commit 4bf72b9616ed53e0e084ac58053a2ddf5717350a
Author: tocmo0nlord <tocmo0nlord@192.168.1.63>
Date:   Tue Jun 23 20:45:56 2026 +0000

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+# AVC Phone Agent — Project Specification
+> Claude Code authoritative reference. All architecture, security, and build decisions live here.
+> Repo: `git.activeblue.net/tocmo0nlord/avc-phone-agent`
+> Last updated: 2026-06-23 | Active Blue LLC
+
+---
+
+## Project Overview
+
+**Name:** AVC Phone Agent
+**Owner:** Active Blue LLC
+**Client:** Advanced Vision Care (AVC) — multi-location ophthalmology/optometry practice (FL + TX)
+**Agent name:** AVA (Advanced Vision Assistant)
+**Purpose:** Automated AI phone agent that answers patient calls, books tentative appointments
+into Odoo CRM with call recordings and transcripts attached, and self-improves via
+Claude-powered transcript monitoring and a fine-tuning feedback loop.
+
+---
+
+## Existing Codebase — What to Keep, What to Change
+
+The previous build at `/home/tocmo0nlord/avc-phone/` is a working foundation.
+**Do not rewrite what works.** Apply only the changes documented in this section.
+
+### Files and their status
+
+| File | Status | Action |
+|------|--------|--------|
+| `bot.py` | Keep with one change | Swap Whisper STT for Deepgram Nova-2 |
+| `server.py` | Keep with one change | Swap Auth Token for API Key Secret |
+| `practice.py` | Keep as-is | No changes |
+| `extract.py` | Keep as-is | No changes |
+| `odoo_client.py` | Keep as-is | Already uses API key auth correctly |
+
+### What is already solved — do not touch
+
+**`EndCallProcessor` in `bot.py`** — AVC-side call termination is fully implemented.
+Watches LLM text stream for closing keywords ("goodbye"), waits for TTS to finish via
+`BotStoppedSpeakingFrame`, then pushes `EndTaskFrame` upstream. `TwilioFrameSerializer`
+with `auto_hang_up` drops the carrier leg. This is correct. Zero changes.
+
+**Mulaw 8kHz ↔ 16kHz conversion** — handled internally by `TwilioFrameSerializer`.
+`PIPELINE_SAMPLE_RATE = 16000`, `WIRE_SAMPLE_RATE = 8000` are already set correctly.
+No custom audio module needed.
+
+**VAD tuned for telephony** — `confidence=0.5`, `min_volume=0.3` already loosened from
+desktop defaults. These settings directly address the repeat-yourself problem on the
+VAD side.
+
+**Capacity gating** — `MAX_CONCURRENT_CALLS=2` with atomic slot reservation in
+`server.py` prevents GPU thrashing. Keep it.
+
+**`AudioHeartbeat`** — diagnostic processor that distinguishes VAD failure from
+transport stall. Keep it.
+
+**Post-call extraction (`extract.py`)** — single JSON-mode completion after call ends.
+Correctly uses `format: json`, uses verified Twilio caller-ID instead of trusting model
+output, falls back to JSONL if Odoo is unreachable. Keep it.
+
+**Odoo integration (`odoo_client.py`)** — already uses `ODOO_API_KEY` for XML-RPC auth,
+not password. Correct pattern. No changes.
+
+---
+
+## Change 1 — Swap Whisper STT for Deepgram Nova-2 (`bot.py`)
+
+**Why:** Whisper buffers audio chunks before transcribing — 1-3 seconds of buffering
+before the LLM sees any input. This is the primary cause of non-reply and the
+repeat-yourself problem. Deepgram Nova-2 via Pipecat's native transport delivers
+end-of-utterance events in under 300ms.
+
+**Remove from `bot.py`:**
+```python
+# Remove this import
+from pipecat.services.whisper.stt import WhisperSTTService
+
+# Remove these env vars
+WHISPER_MODEL = os.environ.get("WHISPER_MODEL", "base")
+WHISPER_DEVICE = os.environ.get("WHISPER_DEVICE", "cuda")
+WHISPER_COMPUTE = os.environ.get("WHISPER_COMPUTE", "float16")
+WHISPER_HOTWORDS = os.environ.get("WHISPER_HOTWORDS", "...")
