tocmo0nlord
465c049251
- fl.attorney.agent (AbstractModel): manual-only substantive analysis fired from the case AI tab. Builds a full case context (parties, children, financials, issue tags, prior analyses) plus candidate statute/caselaw lists, and asks Claude to author a strategy memo, draft arguments/counterarguments, write a risk narrative, and assess substantial change (FL 61.30(1)(b)) - Grounds output in the real library: the model may only pick statutes/case law from the supplied candidates, which are then resolved back to records and linked (fl.analysis.cited_statute_ids / matched_caselaw_ids, case.caselaw_ids) - Rule-based fallback produces a usable memo (complexity, statutes by category, caselaw by tag, risk flags) when the API is unavailable — never a raw error - fl.analysis: add analysis_type, strategy_memo (Html), risk_narrative, cited_statute_ids; surface them in the analysis views - fl.case: add attorney_memo_id + related memo/risk display; action_run_attorney_agent opens the memo; "Generate Attorney Strategy Memo" button on the AI tab (admin) - Refactor fl_ai_engine: extract shared call_claude_json(system, user) + _extract_json so both agents and the engine share one Claude/JSON path Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
98 lines
3.4 KiB
Python
98 lines
3.4 KiB
Python
from odoo import fields, models
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class FlAnalysis(models.Model):
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"""AI case analysis record. Written by the Claude API engine (fl.ai.engine)."""
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_name = 'fl.analysis'
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_description = 'AI Case Analysis Result'
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_order = 'create_date desc'
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case_id = fields.Many2one(
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'fl.case', ondelete='cascade', index=True
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)
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analysis_type = fields.Selection([
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('engine', 'AI Engine Analysis'),
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('attorney', 'Attorney Strategy Memo'),
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], string='Analysis Type', default='engine')
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analysis_date = fields.Datetime(
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string='Analysis Date',
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default=fields.Datetime.now
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)
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model_used = fields.Char(
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string='AI Model',
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default='claude-sonnet-4-20250514'
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)
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# ── Results (referenced by fl_case related fields) ─────────────────────
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attorney_referral_flag = fields.Boolean(
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string='Attorney Referral Recommended',
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default=False
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)
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attorney_referral_reason = fields.Text(
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string='Attorney Referral Reason'
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)
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plain_english_summary = fields.Text(
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string='Plain English Summary (EN)',
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help='3-5 sentence summary of case analysis — no legal jargon'
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)
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plain_english_summary_es = fields.Text(
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string='Plain English Summary (ES)',
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help='Resumen en español — sin jerga legal'
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)
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# ── Attorney Strategy Memo ─────────────────────────────────────────────
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strategy_memo = fields.Html(
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string='Strategy Memo',
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help='Substantive strategy memo authored by the Attorney agent.'
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)
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risk_narrative = fields.Text(
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string='Risk Narrative',
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help='Narrative of substantive risks: DV, hidden assets, income '
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'imputation, unrepresented respondent, etc.'
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)
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cited_statute_ids = fields.Many2many(
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'fl.statute',
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'fl_analysis_statute_rel',
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'analysis_id', 'statute_id',
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string='Cited Statutes'
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)
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# ── Analysis Detail (Phase 5) ──────────────────────────────────────────
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petitioner_arguments = fields.Text(
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string='Petitioner Arguments (JSON)'
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)
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respondent_counterarguments = fields.Text(
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string='Respondent Counter-Arguments (JSON)'
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)
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procedural_risks = fields.Text(
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string='Procedural Risks (JSON)'
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)
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matched_caselaw_ids = fields.Many2many(
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'fl.caselaw',
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'fl_analysis_caselaw_rel',
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'analysis_id', 'caselaw_id',
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string='Matched Case Law'
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)
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confidence_level = fields.Selection([
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('high', 'High'),
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('medium', 'Medium'),
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('low', 'Low'),
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], string='Confidence Level')
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case_complexity = fields.Selection([
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('simple', 'Simple'),
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('moderate', 'Moderate'),
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('complex', 'Complex'),
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], string='Case Complexity')
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raw_response = fields.Text(
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string='Raw AI Response',
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help='Full JSON response from the Claude API — for debugging'
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)
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error_message = fields.Text(
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string='Error (if analysis failed)'
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)
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state = fields.Selection([
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('pending', 'Pending'),
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('complete', 'Complete'),
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('failed', 'Failed'),
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], string='Status', default='pending')
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