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README.md

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+# 🖼️ Image to 🎧 Audio Story Generator
+
+This project showcases an end-to-end pipeline that transforms an image into an audio story using various AI models and tools.
+
+## 🌟 Overview
+
+The goal of this project is to leverage AI capabilities to convert an uploaded image into an audio story. It uses a combination of image captioning, text generation, and text-to-speech models.
+
+## 🚀 Features
+
+### 📷 Image Captioning
+- Utilizes Salesforce's `blip-image-captioning-base` model to generate textual descriptions of uploaded images.
+
+### ✍️ Text Generation (Story Creation)
+- Employs OpenAI's `togethercomputer/llama-2-70b-chat` model to create a short story influenced by the provided image caption within a positive conclusion of 100 words or less.
+
+### 🔊 Text-to-Speech Conversion
+- Utilizes Hugging Face's `espnet/kan-bayashi_ljspeech_vits` model to convert the generated story into an audio file.
+
+### 🌐 Streamlit Web App
+- Built using Streamlit, allowing users to upload images and visualize the generated image caption, story, and audio.
+
+## 📝 Usage
+
+To use this application:
+
+1. Clone this repository.
+2. Install the required dependencies using `pip install -r requirements.txt`.
+3. Set up the necessary environment variables:
+   - `TOGETHER_API_KEY`: OpenAI API key.
+   - `HUGGINGFACEHUB_API_TOKEN`: Hugging Face API token.
+4. Run the Streamlit app with `streamlit run app.py`.
+5. Upload an image file (supported formats: jpg, jpeg, png).
+6. Wait for the AI processing to generate the story and audio.
+7. Access the image caption, story, and audio outputs.
+
+## 📁 Code Structure
+
+- `app.py`: Contains the Streamlit web application code, integrating all functionalities.
+- `README.md`: Documentation explaining the project, usage instructions, and dependencies.
+- `requirements.txt`: Lists all necessary libraries.
+
+## 🙌 Credits
+
+This project was created with love by @Aditya-Neural-Net-Ninja. It makes use of cutting-edge AI models for image analysis, natural language processing, and text-to-speech conversion. Special thanks to Streamlit and Hugging Face for their incredible platforms.
+
+
+**Note:** Please ensure you have the required API keys and tokens for OpenAI and Hugging Face to run this application successfully.
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference