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