hermes-agent/agent/codex_runtime.py
Soju06 174ad45939 perf(state): apply per-call token accounting on a background single-writer queue
Every API call in the tool loop persisted its token/cost delta by
calling SessionDB.update_token_counts() synchronously on the turn
thread — a BEGIN IMMEDIATE sessions UPDATE plus a session_model_usage
upsert, measured in production at p50 3.3ms / p95 70.4ms per call and
up to 299ms against a cold multi-GB state.db. The tool loop stalls for
that long between calls, N times per multi-tool turn.

SessionDB gains queue_token_counts(): same signature and semantics as
update_token_counts(), but the critical path is a deque append plus a
condvar notify. A lazily started daemon thread applies deltas in
enqueue order through the existing update_token_counts ->
_execute_write path, so the established self._lock / BEGIN IMMEDIATE /
jitter-retry discipline is unchanged. When a backlog forms, adjacent
same-route incremental deltas coalesce into one UPDATE: token and
api-call fields sum, cost fields sum None-preservingly (an all-None
run stays None so COALESCE keeps the stored value), and absolute=True
deltas never merge and act as ordering barriers. Route equality is
required for a merge because those fields feed COALESCE backfill, the
last-non-None-wins status fields, and the per-model usage attribution
key — a merged apply is row-equivalent to sequential applies.

Correctness and durability:

- flush_token_counts() gives read-your-writes to token/cost readers
  (get_session, list_sessions_rich, _get_session_rich_row,
  list_gateway_sessions, InsightsEngine.generate) — a plain attribute
  check when nothing is queued. The writer sets its busy flag before
  popping the queue so the lock-free fast path can never miss an
  in-flight batch.
- update_session_model / update_session_billing_route /
  update_session_meta write the sessions row synchronously, bypassing
  the queue, so they flush it first: a still-queued first-of-session
  delta carries the pre-switch route, and applying it after the switch
  UPDATE would trip the first_accounted_route branch (api_call_count
  == 0 plus a route mismatch) and resurrect the old model/provider.
- AIAgent._persist_session flushes at turn finalize and every
  error-exit persist point; close() stops and drains the writer before
  the WAL checkpoint; an atexit hook (registered on first enqueue,
  unregistered on close so closed instances are not pinned until
  interpreter exit) drains at shutdown. Worst-case crash loss is the
  in-flight call's delta — the same window as the old inline write.
- A flush trusts a live stop-flagged writer (its loop drains before
  exiting) and only drains on the caller's thread when the writer is
  dead or never started, claiming the same busy flag so concurrent
  flushes wait instead of racing an in-flight batch.
- After close() has stopped the writer, queue_token_counts applies the
  delta inline instead of parking it on a queue nothing will drain; a
  closed-connection failure then raises at the call site, which
  already guards for it, exactly like the old synchronous path.
- Writer apply failures are logged and never raise into a turn; the
  writer thread survives and keeps applying.

Call sites switched to the queue: the per-call site in
agent/conversation_loop.py and both codex app-server sites in
agent/codex_runtime.py. In-memory per-turn counters
(agent.session_estimated_cost_usd etc.) stay synchronous, so live turn
displays never see the queue.

Tests: tests/agent/test_async_token_accounting.py (19 tests: enqueue
ordering, absolute-as-barrier, backlog coalescing with exact sums,
coalesced-vs-sequential row equivalence, merge unit rules, None-cost
preservation, read-your-writes, flush vs stop-flagged/concurrent
drains, inline apply after writer stop, close/atexit durability,
_persist_session drain, writer failure isolation);
tests/run_agent/test_token_persistence_non_cli.py updated to the
queue_token_counts contract.
2026-07-28 18:47:54 +05:30

1375 lines
59 KiB
Python

"""Codex API runtime — App Server and Responses-API streaming paths.
Extracted from :class:`AIAgent` to keep the agent loop file focused.
Each function takes the parent ``AIAgent`` as its first argument
(``agent``). AIAgent keeps thin forwarder methods for backward
compatibility.
* ``run_codex_app_server_turn`` — drives one turn through the
``codex_app_server`` subprocess client (used when a Codex CLI install
is the active provider).
* ``run_codex_stream`` — streams a Codex Responses API call (the
``codex_responses`` api_mode).
* ``run_codex_create_stream_fallback`` — recovery path when the
Responses ``stream=True`` initial create fails.
"""
from __future__ import annotations
import json
import logging
import os
import time
from types import SimpleNamespace
from typing import Any, Callable, Dict, List
from agent.stream_single_writer import claim_stream_writer, stream_writer_is_current
logger = logging.getLogger(__name__)
def _coerce_usage_int(value: Any) -> int:
if isinstance(value, bool):
return 0
if isinstance(value, int):
return max(value, 0)
if isinstance(value, float):
return max(int(value), 0)
if isinstance(value, str):
try:
return max(int(value), 0)
except ValueError:
return 0
return 0
def _record_codex_app_server_usage(agent, turn) -> dict[str, Any]:
"""Translate Codex app-server token usage into Hermes accounting.
Codex app-server reports usage via thread/tokenUsage/updated as:
inputTokens, cachedInputTokens, outputTokens, reasoningOutputTokens,
totalTokens.
Hermes' canonical prompt bucket includes uncached input + cached input.
The Codex app-server protocol does not currently expose cache-write tokens,
so that bucket remains zero on this runtime.
Even when Codex omits usage for a turn, Hermes should still count that turn
as one API call for session/status accounting.
"""
agent.session_api_calls += 1
usage = getattr(turn, "token_usage_last", None)
if not isinstance(usage, dict) or not usage:
compressor = getattr(agent, "context_compressor", None)
if (
compressor is not None
and getattr(compressor, "awaiting_real_usage_after_compression", False)
):
