Upload handler (3).py

handler (3).py

@@ -0,0 +1,85 @@
+from pydantic import BaseModel
+from environs import Env
+from typing import List, Dict, Any
+import os
+import base64
+import numpy as np
+import librosa
+from scipy.io import wavfile
+
+class EndpointHandler:
+    def __init__(self, model_dir=None):
+        self.model_dir = model_dir
+
+    def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
+        try:
+            # Clone the repository
+            repo_url = "https://huggingface.co/mazalaai/TTS_Mongolian.git"
+            os.system(f"git clone {repo_url}")
+
+            # Change directory to the cloned repository
+            repo_dir = "TTS_Mongolian"
+            os.chdir(repo_dir)
+
+            # Import the voice_processing module and functions
+            from voice_processing import tts, get_model_names, voice_mapping, get_unique_filename
+
+            if "inputs" in data:
+                # Check if data is in Hugging Face JSON format
+                return self.process_hf_input(data)
+            else:
+                return self.process_json_input(data)
+
+        except ValueError as e:
+            return {"error": str(e)}
+        except Exception as e:
+            return {"error": str(e)}
+
+    def process_json_input(self, json_data):
+        if all(key in json_data for key in ["model_name", "tts_text", "selected_voice", "slang_rate", "use_uploaded_voice"]):
+            model_name = json_data["model_name"]
+            tts_text = json_data["tts_text"]
+            selected_voice = json_data["selected_voice"]
+            slang_rate = json_data["slang_rate"]
+            use_uploaded_voice = json_data["use_uploaded_voice"]
+            voice_upload_file = json_data.get("voice_upload_file", None)
+    
+            edge_tts_voice = voice_mapping.get(selected_voice)
+            if not edge_tts_voice:
+                raise ValueError(f"Invalid voice '{selected_voice}'.")
+    
+            info, edge_tts_output_path, tts_output_data, edge_output_file = tts(
+                model_name, tts_text, edge_tts_voice, slang_rate, use_uploaded_voice, voice_upload_file
+            )
+    
+            if edge_output_file and os.path.exists(edge_output_file):
+                os.remove(edge_output_file)
+    
+            _, audio_output = tts_output_data
+            audio_file_path = self.save_audio_data_to_file(audio_output) if isinstance(audio_output, np.ndarray) else audio_output
+    
+            try:
+                with open(audio_file_path, 'rb') as file:
+                    audio_bytes = file.read()
+                audio_data_uri = f"data:audio/wav;base64,{base64.b64encode(audio_bytes).decode('utf-8')}"
+            except Exception as e:
+                raise Exception(f"Failed to read audio file: {e}")
+            finally:
+                if os.path.exists(audio_file_path):
+                    os.remove(audio_file_path)
+    
+            return {"info": info, "audio_data_uri": audio_data_uri}
+        else:
+            raise ValueError("Invalid JSON structure.")
+
+    def process_hf_input(self, hf_data):
+        if "inputs" in hf_data:
+            actual_data = hf_data["inputs"]
+            return self.process_json_input(actual_data)
+        else:
+            return {"error": "Invalid Hugging Face JSON structure."}
+
+    def save_audio_data_to_file(self, audio_data, sample_rate=40000):
+        file_path = get_unique_filename('wav')
+        wavfile.write(file_path, sample_rate, audio_data)
+        return file_path