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latest pypi version
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@ -208,6 +208,7 @@ def serve_files_in_background(interface, port, directory_to_serve=None):
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# Read body of the request.
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if self.path == "/api/predict/":
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print("got hereffffffffffff")
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# Make the prediction.
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self._set_headers()
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data_string = self.rfile.read(int(self.headers["Content-Length"]))
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@ -221,6 +222,7 @@ def serve_files_in_background(interface, port, directory_to_serve=None):
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self.wfile.write(json.dumps(output).encode())
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elif self.path == "/api/flag/":
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print("got here")
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self._set_headers()
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data_string = self.rfile.read(int(self.headers["Content-Length"]))
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print('data_string', data_string)
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@ -1,6 +1,6 @@
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Metadata-Version: 1.0
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Name: gradio
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Version: 0.7.5
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Version: 0.7.6
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Summary: Python library for easily interacting with trained machine learning models
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Home-page: https://github.com/abidlabs/gradio
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Author: Abubakar Abid
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@ -208,6 +208,7 @@ def serve_files_in_background(interface, port, directory_to_serve=None):
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# Read body of the request.
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if self.path == "/api/predict/":
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print("got hereffffffffffff")
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# Make the prediction.
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self._set_headers()
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data_string = self.rfile.read(int(self.headers["Content-Length"]))
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@ -221,6 +222,7 @@ def serve_files_in_background(interface, port, directory_to_serve=None):
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self.wfile.write(json.dumps(output).encode())
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elif self.path == "/api/flag/":
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print("got here")
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self._set_headers()
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data_string = self.rfile.read(int(self.headers["Content-Length"]))
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print('data_string', data_string)
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