TOOLS = {
"calc": lambda expression: _safe_calc(expression),
"kb_search": lambda question, ok=3: _kb_search(question, int(ok)),
"extract_json": lambda textual content: _extract_json(textual content),
"write_file": lambda path, content material: _write_file(path, content material),
}
TOOL_SCHEMAS = [
{"type": "function","function":{"name":"calc","description":"Safely compute a numeric expression.","parameters":{"type":"object","properties":{"expression":{"type":"string"}},"required":["expression"]}}},
{"kind": "operate","operate":{"identify":"kb_search","description":"Search inside mini data base.","parameters":{"kind":"object","properties":{"question":{"kind":"string"},"ok":{"kind":"integer","default":3}},"required":["query"]}}},
{"kind": "operate","operate":{"identify":"extract_json","description":"Extract and parse first JSON object from textual content.","parameters":{"kind":"object","properties":{"textual content":{"kind":"string"}},"required":["text"]}}},
{"kind": "operate","operate":{"identify":"write_file","description":"Write content material to a file path.","parameters":{"kind":"object","properties":{"path":{"kind":"string"},"content material":{"kind":"string"}},"required":["path","content"]}}},
]
@dataclass
class AgentState:
purpose: str
reminiscence: Record[str] = discipline(default_factory=checklist)
hint: Record[Dict[str, Any]] = discipline(default_factory=checklist)
def chat(messages, instruments=None, tool_choice="auto", temperature=0.2):
kwargs = dict(
mannequin=MODEL,
messages=messages,
temperature=temperature,
)
if instruments will not be None:
kwargs["tools"] = instruments
kwargs["tool_choice"] = tool_choice
return consumer.chat.completions.create(**kwargs)
def run_tool(identify, args):
fn = TOOLS.get(identify)
if not fn: return {"okay": False, "error": f"Unknown instrument: {identify}"}
strive:
return fn(**args)
besides Exception as e:
return {"okay": False, "error": str(e), "args": args}









