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Update app.py
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app.py
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@@ -2,10 +2,13 @@
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import gradio as gr
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import requests
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import os
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API_URL1 = "https://api-inference.huggingface.co/models/cardiffnlp/twitter-roberta-base-sentiment"
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API_URL2 = "https://api-inference.huggingface.co/models/facebook/convnext-xlarge-384-22k-1k"
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API_URL3 = "https://api-inference.huggingface.co/models/microsoft/trocr-base-handwritten"
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bt = os.environ['HACKAITHONBEARERTOKEN']
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headers = {"Authorization": bt }
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@@ -21,16 +24,32 @@ def query(mood, select_model, filepath):
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elif (select_model=="WhatIsThat"):
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data = open(filepath, 'rb' ).read()
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response = requests.post(API_URL2, headers=headers, data=data)
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data = open(filepath, 'rb' ).read()
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response = requests.post(API_URL3, headers=headers, data=data)
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def greet(mood,select_model,image):
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output = query({"inputs":mood}, select_model, image)
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iface = gr.Interface(
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fn=greet, inputs=["text", gr.Radio(choices=["Sentiment", "WhatIsThat", "HandWriting"],value="Sentiment"),gr.Image(type="filepath")], outputs="text")
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iface.launch()
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import gradio as gr
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import requests
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import os
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import io
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API_URL1 = "https://api-inference.huggingface.co/models/cardiffnlp/twitter-roberta-base-sentiment"
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API_URL2 = "https://api-inference.huggingface.co/models/facebook/convnext-xlarge-384-22k-1k"
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API_URL3 = "https://api-inference.huggingface.co/models/microsoft/trocr-base-handwritten"
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API_URL4 = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
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bt = os.environ['HACKAITHONBEARERTOKEN']
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headers = {"Authorization": bt }
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elif (select_model=="WhatIsThat"):
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data = open(filepath, 'rb' ).read()
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response = requests.post(API_URL2, headers=headers, data=data)
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elif (select_model=="HandWriting"):
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data = open(filepath, 'rb' ).read()
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response = requests.post(API_URL3, headers=headers, data=data)
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else:
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response = requests.post(API_URL4, headers=headers, json=mood)
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if (select_model=="Sentiment"):
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return str(response.json())
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elif (select_model=="WhatIsThat"):
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return str(response.json())
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elif (select_model=="HandWriting"):
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return str(response.json())
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else:
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return response.content
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def greet(mood,select_model,image):
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output = query({"inputs":mood}, select_model, image)
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if (select_model=="Text2Image"):
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from PIL import Image
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image = Image.open(io.BytesIO(output))
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else:
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print (str(output))
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return str(output)
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iface = gr.Interface(
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fn=greet, inputs=["text", gr.Radio(choices=["Sentiment", "WhatIsThat", "HandWriting","Text2Image"],value="Sentiment"),gr.Image(type="filepath")], outputs="text","image")
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iface.launch()
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