feat: load ai command chain from shared config

automation/ai_config.py

@@ -0,0 +1,112 @@
+"""
+Shared AI configuration loader for CascadingDev automation.
+
+The configuration lives at `config/ai.yml` within the repository (for both the
+maintainer tool and generated projects). It coordinates preferences for:
+  • The automation runner's AI command chain and sentinel token.
+  • Ramble GUI defaults (provider selection and CLI wiring).
+
+This module keeps the parsing logic close to the automation package so the
+installer can ship it alongside the pre-commit runner.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Dict, List
+
+import yaml
+
+DEFAULT_SENTINEL = "CASCADINGDEV_NO_CHANGES"
+DEFAULT_COMMAND_CHAIN = ["claude -p"]
+CONFIG_RELATIVE_PATH = Path("config") / "ai.yml"
+
+
+def parse_command_chain(raw: str | None) -> List[str]:
+    """
+    Split a fallback command string into individual commands.
+
+    We reuse the shell-style '||' delimiter so maintainers can export
+    `CDEV_AI_COMMAND="cmdA || cmdB"`. Empty entries are discarded.
+    """
+    if not raw:
+        return []
+    parts = [segment.strip() for segment in raw.split("||")]
+    return [segment for segment in parts if segment]
+
+
+@dataclass
+class RunnerSettings:
+    command_chain: List[str]
+    sentinel: str
+
+
+@dataclass
+class RambleSettings:
+    default_provider: str
+    providers: Dict[str, Dict[str, Any]]
+
+
+@dataclass
+class AISettings:
+    runner: RunnerSettings
+    ramble: RambleSettings
+
+
+def _load_yaml(path: Path) -> Dict[str, Any]:
+    if not path.exists():
+        return {}
+    try:
+        with path.open("r", encoding="utf-8") as fh:
+            data = yaml.safe_load(fh) or {}
+            if not isinstance(data, dict):
+                return {}
+            return data
+    except OSError:
+        return {}
+
+
+def load_ai_settings(repo_root: Path) -> AISettings:
+    """
+    Load the AI configuration for the given repository root.
+
+    Missing files fall back to sensible defaults so the automation remains
+    usable out of the box.
+    """
+    config_path = (repo_root / CONFIG_RELATIVE_PATH).resolve()
+    data = _load_yaml(config_path)
+
+    runner_data = data.get("runner") if isinstance(data, dict) else {}
+    if not isinstance(runner_data, dict):
+        runner_data = {}
+
+    chain = runner_data.get("command_chain", [])
+    if not isinstance(chain, list):
+        chain = []
+    command_chain = [str(entry).strip() for entry in chain if str(entry).strip()]
+    if not command_chain:
+        command_chain = DEFAULT_COMMAND_CHAIN.copy()
+
+    sentinel = runner_data.get("sentinel")
+    if not isinstance(sentinel, str) or not sentinel.strip():
+        sentinel = DEFAULT_SENTINEL
+
+    ramble_data = data.get("ramble") if isinstance(data, dict) else {}
+    if not isinstance(ramble_data, dict):
+        ramble_data = {}
+
+    default_provider = ramble_data.get("default_provider")
+    if not isinstance(default_provider, str) or not default_provider.strip():
+        default_provider = "mock"
+
+    providers = ramble_data.get("providers", {})
+    if not isinstance(providers, dict):
+        providers = {}
+
+    return AISettings(
+        runner=RunnerSettings(command_chain=command_chain, sentinel=sentinel),
+        ramble=RambleSettings(
+            default_provider=default_provider,
+            providers={str(k): v for k, v in providers.items() if isinstance(v, dict)},
+        ),
+    )

automation/patcher.py

@@ -11,9 +11,15 @@ import re
 import shutil
 import subprocess
 import tempfile
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from pathlib import Path
 
+from automation.ai_config import (
+    DEFAULT_COMMAND_CHAIN,
+    DEFAULT_SENTINEL,
+    load_ai_settings,
+    parse_command_chain,
+)
 from automation.config import RulesConfig
 
