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Parent(s):
557995c
Update app.py (#2)
Browse files- Update app.py (fa9ebbc00bb4fb092af22e7266745dc668bfce99)
Co-authored-by: Nusret Ozates <[email protected]>
app.py
CHANGED
@@ -38,58 +38,19 @@ def get_json(mahalle, il, sokak, apartman):
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return dump
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def
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eval_result =
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return
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eval_result = str(ast.literal_eval(input)["distinct"])
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return eval_result
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def text_dict_street(input):
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eval_result = str(ast.literal_eval(input)["street"])
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return eval_result
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def text_dict_no(input):
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eval_result = str(ast.literal_eval(input)["no"])
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return eval_result
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def text_dict_tel(input):
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eval_result = str(ast.literal_eval(input)["tel"])
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return eval_result
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def text_dict_name(input):
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eval_result = str(ast.literal_eval(input)["name_surname"])
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return eval_result
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def text_dict_address(input):
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eval_result = str(ast.literal_eval(input)["address"])
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return eval_result
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def text_dict_no(input):
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eval_result = str(ast.literal_eval(input)["no"])
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return eval_result
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def openai_response(ocr_input):
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prompt = f"""Tabular Data Extraction You are a highly intelligent and accurate tabular data extractor from
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@@ -165,15 +126,7 @@ with gr.Blocks() as demo:
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ocr_result.change(openai_response, ocr_result, open_api_text, api_name="upload-text")
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open_api_text.change(
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open_api_text.change(text_dict_distinct, [open_api_text], distinct)
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open_api_text.change(text_dict_neighbourhood, [open_api_text], neighbourhood)
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open_api_text.change(text_dict_street, [open_api_text], street)
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open_api_text.change(text_dict_address, [open_api_text], address)
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open_api_text.change(text_dict_tel, [open_api_text], tel)
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open_api_text.change(text_dict_name, [open_api_text], name_surname)
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open_api_text.change(text_dict_no, [open_api_text], no)
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if __name__ == "__main__":
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return dump
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def text_dict(input):
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eval_result = ast.literal_eval(input)
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return (
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str(eval_result['city']),
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str(eval_result['distinct']),
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str(eval_result['neighbourhood']),
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str(eval_result['street']),
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str(eval_result['address']),
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str(eval_result['tel']),
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str(eval_result['name_surname']),
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str(eval_result['no']),
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)
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def openai_response(ocr_input):
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prompt = f"""Tabular Data Extraction You are a highly intelligent and accurate tabular data extractor from
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ocr_result.change(openai_response, ocr_result, open_api_text, api_name="upload-text")
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open_api_text.change(text_dict, open_api_text, [city, distinct, neighbourhood, street, address, tel, name_surname, no])
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if __name__ == "__main__":
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