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import os
import streamlit as st
from PIL import Image
# import pytesseract
from paddleocr import PaddleOCR, draw_ocr
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_groq import ChatGroq
import numpy as np
# import pytesseract
# import easyocr
GROQ_API_KEY = os.environ['GROQ_API_KEY ']
# llm = ChatGroq(temperature=0, groq_api_key=GROQ_API_KEY, model_name="mixtral-8x7b-32768")
llm = ChatGroq(temperature=0, groq_api_key=GROQ_API_KEY, model_name="llama3-groq-70b-8192-tool-use-preview")
ocr = PaddleOCR(use_angle_cls=True, lang='en')
# Function to extract text from an image using OCR
def extract_text_from_image(image):
try:
# Convert PIL Image to NumPy array
image_np = np.array(image)
# Perform OCR using PaddleOCR
results = ocr.ocr(image_np, cls=True)
# Extract text from results
extracted_text = ""
for line in results:
for word_info in line:
extracted_text += word_info[1][0] + " "
return extracted_text.strip() if extracted_text else "No text found in the image."
except Exception as e:
return f"Error processing image: {e}"
# try:
# # Use pytesseract to do OCR on the image
# # text = pytesseract.image_to_string(image)
# text = pytesseract.image_to_string(image, lang='eng', config='--psm 7')
# return text.strip()
# except Exception as e:
# return f"Error processing image: {e}"
# Function to solve a math problem using Groq API and Mistral LLM
def solve_math_problem_with_groq(problem_text):
try:
# Initialize the Groq LLM with the Mistral model
# Create a prompt template for solving the math problem
prompt_template = PromptTemplate(
input_variables=["problem"],
template="Solve the following math problem:\n\n{problem}\n\n"
)
# Create an LLM chain with the prompt template
llm_chain = LLMChain(
llm=llm,
prompt=prompt_template
)
# Run the LLM chain with the problem text
solution = llm_chain.run(problem=problem_text)
return solution.strip()
except Exception as e:
return f"Error solving the problem: {e}"
# Streamlit app
def main():
st.title("Math Solver using ChatGroq, Mistral, and LangChain")
st.write('Developed by Ravi Shankar Prasad- https://www.linkedin.com/in/ravi-shankar-prasad-371825101/')
# Input method selection
input_method = st.radio("Select input method:", ("Upload Image", "Enter Text"))
problem_text = ""
if input_method == "Upload Image":
# Image upload
uploaded_file = st.file_uploader("Choose an image...", type=["png", "jpg", "jpeg"])
if uploaded_file is not None:
# Display uploaded image
image = Image.open(uploaded_file)
st.image(image, caption='Uploaded Image', use_column_width=True)
# Extract text from image
problem_text = extract_text_from_image(image)
if problem_text:
st.write("Extracted Text:", problem_text)
else:
st.write("No text found in the image. Please upload a clearer image.")
else:
# Text input
problem_text = st.text_area("Enter math problem:")
if problem_text:
if st.button("Solve"):
# Solve the math problem using Groq and Mistral
solution = solve_math_problem_with_groq(problem_text)
st.write("Solution:", solution)
if __name__ == "__main__":
main()
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