Update app.py

app.py

@@ -1,13 +1,13 @@
-from fastapi import Depends, FastAPI, HTTPException, Request
+from fastapi import FastAPI, Request
 from fastapi.responses import JSONResponse, StreamingResponse
 from fastapi.middleware.cors import CORSMiddleware
-from typing import Optional
 from logic import synthesize_voice, plot_data, plot_waveforms
 import base64
-import sys
 import numpy as np
 from io import BytesIO
 from hifigan.inference_e2e import hifi_gan_inference
+import asyncio
+from queue import SimpleQueue
 
 app = FastAPI()
 
@@ -20,20 +20,36 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
+# Use a queue to communicate progress between endpoints
+progress_queue = SimpleQueue()
+
 async def send_progress(progress: int):
     data = f"data: {progress}\n\n"
+    progress_queue.put(data)
     return StreamingResponse(content=data.encode(), media_type="text/event-stream")
 
+# Progress bar
+@app.get("/liveprogress")
+async def sse_endpoint():
+    async def generate():
+        while True:
+            if not progress_queue.empty():
+                progress = progress_queue.get()
+                yield progress
+            await asyncio.sleep(0.1)  # Adjust the sleep duration as needed
+
+    return StreamingResponse(generate(), media_type="text/event-stream")
+
 # Existing POST endpoint
 @app.post("/synthesize")
 async def synthesize(request: Request):
     print("call successful")
-    
+
     json = await request.json()
     print(json)
-    
+
     font_type = json['font_select']
-    input_text = json['input_text']     
+    input_text = json['input_text']
 
     # Initial progress update
     await send_progress(0)
@@ -55,19 +71,19 @@ async def synthesize(request: Request):
     buffer = BytesIO()
     np.save(buffer, mel_output_data)
     input_mel = buffer.getvalue()
-    
+
     hifigan_checkpoint = "generator_v1"
-    
-    # Generate audio using Hifigan
+
+    # Step 4: Generate audio using Hifigan
     audio_data = hifi_gan_inference(input_mel, hifigan_checkpoint)
     
-    # Update progress after Hifigan inference
+    # Update progress after audio generation using Hifigan
     await send_progress(90)
 
-    # Step 4: Plot the waveform
+    # Step 5: Plot the waveform
     wave_base64 = plot_waveforms(audio_data)
 
-    # Update progress after plot_waveforms
+    # Wait for all the data to be ready before sending 100% progress
     await send_progress(100)
 
     # Encode audio content as Base64