Update app.py

app.py

@@ -1,63 +1,43 @@
-import requests
-import tiktoken
 import streamlit as st
-import json
-import time
+import requests
+import base64
 
-# Define the API URL
 API_URL = "https://startrz-proagents.hf.space/api/v1/prediction/9ad2e52d-052f-44e5-b3a0-7fd432d86506"
 
-# Function to query the API
 def query(payload):
     response = requests.post(API_URL, json=payload)
     return response.json()
 
-# Function to calculate token usage using tiktoken
-def calculate_tokens(text):
-    encoding = tiktoken.get_encoding("cl100k_base")
-    tokens = encoding.encode(text)
-    return tokens
-
-# Streamlit app
-st.title("API Query with Token Calculation")
-
-# User input for the question
-question = st.text_input("Enter your question:", "Hey, how are you?")
-
-# Button to trigger the API call and calculations
-if st.button("Submit"):
-    with st.spinner("Calculating..."):
-        # Payload for the API
-        payload = {"question": question}
-
-        # Measure the response time
-        start_time = time.time()  # Start the timer
-
-        # Query the API
-        response_data = query(payload)
-
-        # End the timer and calculate response time
-        response_time = time.time() - start_time
-
-        # Calculate input tokens
-        input_tokens = calculate_tokens(str(payload))
-
-        # Calculate output tokens from the response (assuming 'result' field contains the output text)
-        output_text = response_data.get("text", "")
-        output_tokens = calculate_tokens(output_text)
-
-        # Total tokens
-        total_tokens = len(input_tokens) + len(output_tokens)
-
-        # Structure the data with token information
-        data = {
-            "prediction": response_data,
-            "inputTokens": len(input_tokens),
-            "outputTokens": len(output_tokens),
-            "totalTokens": total_tokens,
-            "predictionTime": f"{round(response_time, 2)} secs"
+def main():
+    st.title("Audio Upload and Prediction")
+
+    # File uploader for audio files
+    audio_file = st.file_uploader("Upload an audio file (WebM format)", type=["webm"])
+
+    if audio_file is not None:
+        # Convert the audio file to a Base64 string
+        audio_bytes = audio_file.read()
+        audio_base64 = base64.b64encode(audio_bytes).decode('utf-8')
+        audio_mime_type = audio_file.type  # Get the mime type
+
+        # Prepare the payload
+        payload = {
+            "uploads": [
+                {
+                    "data": f'data:{audio_mime_type};base64,{audio_base64}',
+                    "type": 'audio',
+                    "name": audio_file.name,
+                    "mime": audio_mime_type
+                }
+            ]
         }
 
-        # Display the data
-        st.subheader("Response Data")
-        st.json(data)
+        # Send the request to the API and get the output
+        if st.button("Submit"):
+            with st.spinner("Sending request..."):
+                output = query(payload)
+                st.success("Request sent successfully!")
+                st.json(output)  # Display the API response
+
+if __name__ == "__main__":
+    main()