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# DEPENDENCIES
import sys
import numpy as np
from enum import Enum
from typing import Any
from typing import Dict
from typing import List
from typing import Tuple
from pathlib import Path
from typing import Optional
from dataclasses import field
from dataclasses import dataclass
# Add parent directory to path for imports
sys.path.append(str(Path(__file__).parent.parent))
@dataclass
class ExtractedClause:
"""
Extracted clause with comprehensive metadata
"""
text : str
reference : str # e.g., "Section 5.2", "Clause 11.1"
category : str # e.g., "termination", "compensation", "indemnification"
confidence : float # 0.0-1.0
start_pos : int
end_pos : int
extraction_method : str # "structural", "semantic", "hybrid"
risk_indicators : List[str] = field(default_factory = list)
embeddings : Optional[np.ndarray] = None
subclauses : List[str] = field(default_factory = list)
legal_bert_score : float = 0.0
risk_score : float = 0.0
def to_dict(self) -> Dict[str, Any]:
"""
Convert to dictionary for serialization
"""
return {"text" : self.text,
"reference" : self.reference,
"category" : self.category,
"confidence" : round(self.confidence, 3),
"start_pos" : self.start_pos,
"end_pos" : self.end_pos,
"extraction_method" : self.extraction_method,
"risk_indicators" : self.risk_indicators,
"subclauses" : self.subclauses,
"legal_bert_score" : round(self.legal_bert_score, 3),
"risk_score" : round(self.risk_score, 3),
}
@dataclass
class UnfavorableTerm:
"""
Detected unfavorable term with comprehensive risk analysis
"""
term : str
category : str # Risk category (e.g., "restrictive_covenants")
severity : str # "critical", "high", "medium", "low"
explanation : str
risk_score : float # 0-100 risk score
clause_reference : Optional[str] = None
suggested_fix : Optional[str] = None
contract_type : Optional[str] = None
specific_text : Optional[str] = None
benchmark_info : Optional[str] = None # Industry benchmark comparison
legal_basis : Optional[str] = None # Legal principle violated
def to_dict(self) -> Dict:
"""
Convert to dictionary
"""
return {"term" : self.term,
"category" : self.category,
"severity" : self.severity,
"explanation" : self.explanation,
"risk_score" : round(self.risk_score, 2),
"clause_reference" : self.clause_reference,
"suggested_fix" : self.suggested_fix,
"contract_type" : self.contract_type,
"specific_text" : self.specific_text,
"benchmark_info" : self.benchmark_info,
"legal_basis" : self.legal_basis,
}
@dataclass
class ClauseInterpretation:
"""
LLM interpretation of a clause with comprehensive analysis
"""
clause_reference : str
original_text : str
plain_english_summary : str
key_points : List[str]
potential_risks : List[str]
suggested_improvements : List[str]
favorability : str = "neutral"
confidence_score : float = 0.0
risk_level : str = "unknown"
negotiation_priority : str = "medium"
legal_precedents : List[str] = field(default_factory = list)
negotiation_leverage : List[str] = field(default_factory = list)
market_comparison : Optional[str] = None
risk_score : float = 0.0
def to_dict(self) -> Dict[str, Any]:
return {"clause_reference" : self.clause_reference,
"original_text" : self.original_text,
"plain_english_summary" : self.plain_english_summary,
"key_points" : self.key_points,
"potential_risks" : self.potential_risks,
"suggested_improvements" : self.suggested_improvements,
"favorability" : self.favorability,
"confidence_score" : round(self.confidence_score, 3),
"risk_level" : self.risk_level,
"negotiation_priority" : self.negotiation_priority,
"legal_precedents" : self.legal_precedents,
"negotiation_leverage" : self.negotiation_leverage,
"market_comparison" : self.market_comparison,
"risk_score" : round(self.risk_score, 3),
