Update app.py

app.py

@@ -4,7 +4,6 @@ from pix2tex.cli import LatexOCR
 import sympy as sp
 from sympy.parsing.latex import parse_latex
 import re
-import requests
 
 model = LatexOCR()
 
@@ -13,7 +12,7 @@ def preprocess_handwritten_image(pil_img):
 
 def clean_latex(latex):
     latex = latex.replace('\\ ', '')
-    latex = latex.replace('\\\\', '\\')
+    latex = latex.replace('\\\\', '\n')  # preserve newlines for multiple equations
     latex = re.sub(r'\\[ \t\n\r\f\v]*', '', latex)
     latex = re.sub(r'\\([+\-=])', r'\1', latex)
     replacements = {
@@ -29,48 +28,11 @@ def clean_latex(latex):
     }
     for wrong, correct in replacements.items():
         latex = re.sub(wrong, correct, latex)
-    latex = re.sub(r'\\(cal|mathcal)\s*\{?\s*[Xx]\s*\}?', 'x', latex)
-    latex = re.sub(r'\\(cal|mathcal)\s*\{?\s*[Yy]\s*\}?', 'y', latex)
-    latex = re.sub(r'\\(cal|mathcal)\s*\{?\s*[Zz]\s*\}?', 'z', latex)
-    latex = latex.replace('cal x', 'x').replace('cal X', 'x')
-    latex = latex.replace('mathcal x', 'x').replace('mathcal X', 'x')
-    latex = latex.replace('{', '').replace('}', '')
-    latex = latex.strip().rstrip(',.')
-    latex = re.sub(r'(?<![a-zA-Z0-9])e(?![a-zA-Z0-9])', 'E', latex)
-    latex = re.sub(r'(\d)([a-zA-Z])', r'\1*\2', latex)
-    latex = re.sub(r'(\d+)\s*i', r'\1*I', latex)
-    latex = re.sub(r'(?<![a-zA-Z0-9])i(?![a-zA-Z0-9])', 'I', latex)
-    latex = re.sub(r'\(([^()]+?)\)\s*([a-zA-Z](\^\d+)?)', r'(\1)*\2', latex)
-    latex = latex.replace(r'\cdot', '*')
+    latex = re.sub(r'{|}', '', latex)
     latex = latex.replace('−', '-')
-    latex = re.sub(r'[^\w\s^=+*\-().]', '', latex)
-    if '=' not in latex:
-        latex += '=0'
-    latex = latex.replace('pi', '3.1416')
-    latex = latex.replace('e', '2.7183')
-    return latex
-
-# def request_llm_fallback(bad_latex, llm_url):
-#     pre_cleaned = re.sub(r'(\\!?pm|\\not=?|\\!|\\L|\\perp|\\bar|\\Sigma|\\boldmath|G|L(?=\^))', '', bad_latex)
-#     try:
-#         response = requests.post(f"{llm_url}/clean", json={"prompt": pre_cleaned})
-#         if response.status_code == 200:
-#             return response.json().get("cleaned_latex", pre_cleaned)
-#     except Exception as e:
-#         print(f"LLM fallback failed: {e}")
-#     return pre_cleaned
-
-# def request_llm_explanation(prompt, llm_url):
-#     try:
-#         response = requests.post(f"{llm_url}/explain", json={"prompt": prompt})
-#         if response.status_code == 200:
-#             return response.json().get("explanation", "❌ No explanation returned.")
-#         else:
-#             return f"❌ LLM explanation failed: {response.status_code}"
-#     except Exception as e:
-#         return f"❌ LLM explanation error: {e}"
-
-def solve_polynomial(image):  # removed llm_url
+    return latex.strip()
+
+def solve_polynomial(image):
     try:
         img = preprocess_handwritten_image(image)
         latex_result = model(img)
@@ -86,9 +48,6 @@ def solve_polynomial(image):  # removed llm_url
             if not lhs.is_polynomial():
                 raise ValueError("Not a polynomial")
         except:
-            # Commented out LLM fallback
-            # fixed_latex = request_llm_fallback(cleaned_latex, llm_url)
-            # cleaned_latex = clean_latex(fixed_latex)
             return f"❌ Could not parse expression:\n\n```latex\n{cleaned_latex}\n```", cleaned_latex, ""
 
         output = f"## 📄 Extracted LaTeX\n```latex\n{latex_result}\n```\n"
@@ -113,73 +72,75 @@ def solve_polynomial(image):  # removed llm_url
     except Exception as e:
         return f"❌ Error: {str(e)}", "", ""
 
-def wrapped_solver(img):  # removed url
+def wrapped_solver(img):
     result, cleaned, prompt = solve_polynomial(img)
     return result, cleaned, prompt
 