# No usage means this turn cannot adjudicate the pending compaction.
# Consume the marker so a later unrelated reading is not charged to
# it and preflight deferral cannot stay latched indefinitely.
compressor.update_from_response({})
if agent._session_db and agent.session_id:
try:
if not agent._session_db_created:
agent._ensure_db_session()
# Enqueued for the SessionDB background writer — keeps the
# per-call accounting write off the turn thread (see
# conversation_loop's queue_token_counts call).
agent._session_db.queue_token_counts(
agent.session_id,
model=agent.model,
billing_provider=agent.provider,
billing_base_url=agent.base_url,
billing_mode="subscription_included",
api_call_count=1,
)
except Exception as exc:
logger.debug(
"Codex app-server api-call persistence failed (session=%s): %s",
agent.session_id, exc,
)
return {}
from agent.usage_pricing import CanonicalUsage, estimate_usage_cost
input_tokens = _coerce_usage_int(usage.get("inputTokens"))
cache_read_tokens = _coerce_usage_int(usage.get("cachedInputTokens"))
output_tokens = _coerce_usage_int(usage.get("outputTokens"))
reasoning_tokens = _coerce_usage_int(usage.get("reasoningOutputTokens"))
reported_total = _coerce_usage_int(usage.get("totalTokens"))
canonical_usage = CanonicalUsage(
input_tokens=input_tokens,
output_tokens=output_tokens,
cache_read_tokens=cache_read_tokens,
cache_write_tokens=0,
reasoning_tokens=reasoning_tokens,
raw_usage=usage,
)
prompt_tokens = canonical_usage.prompt_tokens
completion_tokens = canonical_usage.output_tokens
total_tokens = reported_total or canonical_usage.total_tokens
usage_dict = {
"prompt_tokens": prompt_tokens,
"completion_tokens": completion_tokens,
"total_tokens": total_tokens,
"input_tokens": canonical_usage.input_tokens,
"output_tokens": canonical_usage.output_tokens,
"cache_read_tokens": canonical_usage.cache_read_tokens,
"cache_write_tokens": canonical_usage.cache_write_tokens,
"reasoning_tokens": canonical_usage.reasoning_tokens,
}
compressor = getattr(agent, "context_compressor", None)
if compressor is not None:
try:
compressor.update_from_response(usage_dict)
context_window = getattr(turn, "model_context_window", None)
if isinstance(context_window, int) and context_window > 0:
compressor.context_length = context_window
except Exception:
logger.debug("codex app-server usage update failed", exc_info=True)
agent.session_prompt_tokens += prompt_tokens
agent.session_completion_tokens += completion_tokens
agent.session_total_tokens += total_tokens
agent.session_input_tokens += canonical_usage.input_tokens
agent.session_output_tokens += canonical_usage.output_tokens
agent.session_cache_read_tokens += canonical_usage.cache_read_tokens
agent.session_cache_write_tokens += canonical_usage.cache_write_tokens
agent.session_reasoning_tokens += canonical_usage.reasoning_tokens
cost_result = estimate_usage_cost(
agent.model,
canonical_usage,
provider=agent.provider,
base_url=agent.base_url,
api_key=getattr(agent, "api_key", ""),
)
if cost_result.amount_usd is not None:
agent.session_estimated_cost_usd += float(cost_result.amount_usd)
agent.session_cost_status = cost_result.status
agent.session_cost_source = cost_result.source
if agent._session_db and agent.session_id:
try:
if not agent._session_db_created:
agent._ensure_db_session()
# Enqueued for the SessionDB background writer (see above).
agent._session_db.queue_token_counts(
agent.session_id,
input_tokens=canonical_usage.input_tokens,
output_tokens=canonical_usage.output_tokens,
cache_read_tokens=canonical_usage.cache_read_tokens,
cache_write_tokens=canonical_usage.cache_write_tokens,
reasoning_tokens=canonical_usage.reasoning_tokens,
estimated_cost_usd=float(cost_result.amount_usd)
if cost_result.amount_usd is not None else None,
cost_status=cost_result.status,
cost_source=cost_result.source,
billing_provider=agent.provider,
billing_base_url=agent.base_url,
billing_mode="subscription_included"
if cost_result.status == "included" else None,
model=agent.model,
api_call_count=1,
)
except Exception as exc:
logger.debug(
"Codex app-server token persistence failed (session=%s, tokens=%d): %s",
agent.session_id, total_tokens, exc,
)
return {
**usage_dict,
"last_prompt_tokens": prompt_tokens,
"estimated_cost_usd": float(cost_result.amount_usd)
if cost_result.amount_usd is not None else None,
"cost_status": cost_result.status,
"cost_source": cost_result.source,
}
def _record_codex_app_server_compaction(
agent,
turn,
*,
approx_tokens: int | None = None,
force: bool = False,
) -> bool:
"""Record a Codex-native context compaction boundary in Hermes state.
The app-server owns the compacted thread context, so Hermes should not
rewrite local transcript rows here; state.db records the boundary via the
session event/usage counters while preserving the visible transcript.
"""
if not force and not getattr(turn, "compacted", False):
return False
thread_id = getattr(turn, "thread_id", None) or ""
turn_id = getattr(turn, "turn_id", None) or ""
logger.info(
"codex app-server compaction observed: session=%s thread=%s turn=%s force=%s",
getattr(agent, "session_id", None) or "none",
thread_id,
turn_id,
force,
)
if not force:
try:
from agent.conversation_compression import COMPACTION_STATUS
agent._emit_status(COMPACTION_STATUS)
except Exception:
pass
compressor = getattr(agent, "context_compressor", None)
if compressor is not None:
compressor.compression_count = getattr(
compressor, "compression_count", 0
) + 1
compressor.last_compression_rough_tokens = approx_tokens or 0
# The app server has already completed a real compaction boundary. Its
# usage update (when supplied) is therefore the same real-vs-real
# effectiveness verdict used by the normal compression path.
record_boundary = getattr(
type(compressor), "record_completed_compaction", None
)
if callable(record_boundary):
# Codex owns this summary. A prior Hermes deterministic-fallback
# flag must not leak into the native boundary's quality verdict.
record_boundary(compressor, used_fallback=False)
elif hasattr(compressor, "_verify_compaction_cleared_threshold"):
compressor._verify_compaction_cleared_threshold = True
if not getattr(turn, "token_usage_last", None):
compressor.last_prompt_tokens = -1
compressor.last_completion_tokens = 0
compressor.awaiting_real_usage_after_compression = True
agent._last_compaction_in_place = False
try:
if getattr(agent, "event_callback", None):
agent.event_callback(
"session:compress",
{
"platform": getattr(agent, "platform", None) or "",
"session_id": getattr(agent, "session_id", None) or "",
"old_session_id": "",
"in_place": False,
"compression_count": getattr(
compressor, "compression_count", 0
)
if compressor is not None
else 0,
"runtime": "codex_app_server",
"thread_id": thread_id,
"turn_id": turn_id,
},
)
except Exception:
logger.debug("event_callback error on codex session:compress", exc_info=True)
