Update app.py

app.py

@@ -0,0 +1,75 @@
+import os 
+import time 
+import requests
+import gradio as gr 
+from huggingface_hub import login
+from dotenv import load_dotenv
+
+load_dotenv()
+image_API="https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-2"
+translation_API="https://api-inference.huggingface.co/models/facebook/nllb-200-distilled-1.3B"
+whisper_API="https://api-inference.huggingface.co/models/openai/whisper-large-v3"
+
+HF_TOKEN=os.getenv("HF_Token")
+login(HF_TOKEN)
+headers={"Authorization":f"Bearer {HF_TOKEN}"}
+
+
+def query_whisper(audio_path):
+  with open(audio_path,"rb") as audio:
+    data=audio.read()
+    response=requests.post(whisper_API,headers=headers,data=data)
+    return response.json()
+
+def query_translation(text):
+  max_retries=5
+  delay=10
+  payload={"inputs":text,"parameters":{"src_lang":"ta_Taml","tgt_lang":}}
+  for attempt in range(max_retries):
+    response=requests.post(translation_API,headers=headers,json=payload)
+    result= response.json()
+    if isinstance(result,list) and len(result)>0:
+      return {"translated_text":result[0]["translation_text"]}
+    elif isinstance(result,dict) and "translation_text" in result:
+      return {"translated_text":result["translation_text"]}
+    time.sleep(delay)
+  return {"error":"Translation API failed","response":result}
+
+def query_image(prompt):
+  max_retries=5
+  delay=10
+  payload={"inputs":prompt}
+  for attempt in range(max_retries):
+    response=requests.post(image_API,headers=headers,json=payload)
+    if response.status_code==200 and response.get.headers('Content-Type','').startswith('image/'):
+      image_path='generated_image.png'
+      with open(image_path,'wb') as f:
+        f.write(response.content)
+      return image_path
+    time.sleep(delay)
+  return None
+
+def process_audio(audio_path):
+  if not audio_path:
+    return None
+  try:
+    transcription=query_whisper(audio_path)
+    tamil_text=transcription.get("text","Transcription error")
+    translation=query_translation(tamil_text)
+    translated_text=translation.get("translated_text","Translation error")
+    image_path=query_image(translated_text)
+    return tamil_text,translated_text,image_path
+  except Exception as e:
+    return None,str(e),None
+
+iface=gradio.Interface(
+    fn=process_audio,
+    inputs=gradio.Audio(type="filepath",label="Upload Audio"),
+    outputs=[
+        gradio.Textbox(label="Tamil Text"),
+        gradio.Textbox(label="English Translation"),
+        gradio.Image(label="Generated Image")
+    ],
+    title= title="Speech-to-Image Generation"
+)
+iface.launch(share=True,server_name="0.0.0.0",server_port=7860)