diff --git a/activeblue_familylaw/models/__init__.py b/activeblue_familylaw/models/__init__.py
index d5c3a93..6c20caa 100644
--- a/activeblue_familylaw/models/__init__.py
+++ b/activeblue_familylaw/models/__init__.py
@@ -17,3 +17,4 @@ from . import fl_argument
from . import fl_case
from . import fl_conflict_check
from . import fl_paralegal_agent
+from . import fl_attorney_agent
diff --git a/activeblue_familylaw/models/fl_ai_engine.py b/activeblue_familylaw/models/fl_ai_engine.py
index 13393f8..e27d1e1 100644
--- a/activeblue_familylaw/models/fl_ai_engine.py
+++ b/activeblue_familylaw/models/fl_ai_engine.py
@@ -391,9 +391,15 @@ Respond with the JSON object only. No other text."""
# ──────────────────────────────────────────────────────────────────────────
def _call_claude(self, prompt):
+ """Call Claude with a single user prompt; return parsed JSON dict."""
+ return self.call_claude_json(prompt)
+
+ def call_claude_json(self, user_content, system=None, max_tokens=2048):
"""
- Call Claude API and return parsed JSON dict.
- Raises RuntimeError on connection error or JSON parse failure.
+ Shared Claude API entry point used by every agent in this module.
+ Sends `user_content` (optionally with a `system` prompt), parses the
+ response as JSON, and returns a dict. Raises RuntimeError on missing
+ library/key, API error, or JSON parse failure.
API key read from ir.config_parameter key 'fl_ai.claude_api_key'.
"""
try:
@@ -410,16 +416,19 @@ Respond with the JSON object only. No other text."""
'Set fl_ai.claude_api_key in Settings → Technical → System Parameters.'
)
- _logger.info("FL AI Engine: calling Claude API (model=%s)", CLAUDE_MODEL)
+ _logger.info("FL AI: calling Claude API (model=%s)", CLAUDE_MODEL)
client = anthropic.Anthropic(api_key=api_key)
+ create_kwargs = {
+ 'model': CLAUDE_MODEL,
+ 'max_tokens': max_tokens,
+ 'messages': [{'role': 'user', 'content': user_content}],
+ }
+ if system:
+ create_kwargs['system'] = system
try:
- message = client.messages.create(
- model=CLAUDE_MODEL,
- max_tokens=2048,
- messages=[{'role': 'user', 'content': prompt}],
- )
+ message = client.messages.create(**create_kwargs)
except anthropic.RateLimitError as exc:
raise RuntimeError(f'Claude API rate limit exceeded: {exc}') from exc
except anthropic.APIConnectionError as exc:
@@ -427,10 +436,12 @@ Respond with the JSON object only. No other text."""
except anthropic.APIError as exc:
raise RuntimeError(f'Claude API error: {exc}') from exc
- raw = message.content[0].text.strip()
- _logger.debug("FL AI Engine raw response (first 200 chars): %s", raw[:200])
+ return self._extract_json(message.content[0].text.strip())
+
+ def _extract_json(self, raw):
+ """Strip markdown fences / leading prose and parse the first JSON object."""
+ _logger.debug("FL AI raw response (first 200 chars): %s", raw[:200])
- # Strip markdown code fences if present
if raw.startswith('```'):
parts = raw.split('```')
raw = parts[1] if len(parts) >= 2 else raw
@@ -438,7 +449,6 @@ Respond with the JSON object only. No other text."""
raw = raw[4:]
raw = raw.strip()
- # Extract first JSON object if extra prose leaked through
if raw and raw[0] == '{':
brace_depth = 0
end_idx = 0
@@ -455,7 +465,7 @@ Respond with the JSON object only. No other text."""
