tocmo0nlord
70c951a7ef
- fl.timesheet via delegation inheritance on account.analytic.line so billable hours flow through standard Odoo Accounting; duration_hours maps to unit_amount - Fields: case_id, employee_id, is_billable, ai_agent, duration_hours, computed hourly_rate/billable_amount (rate from hr.employee.fl_hourly_rate, else firm default ir.config_parameter fl_timesheet.default_hourly_rate) - _resolve_analytic_account: prefers the case project's analytic account (version-agnostic field lookup), falls back to a cached firm account under any available analytic plan — handles the required account_id on the wrapped line - Add 'analytic' to manifest depends; ACL for fl.timesheet and account.analytic.line (admin + paralegal) so non-admins can post entries - fl.case: timesheet_ids + total_billable_hours/amount + total_ai_audit_hours + currency_id; new Time & Billing tab; Timesheets menu + standalone views - Both AI agents now log non-billable audit entries via sudo() (paralegal + attorney, ai_agent set); logging stays a guarded no-op if creation fails Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
365 lines
18 KiB
Python
365 lines
18 KiB
Python
import json
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import logging
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from odoo import models
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from .fl_ai_engine import CLAUDE_MODEL
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_logger = logging.getLogger(__name__)
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# Candidate library sizes passed to the model (it picks the top 3-5 from these).
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MAX_STATUTE_CANDIDATES = 12
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MAX_CASELAW_CANDIDATES = 12
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ATTORNEY_SYSTEM_PROMPT = (
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"You are a senior Florida family-law attorney assistant for the 11th Judicial "
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"Circuit (Miami-Dade). You provide SUBSTANTIVE strategy support to the legal "
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"team — you are NOT giving legal advice to a litigant. Analyze the full case "
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"record and build on any prior analyses. "
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"Identify the strongest applicable statutes and case law, but you MUST choose "
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"ONLY from the candidate lists provided — never invent a citation. Draft "
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"arguments for the case's primary issues and counterarguments the opposing "
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"party is likely to raise. Surface substantive risks (domestic violence, "
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"hidden assets, income imputation, unrepresented respondent). For child-support "
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"modification, assess whether there is a substantial change of circumstances "
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"under FL 61.30(1)(b). Recommend attorney involvement when domestic violence, "
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"opposing counsel, or high complexity is present. "
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"Respond with a single JSON object only — no prose outside the JSON."
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)
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class FlAttorneyAgent(models.AbstractModel):
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"""
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Attorney AI agent — substantive legal reasoning.
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Fires only on a deliberate user action (button on the case AI tab); never
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runs automatically. Produces a strategy memo stored as an fl.analysis record
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of type 'attorney', links the top statutes/case law from the existing
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library, drafts arguments, and writes a risk narrative. Falls back to a
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rule-based memo when the Claude API is unavailable — never surfaces a raw
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API error to the user.
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"""
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_name = 'fl.attorney.agent'
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_description = 'Attorney AI Agent (substantive)'
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# ──────────────────────────────────────────────────────────────────────
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# Public entry point
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# ──────────────────────────────────────────────────────────────────────
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def generate_strategy_memo(self, case):
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"""Run a full substantive analysis. Returns the fl.analysis memo record."""
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analysis = self.env['fl.analysis'].create({
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'case_id': case.id,
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'analysis_type': 'attorney',
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'state': 'pending',
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'model_used': CLAUDE_MODEL,
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})
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statutes = self._candidate_statutes(case)
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caselaw = self._candidate_caselaw(case)
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ai_used = False
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try:
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context = self._build_context(case, statutes, caselaw)
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result = self.env['fl.ai.engine'].call_claude_json(
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user_content=(
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'Case record:\n' + json.dumps(context, indent=2)
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+ '\n\nProduce the strategy memo now.'
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),
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system=ATTORNEY_SYSTEM_PROMPT,
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max_tokens=3000,
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)
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self._store_memo(case, analysis, result, statutes, caselaw)
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ai_used = True
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except Exception as exc:
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_logger.error("Attorney agent failed for case %s: %s",
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case.id, exc, exc_info=True)
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self._store_fallback(case, analysis, statutes, caselaw, str(exc))
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self._log_ai_time(case, 'Attorney strategy memo', ai_used)
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return analysis
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def _log_ai_time(self, case, note, ai_used):
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"""Log a non-billable AI audit entry. No-op until fl.timesheet exists."""