+
+# Remove the entire HintedWhisperSTTService class
+```
+
+**Add to `bot.py`:**
+```python
+# Add import
+from pipecat.services.deepgram.stt import DeepgramSTTService
+
+# Add env var
+DEEPGRAM_API_KEY = os.environ.get("DEEPGRAM_API_KEY", "")
+
+# Replace stt instantiation in run_agent()
+stt = DeepgramSTTService(
+    api_key=DEEPGRAM_API_KEY,
+    settings=DeepgramSTTService.Settings(
+        model="nova-2",
+        language="en-US",
+        smart_format=True,
+        punctuate=True,
+        interim_results=False,      # final transcripts only — avoids double-firing
+        utterance_end_ms=1000,      # ms of silence before end-of-utterance fires
+    )
+)
+```
+
+**Note on Whisper:** Remove from real-time pipeline only. Whisper large-v3 is retained
+for post-call transcription in Phase 3 (`recording/transcriber.py`) where latency does
+not matter and accuracy is more important than speed.
+
+---
+
+## Change 2 — Swap Auth Token for API Key Secret (`server.py`)
+
+**Why:** `TWILIO_AUTH_TOKEN` is the master credential for the entire Twilio account.
+A leak compromises every Twilio integration. A Standard API Key is scoped to this
+application and revocable independently.
+
+**Credential hierarchy:**
+```
+Twilio Account SID          (not secret on its own)
+├── Auth Token              (master — Twilio console only, rotate quarterly)
+└── API Key: avc-phone-agent-prod   (Standard scope)
+    ├── TWILIO_API_KEY_SID:    SK...
+    └── TWILIO_API_KEY_SECRET: (treat as a password)
+```
+
+**Create the API Key:**
+1. Twilio console → Account → API Keys → Create new Standard key
+2. Name it `avc-phone-agent-prod`
+3. Copy SID (`SK...`) and Secret — Secret is shown once only
+
+**Changes in `server.py`:**
+
+Remove:
+```python
+TWILIO_AUTH_TOKEN = os.environ.get("TWILIO_AUTH_TOKEN")
+```
+
+Add:
+```python
+TWILIO_API_KEY_SID = os.environ.get("TWILIO_API_KEY_SID")
+TWILIO_API_KEY_SECRET = os.environ.get("TWILIO_API_KEY_SECRET")
+```
+
+In `_twilio_signature_ok()`, change the HMAC key:
+```python
+# Before
+digest = hmac.new(TWILIO_AUTH_TOKEN.encode(), payload.encode("utf-8"), hashlib.sha1).digest()
+
+# After
+digest = hmac.new(TWILIO_API_KEY_SECRET.encode(), payload.encode("utf-8"), hashlib.sha1).digest()
+```
+
+Update the guard condition:
+```python
+# Before
+if TWILIO_VALIDATE and TWILIO_AUTH_TOKEN:
+
+# After
+if TWILIO_VALIDATE and TWILIO_API_KEY_SECRET:
+```
+
+Update the warning log:
+```python
+# Before
+elif not TWILIO_AUTH_TOKEN:
+    logger.warning("/voice signature validation DISABLED (no TWILIO_AUTH_TOKEN set)")
+
+# After
+elif not TWILIO_API_KEY_SECRET:
+    logger.warning("/voice signature validation DISABLED (no TWILIO_API_KEY_SECRET set)")
+```
+
+In `TwilioFrameSerializer` instantiation:
+```python
+# Before
+serializer = TwilioFrameSerializer(
+    stream_sid=stream_sid,
+    call_sid=call_sid,
+    account_sid=TWILIO_ACCOUNT_SID,
+    auth_token=TWILIO_AUTH_TOKEN,
+)
+
+# After
+serializer = TwilioFrameSerializer(
+    stream_sid=stream_sid,
+    call_sid=call_sid,
+    account_sid=TWILIO_ACCOUNT_SID,
+    auth_token=TWILIO_API_KEY_SECRET,
+)
+```
+
+**Key rotation procedure:**
+1. Create new Standard API Key in Twilio console
+2. Update `TWILIO_API_KEY_SID` + `TWILIO_API_KEY_SECRET` in `.env`
+3. Restart the service — no rebuild needed
+4. Verify one test call succeeds
+5. Revoke old key in Twilio console
+
+Rotate on: any suspected leak, any team member departure, quarterly as routine.
