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Merged
AVADSA25 merged 1 commit into from
May 23, 2026
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refactor(bridges): extract shared codec_bridges core (A-19, Audit-A complete) #79

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5 changes: 3 additions & 2 deletions AGENTS.md
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Original file line number Diff line number Diff line change
Expand Up @@ -43,8 +43,9 @@ codec_session.py Session lifecycle
codec_sandbox.py Sandboxed file/shell wrappers
codec_config.py Config + dangerous-pattern detection + _HTTP_BLOCKED
codec_ava_client.py AVA cloud proxy client (Gemini/Claude/GPT routing for paid users)
codec_imessage.py iMessage outbound bridge
codec_telegram.py Telegram outbound bridge
codec_imessage.py iMessage outbound bridge (thin adapter over codec_bridges)
codec_telegram.py Telegram outbound bridge (thin adapter over codec_bridges)
codec_bridges.py Shared outbound-bridge core (A-19): load_dispatch/try_skill, call_llm(channel,…), save_to_memory(channel,…). The "add a channel" surface; process_message stays per-bridge
whisper_server.py Local STT server
routes/agents.py /api/agents/* endpoints (custom agents, crew launcher)
routes/_shared.py notifications.json read/write helpers
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139 changes: 139 additions & 0 deletions codec_bridges.py
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@@ -0,0 +1,139 @@
"""CODEC outbound-bridge shared core (A-19, PR-3F).

The genuinely-identical helpers that `codec_telegram` and `codec_imessage` each
had their own copy of: skill dispatch (`load_dispatch`/`try_skill`), the
canonical bridge LLM call (`call_llm`, persona chosen by channel, via the
canonical `codec_llm.call`), and memory persistence (`save_to_memory`). Each
bridge keeps its OWN `process_message` — those have intentionally drifted
(telegram: audio transcription + Gemini fallback + daily briefing; imessage:
goal tracking + intent classification) and unifying them would risk regressing a
working channel. This module is the seed for an "add a channel" surface
(CLAUDE.md §1: future WhatsApp / Discord).

Inbound stays PWA-only — these helpers are OUTBOUND only.
"""
from __future__ import annotations

import logging
import os
import sqlite3
from datetime import datetime

log = logging.getLogger("codec.bridges")

MEMORY_DB = os.path.expanduser("~/.codec/memory.db")

# Skills that need a terminal / GUI and must not run from a headless bridge.
_SKIP_SKILLS = {"open_terminal", "run_command", "vibe_code", "deep_chat",
"memory_search", "ask_mike_to_build"}

# Per-channel assistant persona (the only thing that differed between the two
# bridges' call_llm). `{now}` is the formatted current date/time.
_PERSONAS = {
"telegram": (
"You are CODEC, a personal AI assistant replying via Telegram. "
"Today is {now}. Be concise and direct. "
"Keep replies under 3 sentences unless more detail is needed. "
"You can use Markdown formatting. Be natural and helpful."
),
"imessage": (
"You are CODEC, a personal AI assistant replying via iMessage. "
"Today is {now}. Be concise — this is a text message conversation. "
"Keep replies under 3 sentences unless more detail is needed. "
"Be natural and conversational, like texting a smart friend."
),
}

# ── Skill dispatch (lazy — codec_dispatch pulls pynput/GUI deps) ──────────────
_dispatch_loaded = False
_check_skill = None
_run_skill = None


def load_dispatch() -> bool:
"""Lazy-load codec_dispatch (handling pynput/GUI import issues). Returns
True if skill dispatch is available."""
global _dispatch_loaded, _check_skill, _run_skill
if _dispatch_loaded:
return _check_skill is not None
_dispatch_loaded = True
try:
from codec_dispatch import check_skill, run_skill
_check_skill = check_skill
_run_skill = run_skill
log.info("Skill dispatch loaded")
return True
except Exception as e:
log.warning(f"Skill dispatch unavailable ({e}) — LLM-only mode")
return False


def try_skill(text):
"""Match a CODEC skill for `text`. Returns (skill_name, result) or
(None, None) — skipping terminal/GUI skills that a bridge can't run."""
if not load_dispatch():
return (None, None)
try:
skill = _check_skill(text)
if skill:
if skill["name"] in _SKIP_SKILLS:
return (None, None)
result = _run_skill(skill, text)
if result:
return (skill["name"], str(result))
except Exception as e:
log.warning(f"Skill error: {e}")
return (None, None)


