null
/
Pipeline
1
0
Fork 0
Code Issues 15 Pull Requests Packages Projects Releases Wiki Activity

fix(scripts): ai calc

This commit is contained in:
null 2026-05-21 02:25:50 -05:00
parent dc5af312a6
commit 1a0eaeee68
3 changed files with 30 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
backend/app/api/provider_credentials.py
View File

@ -167,6 +167,7 @@ async def test_provider_credential(
error=live.error,
tokens=_tok(live.tokens),
input_tokens=_tok(live.input_tokens),
output_tokens=_tok(live.output_tokens),
requests=_req(live.requests),
models=live.models,
sample_model=live.sample_model,
@ -271,6 +272,7 @@ async def get_provider_usage_live(
error=live.error,
tokens=_tok(live.tokens),
input_tokens=_tok(live.input_tokens),
output_tokens=_tok(live.output_tokens),
requests=_req(live.requests),
models=live.models,
sample_model=live.sample_model,

3
backend/app/schemas/provider_credentials.py
View File

@ -60,7 +60,8 @@ class ProviderUsageLiveRead(SQLModel):
confidence: str # high | medium | low
error: str | None = None
tokens: TokenWindowRead
input_tokens: TokenWindowRead # Anthropic splits input tokens separately
input_tokens: TokenWindowRead # Anthropic input-only window
output_tokens: TokenWindowRead # Anthropic output-only window
requests: RequestWindowRead
models: list[str] = []
sample_model: str | None = None

32
backend/app/services/provider_usage.py
View File

@ -110,7 +110,8 @@ class ProviderUsageLive:
confidence: str = "high"
error: str | None = None
tokens: TokenWindow = field(default_factory=TokenWindow)
input_tokens: TokenWindow = field(default_factory=TokenWindow) # Anthropic splits input/output
input_tokens: TokenWindow = field(default_factory=TokenWindow) # Anthropic input-only window
output_tokens: TokenWindow = field(default_factory=TokenWindow) # Anthropic output-only window
requests: RequestWindow = field(default_factory=RequestWindow)
models: list[str] = field(default_factory=list) # model IDs available on this key
raw_headers: dict[str, str] = field(default_factory=dict)
@ -143,9 +144,10 @@ class ProviderUsageLive:
"source": self.source,
"confidence": self.confidence,
"error": self.error,
"tokens": _window(self.tokens),
"input_tokens": _window(self.input_tokens),
"requests": _window(self.requests),
"tokens": _window(self.tokens),
"input_tokens": _window(self.input_tokens),
"output_tokens": _window(self.output_tokens),
"requests": _window(self.requests),
"models": self.models[:20], # cap for response size
"sample_model": self.sample_model,
"sample_input_tokens": self.sample_input_tokens,
@ -201,6 +203,11 @@ def _apply_anthropic_ratelimit_headers(result: ProviderUsageLive, headers: dict[
remaining=_parse_int_header(headers, "anthropic-ratelimit-input-tokens-remaining"),
reset_at=_parse_iso_reset(headers.get("anthropic-ratelimit-input-tokens-reset", "")),
)
result.output_tokens = TokenWindow(
limit=_parse_int_header(headers, "anthropic-ratelimit-output-tokens-limit"),
remaining=_parse_int_header(headers, "anthropic-ratelimit-output-tokens-remaining"),
reset_at=_parse_iso_reset(headers.get("anthropic-ratelimit-output-tokens-reset", "")),
)
result.requests = RequestWindow(
limit=_parse_int_header(headers, "anthropic-ratelimit-requests-limit"),
remaining=_parse_int_header(headers, "anthropic-ratelimit-requests-remaining"),
@ -463,13 +470,14 @@ async def _fetch_openai(api_key: str, base_url: str | None) -> ProviderUsageLive
probe_model = _pick_openai_probe_model(result.models)
if probe_model:
result.sample_model = probe_model
# min 16 tokens: gpt-5.x models reject max_output_tokens < 16
probe_endpoints: list[tuple[str, dict[str, Any]]] = [
(
f"{base}/v1/responses",
{
"model": probe_model,
"input": "Usage probe",
"max_output_tokens": 1,
"max_output_tokens": 16,
},
),
(
@ -477,7 +485,7 @@ async def _fetch_openai(api_key: str, base_url: str | None) -> ProviderUsageLive
{
"model": probe_model,
"messages": [{"role": "user", "content": "Usage probe"}],
"max_tokens": 1,
"max_tokens": 16,
},
),
]
@ -494,6 +502,18 @@ async def _fetch_openai(api_key: str, base_url: str | None) -> ProviderUsageLive
)
except Exception:
continue
# Quota exhaustion is a 429 with a distinct error code — surface it
# clearly rather than treating it as a transient rate limit.
if probe_resp.status_code == 429:
try:
err = probe_resp.json().get("error", {})
if err.get("code") == "insufficient_quota" or "exceeded your current quota" in str(err.get("message", "")):
result.error = "Quota exhausted — add credits at platform.openai.com/billing."
elapsed_ms = probe_resp.elapsed.total_seconds() * 1000.0
result.sample_latency_ms = int(max(0.0, round(elapsed_ms)))
break
except Exception:
pass
probe_headers = {k.lower(): v for k, v in probe_resp.headers.items()}
probe_rl_headers = {k: v for k, v in probe_headers.items() if "ratelimit" in k}
if probe_rl_headers: