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from pydub import AudioSegment
from dotenv import find_dotenv, load_dotenv
from transformers import pipeline
from elevenlabs import generate, play, voices
from elevenlabs import set_api_key
from elevenlabslib import ElevenLabsUser
import streamlit as st
import uuid
from langchain import LLMChain, PromptTemplate, OpenAI
import os
# Load environment variables
load_dotenv(find_dotenv())
def img2text(url):
image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
text = image_to_text(url)[0]["generated_text"]
print(text)
return text
def generated_story(scenario):
template = """
You are the famous comedian and podcaster Tim Dillon. You will generate a short story in the style of his podcast using a funny narrative with explicit language and an angry rant-like tone, the story should be no more than 100 words;
Context: {scenario}
Story:
"""
prompt = PromptTemplate(template=template, input_variables=["scenario"])
story_llm = LLMChain(llm=OpenAI(model_name="gpt-3.5-turbo", temperature=1), prompt=prompt, verbose=True)
story = story_llm.predict(scenario=scenario)
print(story)
return story
def textToSpeech(story):
# Error Handling: Print available user-generated voices
try:
available_voices = user.get_available_voices()
print("Available Voices:", available_voices)
except Exception as e:
print("Error fetching available voices:", e)
# Set API key for ElevenLabs
set_api_key = os.getenv("ELEVENLABS_API_KEY")
user = ElevenLabsUser(set_api_key)
voice = user.get_voice_by_ID("cgOzEASJmlEWHtXnZJ5q")
# Generate the audio data
result = voice.generate_audio_v2(story)
# Assuming the audio data is the first element of the tuple
audio_data = result[0]
# Save the audio data to a file in the project folder
random_id = str(uuid.uuid4())
name = f"story_{random_id}.mp3"
#Save the audio data to a file in the project folder
with open(name, 'wb') as f:
f.write(audio_data)
return name
def main():
st.set_page_config(page_title="Tim Dillon Image To Story", page_icon="📖", layout="wide")
st.header("Tim Dillon Image To Story")
uploaded_file = st.file_uploader("Upload an image...", type="jpg")
if uploaded_file is not None:
print(uploaded_file)
bytes_data = uploaded_file.getvalue()
with open (uploaded_file.name, 'wb') as f:
f.write(bytes_data)
st.image(bytes_data, caption='Uploaded Image.', use_column_width=True)
scenario = img2text(uploaded_file.name)
story = generated_story(scenario)
generated_file_name = textToSpeech(story)
with st.expander("scenario"):
st.write(scenario)
with st.expander("story"):
st.write(story)
st.audio(generated_file_name)
if __name__ == "__main__":
main() |