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Update app.py
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app.py
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@@ -1,86 +1,86 @@
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import streamlit as st
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import requests
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import pandas as pd
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# --- API Configuration ---
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API_URL = "https://adrienbrdne-fastapi-kig.hf.space/"
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ENDPOINT = f"{API_URL}/generate-key-issues" # API endpoint name remains unchanged
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# --- Streamlit Interface ---
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st.set_page_config(page_title="Problematic Generator", layout="wide")
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st.title("Generate Problematics from Query")
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# Input field for the user query
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user_query = st.text_input(
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"Enter your query here:",
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placeholder="Example: deploying edge computing for real-time AI-driven traffic management systems in smart cities"
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)
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# Button to submit the query
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if st.button("Generate Problematics"):
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if user_query: # Check if the user entered something
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st.info(f"Sending query to API: {ENDPOINT}")
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st.write(f"Query: \"{user_query}\"")
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# Prepare data for the POST request
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data = {"query": user_query}
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try:
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# Show a loading spinner during the API call
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with st.spinner("Calling API to generate problematics..."):
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response = requests.post(ENDPOINT, json=data
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# Check the response status
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if response.status_code == 200:
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st.success("Response received successfully!")
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result = response.json()
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# Check if 'key_issues' key exists and is a list
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if 'key_issues' in result and isinstance(result['key_issues'], list):
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# Convert the 'key_issues' list to a Pandas DataFrame
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df = pd.DataFrame(result['key_issues'])
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# Remove the 'id' column if it exists
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if 'id' in df.columns:
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df_display = df.drop(columns=['id'])
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else:
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st.warning("Column 'id' was not found in the received data.")
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df_display = df
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# Display the DataFrame
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st.subheader("Generated Problematics (DataFrame):")
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st.dataframe(df_display, use_container_width=True) # Display dataframe with full container width
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# Optional: Display raw JSON response for verification
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# st.subheader("Raw JSON Response Received:")
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# st.json(result)
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else:
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st.error("API response does not contain the expected 'key_issues' key or it is not a list.")
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st.json(result) # Display the received response for debugging
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else:
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# Display an error if status is not 200
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st.error(f"API Call Error: Status {response.status_code}")
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try:
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# Try to display the API error message if it's JSON
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error_details = response.json()
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st.json(error_details)
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except requests.exceptions.JSONDecodeError:
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# Otherwise, display the raw text response
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st.text(response.text)
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except requests.exceptions.RequestException as e:
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# Handle connection or timeout errors
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st.error(f"API Connection Error: {e}")
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except Exception as e:
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# Handle any other unexpected errors
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st.error(f"An unexpected error occurred: {e}")
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else:
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# Message if the user clicks the button without entering a query
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st.warning("Please enter a query before generating.")
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# Initial instructions
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else:
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st.info("Enter a query in the field above and click 'Generate Problematics' to query the API.")
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import streamlit as st
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import requests
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import pandas as pd
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# --- API Configuration ---
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API_URL = "https://adrienbrdne-fastapi-kig.hf.space/"
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ENDPOINT = f"{API_URL}/generate-key-issues" # API endpoint name remains unchanged
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# --- Streamlit Interface ---
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st.set_page_config(page_title="Problematic Generator", layout="wide")
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st.title("Generate Problematics from Query")
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+
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# Input field for the user query
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user_query = st.text_input(
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"Enter your query here:",
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placeholder="Example: deploying edge computing for real-time AI-driven traffic management systems in smart cities"
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)
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# Button to submit the query
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if st.button("Generate Problematics"):
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if user_query: # Check if the user entered something
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st.info(f"Sending query to API: {ENDPOINT}")
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st.write(f"Query: \"{user_query}\"")
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# Prepare data for the POST request
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data = {"query": user_query}
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try:
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# Show a loading spinner during the API call
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with st.spinner("Calling API to generate problematics..."):
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response = requests.post(ENDPOINT, json=data) # Added a timeout
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# Check the response status
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if response.status_code == 200:
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st.success("Response received successfully!")
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result = response.json()
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# Check if 'key_issues' key exists and is a list
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if 'key_issues' in result and isinstance(result['key_issues'], list):
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# Convert the 'key_issues' list to a Pandas DataFrame
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df = pd.DataFrame(result['key_issues'])
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# Remove the 'id' column if it exists
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if 'id' in df.columns:
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df_display = df.drop(columns=['id'])
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else:
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st.warning("Column 'id' was not found in the received data.")
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df_display = df
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# Display the DataFrame
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st.subheader("Generated Problematics (DataFrame):")
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st.dataframe(df_display, use_container_width=True) # Display dataframe with full container width
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# Optional: Display raw JSON response for verification
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# st.subheader("Raw JSON Response Received:")
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# st.json(result)
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else:
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st.error("API response does not contain the expected 'key_issues' key or it is not a list.")
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st.json(result) # Display the received response for debugging
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else:
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# Display an error if status is not 200
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st.error(f"API Call Error: Status {response.status_code}")
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try:
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# Try to display the API error message if it's JSON
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error_details = response.json()
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st.json(error_details)
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except requests.exceptions.JSONDecodeError:
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# Otherwise, display the raw text response
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st.text(response.text)
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except requests.exceptions.RequestException as e:
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# Handle connection or timeout errors
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st.error(f"API Connection Error: {e}")
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except Exception as e:
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# Handle any other unexpected errors
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st.error(f"An unexpected error occurred: {e}")
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else:
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# Message if the user clicks the button without entering a query
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st.warning("Please enter a query before generating.")
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+
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# Initial instructions
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else:
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st.info("Enter a query in the field above and click 'Generate Problematics' to query the API.")
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