[ADD] post and search models

.gitignore

@@ -9,6 +9,8 @@ __pycache__
 hubert_base.pt
 /logs
 /env
+/zips/
+/unzips/
 .venv
 alexforkINSTALL.bat
 Changelog_CN.md

app.py

@@ -1,6 +1,56 @@
 import gradio as gr
 from inference import Inference
 import os
+import zipfile
+import hashlib
+from utils.model import model_downloader, get_model
+import requests
+
+api_url = "https://rvc-models-api.onrender.com/uploadfile/"
+
+zips_folder = "./zips"
+unzips_folder = "./unzips"
+if not os.path.exists(zips_folder):
+      os.mkdir(zips_folder)
+if not os.path.exists(unzips_folder):
+  os.mkdir(unzips_folder)
+           
+def calculate_md5(file_path):
+    hash_md5 = hashlib.md5()
+    with open(file_path, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            hash_md5.update(chunk)
+    return hash_md5.hexdigest()
+
+def compress(modelname, files):
+    file_path = os.path.join(zips_folder, f"{modelname}.zip")
+    # Select the compression mode ZIP_DEFLATED for compression
+    # or zipfile.ZIP_STORED to just store the file
+    compression = zipfile.ZIP_DEFLATED
+
+    # Comprueba si el archivo ZIP ya existe
+    if not os.path.exists(file_path):
+        # Si no existe, crea el archivo ZIP
+        with zipfile.ZipFile(file_path, mode="w") as zf:
+            try:
+                for file in files:
+                    if file:
+                        # Agrega el archivo al archivo ZIP
+                        zf.write(unzips_folder if ".index" in file else os.path.join(unzips_folder, file), compress_type=compression)
+            except FileNotFoundError as fnf:
+                print("An error occurred", fnf)
+    else:
+        # Si el archivo ZIP ya existe, agrega los archivos a un archivo ZIP existente
+        with zipfile.ZipFile(file_path, mode="a") as zf:
+            try:
+                for file in files:
+                    if file:
+                        # Agrega el archivo al archivo ZIP
+                         zf.write(unzips_folder if ".index" in file else os.path.join(unzips_folder, file), compress_type=compression)
+            except FileNotFoundError as fnf:
+                print("An error occurred", fnf)
+
+    return file_path
 
 def infer(model, f0_method, audio_file):
     print("****", audio_file)
@@ -15,20 +65,88 @@ def infer(model, f0_method, audio_file):
         return output, output['file']
     else:
         return
+    
+def post_model(name, model_url, version, creator):
+    modelname = model_downloader(model_url, zips_folder, unzips_folder)
+    model_files = get_model(unzips_folder, modelname)
+    md5_hash = calculate_md5(os.path.join(unzips_folder,model_files['pth']))
+    zipfile = compress(modelname, list(model_files.values()))
+    file_to_upload = open(zipfile, "rb")
+    data = {
+        "name": name,
+        "version": version,
+        "creator": creator,
+        "hash": md5_hash
+    }
+    print("Subiendo archivo...")
+    # Realizar la solicitud POST
+    response = requests.post(api_url, files={"file": file_to_upload}, data=data)
+    
+    # Comprobar la respuesta
+    if response.status_code == 200:
+        result = response.json()
+        return result
+    else:
+        print("Error al cargar el archivo:", response.status_code)
+        return result
+
+def search_model(name):
+    web_service_url = "https://script.google.com/macros/s/AKfycbzfIOiwmPj-q8-hEyvjRQfgLtO7ESolmtsQmnNheCujwnitDApBSjgTecdfXb8f2twT/exec"
+    response = requests.post(web_service_url, json={
+        'type': 'search_by_filename',
+        'name': name
+    })
+    result = []
+    response.raise_for_status()  # Lanza una excepción en caso de error
+    json_response = response.json()
+    cont = 0
+    if json_response.get('ok', None):
+        for model in json_response['ocurrences']:
+            if cont < 20:
+                model_name = model.get('name', 'N/A')
+                model_url = model.get('url', 'N/A')
+                result.append(f"**Nombre del modelo: {model_name}**</br>{model_url}</br>")
+                yield "</br>".join(result)
+            cont += 1
 
 with gr.Blocks() as app:
     gr.HTML("<h1> Simple RVC Inference - by Juuxn 💻 </h1>")
-    model_url = gr.Textbox(placeholder="https://huggingface.co/AIVER-SE/BillieEilish/resolve/main/BillieEilish.zip", label="Url del modelo", show_label=True)
-    audio_path = gr.Audio(label="Archivo de audio", show_label=True, type="filepath", )
-    f0_method = gr.Dropdown(choices=["harvest", "pm", "crepe", "crepe-tiny", "mangio-crepe", "mangio-crepe-tiny", "rmvpe"], 
-                            value="harvest", 
-                            label="Algoritmo", show_label=True)
-    # Salida
-    with gr.Row():
-        vc_output1 = gr.Textbox(label="Salida")
-        vc_output2 = gr.Audio(label="Audio de salida")
-                        
-    btn = gr.Button(value="Convertir")
-    btn.click(infer, inputs=[model_url, f0_method, audio_path], outputs=[vc_output1, vc_output2])
+    
+    with gr.Tab("Inferencia"):
+        model_url = gr.Textbox(placeholder="https://huggingface.co/AIVER-SE/BillieEilish/resolve/main/BillieEilish.zip", label="Url del modelo", show_label=True)
+        audio_path = gr.Audio(label="Archivo de audio", show_label=True, type="filepath", )
+        f0_method = gr.Dropdown(choices=["harvest", "pm", "crepe", "crepe-tiny", "mangio-crepe", "mangio-crepe-tiny", "rmvpe"], 
+                                value="harvest", 
+                                label="Algoritmo", show_label=True)
+        # Salida
+        with gr.Row():
+            vc_output1 = gr.Textbox(label="Salida")
+            vc_output2 = gr.Audio(label="Audio de salida")
+                            
+        btn = gr.Button(value="Convertir")
+        btn.click(infer, inputs=[model_url, f0_method, audio_path], outputs=[vc_output1, vc_output2])
+        
+    with gr.Tab("Recursos"):
+        gr.HTML("<h4>Buscar modelos</h4>")
+        search_name = gr.Textbox(placeholder="Billie Eillish (RVC v2 - 100 epoch)", label="Nombre", show_label=True)
+         # Salida
+        with gr.Row():
+            sarch_output = gr.Markdown(label="Salida")
+            
+        btn_search_model = gr.Button(value="Buscar")
+        btn_search_model.click(fn=search_model, inputs=[search_name], outputs=[sarch_output])
+        
+        gr.HTML("<h4>Publica tu modelo</h4>")
+        post_name = gr.Textbox(placeholder="Billie Eillish (RVC v2 - 100 epoch)", label="Nombre", show_label=True)
+        post_model_url = gr.Textbox(placeholder="https://huggingface.co/AIVER-SE/BillieEilish/resolve/main/BillieEilish.zip", label="Url del modelo", show_label=True)
+        post_creator = gr.Textbox(placeholder="ID de discord o enlace al perfil del creador", label="Creador", show_label=True)
+        post_version = gr.Dropdown(choices=["RVC v1", "RVC v2"], value="RVC v1", label="Versión", show_label=True)
+        
+         # Salida
+        with gr.Row():
+            post_output = gr.Markdown(label="Salida")
+            
+        btn_post_model = gr.Button(value="Publicar")
+        btn_post_model.click(fn=post_model, inputs=[post_name, post_model_url, post_version, post_creator], outputs=[post_output])
     
     app.queue(concurrency_count=511, max_size=1022).launch(share=True)