Spaces:
Paused
Paused
File size: 8,958 Bytes
c9844c4 97f7c7f c9844c4 97f7c7f c9844c4 97f7c7f c9844c4 97f7c7f c9844c4 97f7c7f c9844c4 97f7c7f c9844c4 97f7c7f c9844c4 97f7c7f c9844c4 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 | """
Enhanced GU (Gazzetta Ufficiale) Explainer - AI-powered law explanations with context
Generates professional, detailed explanations of laws with:
- Direct law citations and references
- Historical context
- Vigente status and impact
- Related laws and amendments
"""
import logging
from typing import Optional, Dict, Any
from pathlib import Path
logger = logging.getLogger(__name__)
class GUExplainer:
"""Generate AI-enhanced explanations for Italian laws with citations."""
def __init__(self, llm_router=None):
"""
Initialize explainer with optional LLM router.
Args:
llm_router: LLMRouter instance for generating explanations
"""
self.llm_router = llm_router
self.cache = {}
def generate_professional_explanation(
self,
metadata: Dict[str, Any],
text_excerpt: Optional[str] = None,
max_length: int = 500
) -> str:
"""
Generate a professional explanation for a law with AI context.
Args:
metadata: Document metadata from FAISS (urn, source_title, etc.)
text_excerpt: Optional text excerpt from the actual law
max_length: Max length of explanation
Returns:
Professional explanation string with citations
"""
urn = metadata.get("urn", "unknown")
# Check cache first
if urn in self.cache:
return self.cache[urn]
# Build explanation with available metadata
explanation = self._build_explanation(metadata, text_excerpt)
# Enhance with LLM if available — works with or without text excerpt
if self.llm_router:
explanation = self._enhance_with_llm(
metadata, explanation, text_excerpt or metadata.get("source_title", "")
)
self.cache[urn] = explanation
return explanation
def _build_explanation(
self,
metadata: Dict[str, Any],
text_excerpt: Optional[str] = None
) -> str:
"""Build template explanation from metadata."""
source_title = metadata.get("source_title", "Legge")
urn = metadata.get("urn", "")
enactment_date = metadata.get("enactment_date", "")
validity = metadata.get("validity_status", "unknown")
legal_era = metadata.get("legal_era", "unknown")
article_num = metadata.get("article_number", "")
# Format date
date_str = ""
if enactment_date and len(enactment_date) == 8:
date_str = f"{enactment_date[6:8]}/{enactment_date[4:6]}/{enactment_date[:4]}"
# Build explanation
parts = []
# Title with citation
parts.append(f"**{source_title}**")
if article_num:
parts.append(f"Art. {article_num}")
# Status indicator
status_emoji = "✨" if validity == "in_corso" else "⚠️"
status_text = "in vigore (efectiva)" if validity == "in_corso" else "non in vigore"
parts.append(f"{status_emoji} Stato: {status_text}")
# Era and context
era_map = {
"Fascismo": "Era fascista",
"Repubblica": "Era repubblicana",
"Contemporaneo": "Era contemporanea",
"unknown": "Era indeterminata"
}
era_label = era_map.get(legal_era, legal_era)
parts.append(f"📅 Periodo: {era_label}")
if date_str:
parts.append(f"📌 Data di emanazione: {date_str}")
if urn:
parts.append(f"🔗 URN: `{urn}`")
# Text excerpt (if available)
if text_excerpt:
excerpt = text_excerpt[:200].strip()
if len(text_excerpt) > 200:
excerpt += "..."
parts.append(f"\n**Testo**: \"{excerpt}\"")
return "\n".join(parts)
def _enhance_with_llm(
self,
metadata: Dict[str, Any],
base_explanation: str,
text_excerpt: str
) -> str:
"""Enhance explanation with LLM-generated analysis via LLMRouter."""
if not self.llm_router:
return base_explanation
try:
source_title = metadata.get("source_title", "Legge")
article_num = metadata.get("article_number", "")
validity = metadata.get("validity_status", "")
era = metadata.get("legal_era", "")
urn = metadata.get("urn", "")
system_msg = (
"Sei un esperto giurista italiano. Fornisci analisi legali precise, "
"professionali e accessibili. Rispondi sempre in italiano."
)
user_msg = (
f"Analizza questa norma italiana e fornisci una spiegazione professionale:\n\n"
f"**Titolo**: {source_title}\n"
f"**Articolo**: {article_num}\n"
f"**Era giuridica**: {era}\n"
f"**Stato di vigenza**: {validity}\n"
f"**URN**: {urn}\n\n"
f"**Testo**:\n{text_excerpt[:800]}\n\n"
"Fornisci:\n"
"1. Sintesi dello scopo e dell'impatto della norma (2-3 frasi)\n"
"2. Obblighi o diritti principali stabiliti\n"
"3. Soggetti destinatari\n"
"4. Eventuali modifiche o leggi correlate note\n\n"
"Formato: spiegazione legale professionale in italiano, ~150 parole. "
"Cita articoli specifici ove pertinente."
)
messages = [
{"role": "system", "content": system_msg},
{"role": "user", "content": user_msg},
]
response, _provider = self.llm_router.chat(messages, max_tokens=400)
if response and not response.startswith("❌"):
return f"{base_explanation}\n\n**Analisi AI**:\n{response}"
except Exception as e:
logger.warning(f"LLM enhancement failed: {e}")
return base_explanation
def batch_explain(
self,
metadata_records: list,
text_excerpts: Optional[Dict[str, str]] = None
) -> Dict[str, str]:
"""
Generate explanations for multiple laws.
Args:
metadata_records: List of metadata dicts
text_excerpts: Optional dict mapping URN → text excerpt
Returns:
Dict mapping URN → explanation
"""
explanations = {}
for record in metadata_records:
urn = record.get("urn")
if urn:
text = text_excerpts.get(urn) if text_excerpts else None
explanations[urn] = self.generate_professional_explanation(record, text)
return explanations
def explain_with_context(
self,
metadata: Dict[str, Any],
related_docs: Optional[list] = None,
amendments: Optional[list] = None
) -> Dict[str, Any]:
"""
Generate comprehensive explanation with related laws and amendments.
Args:
metadata: Main document metadata
related_docs: List of related document metadata dicts
amendments: List of amendment records
Returns:
Dict with explanation, related laws, amendments
"""
explanation = self.generate_professional_explanation(metadata)
result = {
"main": explanation,
"related": [],
"amendments": [],
"sources": [
{
"type": "Normattiva",
"url": metadata.get("normattiva_url", ""),
"urn": metadata.get("urn", "")
}
]
}
# Add related laws
if related_docs:
for doc in related_docs[:5]: # Limit to 5
result["related"].append({
"title": doc.get("source_title", ""),
"urn": doc.get("urn", ""),
"status": doc.get("validity_status", "unknown")
})
# Add amendments
if amendments:
for amend in amendments[:3]: # Limit to 3
result["amendments"].append({
"type": amend.get("type", "amendment"),
"date": amend.get("date", ""),
"description": amend.get("description", "")
})
return result
# Default explanations (fallback when LLM unavailable)
DEFAULT_EXPLANATIONS = {
"in_corso": "Legge attualmente in vigore e applicabile.",
"abrogato": "Legge abrogata (annullata/revocata) e non più applicabile.",
"scaduto": "Legge scaduta e non più applicabile.",
"non_vigente": "Legge non in vigore (non ancora applicabile o cessata).",
}
|