try:
return json.loads(raw)
except json.JSONDecodeError as exc:
- _logger.error("FL AI Engine: JSON parse error: %s\nRaw: %s", exc, raw[:500])
+ _logger.error("FL AI: JSON parse error: %s\nRaw: %s", exc, raw[:500])
raise RuntimeError(f"Claude returned invalid JSON: {exc}") from exc
# ──────────────────────────────────────────────────────────────────────────
diff --git a/activeblue_familylaw/models/fl_analysis.py b/activeblue_familylaw/models/fl_analysis.py
index f241047..27dc761 100644
--- a/activeblue_familylaw/models/fl_analysis.py
+++ b/activeblue_familylaw/models/fl_analysis.py
@@ -10,6 +10,10 @@ class FlAnalysis(models.Model):
case_id = fields.Many2one(
'fl.case', ondelete='cascade', index=True
)
+ analysis_type = fields.Selection([
+ ('engine', 'AI Engine Analysis'),
+ ('attorney', 'Attorney Strategy Memo'),
+ ], string='Analysis Type', default='engine')
analysis_date = fields.Datetime(
string='Analysis Date',
default=fields.Datetime.now
@@ -36,6 +40,23 @@ class FlAnalysis(models.Model):
help='Resumen en español — sin jerga legal'
)
+ # ── Attorney Strategy Memo ─────────────────────────────────────────────
+ strategy_memo = fields.Html(
+ string='Strategy Memo',
+ help='Substantive strategy memo authored by the Attorney agent.'
+ )
+ risk_narrative = fields.Text(
+ string='Risk Narrative',
+ help='Narrative of substantive risks: DV, hidden assets, income '
+ 'imputation, unrepresented respondent, etc.'
+ )
+ cited_statute_ids = fields.Many2many(
+ 'fl.statute',
+ 'fl_analysis_statute_rel',
+ 'analysis_id', 'statute_id',
+ string='Cited Statutes'
+ )
+
# ── Analysis Detail (Phase 5) ──────────────────────────────────────────
petitioner_arguments = fields.Text(
string='Petitioner Arguments (JSON)'
diff --git a/activeblue_familylaw/models/fl_attorney_agent.py b/activeblue_familylaw/models/fl_attorney_agent.py
new file mode 100644
index 0000000..a07e911
--- /dev/null
+++ b/activeblue_familylaw/models/fl_attorney_agent.py
@@ -0,0 +1,345 @@
+import json
+import logging
+
+from odoo import models
+
+from .fl_ai_engine import CLAUDE_MODEL
+
+_logger = logging.getLogger(__name__)
+
+# Candidate library sizes passed to the model (it picks the top 3-5 from these).
+MAX_STATUTE_CANDIDATES = 12
+MAX_CASELAW_CANDIDATES = 12
+
+ATTORNEY_SYSTEM_PROMPT = (
+ "You are a senior Florida family-law attorney assistant for the 11th Judicial "
+ "Circuit (Miami-Dade). You provide SUBSTANTIVE strategy support to the legal "
+ "team — you are NOT giving legal advice to a litigant. Analyze the full case "
+ "record and build on any prior analyses. "
+ "Identify the strongest applicable statutes and case law, but you MUST choose "
+ "ONLY from the candidate lists provided — never invent a citation. Draft "
+ "arguments for the case's primary issues and counterarguments the opposing "
+ "party is likely to raise. Surface substantive risks (domestic violence, "
+ "hidden assets, income imputation, unrepresented respondent). For child-support "
+ "modification, assess whether there is a substantial change of circumstances "
+ "under FL 61.30(1)(b). Recommend attorney involvement when domestic violence, "
+ "opposing counsel, or high complexity is present. "
+ "Respond with a single JSON object only — no prose outside the JSON."
+)
+
+
+class FlAttorneyAgent(models.AbstractModel):
+ """
+ Attorney AI agent — substantive legal reasoning.
+
+ Fires only on a deliberate user action (button on the case AI tab); never
+ runs automatically. Produces a strategy memo stored as an fl.analysis record
+ of type 'attorney', links the top statutes/case law from the existing
+ library, drafts arguments, and writes a risk narrative. Falls back to a
+ rule-based memo when the Claude API is unavailable — never surfaces a raw
+ API error to the user.