-# def solve_from_coeffs(degree, coeff_str):
-#     try:
-#         coeffs = [float(c.strip()) for c in coeff_str.split(",")]
-#         if len(coeffs) != int(degree) + 1:
-#             return f"❌ You entered {len(coeffs)} coefficients, but degree {degree} needs {int(degree)+1}.", ""
-
-#         x = sp.Symbol("x")
-#         poly_expr = sum(coeffs[i] * x**(int(degree) - i) for i in range(len(coeffs)))
-#         factored = sp.factor(poly_expr)
-#         roots = sp.solve(poly_expr, x)
-
-#         result = "## 🧮 Symbolic Roots:\n"
-#         for i, r in enumerate(roots, 1):
-#             result += f"- Root {i}: $${sp.latex(sp.N(r, 6))}$$\n"
-
-#         terms = []
-#         for i, c in enumerate(coeffs):
-#             power = int(degree) - i
-#             if power == 0:
-#                 terms.append(f"{c}")
-#             elif power == 1:
-#                 terms.append(f"{c}x")
-#             else:
-#                 terms.append(f"{c}x^{power}")
-#         equation_str = " + ".join(terms).replace("+ -", "- ") + " = 0"
-#         roots_str = f"[{', '.join(str(sp.N(r, 6)) for r in roots)}]"
-#         factored_str = sp.pretty(factored)
-
-#         llm_prompt = (
-#             f"Equation: {equation_str}\n"
-#             f"Factor: {factored_str} = 0\n"
-#             f"Roots: {roots_str}\n\n"
-#             "Explain the solution step-by-step in human language. "
-#             "These roots are correct (up to approximation), so base your reasoning on them."
-#         )
-
-#         return result, llm_prompt
-#     except Exception as e:
-#         return f"❌ Error: {str(e)}", ""
+# ---------- Tab 2 Logic: Solve Simultaneous Linear Equations ----------
+
+def solve_simultaneous_equations(img):
+    try:
+        img = preprocess_handwritten_image(img)
+        latex_result = model(img)
+        cleaned_latex = clean_latex(latex_result)
+
+        lines = [line.strip() for line in cleaned_latex.splitlines() if line.strip()]
+        if len(lines) < 2:
+            return f"❌ Expected at least 2 equations but found {len(lines)}.\n\nExtracted:\n{cleaned_latex}"
+
+        equations = []
+        symbols = set()
+
+        for line in lines:
+            parsed = parse_latex(line)
+            if not isinstance(parsed, sp.Equality):
+                return f"❌ Failed to parse line as equation: {line}"
+            lhs = parsed.lhs - parsed.rhs
+            symbols.update(lhs.free_symbols)
+            equations.append(lhs)
+
+        if len(symbols) < 2:
+            return f"❌ Need at least 2 variables to solve system. Found: {symbols}"
+
+        sols = sp.linsolve(equations, *symbols)
+        if not sols:
+            return "❌ No solution found."
+
+        sym_list = list(symbols)
+        output = "## 🧠 Extracted System:\n"
+        for line in lines:
+            output += f"$$ {line} $$\n"
+
+        output += "\n---\n## ✅ Solution:\n"
+        output += "$$\n\\begin{aligned}\n"
+        for var, val in zip(sym_list, list(sols)[0]):
+            output += f"{sp.latex(var)} &= {sp.latex(sp.N(val, 6))} \\\\\n"
+        output += "\\end{aligned}\n$$"
+
+        return output
+    except Exception as e:
+        return f"❌ Error: {e}"
+
+# ------------------ UI ------------------
 
 with gr.Blocks() as demo:
     with gr.Tab("🖼️ Parse from Image"):
-        # llm_url = gr.Textbox(label="🔗 Enter LLM Microservice URL (from Colab)", placeholder="https://xxxx.ngrok-free.app")
         image_input = gr.Image(type="pil", label="📷 Upload Image of Polynomial")
         hidden_latex = gr.Textbox(visible=False)
         explanation_prompt = gr.Textbox(visible=False)
         output_box = gr.Markdown(label="📋 Step-by-step Solution")
         submit_btn = gr.Button("🔍 Solve")
         submit_btn.click(fn=wrapped_solver, inputs=[image_input], outputs=[output_box, hidden_latex, explanation_prompt])
+        # Human explanation (commented out)
         # explain_box = gr.Markdown(label="🗣️ Human-style Explanation")
         # explain_btn = gr.Button("🧠 Explain Human-Solution")
         # explain_btn.click(fn=request_llm_explanation, inputs=[explanation_prompt, llm_url], outputs=explain_box)
 
-    # with gr.Tab("🧮 Solve by Coefficients"):
-    #     degree_input = gr.Number(label="Enter Degree of Polynomial (e.g. 3)")
-    #     coeffs_input = gr.Textbox(label="Enter Coefficients (comma-separated)", placeholder="e.g. 1, 2, 0, -4")
-    #     roots_output = gr.Markdown(label="✅ Roots")
-    #     coeff_hidden_equation = gr.Textbox(visible=False)
-    #     coeff_btn = gr.Button("📌 Solve")
-    #     coeff_btn.click(fn=solve_from_coeffs, inputs=[degree_input, coeffs_input], outputs=[roots_output, coeff_hidden_equation])
-    #     coeff_explain_box = gr.Markdown(label="🗣️ Human-style Explanation")
-    #     coeff_explain_btn = gr.Button("🧠 Explain Human-Solution")
-    #     coeff_explain_btn.click(fn=request_llm_explanation, inputs=[coeff_hidden_equation, llm_url], outputs=coeff_explain_box)
+    with gr.Tab("🧮 Simultaneous Equations"):
+        sim_image_input = gr.Image(type="pil", label="📷 Upload Image with 2 or 3 Linear Equations")
+        sim_output = gr.Markdown(label="📋 Solved Result")
+        sim_submit = gr.Button("🔍 Solve Simultaneous Equations")
+        sim_submit.click(fn=solve_simultaneous_equations, inputs=[sim_image_input], outputs=[sim_output])
 
 if __name__ == "__main__":
     demo.launch()