Create app.py

app.py

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+import openai
+import pandas as pd
+import pygwalker as pyg
+import streamlit as st
+import streamlit.components.v1 as components
+from pandasai import PandasAI
+from pandasai.llm.openai import OpenAI
+from streamlit_chat import message
+
+# Adjust the width of the Streamlit page
+st.set_page_config(page_title="W.Y.N. Data Viz ⭐", layout="wide")
+
+# Add Title
+st.title("W.Y.N. Data Viz ⭐")
+
+# Sidebar
+# Sidebar - Instruction Manual
+with st.sidebar:
+    with st.expander("Instruction Manual 📖"):
+        st.markdown(
+            """
+            # 🌟 Pyg.Walk Chatbot on Streamlit 🌟
+
+            This Streamlit application serves as a user-friendly interface, similar to Excel or PowerBI dashboards, designed to expedite the navigation and visualization of datasets. Powered by the `pyg.walk` package, it provides a seamless experience, allowing users to traverse their data with speed and efficiency 🚀. The layout is intuitive, presenting data in an organized manner that's easy to analyze at a glance 📊.
+
+            ## 💬 Chatbot Interface
+
+            Behind the scenes, a chatbot interface is integrated into the application, enabling users to interact with their data conversationally 🤖. You can ask the chatbot simple questions regarding your dataset, such as:
+
+            - "What are the column names?" 📝
+            - "What is the average of [specific column]?" 📈
+
+            These questions are processed by the chatbot to provide quick, straightforward answers, making data analysis more accessible 🙌.
+
+            ## ⚠️ Limitations
+
+            Please note that the chatbot is designed for basic inquiries only 🛑. It is not equipped to handle complex data analysis or sophisticated queries. To maintain accuracy and avoid potential errors, keep your questions simple. This interface is a prototype aimed at demonstrating the capabilities of `pyg.walk` and should not be used for in-depth analysis 🧐.
+
+            ## 🚀 Getting Started
+
+            To begin, simply drag and drop your dataset in `.csv` format into the designated area of the application 📁➡️📊. Once your file is uploaded, you can start asking your data-related questions in plain English ✍️. The chatbot will respond with the requested information or appropriate guidance on how to phrase your questions for optimal results 💡.
+
+            """
+        )
+clear_button = st.sidebar.button("Clear Conversation", key="clear")
+counter_placeholder = st.sidebar.empty()
+st.sidebar.markdown(
+    "@ [Yiqiao Yin](https://www.y-yin.io/) | [LinkedIn](https://www.linkedin.com/in/yiqiaoyin/) | [YouTube](https://youtube.com/YiqiaoYin/)"
+)
+
+
+
+# Initialization
+# Session State also supports the attribute based syntax
+if 'generated' not in st.session_state:
+    st.session_state.generated = []
+
+# Session State also supports the attribute based syntax
+if 'past' not in st.session_state:
+    st.session_state.past = []
+
+# Reset everything    
+if clear_button:
+    st.session_state["generated"] = []
+    st.session_state["past"] = []
+    st.session_state["messages"] = [
+        {"role": "system", "content": "You are a helpful assistant."}
+    ]
+    st.session_state["number_tokens"] = []
+    st.session_state["domain_name"] = []
+    counter_placeholder.write(f"Next item ...")
+
+# Insert a file uploader that accepts multiple files at a time
+uploaded_file = st.file_uploader("Choose a CSV file")
+if uploaded_file is not None:
+    # Success message
+    st.success("File uploaded successfully.")
+
+    # Can be used wherever a "file-like" object is accepted:
+    df = pd.read_csv(uploaded_file)
+
+    # Generate the HTML using Pygwalker
+    pyg_html = pyg.walk(df, return_html=True)
+
+    # Embed the HTML into the Streamlit app
+    components.html(pyg_html, height=1000, scrolling=True)
+
+    # Instantiate a LLM
+    OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
+    llm = OpenAI(api_token=OPENAI_API_KEY)
+    pandas_ai = PandasAI(llm)
+
+    # Container for chat history
+    response_container = st.container()
+    container = st.container()
+    with container:
+        with st.form(key="my_form", clear_on_submit=True):
+            user_input = st.text_area(
+                "Enter your question here:", key="input", height=100
+            )
+            submit_button = st.form_submit_button(label="Send")
+
+        if submit_button:
+            output = pandas_ai(df, prompt=user_input)
+            st.session_state["past"].append(user_input)
+            st.session_state["generated"].append(
+                {"type": "normal", "data": f"{output}"}
+            )
+
+    if st.session_state["generated"]:
+        with response_container:
+            for i in range(len(st.session_state["generated"])):
+                message(st.session_state["past"][i], is_user=True, key=str(i) + "_user")
+                answer = st.session_state["generated"][i]["data"]
+                message(answer)
+                counter_placeholder.write(f"All rights reserved @ Yiqiao Yin")
+
+else:
+    st.warning("Please upload a csv file.")