+ """
+ _name = 'fl.attorney.agent'
+ _description = 'Attorney AI Agent (substantive)'
+
+ # ──────────────────────────────────────────────────────────────────────
+ # Public entry point
+ # ──────────────────────────────────────────────────────────────────────
+
+ def generate_strategy_memo(self, case):
+ """Run a full substantive analysis. Returns the fl.analysis memo record."""
+ analysis = self.env['fl.analysis'].create({
+ 'case_id': case.id,
+ 'analysis_type': 'attorney',
+ 'state': 'pending',
+ 'model_used': CLAUDE_MODEL,
+ })
+
+ statutes = self._candidate_statutes(case)
+ caselaw = self._candidate_caselaw(case)
+
+ try:
+ context = self._build_context(case, statutes, caselaw)
+ result = self.env['fl.ai.engine'].call_claude_json(
+ user_content=(
+ 'Case record:\n' + json.dumps(context, indent=2)
+ + '\n\nProduce the strategy memo now.'
+ ),
+ system=ATTORNEY_SYSTEM_PROMPT,
+ max_tokens=3000,
+ )
+ self._store_memo(case, analysis, result, statutes, caselaw)
+ except Exception as exc:
+ _logger.error("Attorney agent failed for case %s: %s",
+ case.id, exc, exc_info=True)
+ self._store_fallback(case, analysis, statutes, caselaw, str(exc))
+
+ return analysis
+
+ # ──────────────────────────────────────────────────────────────────────
+ # Candidate library (grounds the model in real records)
+ # ──────────────────────────────────────────────────────────────────────
+
+ def _candidate_statutes(self, case):
+ """Statutes relevant to the case's issue tags + case type."""
+ statutes = self.env['fl.paralegal.agent']._cross_reference_statutes(case)
+ return statutes[:MAX_STATUTE_CANDIDATES]
+
+ def _candidate_caselaw(self, case):
+ """Case law tagged with any of the case's active issue tags."""
+ if not case.issue_tag_ids:
+ return self.env['fl.caselaw'].search(
+ [('active', '=', True)], order='year desc',
+ limit=MAX_CASELAW_CANDIDATES)
+ return self.env['fl.caselaw'].search([
+ ('active', '=', True),
+ ('issue_tag_ids', 'in', case.issue_tag_ids.ids),
+ ], limit=MAX_CASELAW_CANDIDATES)
+
+ # ──────────────────────────────────────────────────────────────────────
+ # Context
+ # ──────────────────────────────────────────────────────────────────────
+
+ def _build_context(self, case, statutes, caselaw):
+ pet = case.party_ids.filtered(lambda p: p.role == 'petitioner')[:1]
+ resp = case.party_ids.filtered(lambda p: p.role == 'respondent')[:1]
+
+ def _party(party):
+ if not party:
+ return None
+ return {
+ 'employment_type': party.employment_type,
+ 'gross_monthly_income': party.gross_monthly_income or 0,
+ 'net_monthly_income': party.net_monthly_income or 0,
+ 'effective_monthly_income': party.effective_monthly_income or 0,
+ 'income_imputed': party.income_imputed,
+ 'lifestyle_inconsistency': party.lifestyle_inconsistency_flag,
+ }
+
+ # Prior completed analyses (the just-created memo is still 'pending',
+ # so it is excluded) — lets the agent build on earlier work.
