tutorial71

tutorial71/audio_gen.py

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+# Import necessary libraries
+import requests  # Used for making HTTP requests
+import os  # Used for working with JSON data
+
+# Define constants for the script
+CHUNK_SIZE = 1024  # Size of chunks to read/write at a time
+XI_API_KEY = os.getenv("ELEVEN_API_KEY")  # Your API key for authentication
+VOICE_ID = "GBv7mTt0atIp3Br8iCZE"  # ID of the voice model to use
+OUTPUT_PATH = "output.wav"  # Path to save the output audio file
+
+# Construct the URL for the Text-to-Speech API request
+tts_url = f"https://api.elevenlabs.io/v1/text-to-speech/{VOICE_ID}/stream"
+
+# Set up headers for the API request, including the API key for authentication
+headers = {
+    "Accept": "application/json",
+    "xi-api-key": XI_API_KEY
+}
+def generate_audio(text):
+# Set up the data payload for the API request, including the text and voice settings
+    data = {
+        "text": text,
+        "model_id": "eleven_multilingual_v2",
+        "voice_settings": {
+            "stability": 1,
+            "similarity_boost": 0.8,
+            "style": 0.0,
+            "use_speaker_boost": True
+        }
+    }
+
+    # Make the POST request to the TTS API with headers and data, enabling streaming response
+    response = requests.post(tts_url, headers=headers, json=data, stream=True)
+
+    # Check if the request was successful
+    if response.ok:
+        # Open the output file in write-binary mode
+        with open(OUTPUT_PATH, "wb") as f:
+            # Read the response in chunks and write to the file
+            for chunk in response.iter_content(chunk_size=CHUNK_SIZE):
+                f.write(chunk)
+        # Inform the user of success
+        print("Audio stream saved successfully.")
+    else:
+        # Print the error message if the request was not successful
+        print(response.text)

tutorial71/ids.py

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+# The 'requests' and 'json' libraries are imported. 
+# 'requests' is used to send HTTP requests, while 'json' is used for parsing the JSON data that we receive from the API.
+import requests
+import json,os
+
+# An API key is defined here. You'd normally get this from the service you're accessing. It's a form of authentication.
+XI_API_KEY = "<xi-api-key>"
+
+# This is the URL for the API endpoint we'll be making a GET request to.
+url = "https://api.elevenlabs.io/v1/voices"
+
+# Here, headers for the HTTP request are being set up. 
+# Headers provide metadata about the request. In this case, we're specifying the content type and including our API key for authentication.
+headers = {
+  "Accept": "application/json",
+  "xi-api-key":  os.getenv("ELEVEN_API_KEY"),
+  "Content-Type": "application/json"
+}
+
+# A GET request is sent to the API endpoint. The URL and the headers are passed into the request.
+response = requests.get(url, headers=headers)
+
+# The JSON response from the API is parsed using the built-in .json() method from the 'requests' library. 
+# This transforms the JSON data into a Python dictionary for further processing.
+data = response.json()
+
+# A loop is created to iterate over each 'voice' in the 'voices' list from the parsed data. 
+# The 'voices' list consists of dictionaries, each representing a unique voice provided by the API.
+for voice in data['voices']:
+  # For each 'voice', the 'name' and 'voice_id' are printed out. 
+  # These keys in the voice dictionary contain values that provide information about the specific voice.
+  print(f"{voice['name']}; {voice['voice_id']}")

tutorial71/main.py

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+import streamlit as st
+from streamlit_mic_recorder import speech_to_text
+from langchain_openai import ChatOpenAI
+from audio_gen import generate_audio
+
+llm=ChatOpenAI(model="gpt-4o")
+st.title("VOICE ENABLED CHAT APP")
+st.write("ask anything")
+text=speech_to_text(language="en",use_container_width=True,just_once=True,key="STT")
+if text:
+    response=llm.invoke(text)
+    content=response.content
+    st.write(content)
+    generate_audio(content)
+    st.audio(data="output.wav",format="audio/wav",autoplay=True)