v1: executing-plans 模式生成，54 文件 1320 行 Python

config.py

@@ -0,0 +1,56 @@
+from dataclasses import dataclass, field
+from pathlib import Path
+try:
+    import tomllib
+except ImportError:
+    try:
+        import tomli as tomllib
+    except ImportError:
+        tomllib = None
+
+
+@dataclass
+class Config:
+    project_name: str = ""
+    copybook_paths: list[str] = field(default_factory=lambda: ["./copybooks"])
+    dialect: str = "ibm"
+    llm_model: str = "gpt-4o-mini"
+    llm_timeout: int = 15
+    llm_cache_dir: str = ".cache/llm"
+    coverage_default: str = "boundary"
+    rounding_mode: str = "TRUNCATE"
+    tolerance: float = 0.01
+    runner_mode: str = "native"
+    spark_master: str = "local[*]"
+    spark_input_format: str = "json"
+    num_records: int = 1000
+    branch_pass: float = 0.80
+    max_llm_cost: float = 0.50
+
+    @classmethod
+    def from_toml(cls, path: str = "aurak.toml") -> "Config":
+        if tomllib is None:
+            return cls()
+        with open(path, "rb") as f:
+            data = tomllib.load(f)
+        c = cls()
+        p = data.get("project", {})
+        c.project_name = p.get("name", c.project_name)
+        c.copybook_paths = p.get("copybook_paths", c.copybook_paths)
+        c.dialect = p.get("dialect", c.dialect)
+        llm = data.get("llm", {})
+        c.llm_model = llm.get("model", c.llm_model)
+        c.llm_timeout = llm.get("timeout", c.llm_timeout)
+        c.llm_cache_dir = llm.get("cache_dir", c.llm_cache_dir)
+        cov = data.get("coverage", {})
+        c.coverage_default = cov.get("default_target", c.coverage_default)
+        cmp = data.get("comparison", {})
+        c.rounding_mode = cmp.get("rounding_mode", c.rounding_mode)
+        c.tolerance = cmp.get("default_tolerance", c.tolerance)
+        r = data.get("runner", {})
+        c.runner_mode = r.get("mode", c.runner_mode)
+        sp = data.get("spark", {})
+        c.spark_master = sp.get("master", c.spark_master)
+        c.spark_input_format = sp.get("input_format", c.spark_input_format)
+        c.num_records = sp.get("num_records", c.num_records)
+        return c