+
+---
+
+## Change 3 — Update `.env`
+
+**Remove:**
+```env
+TWILIO_AUTH_TOKEN=
+```
+
+**Add:**
+```env
+TWILIO_API_KEY_SID=SK...
+TWILIO_API_KEY_SECRET=
+DEEPGRAM_API_KEY=
+```
+
+**Full `.env` reference:**
+```env
+# Twilio — Auth Token lives in Twilio console only, never on this server
+TWILIO_ACCOUNT_SID=AC...
+TWILIO_API_KEY_SID=SK...
+TWILIO_API_KEY_SECRET=
+TWILIO_PHONE_NUMBER=+1...
+
+# STT: Deepgram (real-time, in-call only)
+DEEPGRAM_API_KEY=
+DEEPGRAM_MODEL=nova-2
+
+# LLM: Ollama
+OLLAMA_URL=http://127.0.0.1:11434/v1
+OLLAMA_MODEL=activeblue-avc:latest
+LLM_PROVIDER=ollama
+LLM_TEMPERATURE=0.3
+LLM_MAX_TOKENS=160
+
+# Anthropic (optional LLM swap + monitoring + synthetic data)
+ANTHROPIC_API_KEY=
+ANTHROPIC_MODEL=claude-sonnet-4-6
+
+# TTS: Kokoro
+KOKORO_VOICE=af_heart
+KOKORO_MODEL_DIR=/home/tocmo0nlord/pipecat-run/models
+
+# Odoo
+ODOO_URL=https://avc.activeblue.net
+ODOO_DB=avc
+ODOO_USER=
+ODOO_API_KEY=
+ODOO_TARGET=crm
+ODOO_STAGE_ID=
+ODOO_TEAM_ID=
+ODOO_USER_ID=
+
+# Server
+PUBLIC_HOST=avc-phone.activeblue.net
+PORT=8200
+BIND_HOST=127.0.0.1
+MAX_CONCURRENT_CALLS=2
+STREAM_TOKEN=
+
+# Call behaviour
+AGENT_NAME=AVA
+ENABLE_TOOLS=
+VAD_CONFIDENCE=0.5
+VAD_MIN_VOLUME=0.3
+VAD_START_SECS=0.2
+VAD_STOP_SECS=0.5
+
+# Monitoring (Phase 4)
+MONITORING_ENABLED=true
+MONITORING_SCHEDULE=0 2 * * *
+
+# A/B model routing (Phase 5 only)
+AB_SPLIT_PERCENT=0
+AB_MODEL_B=
+```
+
+---
+
+## Model Configuration
+
+### Current production model: `activeblue-avc:latest`
+
+| Property | Value | Notes |
+|----------|-------|-------|
+| Base | `llama3.1:8b-instruct-q4_K_M` | Llama 3.1 8B, Q4_K_M quantization |
+| ID | `366a6cc15bb7` | Rebuilt clean 2026-06-23 |
+| Size | 4.9GB | Down from 8.7GB Q8_0 |
+| VRAM usage | ~4.5GB | Leaves 11.5GB headroom on RTX 5080 |
+| Context | 4096 tokens | Sufficient for any phone call |
+| Temperature | 0.3 | Low — maximizes JSON schema compliance |
+| Top-p | 0.9 | Standard |
+| Adapter | None | 44-pair LoRA adapter discarded |
+
+### Modelfile (rebuild reference)
+
+```
+FROM llama3.1:8b-instruct-q4_K_M
+
+PARAMETER stop "<|start_header_id|>"
+PARAMETER stop "<|end_header_id|>"
+PARAMETER stop "<|eot_id|>"
+PARAMETER num_ctx 4096
+PARAMETER temperature 0.3
+PARAMETER top_p 0.9
+
+TEMPLATE "{{- range .Messages }}<|start_header_id|>{{ .Role }}<|end_header_id|>
+{{ .Content }}<|eot_id|>
+{{- end }}<|start_header_id|>assistant<|end_header_id|>
+"
+```
+
+### Why Q4_K_M not Q8_0
+
+Q8_0 consumed ~8.5GB VRAM for weights alone. Under telephony load this caused
+inference latency spikes. Q4_K_M cuts weight VRAM to ~4.5GB with negligible quality
+difference at 8B scale.
