rahul755025/Mathematical_Calculation

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference import gradio as gr import sympy as sp import pandas as pd import kagglehub import time

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LOAD DATASET (AI CHAT)

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try: path = kagglehub.datasetdownload("ashishkumarak/chatgpt-reviews-daily-updated") df = pd.readcsv(path + "/chatgpt_reviews.csv") df = df[['review', 'rating']].dropna() except: df = pd.DataFrame({"review": ["Dataset not loaded"], "rating": [0]})

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MATRIX PARSER

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def parsematrix(matrixinputstr): rows = matrixinput_str.strip().split('\n')

if not rows or all(not row.strip() for row in rows): raise ValueError("Matrix input cannot be empty.")

matrixlist = [] numcols = None

for i, row in enumerate(rows): elements = [e.strip() for e in row.replace(',', ' ').split() if e.strip()]

if not elements: raise ValueError(f"Row {i+1} is empty.")

try: row_values = [sp.Rational(e) for e in elements] except: raise ValueError(f"Invalid number in row {i+1}")

if numcols is None: numcols = len(rowvalues) elif len(rowvalues) != num_cols: raise ValueError("All rows must have same number of columns.")

matrixlist.append(rowvalues)

A = sp.Matrix(matrix_list)

if not A.is_square: raise ValueError("Matrix must be square.")

return A

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MATRIX OPERATIONS

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def matrixoperations(matrixinput_str): steps = []

try: steps.append("⏳ Parsing matrix...") A = parsematrix(matrixinput_str) time.sleep(0.3)

steps.append("🔢 Calculating determinant...") det = A.det() time.sleep(0.3)

steps.append("📐 Computing cofactor matrix...") cofactor = A.cofactor_matrix() time.sleep(0.3)

steps.append("🔄 Computing adjugate matrix...") adjugate = A.adjugate() time.sleep(0.3)

steps.append("🧮 Computing inverse...") if det == 0: inversetext = "❌ Inverse does not exist (Determinant = 0)" inverselatex = inversetext else: inverse = A.inv() inversetext = sp.pretty(inverse) inverse_latex = f"${sp.latex(inverse)}$" time.sleep(0.3)

steps.append("📊 Computing advanced properties...") rank = A.rank() transpose = A.T eigenvals = A.eigenvals()

return ( "\n".join(steps),

f"Determinant:\n{det}", f"Cofactor Matrix:\n{sp.pretty(cofactor)}", f"Adjugate Matrix:\n{sp.pretty(adjugate)}", f"Inverse Matrix:\n{inverse_text}",

f"### Determinant\n${sp.latex(det)}$", f"### Cofactor\n${sp.latex(cofactor)}$", f"### Adjugate\n${sp.latex(adjugate)}$", f"### Inverse\n{inverse_latex}",

f"### Rank\n${rank}$", f"### Transpose\n${sp.latex(transpose)}$", f"### Eigenvalues\n${sp.latex(eigenvals)}$" )

except Exception as e: return (f"Error: {e}", "", "", "", "", "", "", "", "", "", "")

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AI CHAT (DATASET BASED)

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def chatbotresponse(userinput): userinput = userinput.lower()

matches = df[df['review'].str.lower().str.contains(user_input)]

if not matches.empty: row = matches.iloc[0] return f"📊 Similar Review:\n\n{row['review']}\n\n⭐ Rating: {row['rating']}" else: return "No similar review found. Try different keywords."

def chatinterface(message, history): response = chatbotresponse(message) history.append((message, response)) return "", history

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UI DESIGN

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with gr.Blocks(theme=gr.themes.Soft()) as demo:

gr.Markdown("## 🧮 Advanced Matrix + AI Chat System") gr.Markdown("Matrix Operations + AI Chat (Dataset-based)")

# -------- MATRIX INPUT -------- matrix_input = gr.Textbox( lines=6, label="Enter Matrix", placeholder="Example:\n1 2 3\n4 5 6\n7 8 9" )

run_btn = gr.Button("🚀 Compute")

progress = gr.Textbox(label="Processing Steps")

with gr.Tabs():

# ===== TAB 1 ===== with gr.Tab("📌 Basic Outputs"): detout = gr.Textbox(label="Determinant") cofout = gr.Textbox(label="Cofactor Matrix") adjout = gr.Textbox(label="Adjugate Matrix") invout = gr.Textbox(label="Inverse Matrix")

# ===== TAB 2 ===== with gr.Tab("📊 Mathematical View"): detlatex = gr.Markdown() coflatex = gr.Markdown() adjlatex = gr.Markdown() invlatex = gr.Markdown()

# ===== TAB 3 ===== with gr.Tab("🚀 Advanced Properties"): rankout = gr.Markdown() transposeout = gr.Markdown() eigen_out = gr.Markdown()

# ===== TAB 4 (AI CHAT) ===== with gr.Tab("🤖 AI Chat"): chatbot = gr.Chatbot() msg = gr.Textbox(label="Ask about reviews") clear = gr.Button("Clear Chat")

msg.submit(chat_interface, [msg, chatbot], [msg, chatbot]) clear.click(lambda: None, None, chatbot, queue=False)

runbtn.click( matrixoperations, inputs=matrixinput, outputs=[ progress, detout, cofout, adjout, invout, detlatex, coflatex, adjlatex, invlatex, rankout, transposeout, eigenout ] )

demo.launch()