tempCodeRunnerFile.py

from ragdash.chromadb import ChromaDB_VectorStore
from ragdash.groq import Groq
from ragdash.exceptions import ValidationError 
import os
import streamlit as st
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()

class MyRAGdash(ChromaDB_VectorStore, Groq):
 def __init__(self, config=None):
 # Initialize both base classes
 ChromaDB_VectorStore.__init__(self, config=config)
 Groq.__init__(self, config=config)

# Usage example
config = {
 'db_user': os.getenv('DB_USER'),
 'db_password': os.getenv('DB_PASSWORD'),
 'db_host': os.getenv('DB_HOST'),
 'db_name': os.getenv('DB_NAME')
}

print(config)

rd = MyRAGdash(config=config)

try:
 rd.connect_to_mysql(host=config['db_host'], dbname=config['db_name'], user=config['db_user'], password=config['db_password'], port=3306)
except Exception as e:
 st.error(f"Error connecting to the database: {e}")
 st.stop()


# data ka extarction
my_questions = {
 "bar": "extract the data appropriate for bar chart",
 "pie": "extract the data appropriate for pie chart",
 "line": "extract the data appropriate for line chart",
 "scatter": "extract the data appropriate for scatter chart",
 "bubble": "extract the data appropriate for bubble chart",
 "heatmap": "extract the data appropriate for heatmap chart",
 "box": "extract the data appropriate for box chart",
 "histogram": "extract the data appropriate for histogram chart",

}


results = {}

# Generate SQL queries and DataFrames for each chart type with error handling
for chart_type, question in my_questions.items():
 try:
 sql = rd.generate_sql(question)
 df = rd.run_sql(sql)

 # Store DataFrame and SQL in results
 results[chart_type] = {
 "df": df,
 "sql": sql
 }

 # Display DataFrame
 st.dataframe(df, use_container_width=True)

 except ValidationError as e:
 st.error(f"Validation error for {chart_type} chart: {e}")
 results[chart_type] = None # Store None to indicate failure

 except Exception as e:
 st.error(f"Error processing {chart_type} chart: {e}")
 results[chart_type] = None # Store None to indicate failure

# Generate Plotly code and figures with error handling
for chart_type in results:
 if results[chart_type] is not None:
 try:
 df = results[chart_type]["df"]
 sql = results[chart_type]["sql"]
 code = rd.generate_plotly_code(question=my_questions[chart_type], sql=sql, df=df, type_c=chart_type)
 fig = rd.get_plotly_figure(plotly_code=code, df=df)
 st.plotly_chart(fig, use_container_width=True)

 except Exception as e:
 st.error(f"Error generating {chart_type} plot: {e}")