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Update app.py
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app.py
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import gradio as gr
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# Using openai models ---------------------------------------------------------
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from langchain_openai import OpenAI
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import os
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openai_api_key = os.getenv("OPENAI_API_KEY")
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@@ -11,58 +7,60 @@ import base64
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import requests
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from PIL import Image
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def generate_story(image, theme, genre, word_count):
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try:
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width = 1000
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# Function to resize image maintaining aspect ratio with a maximum width of 1000 pixels
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def resize_image(image, max_width=width):
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with Image.open(image) as img:
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ratio = max_width / img.width
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new_height = int(img.height * ratio)
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resized_img = img.resize((max_width, new_height), Image.ANTIALIAS)
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img_byte_arr = io.BytesIO()
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resized_img.save(img_byte_arr, format=img.format)
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return img_byte_arr.getvalue()
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# Function to encode the image to base64
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def encode_image(image):
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resized_image_bytes = resize_image(image) # Resize the image
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return base64.b64encode(resized_image_bytes).decode('utf-8')
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# Function to call the API for image and get the response
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def get_response_for_image(openai_api_key, image):
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base64_image = encode_image(image)
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {openai_api_key}"
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}
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payload = {
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"model": "gpt-4o",
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"messages": [
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": '''Describe or caption the image within 20 words.'''
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},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{base64_image}",
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"detail": "low"
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}
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}
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]
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}
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],
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"max_tokens": 500
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}
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response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
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return response['choices'][0]['message']['content']
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# Decode the caption
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caption_text = get_response_for_image(openai_api_key, image)
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@@ -139,3 +137,4 @@ gr.Interface(
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title="Image to Story Generator",
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description="Generate a story from an image taking theme and genre as input. It leverages image captioning and text generation models.",
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).launch()
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from langchain_openai import OpenAI
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import os
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openai_api_key = os.getenv("OPENAI_API_KEY")
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import requests
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from PIL import Image
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width = 1000
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# Function to resize image maintaining aspect ratio with a maximum width of 1000 pixels
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def resize_image(image, max_width=width):
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with Image.open(image) as img:
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ratio = max_width / img.width
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new_height = int(img.height * ratio)
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resized_img = img.resize((max_width, new_height), Image.ANTIALIAS)
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img_byte_arr = io.BytesIO()
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resized_img.save(img_byte_arr, format=img.format)
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return img_byte_arr.getvalue()
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# Function to encode the image to base64
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def encode_image(image):
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resized_image_bytes = resize_image(image) # Resize the image
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return base64.b64encode(resized_image_bytes).decode('utf-8')
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# Function to call the API for image and get the response
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def get_response_for_image(openai_api_key, image):
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base64_image = encode_image(image)
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {openai_api_key}"
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}
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payload = {
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"model": "gpt-4o",
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"messages": [
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": '''Describe or caption the image within 20 words.'''
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},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{base64_image}",
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"detail": "low"
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}
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}
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]
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}
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],
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"max_tokens": 500
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}
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response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
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return response['choices'][0]['message']['content']
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def generate_story(image, theme, genre, word_count):
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try:
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# Decode the caption
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caption_text = get_response_for_image(openai_api_key, image)
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title="Image to Story Generator",
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description="Generate a story from an image taking theme and genre as input. It leverages image captioning and text generation models.",
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).launch()
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