return True
# ---------------------------------------------------------------------------
# Codex app-server → Hermes UI bridge (#33200)
#
# The codex_app_server runtime hands the entire turn to a subprocess and
# bypasses the normal Hermes tool loop. Without this bridge gateway
# adapters (Discord, Telegram, TUI) never see live tool-progress bubbles
# or interim assistant commentary while codex is working — the user just
# stares at a quiet channel until the final answer lands. The bridge
# translates raw codex JSON-RPC notifications into the same three agent
# callbacks the standard runtime fires:
# - tool_progress_callback("tool.started"|"tool.completed", name, ...)
# - _fire_stream_delta(text) for streaming agentMessage chunks
# - _emit_interim_assistant_message({...}) for completed agentMessages
# ---------------------------------------------------------------------------
# Codex item types that map to a Hermes tool_call in the projector (and
# therefore deserve a tool_progress bubble pair). The projector lives in
# agent/transports/codex_event_projector.py — keep these in sync so the
# tool name shown in the UI matches the name recorded in messages.
# webSearch is codex's built-in web search tool — it has no projector
# entry (codex handles it internally) but still deserves a bubble.
_CODEX_TOOL_ITEM_TYPES = frozenset(
{"commandExecution", "fileChange", "mcpToolCall", "dynamicToolCall", "webSearch"}
)
# Internal MCP server that wraps Hermes' native tools for codex. When
# codex calls back through it, the inner dispatch runs in a SEPARATE
# hermes-tools-mcp-server subprocess that has no access to the parent
# agent's tool_progress_callback — so the inner call can never surface
# its own native progress event. The codex-level mcpToolCall event IS
# the display event for those calls; we strip the mcp.hermes-tools.*
# namespacing and emit the bare tool name (web_search, browser_navigate,
# vision_analyze, ...) since the user thinks of these as Hermes tools,
# not as MCP calls.
_INTERNAL_MCP_SERVER = "hermes-tools"
def _codex_item_to_tool_name(item: dict) -> str:
"""Synthetic Hermes tool name for a codex item. Mirrors
CodexEventProjector so the progress bubble and the projected
tool_calls entry use the same identifier."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
return "exec_command"
if item_type == "fileChange":
return "apply_patch"
if item_type == "mcpToolCall":
server = item.get("server") or "mcp"
tool = item.get("tool") or "unknown"
if server == _INTERNAL_MCP_SERVER:
return tool
return f"mcp.{server}.{tool}"
if item_type == "dynamicToolCall":
return item.get("tool") or "dynamic"
if item_type == "webSearch":
return "web_search"
return item_type or "unknown"
def _codex_item_to_args(item: dict) -> dict:
"""Args dict surfaced to tool_progress_callback("tool.started", ...).
Mirrors the projector's _project_command / _project_file_change /
_project_mcp_tool_call / _project_dynamic_tool_call shapes."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
return {"command": item.get("command") or "",
"cwd": item.get("cwd") or ""}
if item_type == "fileChange":
return {"changes": [
{"kind": (c.get("kind") or {}).get("type") or "update",
"path": c.get("path") or ""}
for c in (item.get("changes") or []) if isinstance(c, dict)
]}
if item_type in {"mcpToolCall", "dynamicToolCall"}:
args = item.get("arguments") or {}
return args if isinstance(args, dict) else {"arguments": args}
if item_type == "webSearch":
return {"query": item.get("query") or ""}
return {}
def _codex_item_to_preview(item: dict) -> Any:
"""Short human-readable preview for the tool.started bubble. Returns
None when no useful preview is available (Hermes' UI tolerates None)."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
cmd = item.get("command") or ""
return cmd[:120] if cmd else None
if item_type == "fileChange":
paths = [c.get("path") for c in (item.get("changes") or [])
if isinstance(c, dict) and c.get("path")]
if not paths:
return None
preview = ", ".join(paths[:3])
if len(paths) > 3:
preview += f", +{len(paths) - 3} more"
return preview
if item_type in {"mcpToolCall", "dynamicToolCall"}:
args = item.get("arguments") or {}
if not isinstance(args, dict) or not args:
return None
try:
return json.dumps(args, ensure_ascii=False)[:120]
except (TypeError, ValueError):
return None
if item_type == "webSearch":
query = item.get("query") or ""
return query[:120] if query else None
return None
def _codex_item_completion_payload(item: dict) -> tuple[str, bool]:
"""Return (result_text, is_error) for a completed codex tool item.
Mirrors the projector's tool-result content so the bubble shows the
same outcome string that ends up in the messages list."""
item_type = item.get("type") or ""
if item_type == "commandExecution":
out = item.get("aggregatedOutput") or ""
exit_code = item.get("exitCode")
is_error = bool(exit_code is not None and exit_code != 0)
if is_error:
out = f"[exit {exit_code}]\n{out}"
return out, is_error
if item_type == "fileChange":
status = item.get("status") or "unknown"
n = len(item.get("changes") or [])
return (
f"apply_patch status={status}, {n} change(s)",
status not in {"completed", "applied", "success"},
)
if item_type == "mcpToolCall":
error = item.get("error")
if error:
return (
f"[error] {json.dumps(error, ensure_ascii=False)[:1000]}",
True,
)
result = item.get("result")
return (
json.dumps(result, ensure_ascii=False)[:4000]
if result is not None else "",
False,
)
if item_type == "dynamicToolCall":
content_items = item.get("contentItems") or []
if isinstance(content_items, list) and content_items:
return (
json.dumps(content_items, ensure_ascii=False)[:4000],
not bool(item.get("success", True)),
)
success = item.get("success", True)
return f"success={success}", not bool(success)
return "", False
def make_codex_app_server_event_bridge(agent) -> Callable[[dict], None]:
"""Build an ``on_event`` callback that wires codex app-server JSON-RPC
notifications into Hermes' gateway UI callbacks.
Returns a single-argument callable suitable for
``CodexAppServerSession(on_event=...)``.
Translation map:
* ``item/started`` for tool-shaped items → ``tool_progress_callback(
"tool.started", name, preview, args)``
* ``item/completed`` for tool-shaped items → ``tool_progress_callback(
"tool.completed", name, None, None, duration=..., is_error=...,
result=...)``
* ``item/agentMessage/delta`` → ``_fire_stream_delta(text)`` so chat
adapters can render the assistant's reply as it streams.
* ``item/reasoning/delta`` → ``_fire_reasoning_delta(text)``
* ``item/completed`` for ``agentMessage`` →
``_emit_interim_assistant_message({"role": "assistant",
"content": text})``. The gateway's ``already_streamed`` check
dedupes against any text the stream-delta callback already
rendered for the same message.