# ── Canonical bridge LLM call ────────────────────────────────────────────────
def call_llm(channel, text, llm_cfg, conversation_history=None,
system_prompt_override=None):
"""The shared outbound-bridge LLM call. `channel` selects the persona;
routes through codec_llm.call (default never-raise → "" → None for graceful
bridge degradation). `chat_template_kwargs` is filtered out of
`llm_cfg["kwargs"]` so codec_llm's enable_thinking=False is preserved."""
import codec_llm
if system_prompt_override:
sys_prompt = system_prompt_override
else:
now_str = datetime.now().strftime("%A %B %d, %Y at %H:%M")
sys_prompt = _PERSONAS[channel].format(now=now_str)

messages = [{"role": "system", "content": sys_prompt}]
if conversation_history:
messages.extend(conversation_history[-8:])
messages.append({"role": "user", "content": text})

extra = {k: v for k, v in llm_cfg["kwargs"].items() if k != "chat_template_kwargs"}
content = codec_llm.call(
messages, base_url=llm_cfg["base_url"], model=llm_cfg["model"],
api_key=llm_cfg["api_key"], max_tokens=1500, temperature=0.7,
timeout=120, extra_kwargs=extra,
)
return content if content else None


# ── Memory persistence (cross-channel recall via memory.db) ──────────────────
def save_to_memory(channel, conv_id, user_text, assistant_text):
"""Store the exchange in memory.db under session_id `<channel>-<conv_id>`."""
try:
os.makedirs(os.path.dirname(MEMORY_DB), exist_ok=True)
conn = sqlite3.connect(MEMORY_DB)
c = conn.cursor()
c.execute("""
CREATE TABLE IF NOT EXISTS conversations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
session_id TEXT, timestamp TEXT, role TEXT, content TEXT
)
""")
session_id = f"{channel}-{conv_id}"
ts = datetime.now().isoformat()
c.execute("INSERT INTO conversations (session_id, timestamp, role, content) VALUES (?,?,?,?)",
(session_id, ts, "user", user_text[:2000]))
c.execute("INSERT INTO conversations (session_id, timestamp, role, content) VALUES (?,?,?,?)",
(session_id, ts, "assistant", assistant_text[:2000]))
conn.commit()
conn.close()
except Exception as e:
log.debug(f"Memory save error: {e}")
113 changes: 15 additions & 98 deletions codec_imessage.py
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Expand Up @@ -260,80 +260,22 @@ def is_sender_allowed(sender, im_cfg):


# ── CODEC Skill dispatch ────────────────────────────────────────────────────
_dispatch_available = True
_check_skill = None
_run_skill = None

def _load_dispatch():
"""Lazy-load codec_dispatch, handling pynput/GUI dependency issues."""
global _dispatch_available, _check_skill, _run_skill
if _check_skill is not None:
return _dispatch_available
try:
from codec_dispatch import check_skill, run_skill
_check_skill = check_skill
_run_skill = run_skill
return True
except Exception as e:
log.warning(f"Skill dispatch unavailable ({e}) — LLM-only mode")
_dispatch_available = False
return False


def try_skill(text):
"""Try matching a CODEC skill. Returns (skill_name, result) or (None, None)."""
if not _load_dispatch():
return (None, None)
try:
skill = _check_skill(text)
if skill:
# Skip skills that need a terminal/GUI
_SKIP_SKILLS = {"open_terminal", "run_command", "vibe_code", "deep_chat",
"memory_search", "ask_mike_to_build"}
if skill["name"] in _SKIP_SKILLS:
return (None, None)
result = _run_skill(skill, text)
if result:
return (skill["name"], str(result))
except Exception as e:
log.warning(f"Skill error: {e}")
return (None, None)
# A-19 (PR-3F): skill dispatch, the LLM call, and memory persistence are shared
# with codec_telegram via codec_bridges. process_message stays local (the two
# bridges' flows have intentionally drifted — goals/intent here, audio there).
from codec_bridges import try_skill


