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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 = """You are a helpful assistant to answer user queries.
{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() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.
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