All callback invocations are guarded — a buggy display callback must
not tear down the codex turn loop. Errors are logged at DEBUG so the
notification stream keeps flowing regardless.
"""
# item_id -> (tool_name, args, started_wall_time). Populated on
# item/started and consumed on item/completed so duration is correct
# even when codex doesn't report durationMs.
started: dict[str, tuple[str, dict, float]] = {}
def _stable_call_id(item: dict, name: str) -> str:
"""Deterministic tool_call id mirroring CodexEventProjector, so a
live TUI tool card correlates with the same tool call after the
session is resumed and history is projected."""
from agent.transports.codex_event_projector import _deterministic_call_id
item_id = item.get("id") or ""
item_type = item.get("type") or ""
if item_type == "commandExecution":
return _deterministic_call_id("exec", item_id)
if item_type == "fileChange":
return _deterministic_call_id("apply_patch", item_id)
if item_type == "mcpToolCall":
server = item.get("server") or "mcp"
tool = item.get("tool") or "unknown"
return _deterministic_call_id(f"mcp__{server}__{tool}", item_id)
if item_type == "dynamicToolCall":
tool = item.get("tool") or "unknown"
return _deterministic_call_id(f"dyn_{tool}", item_id)
return _deterministic_call_id(name, item_id)
def _fire_tool_started(item: dict) -> None:
item_id = item.get("id") or ""
name = _codex_item_to_tool_name(item)
args = _codex_item_to_args(item)
if item_id:
started[item_id] = (name, args, time.monotonic())
cb = getattr(agent, "tool_progress_callback", None)
if cb is not None:
try:
cb("tool.started", name, _codex_item_to_preview(item), args)
except Exception:
logger.debug(
"tool_progress_callback raised on tool.started for %s",
name, exc_info=True,
)
# Authoritative stable-ID tool card (TUI / desktop). Fires
# alongside tool_progress so surfaces that render structured tool
# cards (not just progress bubbles) stay correlated with the
# projected history entry after a resume.
start_cb = getattr(agent, "tool_start_callback", None)
if start_cb is not None:
try:
start_cb(_stable_call_id(item, name), name, args)
except Exception:
logger.debug(
"tool_start_callback raised for %s", name, exc_info=True,
)
def _fire_tool_completed(item: dict) -> None:
item_id = item.get("id") or ""
name = _codex_item_to_tool_name(item)
prior = started.pop(item_id, None)
# Prefer codex's own durationMs when present so the bubble shows
# exact tool wall-time; fall back to our started timestamp; fall
# back to None if we never saw an item/started (some codex
# versions only emit completed for fast items).
duration: Any = None
codex_ms = item.get("durationMs")
if isinstance(codex_ms, (int, float)) and codex_ms >= 0:
duration = codex_ms / 1000.0
elif prior is not None:
duration = time.monotonic() - prior[2]
result, is_error = _codex_item_completion_payload(item)
cb = getattr(agent, "tool_progress_callback", None)
if cb is not None:
try:
cb("tool.completed", name, None, None,
duration=duration, is_error=is_error, result=result)
except Exception:
logger.debug(
"tool_progress_callback raised on tool.completed for %s",
name, exc_info=True,
)
complete_cb = getattr(agent, "tool_complete_callback", None)
if complete_cb is not None:
args = prior[1] if prior is not None else _codex_item_to_args(item)
try:
complete_cb(_stable_call_id(item, name), name, args, result)
except Exception:
logger.debug(
"tool_complete_callback raised for %s", name, exc_info=True,
)
def _fire_text_delta(params: dict) -> None:
text = params.get("delta") or params.get("text") or ""
if not isinstance(text, str) or not text:
return
fn = getattr(agent, "_fire_stream_delta", None)
if fn is None:
return
try:
fn(text)
except Exception:
logger.debug("_fire_stream_delta raised", exc_info=True)
def _fire_reasoning_delta(params: dict) -> None:
text = params.get("delta") or params.get("text") or ""
if not isinstance(text, str) or not text:
return
fn = getattr(agent, "_fire_reasoning_delta", None)
if fn is None:
return
try:
fn(text)
except Exception:
logger.debug("_fire_reasoning_delta raised", exc_info=True)
def _fire_agent_message_completed(item: dict) -> None:
text = item.get("text") or ""
if not isinstance(text, str) or not text.strip():
return
# display.show_commentary=false — mid-turn narration stays off the
# visible interim path on this runtime too (same contract as the
# codex_responses commentary channel).
if not getattr(agent, "show_commentary", True):
return
emit = getattr(agent, "_emit_interim_assistant_message", None)
if emit is None:
return
try:
emit({"role": "assistant", "content": text})
except Exception:
logger.debug(
"_emit_interim_assistant_message raised", exc_info=True,
)
def on_event(note: dict) -> None:
if not isinstance(note, dict):
return
method = note.get("method") or ""
params = note.get("params") or {}
if not isinstance(params, dict):
params = {}
if method == "item/agentMessage/delta":
_fire_text_delta(params)
return
if method in {"item/reasoning/delta", "item/reasoning/summaryDelta"}:
_fire_reasoning_delta(params)
return
item = params.get("item")
if not isinstance(item, dict):
return
item_type = item.get("type") or ""
if method == "item/started" and item_type in _CODEX_TOOL_ITEM_TYPES:
_fire_tool_started(item)
return
if method == "item/completed":
if item_type in _CODEX_TOOL_ITEM_TYPES:
_fire_tool_completed(item)
elif item_type == "agentMessage":
_fire_agent_message_completed(item)
return on_event
def run_codex_app_server_turn(
agent,
*,
user_message: str,
original_user_message: Any,
messages: List[Dict[str, Any]],
effective_task_id: str,
should_review_memory: bool = False,
) -> Dict[str, Any]:
"""Codex app-server runtime path. Hands the entire turn to a `codex
app-server` subprocess and projects its events back into Hermes'
messages list so memory/skill review keep working.
Called from run_conversation() when agent.api_mode == "codex_app_server".
Returns the same dict shape as the chat_completions path.
