Update app.py

app.py

@@ -1,5 +1,7 @@
 import streamlit as st
 import requests
+from transformers import pipeline
+
 
 # Function to send the audio file to the Hugging Face Whisper API
 def query(file_data, my_key):
@@ -7,47 +9,49 @@ def query(file_data, my_key):
     headers = {"Authorization": f"Bearer {my_key}"}
     
     try:
-        response = requests.post(API_URL, headers=headers, files={'file': file_data})
-        return response.json()
+        response = requests.post(API_URL, headers=headers, files={"file": file_data})
+        if response.status_code == 200:
+            return response.json()
+        else:
+            return {"error": f"API returned status code {response.status_code}: {response.text}"}
     except requests.exceptions.RequestException as e:
         return {"error": str(e)}
 
 # Streamlit UI elements
 st.title("Whisper Transcription App")
-st.write("Upload a .wav, .mp3, or .flac audio file, and get the transcription.")
+st.write("Upload one or more .wav, .mp3, or .flac audio files, and get the transcription.")
 
 # Get the user's Hugging Face API key
-my_key = st.text_input('Enter your Hugging Face API Key', type='password')
+my_key = st.text_input("Enter your Hugging Face API Key", type="password")
 
 # File uploader for audio files
-uploaded = st.file_uploader("Choose an audio file", type=["mp3", "wav", "flac"], accept_multiple_files=True)
+uploaded_files = st.file_uploader("Choose audio file(s)", type=["mp3", "wav", "flac"], accept_multiple_files=True)
 
-if my_key:  # Proceed only if the API key is provided
-    API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo"
-    headers = {"Authorization": f"Bearer {my_key}"}
-    
-    def query(filename):
-      filename = list(uploaded.keys())[0]  # Get the uploaded file's nameprint("Uploaded filename:", filename)
-      with open(filename, "rb") as f:
-            data = f.read()
-      response = requests.post(API_URL, headers=headers, data=data)
-      return response.json()
+if my_key and uploaded_files:  # Proceed only if the API key is provided and files are uploaded
+    st.write("Processing your files...")
+    results = {}
     
-    results = {}  
-    for filename, file_data in uploaded.items():
-        # Save the file locally
-        with open(filename, "wb") as f:
-            f.write(file_data)
-        
-        print(f"Sending {filename} to API...")
-        output = query(filename)
-        
-        # Store the result
-        results[filename] = output
+    for uploaded_file in uploaded_files:
+        try:
+            # Read the file data
+            file_data = uploaded_file.read()
+            
+            # Query the API
+            st.write(f"Transcribing: {uploaded_file.name}")
+            result = query(file_data, my_key)
+            
+            # Store the result
+            results[uploaded_file.name] = result
+        except Exception as e:
+            st.write(f"Error processing {uploaded_file.name}: {str(e)}")
     
-    # Step 3: Print results
+    # Display results
     for file, result in results.items():
-        st.write(f"\nResults for {file}:\n{result}")
+        st.write(f"**Results for {file}:**")
+        if "error" in result:
+            st.error(result["error"])
+        else:
+            st.json(result)