Create app.py

app.py

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+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from langchain.llms import GooglePalm
+from langchain import LLMChain, PromptTemplate
+from gtts import gTTS
+from IPython.display import Audio
+import gradio as gr
+import numpy as np
+import os
+
+# Load image captioning model
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+
+def generate_caption_from_image(image_path):
+    # Process the image and generate caption
+    raw_image = Image.open(image_path).convert("RGB")
+    inputs = processor(raw_image, return_tensors="pt")
+    out = model.generate(**inputs)
+    caption = processor.decode(out[0], skip_special_tokens=True)
+    return caption
+
+def generate_story_from_caption(caption):
+    # Generate story based on caption
+    api_key = os.getenv("GOOGLE_API")
+    prompt_template = """You are a story teller;
+    You can generate a short story based on a simple narrative, the story should between 30 to 50 words;
+    CONTEXT: {scenario}
+    Story: """
+    PROMPT = PromptTemplate(template=prompt_template, input_variables=["scenario"])
+    llm_chain = LLMChain(prompt=PROMPT,
+                        llm=GooglePalm(google_api_key=api_key, temperature=0.8))
+    scenario = caption
+    story = llm_chain.run(scenario)
+    return story
+
+def text_to_speech(text):
+    # Convert text to speech
+    tts = gTTS(text=text, lang='en')
+    tts.save("output.mp3")
+    return "output.mp3"
+
+def generate_story_from_image(image_input):
+    input_image = Image.fromarray(image_input)
+    input_image.save("input_image.jpg")
+    image_path = 'input_image.jpg'
+    caption = generate_caption_from_image(image_path)
+    story = generate_story_from_caption(caption)
+    audio = text_to_speech(story)
+    return audio
+
+
+# Define the input and output components
+inputs = gr.Image(label="Image")
+outputs = gr.Audio(label="Story Audio")
+
+# Create the Gradio interface
+gr.Interface(fn=generate_story_from_image, inputs=inputs, outputs=outputs, title="Story Teller").launch(debug=True,share=True)