"""
from agent.transports.codex_app_server_session import (
CodexAppServerSession,
_ServerRequestRouting,
)
# Lazy session: one CodexAppServerSession per AIAgent instance.
# Spawned on first turn, reused across turns, closed at AIAgent
# shutdown (see _cleanup hook).
if not hasattr(agent, "_codex_session") or agent._codex_session is None:
from agent.runtime_cwd import resolve_agent_cwd
cwd = getattr(agent, "session_cwd", None) or str(resolve_agent_cwd())
# Approval callback: defer to Hermes' standard prompt flow if a
# CLI thread has installed one. Gateway / cron contexts get the
# codex-side fail-closed default.
try:
from tools.terminal_tool import _get_approval_callback
approval_callback = _get_approval_callback()
except Exception:
approval_callback = None
# Gateway / cron contexts have no UI to surface codex's approval
# requests through, so codex app-server exec / apply_patch requests
# fail closed (silently decline) by default. When the user has
# explicitly opted out of Hermes approvals — via `approvals.mode: off`
# in config, the /yolo session toggle, or --yolo / HERMES_YOLO_MODE —
# honor that and let codex's own sandbox permission profile
# (~/.codex/config.toml) be the policy gate instead of double-gating
# with a missing Hermes UI. Defaults (manual/smart/unset) preserve the
# current fail-closed behavior — this is a no-op for those users.
auto_approve_requests = False
try:
from tools.approval import is_approval_bypass_active
auto_approve_requests = is_approval_bypass_active()
except Exception:
logger.debug(
"codex app-server: approval-bypass lookup failed; "
"keeping fail-closed default",
exc_info=True,
)
# Bridge codex JSON-RPC notifications (item/started, item/completed,
# item/agentMessage/delta, ...) into Hermes' gateway UI callbacks
# (tool_progress_callback, _fire_stream_delta,
# _emit_interim_assistant_message). Without this, Discord/Telegram
# users see no live tool-progress or interim commentary while
# codex_app_server is running — only the final answer (#33200).
# Supersedes the narrower item/started-only bridge from #38835.
agent._codex_session = CodexAppServerSession(
cwd=cwd,
approval_callback=approval_callback,
request_routing=_ServerRequestRouting(
auto_approve_exec=auto_approve_requests,
auto_approve_apply_patch=auto_approve_requests,
),
on_event=make_codex_app_server_event_bridge(agent),
)
# NOTE: the user message is ALREADY appended to messages by the
# standard run_conversation() flow (line ~11823) before the early
# return reaches us. Do NOT append again — that would duplicate.
try:
turn = agent._codex_session.run_turn(user_input=user_message)
except Exception as exc:
logger.exception("codex app-server turn failed")
# Crash → unconditionally drop the session so the next turn
# respawns from scratch instead of reusing a dead client.
try:
agent._codex_session.close()
except Exception:
pass
agent._codex_session = None
_user_interrupted = bool(
getattr(agent, "_interrupt_requested", False)
)
_interrupt_message = (
getattr(agent, "_interrupt_message", None)
if _user_interrupted
else None
)
if _user_interrupted:
agent.clear_interrupt()
return {
"final_response": (
f"Codex app-server turn failed: {exc}. "
f"Fall back to default runtime with `/codex-runtime auto`."
),
"messages": messages,
"api_calls": 0,
"completed": False,
"partial": True,
"interrupted": _user_interrupted,
**(
{"interrupt_message": _interrupt_message}
if _interrupt_message
else {}
),
"error": str(exc),
}
# This runtime bypasses the normal conversation-loop finalizer. Mirror its
# interrupt handoff/cleanup so a hard stop cannot poison the next turn and a
# message-bearing compatibility interrupt can still be replayed by callers.
_user_interrupted = bool(
turn.interrupted and getattr(agent, "_interrupt_requested", False)
)
_interrupt_message = (
getattr(agent, "_interrupt_message", None) if _user_interrupted else None
)
if _user_interrupted:
agent.clear_interrupt()
# If the turn signalled the underlying client is wedged (deadline
# blown, post-tool watchdog tripped, OAuth refresh died, subprocess
# exited), retire the session so the next turn respawns codex
# rather than riding the broken process. Mirrors openclaw beta.8's
# "retire timed-out app-server clients" fix.
if getattr(turn, "should_retire", False):
logger.warning(
"codex app-server session retired (turn error: %s)",
turn.error,
)
try:
agent._codex_session.close()
except Exception:
pass
agent._codex_session = None
# Splice projected messages into the conversation. The projector emits
# standard {role, content, tool_calls, tool_call_id} entries, which
# is exactly what curator.py / sessions DB expect.
if turn.projected_messages:
messages.extend(turn.projected_messages)
# Persist the newly-projected assistant/tool messages ourselves.
# This path is an early return that bypasses conversation_loop, whose
# normal per-step _persist_session() calls would otherwise flush them.
# The inbound user turn was already flushed at turn start
# (turn_context.py _persist_session), and _flush_messages_to_session_db
# is idempotent via the intrinsic _DB_PERSISTED_MARKER — so this writes
# ONLY the new codex projected rows and does NOT re-write the user turn.
# Keeping the agent as the sole persister lets us return
# agent_persisted=True below, so the gateway skips its own DB write and
# we avoid the #860/#42039 duplicate user-message write (append_message
# is a raw INSERT with no dedup, so a gateway re-write would duplicate
# the already-flushed user turn). See gateway/run.py agent_persisted.
if getattr(agent, "_session_db", None) is not None:
try:
_codex_flush_ok = agent._flush_messages_to_session_db(messages)
except Exception:
_codex_flush_ok = False
logger.warning(
"codex app-server projected-message flush failed",
exc_info=True,
)
if _codex_flush_ok is False:
# Unlike the chat-completions loop (which fails closed BEFORE
# projection — see conversation_loop session_persistence_failed),
# codex output has already streamed to the user by the time this
# flush runs, so there is nothing left to withhold. We cannot
# flip agent_persisted=False either: the gateway fallback write
# would re-INSERT the already-flushed user turn (#860/#42039).
# Surface the durability gap loudly instead of a silent debug.
logger.warning(
"codex app-server turn was delivered but could NOT be "
"persisted to the session DB (session=%s) — this turn "
"will be missing after restart/resume",
getattr(agent, "session_id", None),
)