}
@dataclass
class MissingProtection:
"""
Missing protection item with comprehensive risk analysis
"""
protection_id : str # Internal identifier
protection : str
importance : str # "critical", "high", "medium", "low"
risk_score : float # 0-100 from risk_rules
explanation : str
recommendation : str
categories : List[str]
contract_type : Optional[str] = None
suggested_language : Optional[str] = None
legal_basis : Optional[str] = None
affected_clauses : Optional[List[str]] = None
def to_dict(self) -> Dict:
"""
Convert to dictionary
"""
return {"protection_id" : self.protection_id,
"protection" : self.protection,
"importance" : self.importance,
"risk_score" : round(self.risk_score, 2),
"explanation" : self.explanation,
"recommendation" : self.recommendation,
"categories" : self.categories,
"contract_type" : self.contract_type,
"suggested_language" : self.suggested_language,
"legal_basis" : self.legal_basis,
"affected_clauses" : self.affected_clauses or [],
}
@dataclass
class ContractCategory:
"""
Contract classification result with metadata
"""
category : str
subcategory : Optional[str]
confidence : float
reasoning : List[str]
detected_keywords : List[str]
alternative_categories : List[Tuple[str, float]] = None # (category, confidence) pairs
def to_dict(self) -> Dict[str, Any]:
"""
Convert to dictionary for serialization
"""
return {"category" : self.category,
"subcategory" : self.subcategory,
"confidence" : round(self.confidence, 3),
"reasoning" : self.reasoning,
"detected_keywords" : self.detected_keywords,
"alternative_categories" : [{"category": cat, "confidence": round(conf, 3)} for cat, conf in (self.alternative_categories or [])]
}
@dataclass
class RiskBreakdownItem:
"""
Individual risk category breakdown
"""
category : str
score : int # 0-100
summary : str
findings : List[str] = field(default_factory = list)
def to_dict(self) -> Dict[str, Any]:
"""
Convert to dictionary
"""
return {"category" : self.category,
"score" : self.score,
"summary" : self.summary,
"findings" : self.findings,
}
@dataclass
class RiskScore:
"""
Comprehensive risk score with detailed breakdown
"""
overall_score : int # 0-100
risk_level : str # "CRITICAL", "HIGH", "MEDIUM", "LOW"
category_scores : Dict[str, int]
risk_factors : List[str]
detailed_findings : Dict[str, List[str]]
benchmark_comparison : Dict[str, str]
risk_breakdown : List[RiskBreakdownItem]
contract_type : str
unfavorable_terms : List[Dict]
missing_protections : List[Dict]
high_risk_clauses : List[Dict] = field(default_factory = list)
explanation : str = ""
recommendations : List[str] = field(default_factory = list)
analysis_timestamp : Optional[str] = None
contract_subtype : Optional[str] = None
contract_metadata : Optional[Dict[str, Any]] = field(default_factory = dict)
def to_dict(self) -> Dict[str, Any]:
"""
Convert to dictionary for serialization
"""
return {"overall_score" : self.overall_score,
"risk_level" : self.risk_level,
"category_scores" : self.category_scores,
"risk_factors" : self.risk_factors,
"detailed_findings" : self.detailed_findings,
"benchmark_comparison" : self.benchmark_comparison,
"risk_breakdown" : [item.to_dict() for item in self.risk_breakdown],
"contract_type" : self.contract_type,
"unfavorable_terms" : self.unfavorable_terms,
"missing_protections" : self.missing_protections,
"high_risk_clauses" : self.high_risk_clauses,
"explanation" : self.explanation,
"recommendations" : self.recommendations,
"analysis_timestamp" : self.analysis_timestamp,
"contract_subtype" : self.contract_subtype,
"contract_metadata" : self.contract_metadata,
}
@dataclass
class RiskInterpretation:
"""
Comprehensive risk interpretation with LLM-enhanced explanations
"""
overall_risk_explanation : str
key_concerns : List[str]