+
+### Why no adapter
+
+44-pair LoRA adapter was adding noise not signal. Minimum viable dataset is 200+ pairs
+per intent category. Rebuilt correctly in Phase 5 with 500+ pairs in JSON output format.
+
+### Ollama inventory (current)
+
+```
+activeblue-avc:latest          366a6cc15bb7    4.9GB    production
+llama3.1:8b-instruct-q4_K_M    46e0c10c039e    4.9GB    base
+nomic-embed-text:latest        0a109f422b47    274MB    embeddings
+```
+
+### Phase 5 training note
+
+Axolotl pulls from HuggingFace in safetensors format, not Ollama GGUF:
+```bash
+# Phase 5 only — do not run now
+huggingface-cli download meta-llama/Llama-3.1-8B-Instruct
+# ~16GB on disk, separate from Ollama storage
+```
+
+---
+
+## Build Phases
+
+Claude Code must not scaffold Phase N+1 until Phase N gate is marked complete.
+
+### Phase 1 — Reliable call loop
+
+**Goal:** Every utterance gets a response. Zero silent failures. AVC hangs up — not
+the caller.
+
+- [ ] Apply Change 1: swap Whisper for Deepgram in `bot.py`
+- [ ] Apply Change 2: swap Auth Token for API Key Secret in `server.py`
+- [ ] Apply Change 3: update `.env`
+- [ ] Verify `EndCallProcessor` termination in Twilio call logs (AVC side, not caller)
+- [ ] Verify `AudioHeartbeat` diagnostic logging active
+- [ ] Verify `MAX_CONCURRENT_CALLS` capacity gating works
+
+**Gate — all five must pass:**
+1. 10 consecutive test calls — zero silent non-responses
+2. Zero zombie pipeline instances after call ends (`docker stats`)
+3. Call termination from AVC side confirmed in Twilio call logs
+4. JSON parse failure rate visible in logs — measurable not invisible
+5. Response latency P95 under 3 seconds from STT end-of-utterance to first TTS audio
+
+### Phase 2 — Accuracy (RAG + validation)
+
+- [ ] Populate `rag/data/*.jsonl` with real AVC data (human task — see RAG section)
+- [ ] ChromaDB RAG retriever wired into pipeline
+- [ ] Response validator: JSON schema + factual cross-check + PHI leak scan
+- [ ] Keyword blocklist (uncertainty phrases → handoff)
+- [ ] Intent classifier routing
+- [ ] Turn counter: max 3 failed turns before forced handoff + termination
+
+**Gate:** 20 manual test calls, zero hallucinations on AVC-specific facts
+
+### Phase 3 — Booking
+
+- [ ] Real-time calendar availability check (`odoo/calendar.py`)
+- [ ] Whisper large-v3 post-call transcription (`recording/transcriber.py`)
+- [ ] Recording + transcript attached to Odoo lead chatter
+- [ ] Staff review flow confirmed in Odoo
+
+**Gate:** Staff receives, reviews, and confirms a lead end-to-end
+
+### Phase 4 — Monitoring
+
+- [ ] Transcript index (`recordings/index.jsonl`)
+- [ ] Claude monitoring job
+- [ ] Dashboard: toggle, alert queue, one-click apply, playback, quality tagging
+
+**Gate:** First monitoring run produces actionable suggestions
+
+### Phase 5 — Fine-tuning
+
+- [ ] Pull HuggingFace base (see model section)
+- [ ] Synthetic data generation via Claude API in JSON output format
+- [ ] Real call exporter using staff quality tags
+- [ ] Axolotl QLoRA on RTX 5080
+- [ ] Model registry + versioning + A/B routing
+
+**Gate:** New model outperforms baseline over 50+ calls
+
+---
+
+## Repository Structure
+
+```
+avc-phone-agent/
+├── CLAUDE.md                          ← this file
+├── README.md
+├── .env                               ← never committed
+├── .env.example
+├── .gitignore                         ← includes .env, recordings/, *.gguf
+│
+├── bot.py                             ← Pipecat pipeline (Phase 1 changes here)
+├── server.py                          ← Twilio webhook server (Phase 1 changes here)
+├── practice.py                        ← AVC facts + Odoo persistence
+├── extract.py                         ← post-call appointment extraction
