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import re
def _extract_section(text: str, start_marker: str, end_marker: str) -> str:
"""Extract content between two markers"""
start = text.find(start_marker)
if start == -1:
return ""
start += len(start_marker)
end = text.find(end_marker, start)
if end == -1:
return ""
return text[start:end].strip()
class AnswerExtractor:
def __init__(self, task_name):
"""Initialize answer extractor"""
self.task_name = task_name
def extract_answers(self, response):
"""Extract answers based on task type"""
try:
task_extractors = {
"S_0D": self.extract_S_0D,
"S_1D": self.extract_S_1D,
"S_Modification": self.extract_S_Modification,
"M_Birth": self.extract_M_Birth,
"M_Merge": self.extract_M_Merge,
"M_Filtration": self.extract_M_Filtration,
"H_Selection": self.extract_H_Selection,
"H_Generation": self.extract_H_Generation,
"R_Selection": self.extract_R_Selection,
"R_Generation": self.extract_R_Generation,
"R_Directly": self.extract_R_Directly
}
answer = task_extractors.get(self.task_name)(response) if self.task_name in task_extractors else None
return answer
except Exception as e:
print(f"Error extracting answer: {str(e)}")
return None
def extract_S_0D(self, answer: str) -> Dict[str, Any]:
"""Extract information from 0-dimensional topology structure identification answer"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Extract the filtration value with more flexible pattern matching
value_match = re.search(r'connected components:\s*(\d+)', answer_section)
if not value_match:
return {"error": "connected components not found"}
# Parse the value
try:
value = int(value_match.group(1).strip())
return {
"connected_components": value
}
except ValueError as e:
return {"error": f"Error parsing value: {str(e)}"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_S_1D(self, answer: str) -> Dict[str, Any]:
"""Extract information from 1-dimensional topology structure identification answer"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Extract the filtration value with more flexible pattern matching
value_match = re.search(r'cycle holes:\s*(\d+)', answer_section)
if not value_match:
return {"error": "cycle holes not found"}
# Parse the value
try:
value = int(value_match.group(1).strip())
return {
"cycle_holes": value
}
except ValueError as e:
return {"error": f"Error parsing value: {str(e)}"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_S_Modification(self, answer: str) -> Dict[str, Any]:
"""Extract information from graph structure modification answer"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Try multiple matching patterns
patterns = [
r'Edge to add:\s*\[(.*?)\]', # Match "Edge to add: [0, 7]" format
r'Edge to add:\s*\((\d+)\s*,\s*(\d+)\)', # Match "Edge to add: (0, 7)" format
r'Edge to add:\s*(\d+)\s*-\s*(\d+)', # Match "Edge to add: 0-7" format
r'Edge to add:\s*(\d+)\s*,\s*(\d+)' # Match "Edge to add: 0, 7" format
]
for pattern in patterns:
value_match = re.search(pattern, answer_section)
if value_match:
try:
if pattern == r'Edge to add:\s*\[(.*?)\]':
# Handle [0, 7] format
values_str = value_match.group(1).strip()
values = [int(x.strip()) for x in values_str.split(',')]
else:
# Handle other formats
values = [int(value_match.group(1)), int(value_match.group(2))]
return {
"edge_to_add": values
}
except (ValueError, IndexError):
continue
return {"error": "Edge to add not found or invalid format"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_M_Birth(self, answer: str) -> Dict[str, Any]:
"""Extract birth time calculation task answer"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Extract the filtration value
value_match = re.search(r'birth time:\s*\[(.*?)\]', answer_section)
if not value_match:
return {"error": "birth_time not found"}
# Parse the values
try:
values = [self._parse_number(x) for x in value_match.group(1).split(',')]
return {
"birth_time": values
}
except ValueError as e:
return {"error": f"Error parsing : {str(e)}"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_M_Merge(self, answer: str) -> Dict[str, Any]:
"""Extract information from 0-dimensional persistent homology calculation task answer"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Extract the filtration value
value_match = re.search(r'death time:\s*\[(.*?)\]', answer_section)
if not value_match:
return {"error": "death_time not found"}
# Parse the values
try:
values = [self._parse_number(x) for x in value_match.group(1).split(',')]
return {
"death_time": values
}
except ValueError as e:
return {"error": f"Error parsing : {str(e)}"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_M_Filtration(self,answer:str) -> Dict[str, Any]:
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Extract the filtration value
value_match = re.search(r'connected components:\s*\[(.*?)\]', answer_section)
if not value_match:
return {"error": "connected components not found"}
# Parse the values
try:
values = [self._parse_number(x) for x in value_match.group(1).split(',')]
return {
"connected_components": values
}
except ValueError as e:
return {"error": f"Error parsing : {str(e)}"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_H_Selection(self, answer: str) -> Dict[str, Any]:
"""Extract selected filtration method from the response"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Try multiple matching patterns
patterns = [
r'Method:\s*([\w-]+)', # Match "Method: k-shell" format
r'Method:\s*\[([\w-]+)\]', # Match "Method: [k-shell]" format
r'selected_method:\s*([\w-]+)', # Match "selected_method: k-shell" format
r'Selected Method:\s*([\w-]+)' # Match "Selected Method: k-shell" format
]
for pattern in patterns:
value_match = re.search(pattern, answer_section, re.IGNORECASE)
if value_match:
method = value_match.group(1).strip().lower()
# Validate method name
valid_methods = ['degree', 'betweenness', 'k-shell', 'closeness', 'weight', 'eigenvector']
if method in valid_methods:
return {
"selected_method": method
}
return {"error": "Method not found or invalid"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_H_Generation(self, answer: str) -> Dict[str, Any]:
"""Extract information from filteration value selection task answer"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Extract the filtration value
value_match = re.search(r'filtration value:\s*\[(.*?)\]', answer_section)
if not value_match:
return {"error": "Filtration value not found"}
# Parse the values
try:
values = [int(x.strip()) for x in value_match.group(1).split(',')]
return {
"selected_filtration_values": values
}
except ValueError as e:
return {"error": f"Error parsing filtration values: {str(e)}"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_filtration_edge_construction(self, answer: str) -> Dict[str, Any]:
"""Extract information from filtration edge construction task answer"""
result = {
"filtration": {}
}
try:
# Extract filtration process
filtration_section = _extract_section(answer, "===FILTRATION_START===", "===FILTRATION_END===")
result["filtration"] = self._parse_filtration_edges(filtration_section)
# Validate results
if not result["filtration"]:
print("Warning: Failed to extract filtration process")
print("Filtration process:", result["filtration"])
except Exception as e:
import traceback
print(f"Error during extraction: {str(e)}")
print("Error details:")
print(traceback.format_exc())
return result # Return partially parsed results instead of None
return result
def extract_simplicial_complex_construction(self, answer: str) -> Dict[str, Any]:
"""
Extract answer for simplicial_complex_construction task
Parameters:
answer: Model generated answer text
Returns:
dict: Contains extracted simplicial complex information
"""
try:
# Extract simplicial complex section
simplex_text = self._extract_section(answer, "===SIMPLICIAL_COMPLEX_START===", "===SIMPLICIAL_COMPLEX_END===")
if not simplex_text:
return {"error": "Simplicial complex section not found"}
# Parse simplicial complex
simplices = {}
for line in simplex_text.split('\n'):
line = line.strip()
if not line:
continue
# Check if it's a simplex
if line.startswith('[') and line.endswith(']'):
try:
# Parse node list and filtration value
content = line[1:-1] # Remove outer brackets
nodes_part, value_part = content.split('),')
nodes = [int(x.strip()) for x in nodes_part[1:].split(',')] # Remove inner brackets
value = float(value_part.strip())
if len(nodes) == 3: # Only process 2-dimensional simplices (triangles)
if value not in simplices:
simplices[value] = []
simplices[value].append(nodes)
except (ValueError, IndexError) as e:
print(f"Error parsing simplex: {line}, error: {str(e)}")
continue
return {
"simplicial_complexes": simplices
}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def _parse_number(self, value_str: str) -> float:
"""Parse number intelligently, try integer first, then float"""
value_str = value_str.strip()
try:
# Try parsing as integer first
return int(value_str)
except ValueError:
try:
# If integer parsing fails, try parsing as float
value = float(value_str)
# If it's an integer (no decimal part), return integer
if value.is_integer():
return int(value)
return value
except ValueError:
raise ValueError(f"Cannot parse number: {value_str}")
def extract_R_Selection(self, answer: str) -> Dict[str, Any]:
"""Extract selected filtration method from the response"""
try:
# Extract the answer section
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Try multiple matching patterns
patterns = [
r'Method:\s*(\w+)', # Match "Method: weight" format
r'Method:\s*\[(.*?)\]', # Match "Method: [weight]" format
r'selected_method:\s*(\w+)', # Match "selected_method: weight" format
r'Selected Method:\s*(\w+)' # Match "Selected Method: weight" format
]
for pattern in patterns:
value_match = re.search(pattern, answer_section, re.IGNORECASE)
if value_match:
method = value_match.group(1).strip().lower()
# 验证方法名称是否有效
valid_methods = ['degree', 'betweenness', 'k-shell', 'closeness', 'weight','eigenvector']
if method in valid_methods:
return {
"selected_method": method
}
return {"error": "Method not found or invalid"}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_R_Generation(self, answer: str) -> Dict[str, Any]:
"""Extract filtration values from the response"""
try:
# Extract content after "Answer:" if present
answer_section = answer
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
# Match pattern like Filtration value: [0.1,0.4,0.5,...]
pattern = r'Filtration\s*value[s]?:\s*\[([^\]]+)\]'
match = re.search(pattern, answer_section, re.IGNORECASE)
if not match:
return {"error": "Filtration values not found"}
# Extract numbers inside brackets, split by comma and convert to float
nums_str = match.group(1)
values: List[float] = []
for part in nums_str.split(','):
part = part.strip()
if part:
try:
values.append(float(part))
except ValueError:
return {"error": f"Cannot convert '{part}' to float"}
return {"filtration_values": values}
except Exception as e:
return {"error": f"Error during extraction: {str(e)}"}
def extract_R_Directly(self, answer: str) -> Dict[str, Any]:
"""Extract category classification from the response"""
# Get content after "Answer:" if present
if "Answer:" in answer:
answer_section = answer.split("Answer:")[-1].strip()
else:
answer_section = answer
pattern = r'Category:\s*[\[\(]\s*([\d\.\s,]+)[\]\)]\s*,\s*[\[\(]\s*([\d\.\s,]+)[\]\)]'
match = re.search(pattern, answer_section, re.IGNORECASE | re.DOTALL)
if not match:
return {"error": "Category format not found or incorrect"}
def parse_group(group_str: str) -> List[int]:
return [int(float(x.strip())) for x in group_str.split(',') if x.strip()]
category1 = parse_group(match.group(1))
category2 = parse_group(match.group(2))
all_indices = sorted(category1 + category2)
if all_indices != [1, 2, 3, 4]:
return {"error": f"Graph indices must be [1, 2, 3, 4], got: {all_indices}"}
return {
"categories": [category1, category2]
}
# def _parse_filtration_edges(self, section: str) -> Dict[float, List[Tuple[int, int]]]:
# """Parse filtration process, specific to the format of filtration edge construction task"""
# filtration = {}
# current_value = None
# for line in section.split('\n'):
# line = line.strip()
# if line.startswith('**Value='):
# value_part = line.replace('**', '').replace('Value=', '').strip()
# current_value = float(value_part)
# filtration[current_value] = []
# elif line.startswith('(') and line.endswith(')'):
# try:
# u, v = map(int, line[1:-1].split(','))
# filtration[current_value].append((u, v))
# except:
# print(f"Cannot parse edge: {line}")
# return filtration
# def extract_structure_identification(self, answer: str) -> Dict[str, Any]:
# """Extract information from topology structure identification answer"""
# result = {
# "cavities": [],
# "temporal_evolution": {}
# }
# # Extract cavity information
# if "2-DIMENSIONAL CAVITIES:" in answer:
# cavities_section = self._extract_section(
# answer, "2-DIMENSIONAL CAVITIES:", "TEMPORAL EVOLUTION:"
# )
# result["cavities"] = self._extract_cavities(cavities_section)
# # Extract temporal evolution
# if "TEMPORAL EVOLUTION:" in answer:
# evolution_section = answer.split("TEMPORAL EVOLUTION:")[1]
# result["temporal_evolution"] = self._extract_temporal_evolution(evolution_section)
# return result
# def extract_simplex_structure_identification(self, answer: str) -> Dict[str, Any]:
# """Extract information from simplex structure identification answer"""
# result = {
# "simplex_count": 0
# }
# lines = answer.strip().split('\n')
# for line in lines:
# line = line.strip()
# if line.startswith('2维单纯形数量：'):
# count_str = line.split('：')[1].strip()
# try:
# result["simplex_count"] = int(count_str)
# except ValueError:
# # Keep default value 0 if cannot parse as integer
# pass
# return result
# def _extract_section(self, text: str, start_marker: str, end_marker: str) -> str:
# """Extract text between two markers"""
# if start_marker in text and end_marker in text:
# start_idx = text.find(start_marker) + len(start_marker)
# end_idx = text.find(end_marker)
# return text[start_idx:end_idx].strip()
# return ""
# def _extract_list(self, text: str) -> List:
# """Extract list from text"""
# items = text.split(':')[1].strip()
# if items.startswith('[') and items.endswith(']'):
# return eval(items)
# return []
# def _extract_feature_info(self, line: str) -> Dict[str, Any]:
# """Extract feature information from text"""
# info = {}
# if 'Birth time:' in line:
# info['birth'] = float(line.split(':')[1].strip())
# elif 'Death time:' in line:
# info['death'] = float(line.split(':')[1].strip())
# elif 'Persistence:' in line:
# info['persistence'] = float(line.split(':')[1].strip())
# elif 'Description:' in line:
# info['description'] = line.split(':')[1].strip()
# return info
# def _extract_cavities(self, text: str) -> List[Dict[str, Any]]:
# """Extract cavity information"""
# cavities = []
# current_cavity = None
# for line in text.split('\n'):
# if line.startswith('Cavity'):
# if current_cavity:
# cavities.append(current_cavity)
# current_cavity = {}
# elif current_cavity is not None and line.startswith('-'):
# key = line.split(':')[0].strip('- ').lower()
# value = line.split(':')[1].strip()
# if key in ['birth threshold', 'death threshold', 'persistence']:
# value = float(value)
# elif key in ['nodes', 'edges']:
# value = eval(value)
# current_cavity[key] = value
# if current_cavity:
# cavities.append(current_cavity)
# return cavities
# def _extract_temporal_evolution(self, text: str) -> Dict[float, Dict[str, List[int]]]:
# """Extract temporal evolution information"""
# evolution = {}
# current_threshold = None
# for line in text.split('\n'):
# if line.startswith('Threshold'):
# current_threshold = float(line.split()[1])
# evolution[current_threshold] = {
# 'active': [],
# 'new': [],
# 'disappeared': []
# }
# elif current_threshold is not None and line.startswith('-'):
# key = line.split(':')[0].strip('- ').lower()
# value = eval(line.split(':')[1].strip())
# evolution[current_threshold][key] = value
# return evolution
# def _extract_current_state(self, text: str) -> Dict[str, Any]:
# """Extract current state information"""
# state = {}
# for line in text.split('\n'):
# if line.startswith('- Number of cycles:'):
# state['cycles'] = int(line.split(':')[1].strip())
# elif line.startswith('- Cycle locations:'):
# state['locations'] = eval(line.split(':')[1].strip())
# return state
# def _extract_proposed_modifications(self, text: str) -> List[Dict[str, Any]]:
# """Extract proposed modifications"""
# modifications = []
# current_mod = None
# for line in text.split('\n'):
# if line.startswith('Modification'):
# if current_mod:
# modifications.append(current_mod)
# current_mod = {}
# elif current_mod is not None and line.startswith('-'):
# key = line.split(':')[0].strip('- ').lower()
# value = line.split(':')[1].strip()
# if key == 'new edge':
# value = tuple(map(int, value.split('-')))
# elif key == 'expected new cycles':
# value = eval(value)
# current_mod[key] = value
# if current_mod:
# modifications.append(current_mod)
# return modifications
# def _extract_expected_outcome(self, text: str) -> Dict[str, Any]:
# """Extract expected outcome"""
# outcome = {}
# for line in text.split('\n'):
# if line.startswith('- New number of cycles:'):
# outcome['new_cycles'] = int(line.split(':')[1].strip())
# elif line.startswith('- New cycle locations:'):
# outcome['new_locations'] = eval(line.split(':')[1].strip())
# elif line.startswith('- Changes in persistence:'):
# outcome['persistence_changes'] = line.split(':')[1].strip()
# return outcome
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