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feat: parse codex exec json output for fallbacks

This commit is contained in:
rob 2025-11-01 17:28:57 -03:00
parent e9cc23685d
commit 0e83b6cf88
3 changed files with 127 additions and 24 deletions
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139
automation/patcher.py
View File

@ -13,6 +13,9 @@ import subprocess
import tempfile
from dataclasses import dataclass
from pathlib import Path
from typing import Any
import json
from automation.ai_config import (
DEFAULT_COMMAND_CHAIN,
@ -32,6 +35,7 @@ class ModelConfig:
"""Configuration for invoking the AI model command."""
commands: list[str]
sentinel: str
runner_settings: Any | None = None # RunnerSettings from ai_config
@classmethod
def from_sources(cls, repo_root: Path, override: str | None = None) -> "ModelConfig":
@ -54,7 +58,23 @@ class ModelConfig:
if not commands:
commands = settings.runner.command_chain or DEFAULT_COMMAND_CHAIN.copy()
return cls(commands=commands, sentinel=sentinel)
return cls(commands=commands, sentinel=sentinel, runner_settings=settings.runner)
def get_commands_for_hint(self, hint: str) -> list[str]:
"""
Get the appropriate command chain based on the model hint.
Args:
hint: 'fast', 'quality', or empty string
Returns:
List of commands to try
"""
if self.runner_settings:
hint_commands = self.runner_settings.get_chain_for_hint(hint)
if hint_commands:
return hint_commands
return self.commands
def generate_output(
@ -64,6 +84,7 @@ def generate_output(
source_rel: Path,
output_rel: Path,
instruction: str,
model_hint: str = "",
) -> None:
"""
Generates or refreshes an output artifact using AI, based on staged changes
@ -82,6 +103,7 @@ def generate_output(
source_rel: The path to the source file relative to repo_root.
output_rel: The path to the output file relative to repo_root.
instruction: The instruction for the AI model.
model_hint: Optional hint ('fast' or 'quality') to guide model selection.
Raises:
PatchGenerationError: If AI output is empty or patch application fails.
@ -113,10 +135,11 @@ def generate_output(
output_content=output_preimage,
instruction=instruction,
no_change_token=model.sentinel,
model_hint=model_hint,
)
# Call the AI model and get its raw output.
raw_patch, no_changes = call_model(model, prompt, cwd=repo_root)
raw_patch, no_changes = call_model(model, prompt, model_hint, cwd=repo_root)
if no_changes:
return
@ -299,7 +322,7 @@ PROMPT_TEMPLATE = """You are assisting with automated artifact generation during
SOURCE FILE: {source_path}
OUTPUT FILE: {output_path}
{model_hint_line}
=== SOURCE FILE CHANGES (staged) ===
{source_diff}
@ -348,6 +371,7 @@ def build_prompt(
output_content: str,
instruction: str,
no_change_token: str,
model_hint: str = "",
) -> str:
"""
Constructs the full prompt string for the AI model by formatting the
@ -360,13 +384,20 @@ def build_prompt(
source_content: Content of the staged source file.
output_content: Current content of the output file (pre-image).
instruction: Specific instructions for the AI.
model_hint: Optional hint ('fast' or 'quality') for model selection.
Returns:
The formatted prompt string.
"""
# Format the model hint line if provided
model_hint_line = ""
if model_hint:
model_hint_line = f"TASK COMPLEXITY: {model_hint.upper()}\n"
return PROMPT_TEMPLATE.format(
source_path=source_rel.as_posix(),
output_path=output_rel.as_posix(),
model_hint_line=model_hint_line,
source_diff=source_diff.strip(),
source_content=source_content.strip(),
output_content=output_content.strip() or "(empty)", # Indicate if output content is empty.
@ -375,13 +406,14 @@ def build_prompt(
)
def call_model(model: ModelConfig, prompt: str, cwd: Path) -> tuple[str, bool]:
def call_model(model: ModelConfig, prompt: str, model_hint: str, cwd: Path) -> tuple[str, bool]:
"""
Invokes the AI model command with the given prompt and captures its output.
Args:
model: The ModelConfig object containing the AI command.
prompt: The input prompt string for the AI model.
model_hint: Optional hint ('fast' or 'quality') for model selection.
cwd: The current working directory for executing the command.
Returns:
@ -392,30 +424,28 @@ def call_model(model: ModelConfig, prompt: str, cwd: Path) -> tuple[str, bool]:
"""
errors: list[str] = []
for command in model.commands:
result = subprocess.run(
command,
input=prompt,
text=True,
capture_output=True,
cwd=str(cwd),
shell=True,
)
raw_stdout = result.stdout or ""
stdout = raw_stdout.strip()
stderr = result.stderr.strip()
# Get commands based on hint
commands = model.get_commands_for_hint(model_hint)
if stdout:
if stdout == model.sentinel:
for command in commands:
executor, raw_stdout, stderr, returncode = _run_ai_command(command, prompt, cwd)
if raw_stdout:
stripped = raw_stdout.strip()
if stripped == model.sentinel:
return raw_stdout, True
if "API Error:" in raw_stdout and "Overloaded" in raw_stdout:
raise PatchGenerationError("Claude API is overloaded (500 error) - please retry later")
if "<<<AI_DIFF_START>>>" in raw_stdout:
return raw_stdout, False
# Non-empty output without diff markers counts as failure so we can try fallbacks.
errors.append(f"{executor!r} produced non-diff output: {stripped[:80]}")
continue
if result.returncode == 0:
errors.append(f"{command!r} produced no output")
if returncode == 0:
errors.append(f"{executor!r} produced no output")
else:
errors.append(f"{command!r} exited with {result.returncode}: {stderr or 'no stderr'}")
errors.append(f"{executor!r} exited with {returncode}: {stderr or 'no stderr'}")
raise PatchGenerationError("AI command(s) failed: " + "; ".join(errors))
@ -621,3 +651,70 @@ def run(args: list[str], cwd: Path, check: bool = True) -> subprocess.CompletedP
if check and result.returncode != 0:
raise PatchGenerationError(f"Command {' '.join(args)} failed: {result.stderr.strip()}")
return result
def _run_ai_command(command: str, prompt: str, cwd: Path) -> tuple[str, str, str, int]:
"""Run an AI command and return (executed_command, stdout, stderr, returncode)."""
if command.strip().startswith("codex"):
return _run_codex_command(command, prompt, cwd)
result = subprocess.run(
command,
input=prompt,
text=True,
capture_output=True,
cwd=str(cwd),
shell=True,
)
raw_stdout = result.stdout or ""
stderr = result.stderr.strip()
return command, raw_stdout, stderr, result.returncode
def _run_codex_command(command: str, prompt: str, cwd: Path) -> tuple[str, str, str, int]:
"""Execute codex CLI with JSON output and extract last message text."""
json_command = _ensure_codex_json(command)
result = subprocess.run(
json_command,
input=prompt,
text=True,
capture_output=True,
cwd=str(cwd),
shell=True,
)
stdout_text = result.stdout or ""
last_message = _extract_codex_last_message(stdout_text)
return json_command, last_message, result.stderr.strip(), result.returncode
def _ensure_codex_json(command: str) -> str:
"""Ensure codex command runs via `codex exec --json --color=never` for machine parsing."""
parts = command.strip().split()
if len(parts) >= 2 and parts[1] == "exec":
base = command
else:
base = command.replace("codex", "codex exec", 1)
if "--json" not in base:
base = f"{base} --json"
if "--color" not in base:
base = f"{base} --color=never"
return base
def _extract_codex_last_message(stdout_text: str) -> str:
"""Parse codex JSONL output and return the final agent message text."""
last_text = ""
for line in stdout_text.splitlines():
line = line.strip()
if not line:
continue
try:
payload = json.loads(line)
except json.JSONDecodeError:
continue
item = payload.get("item")
if isinstance(item, dict) and item.get("type") == "agent_message":
text = item.get("text")
if isinstance(text, str):
last_text = text
return last_text

