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()