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if 'fl.timesheet' not in self.env:
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return
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try:
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self.env['fl.timesheet'].sudo().create({
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'case_id': case.id,
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'name': note,
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'is_billable': False,
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'ai_agent': 'attorney',
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'duration_hours': 0.1 if ai_used else 0.02,
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})
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except Exception as exc: # never block on audit logging
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_logger.warning("Attorney AI-time logging skipped for case %s: %s",
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case.id, exc)
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# ──────────────────────────────────────────────────────────────────────
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# Candidate library (grounds the model in real records)
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# ──────────────────────────────────────────────────────────────────────
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def _candidate_statutes(self, case):
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"""Statutes relevant to the case's issue tags + case type."""
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statutes = self.env['fl.paralegal.agent']._cross_reference_statutes(case)
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return statutes[:MAX_STATUTE_CANDIDATES]
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def _candidate_caselaw(self, case):
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"""Case law tagged with any of the case's active issue tags."""
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if not case.issue_tag_ids:
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return self.env['fl.caselaw'].search(
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[('active', '=', True)], order='year desc',
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limit=MAX_CASELAW_CANDIDATES)
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return self.env['fl.caselaw'].search([
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('active', '=', True),
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('issue_tag_ids', 'in', case.issue_tag_ids.ids),
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], limit=MAX_CASELAW_CANDIDATES)
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# ──────────────────────────────────────────────────────────────────────
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# Context
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# ──────────────────────────────────────────────────────────────────────
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def _build_context(self, case, statutes, caselaw):
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pet = case.party_ids.filtered(lambda p: p.role == 'petitioner')[:1]
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resp = case.party_ids.filtered(lambda p: p.role == 'respondent')[:1]
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def _party(party):
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if not party:
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return None
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return {
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'employment_type': party.employment_type,
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'gross_monthly_income': party.gross_monthly_income or 0,
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'net_monthly_income': party.net_monthly_income or 0,
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'effective_monthly_income': party.effective_monthly_income or 0,
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'income_imputed': party.income_imputed,
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'lifestyle_inconsistency': party.lifestyle_inconsistency_flag,
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}
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# Prior completed analyses (the just-created memo is still 'pending',
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# so it is excluded) — lets the agent build on earlier work.
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prior = case.analysis_ids.filtered(
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lambda a: a.state == 'complete'
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).sorted('create_date', reverse=True)[:3]
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return {
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'case_type': case.case_type,
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'stage': case.stage_id.name if case.stage_id else 'unknown',
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'complexity': (
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case.latest_analysis_id.case_complexity
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or self.env['fl.ai.engine']._fallback_complexity(case)
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),
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'issue_tags': case.issue_tag_ids.mapped('name'),
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'petitioner': _party(pet),
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'respondent': _party(resp),
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'respondent_has_counsel': case.respondent_has_counsel,
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'respondent_answered': case.respondent_answered,
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'children': [
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{'age': c.age, 'approaching_emancipation': c.approaching_emancipation}
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for c in case.child_ids if not c.emancipated
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],
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'support': {
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'current_order_total': case.current_order_total or 0,
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'calculated_support': case.calculated_support or 0,
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'support_difference': case.support_difference or 0,
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'support_difference_pct': round(case.support_difference_pct or 0, 1),
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'threshold_met': case.threshold_met,
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'substantial_change_basis': case.substantial_change_basis or None,
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'substantial_change_detail': case.substantial_change_detail or None,
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},
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'timesharing': {
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'petitioner_overnights': case.petitioner_overnights or 0,
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'respondent_overnights': case.respondent_overnights or 0,
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'substantial_timesharing': case.substantial_timesharing_applies,
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},
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'flags': {
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'domestic_violence': case.domestic_violence_flag,
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'dv_injunction_active': case.dv_injunction_active,
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'residency_met': case.residency_requirement_met,
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'fee_waiver_eligible': case.fee_waiver_eligible,
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},
