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| from transformers import pipeline | |
| from langchain import PromptTemplate, LLMChain | |
| from langchain.llms import GooglePalm | |
| import requests | |
| import os | |
| import streamlit as st | |
| os.environ["GOOGLE_API_KEY"] = "AIzaSyD29fEos3V6S2L-AGSQgNu03GqZEIgJads" | |
| os.environ ["HUGGINGFACEHUB_API_TOKEN"] = "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" | |
| llm = GooglePalm(temperature = 0.7) | |
| #image to text | |
| def image2text(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) | |
| #story teller | |
| def generate_story(scenario): | |
| template = """" | |
| You are a story teller; | |
| you can generate a creative fun story based on a sample narrative, the story should not be more than 100 words; | |
| CONTEXT: {scenario} | |
| STORY: | |
| """ | |
| prompt = PromptTemplate(template = template, | |
| input_variables = ['scenario'] | |
| ) | |
| story_llm = LLMChain(llm=llm, prompt = prompt, verbose = True) | |
| story = story_llm.predict(scenario = scenario) | |
| print(story) | |
| return(story) | |
| #text to speech | |
| def text2speech(message): | |
| API_URL = "https://api-inference.huggingface.co/models/espnet/fastspeech2_conformer" | |
| headers = {"Authorization": "Bearer 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"} | |
| payloads = { | |
| "inputs":message | |
| } | |
| response = requests.post(API_URL, headers = headers, json= payloads) | |
| with open("audio.flac", "wb") as file: | |
| file.write(response.content) | |
| def main(): | |
| st.set_page_config(page_title="Your Image to Audio Story", page_icon="🦜") | |
| st.header("Turn Your Image to Audio Story") | |
| uploaded_file = st.file_uploader("Select an Image...") | |
| if uploaded_file is not None: | |
| print(uploaded_file) | |
| bytes_data = uploaded_file.getvalue() | |
| with open(uploaded_file.name, 'wb') as file: | |
| file.write(bytes_data) | |
| st.image(uploaded_file, caption="Uploaded Image", | |
| use_column_width= True) | |
| scenario = image2text(uploaded_file.name) | |
| st.subheader("Image Details:") | |
| st.write(scenario) | |
| story = generate_story(scenario) | |
| st.subheader("Story:") | |
| st.write(story) | |
| text2speech(story) | |
| st.subheader("Generated Audio:") | |
| st.audio("audio.flac", format="audio/flac") | |
| # Add a download link for the audio | |
| st.subheader("Download Audio:") | |
| with open("audio.flac", "rb") as audio_file: | |
| st.download_button(label="Download Audio", data=audio_file, file_name="generated_audio.flac", mime="audio/flac") | |
| if __name__ == "__main__": | |
| main() | |