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Running
Linh Vuu
commited on
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Parent(s):
86652f1
added files
Browse files- .DS_Store +0 -0
- app.py +23 -26
- requirements.txt +1 -1
.DS_Store
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Binary file (6.15 kB). View file
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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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from pandasai import
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from pandasai.llm.openai import OpenAI
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openai_api_key = st.secrets["openai_api_key"]
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# create an LLM by instantiating OpenAI object, and passing API token
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llm = OpenAI(
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pandas_ai = PandasAI(llm)
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st.title("Prompt-driven data analysis with PandasAI")
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uploaded_file = st.file_uploader("Upload a CSV file for analysis", type=['csv'])
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df = pd.read_csv(uploaded_file)
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st.write(df.head(3))
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df =
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st.write(df.head(3))
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prompt = st.text_area("Enter your
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# Generate
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if st.button("
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if prompt:
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st.write("Generating response...")
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else:
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st.warning("Please enter a prompt.")
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if uploaded_file is not None:
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df = pd.read_csv(uploaded_file)
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st.write(df.head(3))
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prompt = st.text_area("Enter your prompt:")
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# Generate output
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if st.button("Generate"):
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if prompt:
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# call pandas_ai.run(), passing dataframe and prompt
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with st.spinner("Generating response..."):
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else:
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st.warning("Please enter a
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import streamlit as st
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import pandas as pd
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from pandasai import SmartDataframe
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from pandasai.llm.openai import OpenAI
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openai_api_key = st.secrets["openai_api_key"]
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# create an LLM by instantiating OpenAI object, and passing API token
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llm = OpenAI(api_token = openai_api_key)
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st.title("Data analysis with PandasAI")
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uploaded_file = st.file_uploader("Upload a CSV file for analysis", type=['csv'])
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df = pd.read_csv(uploaded_file)
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st.write(df.head(3))
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# create PandasAI object, passing the LLM
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sdf = SmartDataframe(df, config={"llm": llm})
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prompt = st.text_area("Enter your question:")
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# Generate the answer
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if st.button("Find the answer"):
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if prompt:
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# call pandas_ai.run(), passing dataframe and prompt
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with st.spinner("Generating response..."):
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st.write("The answer is: ")
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st.write(sdf.chat(prompt))
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st.write("Here is the code to get the answer: ")
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code_string = sdf.last_code_generated
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# Split the string into separate lines
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code_lines = code_string.strip().split('\n')
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# Print the lines
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for line in code_lines:
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st.write(line)
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else:
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st.warning("Please enter a question.")
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requirements.txt
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streamlit
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pandasai
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streamlit
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pandasai
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scikit-learn
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