app2.py

import streamlit as st
import pandas as pd
from pandasai import SmartDataframe
from pandasai.llm import OpenAI
from langchain_groq import ChatGroq
from dotenv import load_dotenv
from datasets import load_dataset
import os

def initialize_llm(model_choice):
    """Initialize the chosen LLM based on the user's selection."""
    groq_api_key = os.getenv("GROQ_API_KEY")
    openai_api_key = os.getenv("OPENAI_API_KEY")

    if model_choice == "llama-3.3-70b":
        if not groq_api_key:
            st.error("Groq API key is missing. Please set the GROQ_API_KEY environment variable.")
            return None
        st.success("Using model: llama-3.3-70b (Groq)")
        return ChatGroq(groq_api_key=groq_api_key, model="groq/llama-3.3-70b-versatile")
    elif model_choice == "GPT-4o":
        if not openai_api_key:
            st.error("OpenAI API key is missing. Please set the OPENAI_API_KEY environment variable.")
            return None
        st.success("Using model: GPT-4o (OpenAI)")
        return OpenAI(api_token=openai_api_key)

def load_dataset_into_session():
    """Load dataset from Hugging Face or via CSV upload."""
    input_option = st.radio("Select Dataset Input:", ["Use Hugging Face Dataset", "Upload CSV File"])
    
    if input_option == "Use Hugging Face Dataset":
        dataset_name = st.text_input("Enter Hugging Face Dataset Name:", value="HUPD/hupd")
        if st.button("Load Dataset"):
            try:
                dataset = load_dataset(
                    dataset_name, 
                    name="sample", 
                    split="train", 
                    trust_remote_code=True, 
                    uniform_split=True
                )
                st.session_state.df = pd.DataFrame(dataset)
                st.success(f"Dataset '{dataset_name}' loaded successfully!")
                st.dataframe(st.session_state.df.head(10))
            except Exception as e:
                st.error(f"Error loading dataset: {e}")
    
    elif input_option == "Upload CSV File":
        uploaded_file = st.file_uploader("Upload CSV File:", type=["csv"])
        if uploaded_file:
            try:
                st.session_state.df = pd.read_csv(uploaded_file)
                st.success("File uploaded successfully!")
                st.dataframe(st.session_state.df.head(10))
            except Exception as e:
                st.error(f"Error reading file: {e}")

if "df" not in st.session_state:
    st.session_state.df = None

# Streamlit app
st.title("Chat With Your Dataset Using PandasAI")

# Section 1: LLM Selection
st.sidebar.title("Choose Your LLM")
model_choice = st.sidebar.radio(
    "Select a model:",
    ("GPT-4o", "llama-3.3-70b"),
    help="Choose between OpenAI GPT-4o or Groq Llama-3.3-70b."
)

# Initialize LLM
llm = initialize_llm(model_choice)
if not llm:
    st.stop()

# Section 2: Dataset Loading
st.header("Dataset Selection")
load_dataset_into_session()

# Section 3: Query and Interaction
if st.session_state.df is not None:
    st.subheader("Ask Questions About Your Dataset")
    chat_df = SmartDataframe(st.session_state.df, config={"llm": llm})

    user_query = st.text_input("Ask a question about your data:", "")
    if user_query:
        try:
            response = chat_df.chat(user_query)
            st.write("### Response:")
            st.write(response)

            # Check for plot-related keywords
            if any(keyword in user_query.lower() for keyword in ["plot", "graph", "draw", "visualize", "chart", "visualise"]):
                st.write("### Generating Plot...")
                try:
                    chat_df.chat(user_query)
                except Exception as e:
                    st.error(f"An error occurred while generating the plot: {e}")
        except Exception as e:
            st.error(f"An error occurred: {e}")
else:
    st.info("Please load a dataset to start interacting.")