Create app.py

app.py

@@ -0,0 +1,46 @@
+import json
+import whisper
+import requests
+
+medium_en = whisper.load_model("medium.en")
+
+def send_results_to_api(data, result_url):
+    headers = {"Content-Type": "application/json"}
+    response = requests.post(result_url, json= data, headers= headers)
+
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return {"error": f"Failed to send results to API: {response.status_code}"}
+
+
+def process_audio(params):
+    try:
+        params = json.loads(params)
+    except json.JSONDecodeError as e:
+        return {"error": f"Invalid JSON input: {e.msg} at line {e.lineno} column {e.colno}"}
+    
+    audio_files = params.get("audio_files",[])
+    api = params.get("api","")
+    job_id = params.get("job_id","")
+
+    solutions=[]
+
+    for audio in audio_files:
+        result_medium = medium_en.transcribe(audio)
+        text = result_medium['text']
+
+        answer_dict = {}
+        answer_dict.update({'file_name':audio, 'text':text})
+        solutions.append(answer_dict)
+    result_url = f"{api}/{job_id}"
+    # send_results_to_api(solutions, result_url)
+
+    return json.dumps({"solutions":solutions}, indent=4)
+
+import gradio as gr
+inputt = gr.Textbox(label="Parameters in json format   Eg. {'audio_files':['file1.mp3','file2.wav'], 'api':'https://api.example.com', 'job_id':'1001'}")
+outputt = gr.JSON()
+
+application = gr.Interface(fn=process_audio, inputs= inputt, outputs = outputt, title = "Audio Transcription with API Integration")
+application.launch()