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

agents/llm.py

@@ -0,0 +1,47 @@
+import json, hashlib, os
+from pathlib import Path
+from typing import Optional
+import httpx
+
+
+class LLMClient:
+    def __init__(self, model: str = "gpt-4o-mini", timeout: int = 15,
+                 cache_dir: str = ".cache/llm"):
+        self.model = model
+        self.timeout = timeout
+        self.cache_dir = Path(cache_dir)
+        self.cache_dir.mkdir(parents=True, exist_ok=True)
+
+    def _cache_key(self, messages: list) -> str:
+        return hashlib.sha256(json.dumps(messages, sort_keys=True).encode()).hexdigest()
+
+    def _cache_get(self, key: str) -> Optional[str]:
+        path = self.cache_dir / f"{key}.json"
+        if path.exists():
+            return json.loads(path.read_text()).get("response")
+        return None
+
+    def _cache_set(self, key: str, response: str):
+        (self.cache_dir / f"{key}.json").write_text(json.dumps({"response": response}))
+
+    def call(self, messages: list, retries: int = 1) -> str:
+        key = self._cache_key(messages)
+        cached = self._cache_get(key)
+        if cached:
+            return cached
+        api_key = os.environ.get("OPENAI_API_KEY", "")
+        for attempt in range(retries + 1):
+            try:
+                resp = httpx.post(
+                    "https://api.openai.com/v1/chat/completions",
+                    json={"model": self.model, "messages": messages},
+                    headers={"Authorization": f"Bearer {api_key}"},
+                    timeout=self.timeout)
+                resp.raise_for_status()
+                result = resp.json()["choices"][0]["message"]["content"]
+                self._cache_set(key, result)
+                return result
+            except Exception:
+                if attempt == retries:
+                    raise
+        return ""