Spaces:
No application file
No application file
File size: 9,127 Bytes
4f24301 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 |
import json
import re
from typing import Dict, List, Any, Optional
def parse_image_quality_for_deepforest(response: str) -> str:
"""
Parse IMAGE_QUALITY_FOR_DEEPFOREST from response.
Args:
response: Model response text
Returns:
"Yes" or "No"
"""
quality_match = re.search(r'(?:\*\*)?IMAGE_QUALITY_FOR_DEEPFOREST[:\*\s]+\[?(YES|NO|Yes|No|yes|no)\]?', response, re.IGNORECASE)
if quality_match:
quality_value = quality_match.group(1).upper()
return "Yes" if quality_value == "YES" else "No"
return "No"
def parse_deepforest_objects_present(response: str) -> List[str]:
"""
Parse DEEPFOREST_OBJECTS_PRESENT from response.
Args:
response: Model response text
Returns:
List of objects present
"""
objects_match = re.search(r'(?:\*\*)?DEEPFOREST_OBJECTS_PRESENT[:\*\s]+(\[.*?\])', response, re.DOTALL)
if objects_match:
try:
objects_str = objects_match.group(1)
objects_str = re.sub(r'[`\'"]', '"', objects_str)
objects_list = json.loads(objects_str)
allowed_objects = ["bird", "tree", "livestock"]
validated_objects = [obj for obj in objects_list if obj in allowed_objects]
return validated_objects
except json.JSONDecodeError:
objects_str = objects_match.group(1)
manual_objects = re.findall(r'"(bird|tree|livestock)"', objects_str)
return list(set(manual_objects))
return []
def parse_additional_objects_json(response: str) -> List[Dict[str, Any]]:
"""
Parse ADDITIONAL_OBJECTS_JSON from response.
Args:
response: Model response text
Returns:
List of additional objects with coordinates
"""
additional_match = re.search(r'(?:\*\*)?ADDITIONAL_OBJECTS_JSON[:\*\s]+(.*?)(?=\n(?:\*\*)?(?:VISUAL_ANALYSIS|IMAGE_QUALITY|DEEPFOREST_OBJECTS)|$)', response, re.DOTALL)
if additional_match:
try:
additional_str = additional_match.group(1).strip()
if additional_str.startswith('```json'):
additional_str = additional_str[7:]
if additional_str.startswith('```'):
additional_str = additional_str[3:]
if additional_str.endswith('```'):
additional_str = additional_str[:-3]
additional_str = additional_str.strip()
if additional_str.startswith('[') and additional_str.endswith(']'):
additional_objects = json.loads(additional_str)
if isinstance(additional_objects, list):
return additional_objects
else:
additional_objects = []
for line in additional_str.split('\n'):
line = line.strip().rstrip(',')
if line and line.startswith('{') and line.endswith('}'):
try:
obj = json.loads(line)
additional_objects.append(obj)
except json.JSONDecodeError:
continue
return additional_objects
except Exception as e:
print(f"Error parsing additional objects JSON: {e}")
return []
def parse_visual_analysis(response: str) -> str:
"""
Parse VISUAL_ANALYSIS from response.
Args:
response: Model response text
Returns:
Visual analysis text
"""
analysis_match = re.search(r'(?:\*\*)?VISUAL_ANALYSIS[:\*\s]+(.*?)(?=\n(?:\*\*)?(?:IMAGE_QUALITY|DEEPFOREST_OBJECTS|ADDITIONAL_OBJECTS)|$)', response, re.IGNORECASE | re.DOTALL)
if analysis_match:
return analysis_match.group(1).strip()
else:
fallback_match = re.search(r'(?:\*\*)?VISUAL_ANALYSIS[:\*\s]+(.*)', response, re.IGNORECASE | re.DOTALL)
if fallback_match:
return fallback_match.group(1).strip()
return response
def parse_deepforest_agent_response_with_reasoning(response: str) -> Dict[str, Any]:
"""
Parse DeepForest detector agent response with reasoning.