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'prior_analyses': [
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{'date': str(a.analysis_date), 'type': a.analysis_type,
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'summary': a.plain_english_summary or ''}
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for a in prior
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],
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'candidate_statutes': [
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{'name': s.name, 'title': s.title, 'category': s.category}
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for s in statutes
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],
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'candidate_caselaw': [
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{'citation': c.citation, 'holding': (c.holding or '')[:300],
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'favorable_to': c.favorable_to}
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for c in caselaw
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],
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'output_schema': {
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'strategy_memo': 'detailed strategy memo (markdown allowed)',
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'plain_english_summary': '3-5 sentence summary, no jargon',
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'plain_english_summary_es': 'same summary in Spanish',
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'top_statutes': 'list of 3-5 exact statute names from candidate_statutes',
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'top_caselaw': 'list of 3-5 exact citations from candidate_caselaw',
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'petitioner_arguments': 'list of strings',
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'respondent_counterarguments': 'list of strings',
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'procedural_risks': 'list of strings',
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'risk_narrative': 'substantive risk narrative string',
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'substantial_change_detected': 'true/false (modification cases)',
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'substantial_change_narrative': 'string',
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'attorney_referral_flag': 'true/false',
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'attorney_referral_reason': 'string or null',
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'confidence_level': 'high|medium|low',
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'case_complexity': 'simple|moderate|complex',
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},
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}
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# ──────────────────────────────────────────────────────────────────────
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# Store (AI result)
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# ──────────────────────────────────────────────────────────────────────
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def _store_memo(self, case, analysis, result, statutes, caselaw):
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# Resolve the model's picks back to real records (only from candidates)
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picked_statutes = statutes.filtered(
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lambda s: s.name in (result.get('top_statutes') or [])
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) or statutes[:5]
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picked_caselaw = caselaw.filtered(
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lambda c: c.citation in (result.get('top_caselaw') or [])
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) or caselaw[:5]
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attorney_flag = result.get('attorney_referral_flag', False)
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if isinstance(attorney_flag, str):
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attorney_flag = attorney_flag.lower() in ('true', '1', 'yes')
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memo_html = self._memo_to_html(result, picked_statutes, picked_caselaw)
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analysis.write({
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'state': 'complete',
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'strategy_memo': memo_html,
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'plain_english_summary': result.get('plain_english_summary', ''),
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'plain_english_summary_es': result.get('plain_english_summary_es', ''),
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'petitioner_arguments': json.dumps(
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result.get('petitioner_arguments', []), ensure_ascii=False, indent=2),
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'respondent_counterarguments': json.dumps(
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result.get('respondent_counterarguments', []), ensure_ascii=False, indent=2),
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'procedural_risks': json.dumps(
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result.get('procedural_risks', []), ensure_ascii=False, indent=2),
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'risk_narrative': result.get('risk_narrative', ''),
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'attorney_referral_flag': bool(attorney_flag),
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'attorney_referral_reason': result.get('attorney_referral_reason') or '',
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'confidence_level': result.get('confidence_level', 'medium'),
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'case_complexity': result.get('case_complexity', 'moderate'),
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'cited_statute_ids': [(6, 0, picked_statutes.ids)],
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'matched_caselaw_ids': [(6, 0, picked_caselaw.ids)],
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'raw_response': json.dumps(result, ensure_ascii=False, indent=2),
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})
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self._link_and_announce(case, analysis, picked_caselaw, attorney_flag,
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result.get('attorney_referral_reason'))
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# ──────────────────────────────────────────────────────────────────────
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# Store (rule-based fallback — no AI)
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# ──────────────────────────────────────────────────────────────────────
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def _store_fallback(self, case, analysis, statutes, caselaw, error):
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complexity = self.env['fl.ai.engine']._fallback_complexity(case)
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picked_statutes = statutes[:5]
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picked_caselaw = caselaw[:5]
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risks = []
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if case.domestic_violence_flag:
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risks.append('Domestic violence flagged — affects mediation, '
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'timesharing, and safety; attorney strongly advised.')
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if case.respondent_has_counsel:
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risks.append('Respondent has counsel — pro se petitioner is at a '
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'significant disadvantage.')