# Counter ticks for the agent-improvement loop.
# _turns_since_memory and _user_turn_count are ALREADY incremented
# in the run_conversation() pre-loop block (lines ~11793-11817) so we
# do NOT touch them here — that would double-count.
# Only _iters_since_skill needs explicit increment, since the
# chat_completions loop bumps it per tool iteration (line ~12110)
# and that loop is bypassed on this path.
agent._iters_since_skill = (
getattr(agent, "_iters_since_skill", 0) + turn.tool_iterations
)
_record_codex_app_server_compaction(agent, turn)
usage_result = _record_codex_app_server_usage(agent, turn)
api_calls = 1
# Now check the skill nudge AFTER iters were incremented — same
# pattern the chat_completions path uses (line ~15432).
should_review_skills = False
if (
agent._skill_nudge_interval > 0
and agent._iters_since_skill >= agent._skill_nudge_interval
and "skill_manage" in agent.valid_tool_names
):
should_review_skills = True
agent._iters_since_skill = 0
# External memory provider sync (mirrors line ~15439). Skipped on
# interrupt/error to avoid feeding partial transcripts to memory.
if not turn.interrupted and turn.error is None:
try:
agent._sync_external_memory_for_turn(
original_user_message=original_user_message,
final_response=turn.final_text,
interrupted=False,
messages=messages,
)
except Exception:
logger.debug("external memory sync raised", exc_info=True)
# Background review fork — same cadence + signature as the default
# path (line ~15449). Only fires when a trigger actually tripped AND
# we have a real final response.
if (
turn.final_text
and not turn.interrupted
and (should_review_memory or should_review_skills)
):
try:
agent._spawn_background_review(
messages_snapshot=list(messages),
review_memory=should_review_memory,
review_skills=should_review_skills,
)
except Exception:
logger.debug("background review spawn raised", exc_info=True)
return {
"final_response": turn.final_text,
"messages": messages,
"api_calls": api_calls,
"completed": not turn.interrupted and turn.error is None,
"partial": turn.interrupted or turn.error is not None,
"interrupted": _user_interrupted,
**(
{"interrupt_message": _interrupt_message}
if _interrupt_message
else {}
),
"error": turn.error,
# The codex app-server runtime IS an early-return path that bypasses
# conversation_loop, but we flush the projected assistant/tool messages
# ourselves above (see the _flush_messages_to_session_db call after
# messages.extend). The inbound user turn was already flushed at turn
# start (turn_context._persist_session) and the flush dedups via
# _DB_PERSISTED_MARKER, so state.db ends up with each real message
# exactly once and session_search / conversation-distill see the full
# gateway conversation. Report agent_persisted=True so the gateway
# skips its own append_to_transcript DB write — writing again there
# would re-INSERT the already-flushed user turn (append_message has no
# dedup), reintroducing the #860 / #42039 duplicate-write bug.
"agent_persisted": True,
"codex_thread_id": turn.thread_id,
"codex_turn_id": turn.turn_id,
**usage_result,
}
# ---------------------------------------------------------------------------
# Event-driven Responses streaming
#
# OpenAI ships its consumer Codex backend (chatgpt.com/backend-api/codex) on
# a different schedule from the openai Python SDK. The high-level
# ``client.responses.stream(...)`` helper reconstructs a typed Response from
# the terminal ``response.completed`` event's ``response.output`` field, and
# when that field drifts to ``null`` (gpt-5.5, May 2026) the SDK raises
# ``TypeError: 'NoneType' object is not iterable`` mid-iteration.
#
# We sidestep the whole class of failure by going one level lower:
# ``client.responses.create(stream=True)`` returns the raw AsyncIterable of
# SSE events, and we assemble the final response object purely from
# ``response.output_item.done`` events as they arrive. We never read
# ``response.completed.response.output`` for content reconstruction, so the
# backend can return ``null``, ``[]``, a string, or omit the field entirely
# and we don't care.
#
# This mirrors what the OpenClaw TS implementation does for the same backend
# and is structurally immune to the bug class rather than patched.
# ---------------------------------------------------------------------------
_TERMINAL_EVENT_TYPES = frozenset({
"response.completed",
"response.incomplete",
"response.failed",
})
def _event_field(event: Any, name: str, default: Any = None) -> Any:
"""Field access that handles both attr-style (SDK objects) and dict (raw JSON) events."""
value = getattr(event, name, None)
if value is None and isinstance(event, dict):
value = event.get(name, default)
return value if value is not None else default
def _item_field(item: Any, name: str, default: Any = None) -> Any:
"""Field access for nested Response items (attr-style SDK object or dict)."""
value = getattr(item, name, None)
if value is None and isinstance(item, dict):
value = item.get(name, default)
return value if value is not None else default
def _raise_stream_error(event: Any) -> None:
"""Raise a ``_StreamErrorEvent`` from a ``type=error`` SSE frame.
The Responses spec puts the failure details at the top level of the
frame (``{"type": "error", "code": ..., "message": ..., "param": ...}``),
but the official OpenAI SDK and several OpenAI-compatible proxies wrap
them in an HTTP-style nested envelope instead
(``{"type": "error", "error": {"code": ..., "message": ..., "param": ...}}``).
Read the top-level fields first, then fall back to the nested envelope so
the error classifier sees the provider's real code/message (rate-limit vs
context-overflow vs entitlement) rather than the generic placeholder.
Port of anomalyco/opencode#36130.
Imported lazily so this module stays importable from places that don't
pull in ``run_agent`` (e.g. plugin code, doc tools).
"""
from run_agent import _StreamErrorEvent
nested = _event_field(event, "error")
def _error_field(name: str) -> Any:
value = _event_field(event, name)
if value is None and nested is not None:
value = _item_field(nested, name)
return value
raw_message = _error_field("message")
if raw_message is not None and not isinstance(raw_message, str):
raw_message = str(raw_message)
message = (raw_message or "stream emitted error event").strip() or "stream emitted error event"
raise _StreamErrorEvent(
message,
code=_error_field("code"),
param=_error_field("param"),
)
def _consume_codex_event_stream(
event_iter: Any,
*,
model: str,
on_text_delta=None,
on_reasoning_delta=None,
on_commentary_message=None,
on_first_delta=None,
on_event=None,
interrupt_check=None,
) -> SimpleNamespace:
"""Consume a Codex Responses SSE event stream and return a final response.
The returned object is a ``SimpleNamespace`` shaped like the SDK's typed
``Response`` for the fields downstream code actually reads:
* ``output``: list of output items, assembled from ``response.output_item.done``.
For tool-call turns this contains the function_call items; for plain-text
turns it contains a synthesized ``message`` item built from streamed deltas
if no message item was emitted directly.
* ``output_text``: assembled text from ``response.output_text.delta`` deltas.
* ``usage``: copied from the terminal event's ``response.usage`` (when present).
* ``status``: ``completed`` / ``incomplete`` / ``failed`` (or ``completed`` if
the stream ended without a terminal frame but produced content).
* ``id``: ``response.id`` when present.
