Чат-бот Python AI Math с использованием Sympy ⇐ Python

[Anonymous]

Может ли кто-нибудь помочь мне разобраться в проблеме с моим кодом? Я пытаюсь разработать чат-бота, который может решать задачи по алгебре с помощью Sympy, но постоянно получаю одни и те же ошибки и не могу в этом разобраться. сообщение об ошибке
*# Ниже приведен мой код: *

Код: Выделить всё

import os
import json
from sympy import symbols, Eq, solve
from sympy.parsing.sympy_parser import standard_transformations, implicit_multiplication_application, parse_expr
from transformers import (
AutoTokenizer,
AutoModelForCausalLM,
pipeline
)
import re

def normalize_text(text):
"""Normalize text for consistent matching."""
text = text.lower().strip()
text = re.sub(r'[^\w\s]', '', text)  # Remove punctuation
return text

# Predefined Responses
def get_predefined_response(user_query, file_path="algebra_data.json"):
with open(file_path, "r") as f:
predefined_responses = json.load(f)

user_query_normalized = normalize_text(user_query)

for entry in predefined_responses:
if normalize_text(entry["prompt"]) == user_query_normalized:
return entry["response"]

return None

# SymPy Solver

def solve_algebra(problem):
try:
# Define the variable(s) used in the equation
x = symbols('x')

# Replace '^' with '**' for SymPy compatibility
problem = problem.replace("^", "**").replace("Solve", "").strip()

# Debug: Print the original input problem
print(f"Debug: Original problem: {problem}")

# Enable implicit multiplication and other transformations
transformations = (standard_transformations + (implicit_multiplication_application,))

# Extract and parse the equation
if "=" in problem:
left, right = problem.split("=")
left_expr = parse_expr(left.strip(), transformations=transformations)
right_expr = parse_expr(right.strip(), transformations=transformations)
equation = Eq(left_expr, right_expr)
else:
equation = parse_expr(problem.strip(), transformations=transformations)

# Debug: Print the parsed equation
print(f"Debug: Parsed equation: {equation}")

# Solve the equation
solutions = solve(equation, x)

# Debug: Print the solutions and their type
print(f"Debug: Solutions: {solutions}, Type: {type(solutions)}")

# Handle solutions
if isinstance(solutions, list):  # Multiple solutions or single solution in a list
if not solutions:  # Empty list
return "No solutions found."
return f"The solutions are: {', '.join(map(str, solutions))}"
elif hasattr(solutions, 'is_real') and not solutions.is_real:  # Complex solution
return f"The solution is a complex number: {solutions}"
elif isinstance(solutions, (int, float, symbols)):  # Single solution (non-list)
return f"The solution is: {solutions}"
else:
# Handle unexpected return types
return f"The solution is: {solutions}"

except Exception as e:
# Debug: Print the error
print(f"Debug: Error in solve_algebra: {e}")
return f"Sorry, I couldn't solve that problem. Error: {e}"

# Load Pretrained Model and Tokenizer
model_name = "microsoft/DialoGPT-medium"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Add a padding token if not present
if tokenizer.pad_token is None:
tokenizer.add_special_tokens({'pad_token': '[PAD]'})
model.resize_token_embeddings(len(tokenizer))  # Resize the embeddings

# Test the Fine-Tuned Chatbot
print("\nTesting the chatbot interactively...\n")
chatbot = pipeline("text-generation", model="./algebra_chatbot", tokenizer="./algebra_chatbot")

# Interactive Chat Loop
print("Algebra Chatbot: Hello! I can help you with basic algebra.  Type 'exit' to quit.\n")
while True:
user_input = input("User: ")
if user_input.lower() in ["exit", "quit", "bye"]:
print("Algebra Chatbot: Goodbye! Keep practicing algebra!")
break

# Check for predefined responses
predefined_response = get_predefined_response(user_input)
if predefined_response:
print(f"Algebra Chatbot: {predefined_response}")
# Check for algebraic problems and solve them dynamically
elif "solve" in user_input.lower() or "=" in user_input:
print(f"Algebra Chatbot: {solve_algebra(user_input)}")
# Use the fine-tuned model for general questions
else:
response = chatbot(
f"User: {user_input}\nBot:",
max_length=100,
num_return_sequences=1,
truncation=True  # Add truncation explicitly
)
bot_response = response[0]["generated_text"].split("Bot:")[-1].strip()
print(f"Algebra Chatbot: {bot_response}")`

Я пытался добавить обработчик неожиданных решений и явно проверять списки, целые числа, числа с плавающей точкой и символические решения, но по какой-то причине это не работает.>

Подробнее здесь: https://stackoverflow.com/questions/793 ... sing-sympy