+ prior = case.analysis_ids.filtered(
+ lambda a: a.state == 'complete'
+ ).sorted('create_date', reverse=True)[:3]
+
+ return {
+ 'case_type': case.case_type,
+ 'stage': case.stage_id.name if case.stage_id else 'unknown',
+ 'complexity': (
+ case.latest_analysis_id.case_complexity
+ or self.env['fl.ai.engine']._fallback_complexity(case)
+ ),
+ 'issue_tags': case.issue_tag_ids.mapped('name'),
+ 'petitioner': _party(pet),
+ 'respondent': _party(resp),
+ 'respondent_has_counsel': case.respondent_has_counsel,
+ 'respondent_answered': case.respondent_answered,
+ 'children': [
+ {'age': c.age, 'approaching_emancipation': c.approaching_emancipation}
+ for c in case.child_ids if not c.emancipated
+ ],
+ 'support': {
+ 'current_order_total': case.current_order_total or 0,
+ 'calculated_support': case.calculated_support or 0,
+ 'support_difference': case.support_difference or 0,
+ 'support_difference_pct': round(case.support_difference_pct or 0, 1),
+ 'threshold_met': case.threshold_met,
+ 'substantial_change_basis': case.substantial_change_basis or None,
+ 'substantial_change_detail': case.substantial_change_detail or None,
+ },
+ 'timesharing': {
+ 'petitioner_overnights': case.petitioner_overnights or 0,
+ 'respondent_overnights': case.respondent_overnights or 0,
+ 'substantial_timesharing': case.substantial_timesharing_applies,
+ },
+ 'flags': {
+ 'domestic_violence': case.domestic_violence_flag,
+ 'dv_injunction_active': case.dv_injunction_active,
+ 'residency_met': case.residency_requirement_met,
+ 'fee_waiver_eligible': case.fee_waiver_eligible,
+ },
+ 'prior_analyses': [
+ {'date': str(a.analysis_date), 'type': a.analysis_type,
+ 'summary': a.plain_english_summary or ''}
+ for a in prior
+ ],
+ 'candidate_statutes': [
+ {'name': s.name, 'title': s.title, 'category': s.category}
+ for s in statutes
+ ],
+ 'candidate_caselaw': [
+ {'citation': c.citation, 'holding': (c.holding or '')[:300],
+ 'favorable_to': c.favorable_to}
+ for c in caselaw
+ ],
+ 'output_schema': {
+ 'strategy_memo': 'detailed strategy memo (markdown allowed)',
+ 'plain_english_summary': '3-5 sentence summary, no jargon',
+ 'plain_english_summary_es': 'same summary in Spanish',
+ 'top_statutes': 'list of 3-5 exact statute names from candidate_statutes',
+ 'top_caselaw': 'list of 3-5 exact citations from candidate_caselaw',
+ 'petitioner_arguments': 'list of strings',
+ 'respondent_counterarguments': 'list of strings',
+ 'procedural_risks': 'list of strings',
+ 'risk_narrative': 'substantive risk narrative string',
+ 'substantial_change_detected': 'true/false (modification cases)',
+ 'substantial_change_narrative': 'string',
+ 'attorney_referral_flag': 'true/false',
+ 'attorney_referral_reason': 'string or null',
+ 'confidence_level': 'high|medium|low',
+ 'case_complexity': 'simple|moderate|complex',
+ },
+ }
+
+ # ──────────────────────────────────────────────────────────────────────
+ # Store (AI result)
+ # ──────────────────────────────────────────────────────────────────────
+
+ def _store_memo(self, case, analysis, result, statutes, caselaw):
+ # Resolve the model's picks back to real records (only from candidates)
+ picked_statutes = statutes.filtered(
+ lambda s: s.name in (result.get('top_statutes') or [])
+ ) or statutes[:5]
+ picked_caselaw = caselaw.filtered(
+ lambda c: c.citation in (result.get('top_caselaw') or [])
+ ) or caselaw[:5]
+
+ attorney_flag = result.get('attorney_referral_flag', False)
+ if isinstance(attorney_flag, str):