* ``incomplete_details``: passed through for ``response.incomplete`` frames.
* ``error``: passed through for ``response.failed`` frames.
* ``model``: from kwargs (the wire model name is not authoritative).
Critically, we never read ``response.output`` from the terminal event for
content reconstruction — only ``usage``, ``status``, ``id``. That field
being ``null`` / ``[]`` / missing is fine.
Callbacks:
* ``on_text_delta(str)`` — fires per ``response.output_text.delta``, suppressed
once a function_call event is seen (so tool-call turns don't bleed text
into the chat).
* ``on_reasoning_delta(str)`` — fires per ``response.reasoning.*.delta`` and
``phase=analysis`` message deltas. When no dedicated commentary callback
is supplied, commentary also uses this legacy fallback.
* ``on_commentary_message(str)`` — fires once per completed
``phase=commentary`` message, before any following tool item executes.
* ``on_first_delta()`` — one-shot, fires on the first text delta only.
* ``on_event(event)`` — fires for every event before any other processing.
Used for watchdog activity, debug logging, anything wire-shape-agnostic.
* ``interrupt_check()`` — returns True to break the loop early.
"""
collected_output_items: List[Any] = []
collected_text_deltas: List[str] = []
has_tool_calls = False
first_delta_fired = False
active_message_phase: str | None = None
commentary_text_deltas: List[str] = []
terminal_status: str = "completed"
terminal_usage: Any = None
terminal_response_id: str = None
terminal_incomplete_details: Any = None
terminal_error: Any = None
saw_terminal = False
for event in event_iter:
if on_event is not None:
try:
on_event(event)
except (TimeoutError, InterruptedError):
# Control-flow signals from watchdog/cancellation hooks must
# propagate, not get swallowed as "debug noise".
raise
except Exception:
# Genuine bugs in third-party debug/log hooks shouldn't break
# stream consumption.
logger.debug("Codex stream on_event hook raised", exc_info=True)
if interrupt_check is not None and interrupt_check():
break
event_type = _event_field(event, "type", "")
if not isinstance(event_type, str):
event_type = ""
# ``error`` SSE frames carry the provider's real failure reason
# (subscription / quota / model-not-available / rejected-reasoning-replay)
# but never appear in the terminal set. Surface them as a structured
# exception so the credential pool + error classifier see the body.
if event_type == "error":
_raise_stream_error(event)
# Track the phase of the active streamed message item. Codex/Harmony
# ``commentary``/``analysis`` text is mid-turn preamble/progress
# narration, never the final answer. We still collect completed output
# items for replay, but route those deltas to the reasoning callback so
# they display like thinking text instead of assistant content.
if event_type == "response.output_item.added":
item = _event_field(event, "item")
item_type = _item_field(item, "type", "")
if item_type == "message":
phase = _item_field(item, "phase", None)
active_message_phase = phase.strip().lower() if isinstance(phase, str) else None
if active_message_phase == "commentary":
commentary_text_deltas = []
else:
active_message_phase = None
if "function_call" in str(item_type):
has_tool_calls = True
continue
if "output_text.delta" in event_type or event_type == "response.output_text.delta":
delta_text = _event_field(event, "delta", "")
if delta_text and active_message_phase == "commentary":
commentary_text_deltas.append(delta_text)
# Preserve CLI/backward compatibility when no first-class
# commentary consumer is installed.
if on_commentary_message is None and on_reasoning_delta is not None:
try:
on_reasoning_delta(delta_text)
except Exception:
logger.debug("Codex stream on_reasoning_delta raised", exc_info=True)
elif delta_text and active_message_phase == "analysis":
if on_reasoning_delta is not None:
try:
on_reasoning_delta(delta_text)
except Exception:
logger.debug("Codex stream on_reasoning_delta raised", exc_info=True)
elif delta_text:
collected_text_deltas.append(delta_text)
if not has_tool_calls:
if not first_delta_fired:
first_delta_fired = True
if on_first_delta is not None:
try:
on_first_delta()
except Exception:
logger.debug("Codex stream on_first_delta raised", exc_info=True)
if on_text_delta is not None:
try:
on_text_delta(delta_text)
except Exception:
logger.debug("Codex stream on_text_delta raised", exc_info=True)
continue
if "function_call" in event_type:
has_tool_calls = True
# fall through — function_call items still get added on output_item.done
if "reasoning" in event_type and "delta" in event_type:
reasoning_text = _event_field(event, "delta", "")
if reasoning_text and on_reasoning_delta is not None:
try:
on_reasoning_delta(reasoning_text)
except Exception:
logger.debug("Codex stream on_reasoning_delta raised", exc_info=True)
continue
if event_type == "response.output_item.done":
done_item = _event_field(event, "item")
if done_item is not None:
collected_output_items.append(done_item)
done_phase = _item_field(done_item, "phase", None)
done_phase = done_phase.strip().lower() if isinstance(done_phase, str) else None
if done_phase == "commentary" and on_commentary_message is not None:
commentary_text = "".join(commentary_text_deltas).strip()
if not commentary_text:
content_parts = _item_field(done_item, "content", [])
if isinstance(content_parts, list):
commentary_text = "".join(
str(_item_field(part, "text", "") or "")
for part in content_parts
if _item_field(part, "type", "") == "output_text"
).strip()
if commentary_text:
try:
on_commentary_message(commentary_text)
except Exception:
logger.debug(
"Codex stream on_commentary_message raised",
exc_info=True,
)
commentary_text_deltas = []
continue
if event_type in _TERMINAL_EVENT_TYPES:
saw_terminal = True
resp_obj = _event_field(event, "response")
if resp_obj is not None:
terminal_usage = getattr(resp_obj, "usage", None)
if terminal_usage is None and isinstance(resp_obj, dict):
terminal_usage = resp_obj.get("usage")
rid = getattr(resp_obj, "id", None)
if rid is None and isinstance(resp_obj, dict):
rid = resp_obj.get("id")
terminal_response_id = rid
rstatus = getattr(resp_obj, "status", None)
if rstatus is None and isinstance(resp_obj, dict):
rstatus = resp_obj.get("status")
if isinstance(rstatus, str):
terminal_status = rstatus
if event_type == "response.incomplete":
terminal_incomplete_details = getattr(resp_obj, "incomplete_details", None)
if terminal_incomplete_details is None and isinstance(resp_obj, dict):
terminal_incomplete_details = resp_obj.get("incomplete_details")
if event_type == "response.failed":
terminal_error = getattr(resp_obj, "error", None)
if terminal_error is None and isinstance(resp_obj, dict):
terminal_error = resp_obj.get("error")
if event_type == "response.completed":
terminal_status = terminal_status or "completed"
elif event_type == "response.incomplete":
terminal_status = terminal_status or "incomplete"
elif event_type == "response.failed":
terminal_status = terminal_status or "failed"
