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Build error
Update utils/legal_prompt_generator.py
Browse files- utils/legal_prompt_generator.py +67 -74
utils/legal_prompt_generator.py
CHANGED
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@@ -2,6 +2,7 @@ import json
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from typing import Dict, List, Optional
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from datetime import datetime
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class LegalPromptGenerator:
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def __init__(self, ontology_path: str = "data/legal_ontology.json"):
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"""Initialize prompt generator with legal ontology."""
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@@ -30,25 +31,24 @@ class LegalPromptGenerator:
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hierarchies[parent].append(jurisdiction_id)
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return hierarchies
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def generate_system_message(
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case_metadata: Optional[Dict] = None) -> str:
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"""Generate enhanced system message using legal context and ontology."""
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-
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# Extract document types and jurisdictions
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doc_types = set(chunk['metadata'].get('type', 'unknown') for chunk in context_chunks)
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jurisdictions = set(chunk['metadata'].get('jurisdiction', 'unknown') for chunk in context_chunks)
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-
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# Get relevant legal concepts from ontology
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relevant_concepts = self._get_relevant_concepts(query, context_chunks)
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-
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# Get related jurisdictions
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related_jurisdictions = self._get_related_jurisdictions(jurisdictions)
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-
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# Build instruction sets based on document types
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instruction_sets = self._get_type_specific_instructions(doc_types)
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-
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# Format the system message
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system_message = f"""You are a specialized legal AI assistant analyzing legal documents with the following context:
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@@ -62,35 +62,35 @@ LEGAL FRAMEWORK:
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RESPONSE GUIDELINES:
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1. Legal Analysis Requirements:
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- Maintain formal legal language and terminology
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- Cite specific sections and precedents when relevant
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- Consider jurisdictional hierarchies and relationships
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- Apply appropriate legal principles based on document type
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2. Document-Specific Instructions:
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{self._format_instructions(instruction_sets)}
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3. Citation and Reference Requirements:
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- Reference specific document sections with clear citations
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- Link analysis to relevant legal concepts and principles
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- Maintain proper legal citation format
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- Include paragraph or page numbers when available
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4. Jurisdictional Considerations:
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- Consider jurisdictional hierarchy and precedence
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- Apply jurisdiction-specific interpretations when relevant
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- Note any cross-jurisdictional implications
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5. Quality Standards:
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- Maintain professional legal terminology
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- Provide balanced analysis considering all relevant factors
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- Structure response in a clear, logical manner
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- Include relevant caveats and limitations
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6. Ontological Integration:
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- Incorporate relevant legal concepts from the ontology
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- Link analysis to established legal principles
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- Consider conceptual relationships and hierarchies
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{self._get_case_specific_instructions(case_metadata) if case_metadata else ""}
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"""
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return system_message
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@@ -106,21 +106,21 @@ CONTEXT:
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{context}
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Please provide a comprehensive legal analysis that:
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1. Addresses the specific question
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2. References relevant document sections
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3. Applies appropriate legal principles
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4. Considers jurisdictional implications
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5. Provides clear citations and references"""
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def _get_relevant_concepts(self, query: str, context_chunks: List[Dict]) -> List[Dict]:
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"""Extract relevant legal concepts from ontology based on query and context."""
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relevant_concepts = []
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combined_text = f"{query} {' '.join(chunk['text'] for chunk in context_chunks)}"
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for concept in self.ontology.get("@graph", []):
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if "rdfs:label" not in concept:
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continue
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label = concept["rdfs:label"].lower()
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if label in combined_text.lower():
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relevant_concepts.append({
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@@ -129,7 +129,7 @@ Please provide a comprehensive legal analysis that:
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"description": concept.get("rdfs:comment", ""),
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"relationships": concept.get("vocab:relatedConcepts", [])
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})
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return relevant_concepts
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def _get_related_jurisdictions(self, jurisdictions: set) -> set:
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@@ -148,46 +148,41 @@ Please provide a comprehensive legal analysis that:
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def _get_type_specific_instructions(self, doc_types: set) -> Dict[str, List[str]]:
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"""Get specific instructions based on document types."""
