Add application file

app.py

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+import pandas as pd
+import gradio as gr
+import gradio as gr; print(gr.__version__)
+
+# Replace with path to your ESG data (CSV or other supported format)
+data_path = "ESG_data.csv"
+company_ratings = [
+  {"Company Name": "Apple Inc.", "Rating": 4.5},
+  {"Company Name": "Amazon.com, Inc.", "Rating": 4.2},
+  {"Company Name": "Microsoft Corporation", "Rating": 4.7},
+  {"Company Name": "Alphabet Inc. (Google)", "Rating": 4.8},
+  {"Company Name": "Tesla, Inc.", "Rating": 3.9},
+  {"Company Name": "Meta Platforms Inc. (Facebook)", "Rating": 3.1},
+]
+
+# Load ESG data
+esg_data = pd.DataFrame(company_ratings)
+import gradio as gr
+import pandas as pd
+
+
+inputs = [gr.Dataframe(row_count = (2, "dynamic"), col_count=(4,"dynamic"), label="Input Data", interactive=1)]
+
+outputs = [gr.Dataframe(row_count = (2, "dynamic"), col_count=(1, "fixed"), label="Predictions", headers=["Failures"])]
+
+
+
+def infer(input_dataframe):
+  return pd.DataFrame(input_dataframe)
+
+gr.Interface(fn = infer, inputs = inputs, outputs = outputs, examples = [[esg_data.head(2)]]).launch()
+
+# def get_esg_scores(ticker):
+#   """
+#   Finds ESG scores for a given ticker symbol in the loaded data.
+
+#   Args:
+#       ticker (str): Ticker symbol of the company.
+
+#   Returns:
+#       pandas.DataFrame: Subset of ESG data for the ticker, 
+#           containing ESG scores if found, or an empty DataFrame 
+#           if not found.
+#   """
+#   filtered_data = esg_data[esg_data["Ticker Symbol"] == ticker.upper()]
+#   return filtered_data if not filtered_data.empty else pd.DataFrame()
+
+# def display_esg_scores(dataframe):
+#   """
+#   Displays ESG scores in a table format if a DataFrame is provided, 
+#   otherwise displays a message indicating no data found.
+
+#   Args:
+#       dataframe (pandas.DataFrame): DataFrame containing ESG scores.
+#   """
+#   if dataframe.empty:
+#     return "No ESG data found for this ticker."
+#   else:
+#     # Select relevant ESG score columns (adjust based on your data)
+#     esg_scores = dataframe[["Ticker Symbol", "Governance Score", "Social Score", "Environmental Score"]]
+#     return gr.DataTable(dataframe=esg_scores.to_dict())
+
+# iface = gr.Interface(
+#   fn=get_esg_scores,
+#   inputs=gr.inputs.Textbox(label="Ticker Symbol"),
+#   outputs=esg_data,
+#   title="ESG Score Lookup",
+#   description="Enter a company ticker symbol to view its ESG scores (if available).",
+# )
+
+# iface.launch()

flagged/log.csv

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+name,Output,timestamp
+,Hello !!,2024-05-20 02:22:21.273157
+,Hello !!,2024-05-20 02:22:22.248193
+,Hello !!,2024-05-20 02:22:23.235456
+,Hello !!,2024-05-20 02:22:23.675012
+,Hello !!,2024-05-20 02:22:27.643848
+,Hello !!,2024-05-20 02:22:28.585934
+,Hello !!,2024-05-20 02:22:29.303183
+,Hello !!,2024-05-20 02:22:30.054843