# Stop on terminal event.
break
# Build the final output list. Prefer items observed via output_item.done;
# if none arrived but we streamed plain text deltas (no tool calls), synthesize
# a single message item so downstream normalization has something to work with.
if collected_output_items:
output = list(collected_output_items)
elif collected_text_deltas and not has_tool_calls:
assembled = "".join(collected_text_deltas)
output = [SimpleNamespace(
type="message",
role="assistant",
status="completed",
content=[SimpleNamespace(type="output_text", text=assembled)],
)]
else:
output = []
# If the stream ended without any terminal event AND produced no usable
# content (no items, no text deltas), surface that as a RuntimeError so
# callers can distinguish "stream truncated mid-flight / provider rejected
# the call" from "stream completed with empty body". This preserves the
# signal the SDK's high-level helper used to raise as
# ``RuntimeError("Didn't receive a `response.completed` event.")``.
if not saw_terminal and not output:
raise RuntimeError(
"Codex Responses stream did not emit a terminal response"
)
assembled_text = "".join(collected_text_deltas)
final = SimpleNamespace(
output=output,
output_text=assembled_text,
usage=terminal_usage,
status=terminal_status,
id=terminal_response_id,
model=model,
incomplete_details=terminal_incomplete_details,
error=terminal_error,
)
return final
def run_codex_stream(agent, api_kwargs: dict, client: Any = None, on_first_delta=None):
"""Execute one streaming Responses API request and return the final response.
Uses ``responses.create(stream=True)`` (low-level raw event iteration)
rather than the high-level ``responses.stream(...)`` helper. This makes
us structurally immune to backend drift in the ``response.completed``
payload shape — we never let the SDK reconstruct a typed object from
the terminal event's ``output`` field.
"""
import httpx as _httpx
active_client = client or agent._ensure_primary_openai_client(reason="codex_stream_direct")
max_stream_retries = 1
# Accumulate streamed text so callers / compat shims can read it.
agent._codex_streamed_text_parts: list = []
def _on_text_delta(text: str) -> None:
agent._codex_streamed_text_parts.append(text)
agent._fire_stream_delta(text)
def _on_reasoning_delta(text: str) -> None:
agent._fire_reasoning_delta(text)
def _on_commentary_message(text: str) -> None:
agent._fire_streamed_codex_commentary(text)
def _on_event(event: Any) -> None:
# TTFB watchdog and activity touch — runs once per SSE event.
agent._codex_stream_last_event_ts = time.time()
agent._touch_activity("receiving stream response")
for attempt in range(max_stream_retries + 1):
if agent._interrupt_requested:
raise InterruptedError("Agent interrupted before Codex stream retry")
stream_kwargs = dict(api_kwargs)
stream_kwargs["stream"] = True
try:
event_stream = active_client.responses.create(**stream_kwargs)
except (_httpx.RemoteProtocolError, _httpx.ReadTimeout, _httpx.ConnectError, ConnectionError) as exc:
if attempt < max_stream_retries:
logger.debug(
"Codex Responses stream connect failed (attempt %s/%s); retrying. %s error=%s",
attempt + 1, max_stream_retries + 1,
agent._client_log_context(), exc,
)
continue
raise
# Claim the delta sink for THIS attempt (#65991) — parity with the
# chat_completions/anthropic/bedrock paths. If a prior attempt's
# stream is somehow still alive, this claim supersedes it so its
# late deltas are fenced out of the turn; conversely, a newer
# attempt supersedes us and the interrupt_check below stops our
# consumption immediately.
_writer_token = claim_stream_writer(agent)
def _interrupt_or_superseded(_tok=_writer_token) -> bool:
if agent._interrupt_requested:
return True
if not stream_writer_is_current(agent, _tok):
logger.warning(
"Codex streaming attempt superseded by a newer stream; "
"stopping consumption to preserve the single-writer "
"invariant (model=%s).",
api_kwargs.get("model", "unknown"),
)
return True
return False
try:
# Compatibility: some mocks/providers return a concrete response
# instead of an iterable. Pass it straight through.
if hasattr(event_stream, "output") and not hasattr(event_stream, "__iter__"):
return event_stream
try:
final = _consume_codex_event_stream(
event_stream,
model=api_kwargs.get("model"),
on_text_delta=_on_text_delta,
on_reasoning_delta=_on_reasoning_delta,
on_commentary_message=(
_on_commentary_message
if (
getattr(agent, "interim_assistant_callback", None) is not None
and getattr(agent, "show_commentary", True)
)
else None
),
on_first_delta=on_first_delta,
on_event=_on_event,
interrupt_check=_interrupt_or_superseded,
)
except (_httpx.RemoteProtocolError, _httpx.ReadTimeout, _httpx.ConnectError, ConnectionError) as exc:
if attempt < max_stream_retries:
logger.debug(
"Codex Responses stream transport failed mid-iteration "
"(attempt %s/%s); retrying. %s error=%s",
attempt + 1, max_stream_retries + 1,
agent._client_log_context(), exc,
)
continue
raise
if final.status in {"incomplete", "failed"}:
logger.warning(
"Codex Responses stream terminal status=%s "
"(incomplete_details=%s, error=%s, streamed_chars=%d). %s",
final.status, final.incomplete_details, final.error,
sum(len(p) for p in agent._codex_streamed_text_parts),
agent._client_log_context(),
)
return final
finally:
close_fn = getattr(event_stream, "close", None)
if callable(close_fn):
try:
close_fn()
except Exception:
pass
def run_codex_create_stream_fallback(agent, api_kwargs: dict, client: Any = None):
"""Backward-compatible alias for the unified event-driven path.
Historically this was the fallback when the SDK's high-level
``responses.stream(...)`` helper raised on shape drift. The primary
path now does exactly what the fallback did, so this just forwards.
Kept as a public symbol because tests and a small number of call sites
still reference it by name.
"""
return run_codex_stream(agent, api_kwargs, client=client)
__all__ = [
"run_codex_app_server_turn",
"run_codex_stream",
"run_codex_create_stream_fallback",
"_consume_codex_event_stream",
"make_codex_app_server_event_bridge",
]