+├── odoo_client.py                     ← Odoo XML-RPC client
+│
+├── rag/                               ← Phase 2
+│   ├── store.py
+│   ├── loader.py
+│   ├── retriever.py
+│   └── data/
+│       ├── avc_locations.jsonl
+│       ├── avc_providers.jsonl
+│       ├── avc_services.jsonl
+│       ├── avc_hours.jsonl
+│       ├── avc_insurance.jsonl
+│       └── avc_faqs.jsonl
+│
+├── recording/                         ← Phase 3
+│   ├── transcriber.py                 ← Whisper large-v3 post-call only
+│   └── storage.py
+│
+├── monitoring/                        ← Phase 4
+│   ├── monitor.py
+│   ├── analyzer.py
+│   ├── diff_engine.py
+│   ├── scheduler.py
+│   └── dashboard/
+│       ├── app.py
+│       └── static/
+│
+├── training/                          ← Phase 5 stub
+│   └── README.md
+│
+├── tests/
+│   ├── test_bot.py
+│   ├── test_server.py
+│   ├── test_odoo_client.py
+│   ├── test_extract.py
+│   └── fixtures/
+│       └── sample_transcripts.jsonl
+│
+├── scripts/
+│   ├── deploy.sh
+│   └── smoke_test.sh
+│
+├── avc-phone.service                  ← existing systemd unit
+└── traefik-avc-phone.yml              ← existing Traefik config
+```
+
+---
+
+## Infrastructure
+
+| Component | Host | Address | Notes |
+|-----------|------|---------|-------|
+| Pipecat pipeline | `miaai` | `10.10.1.221` | Python async, systemd |
+| Ollama LLM | `miaai` | `http://127.0.0.1:11434/v1` | `activeblue-avc:latest` |
+| ChromaDB (Phase 2) | `miaai` | `http://10.10.1.221:8001` | Docker volume |
+| Twilio webhook | `miaai` | `https://avc-phone.activeblue.net` | Traefik + Let's Encrypt |
+| Monitoring dashboard | `miaai` | `https://avc-monitor.activeblue.net` | internal only |
+| Odoo CRM | — | `https://avc.activeblue.net` | XML-RPC, db: `avc` |
+| Recordings | `miaai` | `/home/tocmo0nlord/avc-phone/recordings/` | local only |
+| Gitea | — | `https://git.activeblue.net` | user: `tocmo0nlord` |
+
+---
+
+## RAG Store (Phase 2)
+
+**Stack:** ChromaDB + `nomic-embed-text:latest` (already in Ollama)
+**Collection:** `avc_knowledge`
+**Retrieval:** Top-3 chunks per query on caller's current turn only
+
+### JSONL record format
+
+```json
+{
+  "id": "hours-kendall-weekday",
+  "text": "The Kendall location is open Monday through Friday 8:00 AM to 5:00 PM.",
+  "tags": ["hours", "kendall"],
+  "last_updated": "2026-06-23"
+}
+```
+
+### Data files — populated before Phase 2, not before Phase 1
+
+| File | Content |
+|------|---------|
+| `avc_locations.jsonl` | Address, phone, fax, parking per location |
+| `avc_providers.jsonl` | Name, title, specialty, locations, languages |
+| `avc_services.jsonl` | Exam types, procedures |
+| `avc_hours.jsonl` | Hours per location, holiday closures, after-hours |
+| `avc_insurance.jsonl` | Accepted plans per location |
+| `avc_faqs.jsonl` | Approved Q&A pairs |
+
+**Note:** `practice.py` already contains real AVC location and insurance data scraped
+from `advancedvisioncareflorida.com`. Use it as the seed for the JSONL files rather
+than starting from scratch.
+
+---
+
+## Claude Monitoring (Phase 4)
+
+### What it analyzes
+
+- Facts stated by AVA contradicting RAG store
+- System prompt violations
+- Calls that should have been handoffs
+- High failed turn counts — model or prompt signal
+- RAG gaps (AVA said "I don't have that" — should it be added?)
+- Phrasing that caused caller confusion
+
+### Output schema
+
+```json
+{
+  "call_sid": "CA...",
+  "severity": "high",
+  "issue_type": "factual_error",
+  "description": "AVA stated Kendall closes at 6pm. RAG store says 5pm.",
+  "suggested_action": "rag_update",
+  "suggested_change": {
+    "file": "rag/data/avc_hours.jsonl",
+    "record_id": "hours-kendall-weekday",
+    "field": "text",
+    "old": "...open until 6pm...",
+    "new": "...open until 5pm..."