# ── LLM call ────────────────────────────────────────────────────────────────
def call_llm(text, sender, llm_cfg, conversation_history=None, system_prompt_override=None):
"""Send text to CODEC's LLM and return response."""
if system_prompt_override:
sys_prompt = system_prompt_override
else:
now_str = datetime.now().strftime("%A %B %d, %Y at %H:%M")
sys_prompt = (
f"You are CODEC, a personal AI assistant replying via iMessage. "
f"Today is {now_str}. Be concise — this is a text message conversation. "
f"Keep replies under 3 sentences unless more detail is needed. "
f"Be natural and conversational, like texting a smart friend."
)

messages = [{"role": "system", "content": sys_prompt}]

# Add conversation history for context
if conversation_history:
messages.extend(conversation_history[-8:]) # last 8 exchanges

messages.append({"role": "user", "content": text})

# A-12 (PR-3E-bridges): canonical codec_llm.call. Never-raise -> "" on any
# failure (error/no-choices/timeout/empty); mapped back to the bridge's None
# contract for graceful degradation. codec_llm strips <think>; kwargs are
# passed minus chat_template_kwargs so enable_thinking=False is preserved.
import codec_llm
extra = {k: v for k, v in llm_cfg["kwargs"].items() if k != "chat_template_kwargs"}
content = codec_llm.call(
messages, base_url=llm_cfg["base_url"], model=llm_cfg["model"],
api_key=llm_cfg["api_key"], max_tokens=1500, temperature=0.7,
timeout=120, extra_kwargs=extra,
"""Send text to CODEC's LLM and return response (A-19 PR-3F: shared core in
codec_bridges; `sender` is unused by the LLM call, kept for call-site compat)."""
import codec_bridges
return codec_bridges.call_llm(
"imessage", text, llm_cfg,
conversation_history=conversation_history,
system_prompt_override=system_prompt_override,
)
return content if content else None


# ── Vision (image attachments) ──────────────────────────────────────────────
Expand Down Expand Up @@ -872,35 +814,10 @@ def _extract_goals_from_reply(text, sender):

# ── Save to CODEC memory DB ─────────────────────────────────────────────────
def save_to_memory(sender, user_text, assistant_text):
"""Store the exchange in CODEC's memory.db for cross-channel recall."""
try:
os.makedirs(os.path.dirname(MEMORY_DB), exist_ok=True)
conn = sqlite3.connect(MEMORY_DB)
c = conn.cursor()
# Ensure conversations table exists
c.execute("""
CREATE TABLE IF NOT EXISTS conversations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
session_id TEXT,
timestamp TEXT,
role TEXT,
content TEXT
)
""")
session_id = f"imessage-{sender}"
ts = datetime.now().isoformat()
c.execute(
"INSERT INTO conversations (session_id, timestamp, role, content) VALUES (?,?,?,?)",
(session_id, ts, "user", user_text[:2000]),
)
c.execute(
"INSERT INTO conversations (session_id, timestamp, role, content) VALUES (?,?,?,?)",
(session_id, ts, "assistant", assistant_text[:2000]),
)
conn.commit()
conn.close()
except Exception as e:
log.debug(f"Memory save error: {e}")
"""Store the exchange in memory.db (A-19 PR-3F: shared in codec_bridges;
session_id = "imessage-<sender>")."""
import codec_bridges
return codec_bridges.save_to_memory("imessage", sender, user_text, assistant_text)


# ── Main processing loop ────────────────────────────────────────────────────
Expand Down
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