Create app.py

app.py

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+import streamlit as st
+import pysftp
+import os
+import librosa
+import numpy as np
+from transformers import pipeline
+
+# Configure SFTP settings
+st.title("Sentiment Analysis from Remote Audio Files 🎵")
+
+# User inputs for SFTP connection
+st.sidebar.header("📡 SFTP Login")
+host = st.sidebar.text_input("Host", "cph.v4one.co.uk")  
+username = st.sidebar.text_input("Username", "your_username")
+password = st.sidebar.text_input("Password", type="password")
+remote_path = "/path/to/audio/folders"  # Adjust based on your server
+
+# Connect and List Available Folders
+if st.sidebar.button("🔄 Connect & List Folders"):
+    try:
+        cnopts = pysftp.CnOpts()
+        cnopts.hostkeys = None  # Ignore host key check (only for testing)
+        
+        with pysftp.Connection(host, username=username, password=password, cnopts=cnopts) as sftp:
+            folders = sftp.listdir(remote_path)
+            available_dates = [folder for folder in folders if folder.startswith("2025")]  # Filter date-based folders
+
+        st.session_state["available_dates"] = available_dates  # Store in session state
+        st.success("✅ Connected! Select a date below.")
+    except Exception as e:
+        st.error(f"Connection failed: {e}")
+
+# Dropdown for Date Selection
+if "available_dates" in st.session_state:
+    selected_date = st.selectbox("📅 Select a Date", st.session_state["available_dates"])
+
+    if st.button("📥 Download & Analyze"):
+        with pysftp.Connection(host, username=username, password=password, cnopts=cnopts) as sftp:
+            local_folder = f"temp_audio/{selected_date}"
+            os.makedirs(local_folder, exist_ok=True)  # Create local folder
+
+            remote_folder = f"{remote_path}/{selected_date}"
+            audio_files = sftp.listdir(remote_folder)
+
+            # Download each file
+            for file in audio_files:
+                local_file_path = os.path.join(local_folder, file)
+                remote_file_path = f"{remote_folder}/{file}"
+                sftp.get(remote_file_path, local_file_path)
+
+        st.success(f"✅ Downloaded {len(audio_files)} files from {selected_date}")
+
+        # Sentiment Analysis
+        sentiment_model = pipeline("sentiment-analysis")
+        results = []
+
+        for file in os.listdir(local_folder):
+            file_path = os.path.join(local_folder, file)
+            y, sr = librosa.load(file_path, sr=16000)
+            mfccs = np.mean(librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13), axis=1)
+
+            # Mock transcription (Replace with real ASR model)
+            text = "This is a sample transcription"
+            sentiment = sentiment_model(text)
+
+            results.append({"File": file, "Sentiment": sentiment[0]["label"], "Confidence": sentiment[0]["score"]})
+
+        st.write("### Sentiment Analysis Results")
+        st.table(results)