5
tests/test_patcher.py
View File

@ -40,7 +40,10 @@ diff --git a/Docs/features/FR_1/discussions/example.discussion.sum.md b/Docs/fea
patch_file = tmp_path / "patch.txt"
patch_file.write_text(patch_text, encoding="utf-8")
model = ModelConfig(commands=[f"bash -lc 'cat {patch_file.as_posix()}'"], sentinel=DEFAULT_SENTINEL)
model = ModelConfig(
commands=[f"bash -lc 'cat {patch_file.as_posix()}'"],
sentinel=DEFAULT_SENTINEL,
)
rules = RulesConfig(root=temp_repo, global_rules={"file_associations": {}, "rules": {}})
generate_output(

5
tests/test_runner.py
View File

@ -58,7 +58,10 @@ diff --git a/Docs/features/FR_1/discussions/example.discussion.sum.md b/Docs/fea
patch_file.write_text(patch_text, encoding="utf-8")
rules = RulesConfig.load(repo)
model = ModelConfig(commands=[f"bash -lc 'cat {patch_file.as_posix()}'"], sentinel=DEFAULT_SENTINEL)
model = ModelConfig(
commands=[f"bash -lc 'cat {patch_file.as_posix()}'"],
sentinel=DEFAULT_SENTINEL,
)
rc = process(repo, rules, model)
assert rc == 0