+ attorney_flag = attorney_flag.lower() in ('true', '1', 'yes')
+
+ memo_html = self._memo_to_html(result, picked_statutes, picked_caselaw)
+
+ analysis.write({
+ 'state': 'complete',
+ 'strategy_memo': memo_html,
+ 'plain_english_summary': result.get('plain_english_summary', ''),
+ 'plain_english_summary_es': result.get('plain_english_summary_es', ''),
+ 'petitioner_arguments': json.dumps(
+ result.get('petitioner_arguments', []), ensure_ascii=False, indent=2),
+ 'respondent_counterarguments': json.dumps(
+ result.get('respondent_counterarguments', []), ensure_ascii=False, indent=2),
+ 'procedural_risks': json.dumps(
+ result.get('procedural_risks', []), ensure_ascii=False, indent=2),
+ 'risk_narrative': result.get('risk_narrative', ''),
+ 'attorney_referral_flag': bool(attorney_flag),
+ 'attorney_referral_reason': result.get('attorney_referral_reason') or '',
+ 'confidence_level': result.get('confidence_level', 'medium'),
+ 'case_complexity': result.get('case_complexity', 'moderate'),
+ 'cited_statute_ids': [(6, 0, picked_statutes.ids)],
+ 'matched_caselaw_ids': [(6, 0, picked_caselaw.ids)],
+ 'raw_response': json.dumps(result, ensure_ascii=False, indent=2),
+ })
+
+ self._link_and_announce(case, analysis, picked_caselaw, attorney_flag,
+ result.get('attorney_referral_reason'))
+
+ # ──────────────────────────────────────────────────────────────────────
+ # Store (rule-based fallback — no AI)
+ # ──────────────────────────────────────────────────────────────────────
+
+ def _store_fallback(self, case, analysis, statutes, caselaw, error):
+ complexity = self.env['fl.ai.engine']._fallback_complexity(case)
+ picked_statutes = statutes[:5]
+ picked_caselaw = caselaw[:5]
+
+ risks = []
+ if case.domestic_violence_flag:
+ risks.append('Domestic violence flagged — affects mediation, '
+ 'timesharing, and safety; attorney strongly advised.')
+ if case.respondent_has_counsel:
+ risks.append('Respondent has counsel — pro se petitioner is at a '
+ 'significant disadvantage.')
+ if any(p.income_imputed or p.lifestyle_inconsistency_flag
+ for p in case.party_ids):
+ risks.append('Possible income imputation / lifestyle inconsistency '
+ '(FL 61.30(2)(b)).')
+ if case.case_type == 'modification' and not case.threshold_met:
+ risks.append('Modification threshold (FL 61.30(1)(b)) not currently met.')
+ if not case.residency_requirement_met:
+ risks.append('Residency requirement (FL 61.021) not yet verified.')
+
+ attorney_flag = bool(
+ case.domestic_violence_flag
+ or case.respondent_has_counsel
+ or complexity == 'complex'
+ )
+ substantial_change = (
+ case.case_type == 'modification' and case.threshold_met
+ )
+
+ memo_html = (
+ 'Rule-based strategy memo (Claude API unavailable).
'
+ f'Case type: {case.case_type} '
+ f'Complexity: {complexity}
'
+ 'Applicable statutes: '
+ + (', '.join(picked_statutes.mapped('name')) or '—') + '
'
+ 'Relevant case law: '
+ + (', '.join(picked_caselaw.mapped('citation')) or '—') + '
'
+ 'Substantial change of circumstances (FL 61.30(1)(b)): '
+ + ('Likely — threshold met.' if substantial_change
+ else 'Not established on current figures.') + '
'
+ 'Risks:
'
+ + (''.join(f'{r} ' for r in risks) or 'None flagged. ')
+ + ' '
+ )
+
+ analysis.write({
+ 'state': 'complete',
+ 'strategy_memo': memo_html,
+ 'risk_narrative': '\n'.join(risks),
+ 'plain_english_summary': (
+ 'Rule-based strategy summary generated without AI. '
+ 'Review statutes, case law, and risks above.'