Args:
response: Model response text
Returns:
Dictionary with reasoning and tool calls
"""
from deepforest_agent.tools.tool_handler import extract_all_tool_calls
try:
tool_calls = extract_all_tool_calls(response)
if not tool_calls:
return {"error": "No valid tool calls found in response"}
reasoning_text = ""
first_json_match = re.search(r'\{[^}]*"name"[^}]*"arguments"[^}]*\}', response)
if first_json_match:
reasoning_text = response[:first_json_match.start()].strip()
reasoning_text = re.sub(r'^(REASONING:|Reasoning:|Analysis:|\*\*REASONING:\*\*)', '', reasoning_text).strip()
if not reasoning_text:
reasoning_text = "Tool calls generated based on analysis"
return {
"reasoning": reasoning_text,
"tool_calls": tool_calls
}
except Exception as e:
return {"error": f"Unexpected error parsing response: {str(e)}"}
def parse_memory_agent_response(response: str) -> Dict[str, Any]:
"""
Parse memory agent structured response format with new TOOL_CACHE_ID field.
Args:
response: Model response text
Returns:
Dictionary with answer_present, direct_answer, tool_cache_id, and relevant_context
"""
try:
# Parse ANSWER_PRESENT
answer_present_match = re.search(r'(?:\*\*)?ANSWER_PRESENT:(?:\*\*)?\s*\[?(YES|NO)\]?', response, re.IGNORECASE)
answer_present = False
if answer_present_match:
answer_present = answer_present_match.group(1).upper() == "YES"
# Parse TOOL_CACHE_ID
tool_cache_id_match = re.search(r'(?:\*\*)?TOOL_CACHE_ID:(?:\*\*)?\s*(.*?)(?=\n(?:\*\*)?(?:RELEVANT_CONTEXT|$))', response, re.IGNORECASE | re.DOTALL)
tool_cache_id = None
if tool_cache_id_match:
tool_cache_id_text = tool_cache_id_match.group(1).strip()
# Extract all cache IDs using multiple patterns
cache_ids = []
# Pattern 1: IDs within brackets [id1, id2, ...]
bracket_pattern = r'\[([^\[\]]*)\]'
bracket_matches = re.findall(bracket_pattern, tool_cache_id_text)
for bracket_content in bracket_matches:
if bracket_content.strip(): # Skip empty brackets
# Extract hex IDs from bracket content
hex_ids = re.findall(r'([a-fA-F0-9]{8,})', bracket_content)
cache_ids.extend(hex_ids)
# Pattern 2: Direct hex IDs (not in brackets)
# Remove bracketed content first, then find remaining hex IDs
text_without_brackets = re.sub(r'\[[^\[\]]*\]', '', tool_cache_id_text)
direct_hex_ids = re.findall(r'([a-fA-F0-9]{8,})', text_without_brackets)
cache_ids.extend(direct_hex_ids)
# Pattern 3: Standalone hex IDs on separate lines (check the whole response)
standalone_pattern = r'^([a-fA-F0-9]{8,})$'
standalone_matches = re.findall(standalone_pattern, response, re.MULTILINE)
cache_ids.extend(standalone_matches)
# Remove duplicates while preserving order
seen = set()
unique_cache_ids = []
for cache_id in cache_ids:
if cache_id not in seen:
seen.add(cache_id)
unique_cache_ids.append(cache_id)
if unique_cache_ids:
tool_cache_id = ", ".join(unique_cache_ids) if len(unique_cache_ids) > 1 else unique_cache_ids[0]
elif tool_cache_id_text and tool_cache_id_text.lower() not in ["", "empty", "none", "no tool cache id"]:
tool_cache_id = tool_cache_id_text
# Parse RELEVANT_CONTEXT
context_match = re.search(
r'(?:\*\*)?RELEVANT_CONTEXT:(?:\*\*)?\s*(.*?)(?=\n\*\*[A-Z_]+:|\Z)',
response,
re.IGNORECASE | re.DOTALL
)
relevant_context = ""
if context_match:
relevant_context = context_match.group(1).strip()
elif not answer_present:
relevant_context = response
return {
"answer_present": answer_present,
"direct_answer": "YES" if answer_present else "NO",
"tool_cache_id": tool_cache_id,
"relevant_context": relevant_context,
"raw_response": response
}
except Exception as e:
print(f"Error parsing memory response: {e}")
return {
"answer_present": False,
"direct_answer": "NO",
"tool_cache_id": None,
"relevant_context": response,
"raw_response": response
} |