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refactor: plugins dir + opt-in langfuse via __getattr__ guard

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- mv langfuse_tracing.py -> plugins/langfuse_tracing.py
- llmcore: load plugin lazily inside __getattr__ when langfuse_config present
  (PEP 562 module __getattr__ naturally fires only once after globals().update)
- llmcore: extract _record_usage() from 4 scattered [Cache] print sites
- agentmain: /resume scans only latest 10 files
This commit is contained in:
Jiaqing Liang
2026-04-20 15:56:06 +08:00
parent 8e6270e3a3
commit 116d7d3d23
3 changed files with 26 additions and 24 deletions
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48
llmcore.py
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@@ -11,12 +11,15 @@ def _load_mykeys():
if not os.path.exists(p): raise Exception('[ERROR] mykey.py or mykey.json not found, please create one from mykey_template.')
with open(p, encoding='utf-8') as f: return json.load(f)
def __getattr__(name):
if name in ('mykeys', 'proxies'):
def __getattr__(name): # once guard in PEP 562
if name in ('mykeys', 'proxies'):
mk = _load_mykeys()
proxy = mk.get("proxy", 'http://127.0.0.1:2082')
px = {"http": proxy, "https": proxy} if proxy else None
globals().update(mykeys=mk, proxies=px)
if mk.get('langfuse_config'):
try: from plugins import langfuse_tracing
except Exception: pass
return globals()[name]
raise AttributeError(f"module 'llmcore' has no attribute {name}")
@@ -108,8 +111,7 @@ def _parse_claude_sse(resp_lines):
evt_type = evt.get("type", "")
if evt_type == "message_start":
usage = evt.get("message", {}).get("usage", {})
ci, cr, inp = usage.get("cache_creation_input_tokens", 0), usage.get("cache_read_input_tokens", 0), usage.get("input_tokens", 0)
print(f"[Cache] input={inp} creation={ci} read={cr}")
_record_usage(usage, "messages")
elif evt_type == "content_block_start":
block = evt.get("content_block", {})
if block.get("type") == "text": current_block = {"type": "text", "text": ""}
@@ -194,9 +196,7 @@ def _parse_openai_sse(resp_lines, api_mode="chat_completions"):
break
elif etype == "response.completed":
usage = evt.get("response", {}).get("usage", {})
cached = (usage.get("input_tokens_details") or {}).get("cached_tokens", 0)
inp = usage.get("input_tokens", 0)
if inp: print(f"[Cache] input={inp} cached={cached}")
_record_usage(usage, api_mode)
break
blocks = []
if content_text: blocks.append({"type": "text", "text": content_text})
@@ -226,9 +226,7 @@ def _parse_openai_sse(resp_lines, api_mode="chat_completions"):
if tc.get("function", {}).get("name"): tc_buf[idx]["name"] = tc["function"]["name"]
if tc.get("function", {}).get("arguments"): tc_buf[idx]["args"] += tc["function"]["arguments"]
usage = evt.get("usage")
if usage:
cached = (usage.get("prompt_tokens_details") or {}).get("cached_tokens", 0)
print(f"[Cache] input={usage.get('prompt_tokens',0)} cached={cached}")
if usage: _record_usage(usage, api_mode)
blocks = []
if content_text: blocks.append({"type": "text", "text": content_text})
for idx in sorted(tc_buf):
@@ -238,13 +236,24 @@ def _parse_openai_sse(resp_lines, api_mode="chat_completions"):
blocks.append({"type": "tool_use", "id": tc["id"], "name": tc["name"], "input": inp})
return blocks
def _record_usage(usage, api_mode):
if not usage: return
if api_mode == 'responses':
cached = (usage.get("input_tokens_details") or {}).get("cached_tokens", 0)
inp = usage.get("input_tokens", 0)
print(f"[Cache] input={inp} cached={cached}")
elif api_mode == 'chat_completions':
cached = (usage.get("prompt_tokens_details") or {}).get("cached_tokens", 0)
inp = usage.get("prompt_tokens", 0)
print(f"[Cache] input={inp} cached={cached}")
elif api_mode == 'messages':
ci, cr, inp = usage.get("cache_creation_input_tokens", 0), usage.get("cache_read_input_tokens", 0), usage.get("input_tokens", 0)
print(f"[Cache] input={inp} creation={ci} read={cr}")
def _parse_openai_json(data, api_mode="chat_completions"):
blocks = []
if api_mode == "responses":
usage = data.get("usage", {})
cached = (usage.get("input_tokens_details") or {}).get("cached_tokens", 0)
inp = usage.get("input_tokens", 0)
if inp: print(f"[Cache] input={inp} cached={cached}")
_record_usage(data.get("usage") or {}, api_mode)
for item in (data.get("output") or []):
if item.get("type") == "message":
for p in (item.get("content") or []):
@@ -256,10 +265,7 @@ def _parse_openai_json(data, api_mode="chat_completions"):
blocks.append({"type": "tool_use", "id": item.get("call_id", item.get("id", "")),
"name": item.get("name", ""), "input": args})
else:
usage = data.get("usage") or {}
if usage:
cached = (usage.get("prompt_tokens_details") or {}).get("cached_tokens", 0)
print(f"[Cache] input={usage.get('prompt_tokens', 0)} cached={cached}")
_record_usage(data.get("usage") or {}, api_mode)
msg = (data.get("choices") or [{}])[0].get("message", {})
content = msg.get("content", "")
if content:
@@ -577,8 +583,7 @@ class NativeClaudeSession(BaseSession):
if self.stream: return (yield from _parse_claude_sse(resp.iter_lines())) or []
else:
data = resp.json(); content_blocks = data.get("content", [])
usage = data.get("usage", {})
print(f"[Cache] input={usage.get('input_tokens',0)} creation={usage.get('cache_creation_input_tokens',0)} read={usage.get('cache_read_input_tokens',0)}")
_record_usage(data.get("usage", {}), "messages")
for b in content_blocks:
if b.get("type") == "text": yield b.get("text", "")
elif b.get("type") == "thinking": yield ""
@@ -940,6 +945,3 @@ class NativeToolClient:
if resp and hasattr(resp, 'tool_calls') and resp.tool_calls: self._pending_tool_ids = [tc.id for tc in resp.tool_calls]
return resp
try: import langfuse_tracing # opt-in observability; noop if langfuse_config not set in mykey
except Exception: pass