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import streamlit as st
import pandas as pd
from pandasai import SmartDataframe
from pandasai.llm import OpenAI, ChatGroq
from dotenv import load_dotenv
from datasets import load_dataset
import os
# Load environment variables
load_dotenv()
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
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
return OpenAI(api_token=openai_api_key)
# App title and description
st.title("Patent Analytics: Chat With Your Dataset")
st.markdown(
"""
Upload a CSV file or load a dataset from Hugging Face to:
- Analyze data with natural language queries.
- Visualize trends and insights (e.g., "Plot the number of patents filed per year").
"""
)
# Initialize session state for the dataframe
if "df" not in st.session_state:
st.session_state.df = None
# Select the model
model_choice = st.radio("Select LLM", ["GPT-4o", "llama-3.3-70b"], index=0, horizontal=True)
llm = initialize_llm(model_choice)
if not llm:
st.stop()
def load_dataset_into_session():
"""Load dataset based on user input."""
input_option = st.radio("Choose Dataset Input Method", ["Use Hugging Face Dataset", "Upload CSV File"], index=0)
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, split="train", trust_remote_code=True)
st.session_state.df = pd.DataFrame(dataset)
st.success(f"Dataset '{dataset_name}' loaded successfully!")
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!")
except Exception as e:
st.error(f"Error loading file: {e}")
# Load dataset
load_dataset_into_session()
# Show the loaded dataframe preview
if st.session_state.df is not None:
st.subheader("Dataset Preview")
st.dataframe(st.session_state.df.head(10))
# Create a SmartDataFrame for PandasAI
chat_df = SmartDataframe(st.session_state.df, config={"llm": llm})
# Input box for user questions
question = st.text_input(
"Ask a question about your data or request a visualization",
placeholder="E.g., 'Which assignee has the most patents?' or 'Plot patent filings per year'",
)
if question:
with st.spinner("Processing your request..."):
try:
# Chat with the dataframe
response = chat_df.chat(question)
# Display response
if isinstance(response, pd.DataFrame):
st.write("### Response")
st.dataframe(response)
else:
st.write("### Response")
st.write(response)
st.success("Request processed successfully!")
except Exception as e:
st.error(f"An error occurred: {e}")
else:
st.write("Upload a CSV file or load a dataset to get started.") |