+  }
+}
+```
+
+`suggested_action`: `rag_update` | `prompt_change` | `blocklist_add` | `flag_for_review`
+
+### Dashboard
+
+FastAPI + HTML/JS at `https://avc-monitor.activeblue.net` (internal only).
+
+| Feature | Description |
+|---------|-------------|
+| Enable/disable toggle | Pauses scheduler without redeployment |
+| Alert queue | Suggestions sorted by severity |
+| One-click apply | Applies change, commits via Gitea API |
+| Call playback | Audio + transcript side-by-side |
+| Quality tagging | Staff tags calls from dashboard |
+| Manual trigger | `POST /monitor/run` |
+
+---
+
+## Fine-Tuning Pipeline (Phase 5 — stub)
+
+> Not scaffolded until Phase 4 complete and monitoring has run minimum two weeks.
+> See `training/README.md` — populated at Phase 5 start.
+
+- Synthetic data: Claude API generates Q&A in JSON output format — schema not style
+- Real calls: staff-tagged `"good"` + corrected bad calls
+- Target: 500+ pairs per intent before first Axolotl run
+- QLoRA via Axolotl on RTX 5080, base: HuggingFace `meta-llama/Llama-3.1-8B-Instruct`
+- Versioned Ollama models: `activeblue-avc:vN`
+- A/B routing: promote when new version wins on booking + hallucination rate over 50+ calls
+
+---
+
+## HIPAA and Compliance
+
+- AVA identifies as automated at call start — no exceptions
+- No PHI in ChromaDB — practice information only
+- Recordings on `miaai` only — no cloud storage
+- Odoo API user: minimum permissions, not admin
+- All endpoints HTTPS via Traefik
+- `.env` never committed
+
+---
+
+## Deploy Script (`scripts/deploy.sh`)
+
+```bash
+#!/bin/bash
+set -e
+cd /home/tocmo0nlord/avc-phone
+git pull origin main
+pip install -r requirements.txt --quiet
+systemctl restart avc-phone
+systemctl status avc-phone --no-pager
+echo "[deploy] Done."
+```
+
+---
+
+## Development Conventions
+
+- Python 3.13 (matches `miaai` miniconda environment)
+- Async throughout — Pipecat is async-native
+- `loguru` for all logging — already in use, keep consistent
+- Structured log lines for all diagnostic events
+- `python-dotenv` for local dev, env injection in prod
+- Secrets never hardcoded
+- Every module has `if __name__ == "__main__":` for isolated testing
+
+---
+
+## Key Dependencies (current)
+
+```
+pipecat-ai==1.3.0           # installed at /opt/miniconda3
+pipecat-ai[deepgram]        # add for Phase 1 Deepgram swap
+deepgram-sdk                # add for Phase 1
+kokoro-tts                  # already installed
+ollama                      # already installed
+scipy / numpy               # already installed (pipecat deps)
+chromadb                    # add for Phase 2
+sentence-transformers        # add for Phase 2
+anthropic                   # for monitoring + optional LLM swap
+openai-whisper              # retained for post-call transcription only
+fastapi / uvicorn           # already installed
+loguru                      # already installed
+httpx                       # already installed
+```
+
+---
+
+## Open Items
+
+- [ ] Create `avc-phone-agent-prod` Standard API Key in Twilio console
+- [ ] Add `TWILIO_API_KEY_SID` + `TWILIO_API_KEY_SECRET` + `DEEPGRAM_API_KEY` to `.env`
+- [ ] Confirm `ODOO_STAGE_ID`, `ODOO_TEAM_ID`, `ODOO_USER_ID` from live `avc` db
+- [ ] Confirm AVA voice — `af_heart` is current default, confirm with AVC before go-live
+- [ ] Populate `rag/data/*.jsonl` before Phase 2 (seed from `practice.py` data)
+- [ ] Define Odoo confirmed appointment flow: lead → opportunity → calendar event
+- [ ] Staff training on monitoring dashboard quality tagging
+
+---
+
+*Active Blue LLC | git.activeblue.net/tocmo0nlord/avc-phone-agent*