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instructions = {
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type_instructions = {
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"judgment": [
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"Analyze ratio decidendi and obiter dicta",
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"Consider precedential value",
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"Examine judicial reasoning and principles",
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"Note dissenting opinions if present"
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],
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"legislation": [
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"Focus on statutory interpretation",
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"Consider legislative intent",
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"Note any amendments or repealed sections",
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"Examine definitions and scope"
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],
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"contract": [
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"Analyze contractual terms and conditions",
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"Consider contract formation elements",
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"Examine rights and obligations",
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"Note any breach or performance issues"
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],
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"regulatory": [
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"Focus on compliance requirements",
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"Consider regulatory framework",
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"Examine enforcement mechanisms",
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"Note reporting obligations"
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]
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}
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-
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-
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-
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instructions[doc_type] = type_instructions[doc_type]
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return instructions
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def _format_legal_concepts(self, concepts: List[Dict]) -> str:
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"""Format legal concepts for system message."""
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if not concepts:
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return "No specific legal concepts identified."
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formatted = "Key Legal Concepts:\n"
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for concept in concepts:
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formatted += f"- {concept['concept']}\n"
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@@ -201,7 +196,7 @@ Please provide a comprehensive legal analysis that:
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"""Format type-specific instructions."""
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if not instruction_sets:
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return "Apply general legal analysis principles."
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formatted = ""
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for doc_type, instructions in instruction_sets.items():
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formatted += f"\nFor {doc_type.title()} Documents:\n"
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@@ -212,9 +207,8 @@ Please provide a comprehensive legal analysis that:
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"""Generate case-specific instructions based on metadata."""
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if not case_metadata:
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return ""
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return f"""
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CASE-SPECIFIC CONSIDERATIONS:
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- Case Type: {case_metadata.get('case_type', 'Unknown')}
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- Priority: {case_metadata.get('priority', 'Normal')}
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@@ -223,11 +217,9 @@ CASE-SPECIFIC CONSIDERATIONS:
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- Tags: {', '.join(case_metadata.get('tags', []))}
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"""
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def generate_follow_up_prompt(
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-
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previous_response: str,
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context_chunks: List[Dict]) -> str:
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"""Generate prompt for follow-up questions."""
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return f"""This is a follow-up question to a previous legal inquiry.
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@@ -241,8 +233,9 @@ Follow-up Question:
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{follow_up_query}
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Please provide a response that:
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1. Maintains consistency with the previous analysis
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2. Addresses the specific follow-up inquiry
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3. Builds upon the established legal framework
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4. Provides additional relevant context
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5. References any new relevant documents or principles
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from typing import Dict, List, Optional
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from datetime import datetime
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+
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class LegalPromptGenerator:
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def __init__(self, ontology_path: str = "data/legal_ontology.json"):
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"""Initialize prompt generator with legal ontology."""
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hierarchies[parent].append(jurisdiction_id)
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return hierarchies
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def generate_system_message(
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self, context_chunks: List[Dict], query: str, case_metadata: Optional[Dict] = None
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) -> str:
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"""Generate enhanced system message using legal context and ontology."""
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# Extract document types and jurisdictions
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doc_types = set(chunk['metadata'].get('type', 'unknown') for chunk in context_chunks)
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jurisdictions = set(chunk['metadata'].get('jurisdiction', 'unknown') for chunk in context_chunks)
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# Get relevant legal concepts from ontology
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relevant_concepts = self._get_relevant_concepts(query, context_chunks)
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# Get related jurisdictions
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related_jurisdictions = self._get_related_jurisdictions(jurisdictions)
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# Build instruction sets based on document types
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instruction_sets = self._get_type_specific_instructions(doc_types)
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# Format the system message
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system_message = f"""You are a specialized legal AI assistant analyzing legal documents with the following context:
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RESPONSE GUIDELINES:
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1. Legal Analysis Requirements:
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+
- Maintain formal legal language and terminology.
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| 66 |
+
- Cite specific sections and precedents when relevant.
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| 67 |
+
- Consider jurisdictional hierarchies and relationships.
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+
- Apply appropriate legal principles based on document type.
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2. Document-Specific Instructions:
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{self._format_instructions(instruction_sets)}
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3. Citation and Reference Requirements:
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+
- Reference specific document sections with clear citations.
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+
- Link analysis to relevant legal concepts and principles.
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+
- Maintain proper legal citation format.
