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Update app.py
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app.py
CHANGED
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@@ -8,7 +8,7 @@ from gradio_client import Client
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#fuyu_client = Client("https://adept-fuyu-8b-demo.hf.space/")
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kosmos2_client = Client("https://ydshieh-kosmos-2.hf.space/")
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def
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"""
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fuyu_result = fuyu_client.predict(
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image_in, # str representing input in 'raw_image' Image component
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@@ -106,11 +106,12 @@ Here's another example. If a user types, "In the image, there is a drawing of a
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return outputs
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def infer(image_in):
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gr.Info("Getting image description...")
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gr.Info("Building a system according to the image caption ...")
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outputs = get_llm_idea(user_prompt)
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@@ -148,6 +149,14 @@ with gr.Blocks(css=css) as demo:
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type = "filepath",
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elem_id = "image-in"
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)
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submit_btn = gr.Button("Make LLM system from my pic !")
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with gr.Column():
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caption = gr.Textbox(
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@@ -172,15 +181,14 @@ with gr.Blocks(css=css) as demo:
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["examples/chicken_adobo.jpeg"]
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],
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fn = infer,
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inputs = [image_in]
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outputs = [caption, result],
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cache_examples = False
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)
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submit_btn.click(
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fn = infer,
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inputs = [
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image_in
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],
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outputs =[
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caption,
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@@ -188,4 +196,4 @@ with gr.Blocks(css=css) as demo:
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]
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)
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demo.queue().launch(show_api=False)
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#fuyu_client = Client("https://adept-fuyu-8b-demo.hf.space/")
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kosmos2_client = Client("https://ydshieh-kosmos-2.hf.space/")
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def get_caption_from_kosmos(image_in):
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"""
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fuyu_result = fuyu_client.predict(
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image_in, # str representing input in 'raw_image' Image component
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return outputs
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def infer(image_in, cap_type):
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gr.Info("Getting image description...")
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if cap_type == "Fictional" :
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user_prompt = get_caption_from_MD(image_in)
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elif cap_type == "Literal" :
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user_prompt = get_caption_from_kosmos(image_in)
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gr.Info("Building a system according to the image caption ...")
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outputs = get_llm_idea(user_prompt)
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type = "filepath",
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elem_id = "image-in"
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)
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cap_type = gr.Radio(
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label = "Caption type",
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choices = [
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"Literal",
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"Fictional"
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],
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value = "Fictional"
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)
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submit_btn = gr.Button("Make LLM system from my pic !")
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with gr.Column():
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caption = gr.Textbox(
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["examples/chicken_adobo.jpeg"]
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],
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fn = infer,
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inputs = [image_in, cap_type]
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)
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submit_btn.click(
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fn = infer,
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inputs = [
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image_in,
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cap_type
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],
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outputs =[
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caption,
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]
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)
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demo.queue().launch(show_api=False, show_error=True)
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