oclaw/svc/llm/transports/simple.py
oliver 420abac9f1 refactor: root-package imports (svc/runtime/interfaces) and fix PYTHONPATH
- Rename platform/ to svc/ to avoid shadowing stdlib platform.
- Replace from oclaw.* with from svc/runtime/interfaces; update -m CLI paths.
- tests/conftest: prepend repo root to sys.path (no parent-folder package name).
- CI: paths and offline_eval script under repo root.
- Ops scripts: PYTHONPATH must be repo root for python -m runtime.* (fixes gateway/WhatsApp sidecar startup).
- Fix default oclaw.json path in tabular/file attachment limits; stabilize attachment test config.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-13 14:51:17 +08:00

144 lines
6.2 KiB
Python

from __future__ import annotations
import json
import re
from typing import Any, Optional
from collections.abc import Callable
from svc.llm.transports.base import ChatModel, LLMResponse, LLMToolCall
class StaticTextChatModel(ChatModel):
def __init__(self, text: str):
self._text = text or ""
def chat(
self,
messages: list[dict[str, Any]],
tools: list[dict[str, Any]],
*,
on_token: Optional[Callable[[str], None]] = None,
) -> LLMResponse:
if on_token and self._text:
on_token(self._text)
return LLMResponse(content=self._text, tool_calls=[])
class RuleBasedChatModel(ChatModel):
_IP_RE = re.compile(
r"(?P<ip>(?:\d{1,3}\.){3}\d{1,3})|(?P<ipv6>(?:[0-9a-fA-F]{0,4}:){2,}[0-9a-fA-F]{0,4})"
)
def chat(
self,
messages: list[dict[str, Any]],
tools: list[dict[str, Any]],
*,
on_token: Optional[Callable[[str], None]] = None,
) -> LLMResponse:
def make_call(name: str, arguments: dict[str, Any]) -> LLMResponse:
return LLMResponse(
content="",
tool_calls=[LLMToolCall(id=f"rb_{name}_1", name=name, arguments=arguments)],
)
def emit(resp: LLMResponse) -> LLMResponse:
if on_token and (resp.content or "").strip():
on_token(resp.content)
return resp
if messages:
last = messages[-1]
if last.get("role") == "tool":
raw = str(last.get("content") or "")
try:
data = json.loads(raw)
except json.JSONDecodeError:
data = {"ok": True, "raw": raw}
if isinstance(data, dict) and data.get("ok") is False:
return emit(LLMResponse(content=f"工具执行失败:{data.get('error')}", tool_calls=[]))
if isinstance(data, dict) and "route" in data:
r = data.get("route") or {}
return emit(
LLMResponse(
content=f"路由查询结果:目的 {data.get('destination')} 命中 {r.get('prefix')},下一跳 {r.get('next_hop')},出接口 {r.get('out_if')}。",
tool_calls=[],
)
)
if isinstance(data, dict) and "hops" in data:
hops = data.get("hops") or []
return emit(
LLMResponse(
content=f"路径计算结果:{data.get('src')} → {data.get('dst')} 共 {data.get('hop_count')} 跳,路径为:{' -> '.join(map(str, hops))}",
tool_calls=[],
)
)
if isinstance(data, dict) and "diff" in data:
diff = data.get("diff") or ""
if not diff:
return emit(LLMResponse(content="配置对比结果:两段配置一致。", tool_calls=[]))
return emit(LLMResponse(content=f"配置对比结果:\n\n```diff\n{diff}\n```", tool_calls=[]))
if isinstance(data, dict) and "level_count" in data:
lc = data.get("level_count") or {}
return emit(LLMResponse(content=f"日志分析结果:统计 {lc}。建议优先查看 ERROR 样例与日志尾部定位根因。", tool_calls=[]))
if isinstance(data, dict) and "reachable" in data:
reach = bool(data.get("reachable"))
avg = data.get("avg_ms")
if reach:
tail = f"平均时延 {avg}ms" if isinstance(avg, int) else "时延解析失败"
return emit(LLMResponse(content=f"设备状态:可达,{tail}。", tool_calls=[]))
return emit(LLMResponse(content="设备状态:不可达。建议检查 ACL/路由/DNS/防火墙策略,并确认目标在线。", tool_calls=[]))
return emit(LLMResponse(content=f"工具执行结果:{json.dumps(data, ensure_ascii=False)}", tool_calls=[]))
last_user = ""
for m in reversed(messages):
if m.get("role") == "user":
content = m.get("content")
if isinstance(content, list):
texts = [item["text"] for item in content if isinstance(item, dict) and item.get("type") == "text"]
last_user = "\n".join(texts)
else:
last_user = str(content or "")
break
m = self._IP_RE.search(last_user)
if "路由" in last_user and m:
ip = m.group("ip") or m.group("ipv6")
return make_call("query_route", {"destination": ip})
if ("路径" in last_user or "链路" in last_user) and ("到" in last_user or "->" in last_user):
m2 = re.search(r"([A-Za-z0-9_-]+)\s*(?:到|->)\s*([A-Za-z0-9_-]+)", last_user)
if m2:
src, dst = m2.group(1), m2.group(2)
return make_call("get_path", {"src": src, "dst": dst})
if "对比" in last_user or "diff" in last_user.lower():
if "left:" in last_user.lower() and "right:" in last_user.lower():
left = last_user.split("left:", 1)[1].split("right:", 1)[0].strip()
right = last_user.split("right:", 1)[1].strip()
return make_call("config_diff", {"left": left, "right": right})
if "日志" in last_user and ("分析" in last_user or "统计" in last_user):
return make_call("log_analysis", {"log": last_user})
if ("设备" in last_user or "主机" in last_user) and ("状态" in last_user or "可达" in last_user or "ping" in last_user.lower()) and m:
ip = m.group("ip") or m.group("ipv6")
return make_call("device_status", {"host": ip})
return emit(
LLMResponse(
content="我可以进行路由查询、路径计算、配置对比、设备状态检查、日志分析。请直接描述需求并提供必要输入。",
tool_calls=[],
)
)
__all__ = ["StaticTextChatModel", "RuleBasedChatModel"]