update_select(json_results):
+                        try:
+                            return gr.Dropdown(
+                                label="Results",
+                                choices=[(k["f"], k["t"]) for k in json_results],
+                                value=None,
+                            )
+                        except:
+                            return gr.Dropdown(
+                                choices=[],
+                                label="Results",
+                            )
+
+            @input_search.change(
+                outputs=[results, select_results, csv_results, audio_player]
+            )
+            def cleanup_on_url():
+                print("cleanup on url change")
+                return (
+                    gr.JSON([{"f": "Choose a result to play", "t": ""}], visible=False),
+                    gr.Dropdown(choices=[], label="Results"),
+                    gr.File(None, label="Results as CSV"),
+                    gr.Audio(None, label="Results player"),
+                )
+
+    gr.Examples(
+        examples=[
+            ["Mysterious filmscore with Arabic influenced instruments", "en"],
+            [
+                "Let's go on a magical adventure with wizzards, dragons and castles",
+                "en",
+            ],
+            [
+                "Creepy piano opening evolves and speeds up into a cinematic orchestral piece",
+                "en",
+            ],
+            ["Chilled electronic", "en"],
+            # ["","en"],
+            ["Relax piano", "en"],
+            ["Halloween rock with creepy organ", "en"],
+            [
+                "Rhythmic electro dance track for sport, motivation and sweating",
+                "en",
+            ],
+            [
+                "soundtrack for an action movie from the eighties in a retro synth wave style",
+                "en",
+            ],
+            [
+                "Choral female singing is rhythmically accompanied in a church with medieval instruments",
+                "en",
+            ],
+            ["Christmas", "en"],
+            ["love romantic with piano, strings and vocals", "en"],
+            ["Electronic soundscapes for chilling and relaxing", "en"],
+            ["Minimal, emotional, melancholic piano", "en"],
+            ["A calm and romantic acoustic guitar melody", "en"],
+            ["horror suspense piano", "en"],
+            ["Big Band", "en"],
+            ["90 eurodance beat", "en"],
+        ],
+        inputs=[input_search, input_search_lang],
+        outputs=[csv_results, results],
+        cache_examples=False,
+        fn=process,
+        examples_per_page=20,
+        run_on_click=True,
+    )
+
+    analyze_btn.click(
+        process,
+        inputs=[input_search, input_search_lang],
+        outputs=[csv_results, results],
+    )
+
+demo.launch(debug=False)