negotiation_strategy : str
market_comparison : str
clause_interpretations : List[ClauseInterpretation]
def to_dict(self) -> Dict[str, Any]:
"""
Convert to dictionary
"""
return {"overall_risk_explanation" : self.overall_risk_explanation,
"key_concerns" : self.key_concerns,
"negotiation_strategy" : self.negotiation_strategy,
"market_comparison" : self.market_comparison,
"clause_interpretations" : [ci.to_dict() for ci in self.clause_interpretations],
}
class NegotiationTactic(Enum):
"""
Types of negotiation tactics
"""
REMOVAL = "removal"
MODIFICATION = "modification"
ADDITION = "addition"
LIMITATION = "limitation"
MUTUALIZATION = "mutualization"
CLARIFICATION = "clarification"
@dataclass
class NegotiationPoint:
"""
Negotiation talking point with strategic context
"""
priority : int # 1 = highest, 5 = lowest
category : str
issue : str
current_language : str
proposed_language : str
rationale : str
tactic : NegotiationTactic
fallback_position : Optional[str] = None
estimated_difficulty : str = "medium" # "easy", "medium", "hard"
legal_basis : Optional[str] = None
business_impact : Optional[str] = None
counterparty_concerns : Optional[str] = None
timing_suggestion : Optional[str] = None
bargaining_chips : List[str] = None
def to_dict(self) -> Dict[str, Any]:
"""
Convert to dictionary
"""
return {"priority" : self.priority,
"category" : self.category,
"issue" : self.issue,
"current_language" : self.current_language,
"proposed_language" : self.proposed_language,
"rationale" : self.rationale,
"tactic" : self.tactic.value,
"fallback_position" : self.fallback_position,
"estimated_difficulty" : self.estimated_difficulty,
"legal_basis" : self.legal_basis,
"business_impact" : self.business_impact,
"counterparty_concerns" : self.counterparty_concerns,
"timing_suggestion" : self.timing_suggestion,
"bargaining_chips" : self.bargaining_chips or [],
}
@dataclass
class NegotiationPlaybook:
"""
Comprehensive negotiation strategy
"""
overall_strategy : str
critical_points : List[NegotiationPoint]
walk_away_items : List[str]
concession_items : List[str]
timing_guidance : str
risk_mitigation_plan : str
def to_dict(self) -> Dict[str, Any]:
"""
Convert to dictionary
"""
return {"overall_strategy" : self.overall_strategy,
"critical_points" : [point.to_dict() for point in self.critical_points],
"walk_away_items" : self.walk_away_items,
"concession_items" : self.concession_items,
"timing_guidance" : self.timing_guidance,
"risk_mitigation_plan" : self.risk_mitigation_plan,
}
@dataclass
class SummaryContext:
"""
Context data for comprehensive summary generation
"""
contract_type : str
risk_score : int
risk_level : str
category_scores : Dict[str, int]
unfavorable_terms : List[Dict]
missing_protections : List[Dict]
clauses : List
key_findings : List[str]
risk_interpretation : Optional[RiskInterpretation] = None
negotiation_playbook : Optional[NegotiationPlaybook] = None
contract_text_preview : Optional[str] = None
contract_metadata : Optional[Dict[str, Any]] = None
@dataclass
class ModelInfo:
"""
Model metadata and state
"""
name : str
type : str # "legal-bert", "embedding", "tokenizer", "classifier"
status : str # "not_loaded", "loading", "loaded", "error"
model : Optional[Any] = None
tokenizer : Optional[Any] = None
loaded_at : Optional[str] = None
error_message : Optional[str] = None
memory_size_mb : float = 0.0
access_count : int = 0
last_accessed : Optional[str] = None
metadata : Dict[str, Any] = field(default_factory = dict)
def mark_accessed(self):
"""
Update access statistics
"""
self.access_count += 1
# Simple timestamp
self.last_accessed = "now"
def get_age_seconds(self) -> float:
"""
Get seconds since last access (simplified)
"""
return 0.0 if not self.last_accessed else 3600.0 |