session: charming-dirac

track: Track 1 — RLM Bloodstream Activation

description: Full rewrite of memory_digestion.py from 61-line stub to complete session transcript digestion pipeline. Discovers JSONL/MD/TXT session files in C:\Users\P3\.claude\projects\, computes MD5 dedup hash, extracts 6 entity types via regex (error_fix, decision, tool_use, learning, titan_memory, axiom), writes JSONL KG entities to KNOWLEDGE_GRAPH/entities/, upserts vectors to Qdrant genesis_memories collection (384-dim all-MiniLM-L6-v2), tracks processed sessions in digestion_processed_sessions PostgreSQL table, tracks entities in digestion_kg_entities table.

key_patterns: titan_memory extraction from CLAUDE.md format

key_patterns: CLI: --dry-run --source --max-files --max-age-hours

status: complete


description: New file. On session start: queries Qdrant top-20 semantic results against task string, queries PostgreSQL digestion_kg_entities recent 48h, queries bloodstream_knowledge keyword search, loads Titan Memory from KNOWLEDGE_GRAPH/axioms/ JSONL files, falls back to KG entity files. Formats and writes injected context to data/context_state/injected_context.md and injected_context_manifest.json.

key_patterns: 5-layer context query: Titan→Qdrant→PG→bloodstream→KG files

depends_on:
Elestio Qdrant genesis_memories
Elestio PostgreSQL
KNOWLEDGE_GRAPH/axioms/


track: Track 2 — AIVA Vertical Fleet

description: Structured KB specification for PlumberAIVA vertical. Agent name Jordan. 8 KB partitions: aus_compliance, emergency_protocols, job_types, pricing_guide, booking_flow, after_hours, crm_integrations, review_generation. Urgency levels: LIFE_SAFETY (gas leak→000), CRITICAL (burst pipe→30min), HIGH (blocked drain→24h), STANDARD. GHL webhook payload spec, Telnyx voice options (Eucalyptus), agent handoff targets. Pricing sourced from PRICING_STRUCTURE.md research. Rule 13 compliant.

telnyx_voice: Eucalyptus


description: Structured KB specification for CartTalk ecommerce vertical. Agent name Cleo. 11 KB partitions: product_qa, sizing_fit, stock_availability, shipping_delivery, returns_refunds, exit_intent, product_comparison, automotive_mechanics, escalation, shopify_integration, widget_deployment. Automotive mechanics partition covers fitment by make/model/year, tyre sizing, roadworthy state terminology (VIC/NSW/QLD), OEM vs aftermarket. CartTalk roadmap: Phase 1 JS widget, Phase 2 Shopify App Store, Phase 3 Klaviyo voice follow-up.

agency_markup: $197-$297/mo per store


track: Track 3 — GHL Composable Modules

description: Copy-paste telnyx-ai-agent embed widget with placeholder substitution. Placeholders: BUSINESS_NAME, BUSINESS_PHONE, TELNYX_ASSISTANT_ID, BRAND_COLOR, BUSINESS_TYPE, BOOKING_URL. Features: fixed-position pulse-animation launcher, dismissable prompt bubble (session storage), info card with avatar, telnyx-ai-agent loaded on-demand, graceful fallback to phone number, in-call red button state, GA4 events (aiva_call_started), Telnyx event listeners. Deployment: WordPress Custom HTML, Squarespace Code Injection, Wix Custom Code.

key_patterns:
<telnyx-ai-agent> official component
on-demand script loading
session storage dismiss
GA4 event firing
graceful fallback


description: Composable review request module (distinct from GHL_MODULES/review_generator/ghl_api_deploy.py which handles GHL API setup). PostgreSQL table: review_requests with dedup by MD5(contact_id+location_id+date). Target: 30% click-through rate. SMS templates Rule 13 compliant. Functions: send_review_request(), send_followup_review_requests() (48h no-click check), handle_ghl_webhook(), get_review_stats(). CLI: send, followup, stats, webhook subcommands.

key_patterns:
MD5 dedup by contact+location+date
48h follow-up check
GHL API v2 SMS
Rule 13 voice compliance

depends_on:
Elestio PostgreSQL review_requests
GHL API v2


description: 5-touch multi-channel nurture sequence. Sequence: SMS(0h)→Email(4h)→SMS(24h)→CallTask(48h)→SMS(120h). Templates personalised by business_type: Plumber, Electrician, Builder, default. PostgreSQL state machine: mctb_sequences (state) + mctb_touch_log (audit). Functions: start_sequence(), process_pending_touches() for cron, dispatch_touch(), stop_sequence(), ghl_send_sms(), ghl_send_email(), ghl_create_task(). CLI: start, process, stop, stats subcommands.

channel: sms

channel: email

channel: task

depends_on: Elestio PostgreSQL mctb_sequences mctb_touch_log


track: Track 1C — Bloodstream Loader Update

action: update

description: Updated existing bloodstream_loader.py (481L→797L) to add Research reports ingestion. Added: _chunk_text() splitter (1500-char chunks, 200-char overlap), collect_research_reports() reading 178 files from Research reports/ (MD/TXT/JSONL, skipping ~$ Word temp files, keyword-tagging from filename), upsert_reports_to_qdrant() with all-MiniLM-L6-v2 embeddings, batch embed (64), batch upsert (200), chunk_id dedup against existing Qdrant points. Updated main() to add --source reports option, --skip-qdrant flag, full summary line for Qdrant status. RESEARCH_REPORTS_DIR auto-detects Windows E: drive or /mnt/e/ path.

key_patterns:
overlapping text chunking
keyword tag extraction from filename
MD5 chunk_id for Qdrant dedup
sentence-transformers batch encode
Qdrant scroll for existing dedup check
multi-candidate path detection

depends_on:
Elestio Qdrant genesis_memories
Elestio PostgreSQL
sentence-transformers all-MiniLM-L6-v2


track: ALL TRACKS

description: Systems build session FULLY COMPLETE. 8 deliverables across 3 tracks. All files on E: drive. No SQLite. All storage uses Elestio PostgreSQL/Qdrant/Redis. Australian professional voice (Rule 13 compliant). Syntax validated on all Python files.

deliverables: core/memory_digestion.py (full rewrite 595L)

directories_created: RECEPTIONISTAI/verticals/ GHL/modules/