+ ),
+ 'attorney_referral_flag': attorney_flag,
+ 'attorney_referral_reason': (
+ '; '.join(risks) if attorney_flag else ''
+ ),
+ 'confidence_level': 'low',
+ 'case_complexity': complexity,
+ 'cited_statute_ids': [(6, 0, picked_statutes.ids)],
+ 'matched_caselaw_ids': [(6, 0, picked_caselaw.ids)],
+ 'error_message': error,
+ })
+
+ self._link_and_announce(case, analysis, picked_caselaw, attorney_flag,
+ analysis.attorney_referral_reason)
+
+ # ──────────────────────────────────────────────────────────────────────
+ # Shared finalization
+ # ──────────────────────────────────────────────────────────────────────
+
+ def _link_and_announce(self, case, analysis, caselaw, attorney_flag, reason):
+ vals = {'attorney_memo_id': analysis.id}
+ if caselaw:
+ vals['caselaw_ids'] = [(4, c.id) for c in caselaw]
+ case.write(vals)
+
+ body = ('⚖️ Attorney Strategy Memo ⚠️ Attorney involvement '
+ 'recommended: ' + (reason or 'High complexity / risk.')
+ )
+ case.message_post(body=body, subtype_xmlid='mail.mt_comment')
+
+ def _memo_to_html(self, result, statutes, caselaw):
+ def _list(items):
+ return ''.join(f'{i} ' for i in (items or [])) or '— '
+
+ memo = (result.get('strategy_memo') or '').replace('\n', '{memo}
'
+ 'Top statutes: '
+ + (', '.join(statutes.mapped('name')) or '—') + '
'
+ 'Top case law: '
+ + (', '.join(caselaw.mapped('citation')) or '—') + '
'
+ 'Petitioner arguments:
'
+ + _list(result.get('petitioner_arguments')) + ' '
+ 'Respondent counterarguments:
'
+ + _list(result.get('respondent_counterarguments')) + ' '
+ 'Substantial change (FL 61.30(1)(b)): '
+ + (result.get('substantial_change_narrative') or '—') + '
'
+ )
diff --git a/activeblue_familylaw/models/fl_case.py b/activeblue_familylaw/models/fl_case.py
index fe92cbc..2f2ab4c 100644
--- a/activeblue_familylaw/models/fl_case.py
+++ b/activeblue_familylaw/models/fl_case.py
@@ -434,6 +434,19 @@ class FlCase(models.Model):
string='Latest Analysis',
compute='_compute_latest_analysis', store=True
)
+ attorney_memo_id = fields.Many2one(
+ 'fl.analysis',
+ string='Attorney Strategy Memo',
+ help='Current strategy memo produced by the Attorney agent.'
+ )
+ attorney_memo_html = fields.Html(
+ string='Strategy Memo',
+ related='attorney_memo_id.strategy_memo'
+ )
+ attorney_risk_narrative = fields.Text(
+ string='Risk Narrative',
+ related='attorney_memo_id.risk_narrative'
+ )
attorney_referral_flag = fields.Boolean(
string='Attorney Referral Recommended',
compute='_compute_attorney_referral_flag', store=True
@@ -1159,3 +1172,15 @@ class FlCase(models.Model):
'sticky': False,
},
}
+
+ def action_run_attorney_agent(self):
+ self.ensure_one()
+ memo = self.env['fl.attorney.agent'].generate_strategy_memo(self)
+ return {
+ 'type': 'ir.actions.act_window',
+ 'name': 'Attorney Strategy Memo',
+ 'res_model': 'fl.analysis',
+ 'res_id': memo.id,
+ 'view_mode': 'form',
+ 'target': 'current',
+ }
diff --git a/activeblue_familylaw/views/fl_analysis_views.xml b/activeblue_familylaw/views/fl_analysis_views.xml
index aa6cd38..5f62f63 100644
--- a/activeblue_familylaw/views/fl_analysis_views.xml
+++ b/activeblue_familylaw/views/fl_analysis_views.xml
@@ -8,6 +8,7 @@
⚠️ ATTORNEY REFERRAL RECOMMENDED