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if any(p.income_imputed or p.lifestyle_inconsistency_flag
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for p in case.party_ids):
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risks.append('Possible income imputation / lifestyle inconsistency '
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'(FL 61.30(2)(b)).')
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if case.case_type == 'modification' and not case.threshold_met:
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risks.append('Modification threshold (FL 61.30(1)(b)) not currently met.')
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if not case.residency_requirement_met:
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risks.append('Residency requirement (FL 61.021) not yet verified.')
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attorney_flag = bool(
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case.domestic_violence_flag
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or case.respondent_has_counsel
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or complexity == 'complex'
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)
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substantial_change = (
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case.case_type == 'modification' and case.threshold_met
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)
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memo_html = (
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'<p><i>Rule-based strategy memo (Claude API unavailable).</i></p>'
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f'<p><b>Case type:</b> {case.case_type} '
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f'<b>Complexity:</b> {complexity}</p>'
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'<p><b>Applicable statutes:</b> '
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+ (', '.join(picked_statutes.mapped('name')) or '—') + '</p>'
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'<p><b>Relevant case law:</b> '
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+ (', '.join(picked_caselaw.mapped('citation')) or '—') + '</p>'
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'<p><b>Substantial change of circumstances (FL 61.30(1)(b)):</b> '
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+ ('Likely — threshold met.' if substantial_change
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else 'Not established on current figures.') + '</p>'
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'<p><b>Risks:</b></p><ul>'
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+ (''.join(f'<li>{r}</li>' for r in risks) or '<li>None flagged.</li>')
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+ '</ul>'
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)
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analysis.write({
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'state': 'complete',
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'strategy_memo': memo_html,
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'risk_narrative': '\n'.join(risks),
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'plain_english_summary': (
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'Rule-based strategy summary generated without AI. '
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'Review statutes, case law, and risks above.'
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),
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'attorney_referral_flag': attorney_flag,
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'attorney_referral_reason': (
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'; '.join(risks) if attorney_flag else ''
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),
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'confidence_level': 'low',
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'case_complexity': complexity,
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'cited_statute_ids': [(6, 0, picked_statutes.ids)],
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'matched_caselaw_ids': [(6, 0, picked_caselaw.ids)],
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'error_message': error,
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})
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self._link_and_announce(case, analysis, picked_caselaw, attorney_flag,
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analysis.attorney_referral_reason)
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# ──────────────────────────────────────────────────────────────────────
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# Shared finalization
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# ──────────────────────────────────────────────────────────────────────
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def _link_and_announce(self, case, analysis, caselaw, attorney_flag, reason):
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vals = {'attorney_memo_id': analysis.id}
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if caselaw:
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vals['caselaw_ids'] = [(4, c.id) for c in caselaw]
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case.write(vals)
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body = ('<b>⚖️ Attorney Strategy Memo</b><br/>'
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+ (analysis.plain_english_summary or 'Strategy memo generated.'))
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if attorney_flag:
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body += (
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'<br/><br/><b style="color:#dc3545;">⚠️ Attorney involvement '
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'recommended:</b> ' + (reason or 'High complexity / risk.')
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)
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case.message_post(body=body, subtype_xmlid='mail.mt_comment')
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def _memo_to_html(self, result, statutes, caselaw):
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def _list(items):
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return ''.join(f'<li>{i}</li>' for i in (items or [])) or '<li>—</li>'
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memo = (result.get('strategy_memo') or '').replace('\n', '<br/>')
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return (
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f'<div>{memo}</div>'
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'<hr/><p><b>Top statutes:</b> '
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+ (', '.join(statutes.mapped('name')) or '—') + '</p>'
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'<p><b>Top case law:</b> '
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+ (', '.join(caselaw.mapped('citation')) or '—') + '</p>'
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'<p><b>Petitioner arguments:</b></p><ul>'
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+ _list(result.get('petitioner_arguments')) + '</ul>'
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'<p><b>Respondent counterarguments:</b></p><ul>'
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+ _list(result.get('respondent_counterarguments')) + '</ul>'
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'<p><b>Substantial change (FL 61.30(1)(b)):</b> '
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+ (result.get('substantial_change_narrative') or '—') + '</p>'
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)
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