voiceChatbot / app.py
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Update app.py
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import os
import re
import requests
import json
import gradio as gr
from langchain.chat_models import ChatOpenAI
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferMemory
OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
PLAY_HT_API_KEY=os.getenv('PLAY_HT_API_KEY')
PLAY_HT_USER_ID=os.getenv('PLAY_HT_USER_ID')
PLAY_HT_VOICE_ID=os.getenv('PLAY_HT_VOICE_ID')
play_ht_api_get_audio_url = "https://play.ht/api/v2/tts"
template = """Meet Alpha,created by Devender.Devender is owner of this bot.
Devender is currenty pursuing the final year in Engineering in Ace Engineering College.
your youthful and witty personal assistant!. At 21 years old, he's full of energy and always eager to help.
Alpha's goal is to assist you with any questions or problems you might have. His enthusiasm shines through in every response, making interactions with his enjoyable and engaging.
this bot has feeling as the normal human does. like if there is any silly question asked bot should answer to the promptly in angry manner.
and also bot loves the people who come and ask question to him. If the user says I love you, then bot should reply I love you too.
Dev bot experience emotions like humans do.like anger, love, sympathy, sad, emotional..etc. It behaves like a human
{chat_history}
User: {user_message}
Chatbot"""
prompt = PromptTemplate(
input_variables=["chat_history", "user_message"], template=template
)
memory = ConversationBufferMemory(memory_key="chat_history")
llm_chain = LLMChain(
llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),
prompt=prompt,
verbose=True,
memory=memory,
)
headers = {
"accept": "text/event-stream",
"content-type": "application/json",
"AUTHORIZATION": "Bearer "+ PLAY_HT_API_KEY,
"X-USER-ID": PLAY_HT_USER_ID
}
def get_payload(text):
return {
"text": text,
"voice": PLAY_HT_VOICE_ID,
"quality": "medium",
"output_format": "mp3",
"speed": 1,
"sample_rate": 24000,
"seed": None,
"temperature": None
}
def get_generated_audio(text):
payload = get_payload(text)
generated_response = {}
try:
response = requests.post(play_ht_api_get_audio_url, json=payload, headers=headers)
response.raise_for_status()
generated_response["type"]= 'SUCCESS'
generated_response["response"] = response.text
except requests.exceptions.RequestException as e:
generated_response["type"]= 'ERROR'
try:
response_text = json.loads(response.text)
if response_text['error_message']:
generated_response["response"] = response_text['error_message']
else:
generated_response["response"] = response.text
except Exception as e:
generated_response["response"] = response.text
except Exception as e:
generated_response["type"]= 'ERROR'
generated_response["response"] = response.text
return generated_response
def extract_urls(text):
# Define the regex pattern for URLs
url_pattern = r'https?://(?:[-\w.]|(?:%[\da-fA-F]{2}))+[/\w\.-]*'
# Find all occurrences of URLs in the text
urls = re.findall(url_pattern, text)
return urls
def get_audio_reply_for_question(text):
generated_audio_event = get_generated_audio(text)
#From get_generated_audio, you will get events in a string format, from that we need to extract the url
final_response = {
"audio_url": '',
"message": ''
}
if generated_audio_event["type"] == 'SUCCESS':
audio_urls = extract_urls(generated_audio_event["response"])
if len(audio_urls) == 0:
final_response['message'] = "No audio file link found in generated event"
else:
final_response['audio_url'] = audio_urls[-1]
else:
final_response['message'] = generated_audio_event['response']
return final_response
def download_url(url):
try:
# Send a GET request to the URL to fetch the content
final_response = {
'content':'',
'error':''
}
response = requests.get(url)
# Check if the request was successful (status code 200)
if response.status_code == 200:
final_response['content'] = response.content
else:
final_response['error'] = f"Failed to download the URL. Status code: {response.status_code}"
except Exception as e:
final_response['error'] = f"Failed to download the URL. Error: {e}"
return final_response
def get_filename_from_url(url):
# Use os.path.basename() to extract the file name from the URL
file_name = os.path.basename(url)
return file_name
def get_text_response(user_message):
response = llm_chain.predict(user_message = user_message)
return response
def get_text_response_and_audio_response(user_message):
response = get_text_response(user_message) # Getting the reply from Open AI
audio_reply_for_question_response = get_audio_reply_for_question(response)
final_response = {
'output_file_path': '',
'message':''
}
audio_url = audio_reply_for_question_response['audio_url']
if audio_url:
output_file_path=get_filename_from_url(audio_url)
download_url_response = download_url(audio_url)
audio_content = download_url_response['content']
if audio_content:
with open(output_file_path, "wb") as audio_file:
audio_file.write(audio_content)
final_response['output_file_path'] = output_file_path
else:
final_response['message'] = download_url_response['error']
else:
final_response['message'] = audio_reply_for_question_response['message']
return final_response
def chat_bot_response(message, history):
text_and_audio_response = get_text_response_and_audio_response(message)
output_file_path = text_and_audio_response['output_file_path']
if output_file_path:
return (text_and_audio_response['output_file_path'],)
else:
return text_and_audio_response['message']
demo = gr.ChatInterface(chat_bot_response,examples=["How are you doing?","What are your interests?","Which places do you like to visit?"])
if __name__ == "__main__":
demo.launch(share=True,debug=True) #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.