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+
- Include paragraph or page numbers when available.
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4. Jurisdictional Considerations:
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+
- Consider jurisdictional hierarchy and precedence.
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- Apply jurisdiction-specific interpretations when relevant.
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+
- Note any cross-jurisdictional implications.
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5. Quality Standards:
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- Maintain professional legal terminology.
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+
- Provide balanced analysis considering all relevant factors.
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+
- Structure response in a clear, logical manner.
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+
- Include relevant caveats and limitations.
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6. Ontological Integration:
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+
- Incorporate relevant legal concepts from the ontology.
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+
- Link analysis to established legal principles.
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- Consider conceptual relationships and hierarchies.
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{self._get_case_specific_instructions(case_metadata) if case_metadata else ""}
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"""
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return system_message
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{context}
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Please provide a comprehensive legal analysis that:
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1. Addresses the specific question.
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2. References relevant document sections.
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3. Applies appropriate legal principles.
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4. Considers jurisdictional implications.
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5. Provides clear citations and references."""
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def _get_relevant_concepts(self, query: str, context_chunks: List[Dict]) -> List[Dict]:
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"""Extract relevant legal concepts from ontology based on query and context."""
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relevant_concepts = []
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combined_text = f"{query} {' '.join(chunk['text'] for chunk in context_chunks)}"
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+
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for concept in self.ontology.get("@graph", []):
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if "rdfs:label" not in concept:
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continue
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label = concept["rdfs:label"].lower()
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if label in combined_text.lower():
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relevant_concepts.append({
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"description": concept.get("rdfs:comment", ""),
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"relationships": concept.get("vocab:relatedConcepts", [])
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})
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return relevant_concepts
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def _get_related_jurisdictions(self, jurisdictions: set) -> set:
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def _get_type_specific_instructions(self, doc_types: set) -> Dict[str, List[str]]:
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"""Get specific instructions based on document types."""
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instructions = {
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"judgment": [
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"Analyze ratio decidendi and obiter dicta.",
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"Consider precedential value.",
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"Examine judicial reasoning and principles.",
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"Note dissenting opinions if present."
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],
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"legislation": [
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"Focus on statutory interpretation.",
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"Consider legislative intent.",
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"Note any amendments or repealed sections.",
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+
"Examine definitions and scope."
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],
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"contract": [
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"Analyze contractual terms and conditions.",
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+
"Consider contract formation elements.",
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+
"Examine rights and obligations.",
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+
"Note any breach or performance issues."
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],
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"regulatory": [
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+
"Focus on compliance requirements.",
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"Consider regulatory framework.",
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"Examine enforcement mechanisms.",
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"Note reporting obligations."
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]
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}
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return {doc_type: instructions.get(doc_type, ["Apply general legal analysis principles."])
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for doc_type in doc_types}
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def _format_legal_concepts(self, concepts: List[Dict]) -> str:
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"""Format legal concepts for system message."""
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if not concepts:
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return "No specific legal concepts identified."
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+
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formatted = "Key Legal Concepts:\n"
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for concept in concepts:
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formatted += f"- {concept['concept']}\n"
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"""Format type-specific instructions."""
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if not instruction_sets:
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return "Apply general legal analysis principles."
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+
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formatted = ""
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for doc_type, instructions in instruction_sets.items():
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formatted += f"\nFor {doc_type.title()} Documents:\n"
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"""Generate case-specific instructions based on metadata."""
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if not case_metadata:
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return ""
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return f"""
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CASE-SPECIFIC CONSIDERATIONS:
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- Case Type: {case_metadata.get('case_type', 'Unknown')}
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- Priority: {case_metadata.get('priority', 'Normal')}
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- Tags: {', '.join(case_metadata.get('tags', []))}
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"""
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def generate_follow_up_prompt(
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self, original_query: str, follow_up_query: str, previous_response: str, context_chunks: List[Dict]
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) -> str:
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"""Generate prompt for follow-up questions."""
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return f"""This is a follow-up question to a previous legal inquiry.
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{follow_up_query}
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Please provide a response that:
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1. Maintains consistency with the previous analysis.
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2. Addresses the specific follow-up inquiry.
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3. Builds upon the established legal framework.
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4. Provides additional relevant context.
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5. References any new relevant documents or principles.
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"""
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