 
@@ -21,36 +27,34 @@ class PatchGenerationError(RuntimeError):
     pass
 
 
-NO_CHANGES_SENTINEL = "CASCADINGDEV_NO_CHANGES"
-COMMAND_DELIMITER = "||"
-
-
-def _parse_command_chain(raw: str) -> list[str]:
-    """
-    Split a fallback command string into individual commands.
-
-    Commands are separated by '||' to align with common shell semantics.
-    Whitespace-only segments are ignored.
-    """
-    parts = [segment.strip() for segment in raw.split(COMMAND_DELIMITER)]
-    commands = [segment for segment in parts if segment]
-    return commands or ["claude -p"]
-
-
 @dataclass
 class ModelConfig:
     """Configuration for invoking the AI model command."""
-    raw: str | None = None
+    commands: list[str]
-    commands: list[str] = field(init=False, repr=False)
+    sentinel: str
 
-    def __post_init__(self) -> None:
+    @classmethod
-        source = self.raw or os.environ.get("CDEV_AI_COMMAND", "claude -p")
+    def from_sources(cls, repo_root: Path, override: str | None = None) -> "ModelConfig":
-        self.commands = _parse_command_chain(source)
+        """
+        Build a ModelConfig using CLI override, environment variable, or
+        repository configuration (in that precedence order).
+        """
+        settings = load_ai_settings(repo_root)
+        sentinel = settings.runner.sentinel or DEFAULT_SENTINEL
 
-    @property
+        if override and override.strip():
-    def command(self) -> str:
+            commands = parse_command_chain(override)
-        """Return the primary command (first in the fallback chain)."""
+        else:
-        return self.commands[0]
+            env_override = os.environ.get("CDEV_AI_COMMAND")
+            if env_override and env_override.strip():
+                commands = parse_command_chain(env_override)
+            else:
+                commands = settings.runner.command_chain
+
+        if not commands:
+            commands = settings.runner.command_chain or DEFAULT_COMMAND_CHAIN.copy()
+
+        return cls(commands=commands, sentinel=sentinel)
 
 
 def generate_output(
@@ -108,6 +112,7 @@ def generate_output(
         source_content=source_content,
         output_content=output_preimage,
         instruction=instruction,
+        no_change_token=model.sentinel,
     )
 
     # Call the AI model and get its raw output.
@@ -342,6 +347,7 @@ def build_prompt(
     source_content: str,
     output_content: str,
     instruction: str,
+    no_change_token: str,
 ) -> str:
     """
     Constructs the full prompt string for the AI model by formatting the
@@ -365,7 +371,7 @@ def build_prompt(
         source_content=source_content.strip(),
         output_content=output_content.strip() or "(empty)", # Indicate if output content is empty.
         instruction=instruction.strip(),
-        no_change_token=NO_CHANGES_SENTINEL,
+        no_change_token=no_change_token,
     )
 
 
@@ -400,7 +406,7 @@ def call_model(model: ModelConfig, prompt: str, cwd: Path) -> tuple[str, bool]:
         stderr = result.stderr.strip()
 
         if stdout:
-            if stdout == NO_CHANGES_SENTINEL:
+            if stdout == 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")

automation/runner.py

@@ -133,7 +133,7 @@ def main(argv: list[str] | None = None) -> int:
         return 0
 
     # Instantiate the model config and delegate to the processing pipeline.
-    model = ModelConfig(args.model)
+    model = ModelConfig.from_sources(repo_root, args.model)
     return process(repo_root, rules, model)
 
 

tests/test_patcher.py

@@ -4,6 +4,7 @@ from pathlib import Path
 import pytest
 
 from automation.config import RulesConfig
+from automation.ai_config import DEFAULT_SENTINEL
 from automation.patcher import ModelConfig, PatchGenerationError, generate_output
 
 
@@ -39,7 +40,7 @@ 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(f"bash -lc 'cat {patch_file.as_posix()}'")
+    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(

tests/test_runner.py

@@ -5,6 +5,7 @@ import textwrap
 import pytest
 
 from automation.config import RulesConfig
+from automation.ai_config import DEFAULT_SENTINEL
 from automation.patcher import ModelConfig
 from automation.runner import process
 
@@ -57,7 +58,7 @@ 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(f"bash -lc 'cat {patch_file.as_posix()}'")
+    model = ModelConfig(commands=[f"bash -lc 'cat {patch_file.as_posix()}'"], sentinel=DEFAULT_SENTINEL)
 
     rc = process(repo, rules, model)
     assert rc == 0