Duplicate from fffiloni/Image-to-Story

Co-authored-by: Sylvain Filoni <[email protected]>

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README.md

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+---
+title: Image To Story
+emoji: 👁
+colorFrom: pink
+colorTo: red
+sdk: gradio
+sdk_version: 3.39.0
+app_file: app.py
+pinned: false
+duplicated_from: fffiloni/Image-to-Story
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+
+import os 
+hf_token = os.environ.get('HF_TOKEN')
+from gradio_client import Client
+client = Client("https://fffiloni-test-llama-api.hf.space/", hf_token=hf_token)
+
+clipi_client = Client("https://fffiloni-clip-interrogator-2.hf.space/")
+
+def get_text_after_colon(input_text):
+    # Find the first occurrence of ":"
+    colon_index = input_text.find(":")
+    
+    # Check if ":" exists in the input_text
+    if colon_index != -1:
+        # Extract the text after the colon
+        result_text = input_text[colon_index + 1:].strip()
+        return result_text
+    else:
+        # Return the original text if ":" is not found
+        return input_text
+
+def infer(image_input):
+    
+    clipi_result = clipi_client.predict(
+    				image_input,	# str (filepath or URL to image) in 'parameter_3' Image component
+    				"best",	# str in 'Select mode' Radio component
+    				4,	# int | float (numeric value between 2 and 24) in 'best mode max flavors' Slider component
+    				api_name="/clipi2"
+    )
+    print(clipi_result)
+   
+
+    llama_q = f"""
+    I'll give you a simple image caption, from i want you to provide a story that would fit well with the image:
+    '{clipi_result[0]}'
+    
+    """
+    
+    result = client.predict(
+    				llama_q,	# str in 'Message' Textbox component
+    				api_name="/predict"
+    )
+
+    print(f"Llama2 result: {result}")
+
+    result = get_text_after_colon(result)
+
+    return result
+
+css="""
+#col-container {max-width: 910px; margin-left: auto; margin-right: auto;}
+a {text-decoration-line: underline; font-weight: 600;}
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(
+            """
+            <h1 style="text-align: center">Image to Story</h1>
+            <p style="text-align: center">Upload an image, get a story made by Llama2 !</p>
+            """
+        )
+        with gr.Row():
+            with gr.Column():
+                image_in = gr.Image(label="Image input", type="filepath")
+                submit_btn = gr.Button('Tell me a story')
+            with gr.Column():
+                #caption = gr.Textbox(label="Generated Caption")
+                story = gr.Textbox(label="generated Story")
+        gr.Examples(examples=[["./examples/crabby.png"],["./examples/hopper.jpeg"]],
+                    fn=infer,
+                    inputs=[image_in],
+                    outputs=[story],
+                    cache_examples=True
+                   )
+    submit_btn.click(fn=infer, inputs=[image_in], outputs=[story])
+
+demo.queue(max_size=12).launch()