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Create app.py
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app.py
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import streamlit as st
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import pandas as pd
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import json
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from agent import query_agent, create_agent
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def decode_response(response: str) -> dict:
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""" This function converts the string response from the model to a dictionary.
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Args:
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response (str): The string response from the model.
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Returns:
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dict: The dictionary representation of the response.
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"""
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response_dict = json.loads(response)
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return response_dict
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def write_response(response_dict: dict):
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""" This function writes the response from the model to the Streamlit app.
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Args:
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response_dict (dict): The dictionary representation of the response.
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"""
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# Check if the response is an answer.
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if "answer" in response_dict:
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st.write(response_dict["answer"])
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# Check if the response is a bar chart.
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if "bar" in response_dict:
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data = response_dict["bar"]
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df = pd.DataFrame(data)
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df.set_index("columns", inplace=True)
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st.bar_chart(df)
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# Check if the response is a line chart.
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if "line" in response_dict:
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data = response_dict["line"]
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df = pd.DataFrame(data)
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df.set_index("columns", inplace=True)
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st.line_chart(df)
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# Check if the response is a table.
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if "table" in response_dict:
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data = response_dict["table"]
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df = pd.DataFrame(data["data"], columns=data["columns"])
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st.table(df)
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st.title("👨💻 Chat with your CSV")
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st.write("Please upload your CSV file below.")
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data = st.file_uploader("Upload a CSV")
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query = st.text_area("Type your query here")
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if st.button("Submit Query", type="primary"):
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# Create an agent from the CSV file.
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agent = create_agent(data)
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# Query the agent.
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response = query_agent(agent=agent, query=query)
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# Decode the response.
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decoded_response = decode_response(response)
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print(decoded_response)
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# Write the response to the Streamlit app.
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write_response(decoded_response)
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