src/streamlit_app.py

import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
import sympy as sp
from sympy.parsing.sympy_parser import parse_expr
from sympy.utilities.lambdify import lambdify
import io
import os
import base64
from datetime import datetime
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Create required directories
os.makedirs("uploads", exist_ok=True)

# Page config
st.set_page_config(page_title="Equation2Graph", page_icon="📈", layout="wide")

# Session state
if 'history' not in st.session_state:
    st.session_state.history = []

# Initialize NLP model
@st.cache_resource
def load_nlp_model():
    try:
        tokenizer = AutoTokenizer.from_pretrained("t5-small")
        model = AutoModelForSeq2SeqLM.from_pretrained("t5-small")
        return tokenizer, model
    except Exception as e:
        st.warning(f"⚠ AI model could not be loaded: {str(e)}. Falling back to basic equation parsing.")
        return None, None

# Load models
tokenizer, model = load_nlp_model()

def convert_nl_to_equation(nl_input):
    """Convert natural language to equation using AI model or fallback to basic parsing"""
    if tokenizer and model:
        try:
            inputs = tokenizer.encode(nl_input, return_tensors="pt", truncation=True)
            outputs = model.generate(inputs, max_length=50)
            return tokenizer.decode(outputs[0], skip_special_tokens=True)
        except Exception as e:
            st.error(f"Error in AI conversion: {str(e)}")
            return basic_nl_to_equation(nl_input)
    else:
        return basic_nl_to_equation(nl_input)

def basic_nl_to_equation(text):
    """Basic natural language to equation conversion"""
    # Define basic math terms
    terms = {
        'squared': '^2',
        'cubed': '^3',
        'plus': '+',
        'minus': '-',
        'times': '*',
        'multiply by': '*',
        'divided by': '/',
        'over': '/',
        'to the power of': '^',
        'sin of': 'sin(',
        'cos of': 'cos(',
        'tan of': 'tan(',
        'exponential of': 'exp(',
        'log of': 'log(',
        'absolute value of': 'abs('
    }
    
    # Normalize text
    text = text.lower().strip()
    
    # Replace terms
    for term, symbol in terms.items():
        text = text.replace(term, symbol)
    
    # Clean up the equation
    text = text.replace(' ', '')
    if text.count('(') > text.count(')'):
        text += ')'  # Close any unclosed parentheses
        
    # Remove any invalid characters
    text = ''.join(c for c in text if c.isalnum() or c in '+-*/^().')
    return text

def parse_and_validate_equation(equation_str):
    try:
        equation_str = equation_str.replace('^', '')
        expr = parse_expr(equation_str)
        x = sp.Symbol('x')
        f = lambdify(x, expr, modules=['numpy'])
        return f, expr
    except Exception as e:
        st.error(f"Error parsing equation: {str(e)}")
        return None, None

def plot_equation(f, expr, x_range=(-10, 10), points=1000):
    try:
        fig, ax = plt.subplots(figsize=(10, 6))
        x = np.linspace(x_range[0], x_range[1], points)
        y = f(x)
        ax.plot(x, y, '-b', label=str(expr))
        ax.grid(True, alpha=0.3)
        ax.axhline(y=0, color='k', linestyle='-', alpha=0.3)
        ax.axvline(x=0, color='k', linestyle='-', alpha=0.3)
        ax.set_xlabel('x')
        ax.set_ylabel('y')
        ax.set_title(f'Graph of {str(expr)}')
        ax.legend()
        return fig
    except Exception as e:
        st.error(f"Error plotting equation: {str(e)}")
        return None

def get_download_link(fig):
    buf = io.BytesIO()
    fig.savefig(buf, format='png', bbox_inches='tight')
    buf.seek(0)
    b64 = base64.b64encode(buf.read()).decode()
    return f'<a href="data:image/png;base64,{b64}" download="equation_plot.png">📥 Download Plot</a>'

# Header
st.title("📈 Equation2Graph")
st.markdown("Visualize mathematical equations instantly, from symbolic or natural language input!")

# Columns
col1, col2 = st.columns([2, 1])

with col1:
    # Natural language input
    st.subheader("🗣 Describe your equation (optional)")
    nl_input = st.text_input(
        "Enter your equation in plain English:",
        placeholder="e.g., the square of x plus two times x plus one"
    )
    
    equation = ""
    if nl_input:
        equation = convert_nl_to_equation(nl_input)
        if equation:
            st.success(f"Converted to equation: {equation}")
        else:
            st.error("Failed to convert input")

    # Direct equation input (fallback or primary)
    equation = st.text_input(
        "Or enter your equation directly:",
        value=equation,
        placeholder="e.g., x^2 + 2*x + 1"
    )

    # Plot settings
    with st.expander("⚙ Plot Settings"):
        col_a, col_b = st.columns(2)
        with col_a:
            x_min = st.number_input("X-axis minimum", value=-10.0)
        with col_b:
            x_max = st.number_input("X-axis maximum", value=10.0)
        points = st.slider("Number of points", 100, 2000, 1000)

    # Process and plot
    if equation:
        f, expr = parse_and_validate_equation(equation)
        if f and expr:
            fig = plot_equation(f, expr, (x_min, x_max), points)
            if fig:
                st.pyplot(fig)
                st.markdown(get_download_link(fig), unsafe_allow_html=True)
                if equation not in [h['equation'] for h in st.session_state.history]:
                    st.session_state.history.append({
                        'equation': equation,
                        'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M:%S")
                    })

with col2:
    st.subheader("📚 Example Equations")
    examples = [
        "x^2 + 2*x + 1",
        "sin(x) + cos(x)",
        "exp(-x^2)",
        "x^3 - 4*x",
        "tan(x)",
        "log(abs(x))"
    ]
    for ex in examples:
        if st.button(ex):
            st.experimental_set_query_params(equation=ex)

    st.subheader("📖 Recent Equations")
    for item in reversed(st.session_state.history[-5:]):
        st.text(f"{item['equation']}")
        st.caption(f"Plotted on: {item['timestamp']}")

with st.expander("ℹ How to use Equation2Graph"):
    st.markdown("""
    ### Instructions:
    1. Describe or type your equation
    2. The graph updates automatically
    3. Adjust plot settings if needed
    4. Download the graph as PNG

    ### Natural Language Support:
    - Try: "the square of x plus two times x"
    - You can still type equations like: x^2 + 2*x

    ### Supported Math Functions:
    - Basic: +, -, *, /, ^
    - Trig: sin(x), cos(x), tan(x)
    - Exponential/log: exp(x), log(x)
    """)

# Footer
st.markdown("---")
st.markdown("Equation2Graph | Now with 🧠 AI-powered equation parser | Made by webwhiz")