visual_functions.py

import pandas as pd 
import streamlit as st 
from langchain.chat_models import ChatOpenAI
from langchain.agents import create_pandas_dataframe_agent
from langchain.agents.agent_types import AgentType
import plotly
import matplotlib
import matplotlib.pyplot as plt
import sklearn
from sklearn.linear_model import LinearRegression
import bokeh
import altair
import re #re stands for regular expression

# PAGE FOR MAKING DATA VISUALIZATION WITHOUT WRITING CODE


# User Uploads a CSV File in the other page
# For new functions we must run this function again to obtain a usable dataframe 
def load_csv(input_csv):
    df = pd.read_csv(input_csv)
    
    

    # Now we need to have the user be able to preview the dataframe 
    with st.expander("See the Dataframe"):
        st.write(df)
        
    df2 = df
    
    return df2






# Generate LLM Responses 
def generate_response(csv_file, input_query, ai_key): #input_question, question_list):
    llm = ChatOpenAI(model_name='gpt-3.5-turbo-0613', temperature=0.2, openai_api_key= ai_key)
    
    df = csv_file
    
    # Create Pandas Dataframe Agent 
    agent = create_pandas_dataframe_agent(llm, df, verbose= True, agent_type = AgentType.OPENAI_FUNCTIONS)
    
    # Perform Queries with the agent 
    response = agent.run(input_query)
    
    return st.success(response)
    
 
    




# Other Inputs 
def other_inputs(list_of_questions, input_file_csv):
    """Add an additional question etc."""
    question_list = list_of_questions
    input_file = input_file_csv
    
    #Select the question.
    #query_text = st.selectbox("Select an example query:", question_list, disabled= not input_file)
    query_text = st.selectbox("Select an example query:", question_list, disabled= input_file.empty)
    
    # openai_api_key = st.text_input("OpenAI API Key", type = "password", disabled = not (input_file and query_text))
    openai_api_key = st.text_input("OpenAI API Key", type = "password", disabled = not (query_text) and input_file.empty)
    
    # Dealing with other questions and verifying API key
    if query_text is "Other":
        # query_text = st.text_input("Enter your query", placeholder= "Enter your query...", disabled = not input_file)
        st.warning("Must include in prompt that you want the PLOTLY CODE IN PYTHON. Omitting this information will cause an error!", icon = "🚨")
        st.info("Enter in your custom question below. Leaving the line blank will result in the LLM interpreting your dataset's columns." ,icon = "ℹ")
        query_text_custom = st.text_area("Enter your query", placeholder= "Enter your query...", disabled = input_file.empty)
        # st.header("Output")
        
        # We want to comment the below line out in order to have the functionality called when it is ready.
        #return generate_response(input_file, query_text_custom, openai_api_key)
        
        # We need to make the query_text and the custom text the same
        
        query_text = query_text_custom
        
    if not openai_api_key.startswith("sk-"):
        st.warning("Please enter your OpenAI API key to enable functionality!", icon = "⚠")
    if openai_api_key.startswith("sk-") and (input_file is not None):
        st.header("Output")
        return generate_response(input_file, query_text, openai_api_key)