mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-04-25 00:51:20 +00:00
feat: add route-aware pricing estimates (#1695)
Salvaged from PR #1563 by @kshitijk4poor. Cherry-picked with authorship preserved. - Route-aware pricing architecture replacing static MODEL_PRICING + heuristics - Canonical usage normalization (Anthropic/OpenAI/Codex API shapes) - Cache-aware billing (separate cache_read/cache_write rates) - Cost status tracking (estimated/included/unknown/actual) - OpenRouter live pricing via models API - Schema migration v4→v5 with billing metadata columns - Removed speculative forward-looking entries - Removed cost display from CLI status bar - Threaded OpenRouter metadata pre-warm Co-authored-by: kshitij <82637225+kshitijk4poor@users.noreply.github.com>
This commit is contained in:
Teknium
GitHub
parent
d9b9987ad3
commit
d417ba2a48
14 changed files with 1694 additions and 254 deletions
|
|
@ -22,14 +22,21 @@ from collections import Counter, defaultdict
|
|||
from datetime import datetime
|
||||
from typing import Any, Dict, List
|
||||
|
||||
from agent.usage_pricing import DEFAULT_PRICING, estimate_cost_usd, format_duration_compact, get_pricing, has_known_pricing
|
||||
from agent.usage_pricing import (
|
||||
CanonicalUsage,
|
||||
DEFAULT_PRICING,
|
||||
estimate_usage_cost,
|
||||
format_duration_compact,
|
||||
get_pricing,
|
||||
has_known_pricing,
|
||||
)
|
||||
|
||||
_DEFAULT_PRICING = DEFAULT_PRICING
|
||||
|
||||
|
||||
def _has_known_pricing(model_name: str) -> bool:
|
||||
def _has_known_pricing(model_name: str, provider: str = None, base_url: str = None) -> bool:
|
||||
"""Check if a model has known pricing (vs unknown/custom endpoint)."""
|
||||
return has_known_pricing(model_name)
|
||||
return has_known_pricing(model_name, provider=provider, base_url=base_url)
|
||||
|
||||
|
||||
def _get_pricing(model_name: str) -> Dict[str, float]:
|
||||
|
|
@ -41,9 +48,43 @@ def _get_pricing(model_name: str) -> Dict[str, float]:
|
|||
return get_pricing(model_name)
|
||||
|
||||
|
||||
def _estimate_cost(model: str, input_tokens: int, output_tokens: int) -> float:
|
||||
"""Estimate the USD cost for a given model and token counts."""
|
||||
return estimate_cost_usd(model, input_tokens, output_tokens)
|
||||
def _estimate_cost(
|
||||
session_or_model: Dict[str, Any] | str,
|
||||
input_tokens: int = 0,
|
||||
output_tokens: int = 0,
|
||||
*,
|
||||
cache_read_tokens: int = 0,
|
||||
cache_write_tokens: int = 0,
|
||||
provider: str = None,
|
||||
base_url: str = None,
|
||||
) -> tuple[float, str]:
|
||||
"""Estimate the USD cost for a session row or a model/token tuple."""
|
||||
if isinstance(session_or_model, dict):
|
||||
session = session_or_model
|
||||
model = session.get("model") or ""
|
||||
usage = CanonicalUsage(
|
||||
input_tokens=session.get("input_tokens") or 0,
|
||||
output_tokens=session.get("output_tokens") or 0,
|
||||
cache_read_tokens=session.get("cache_read_tokens") or 0,
|
||||
cache_write_tokens=session.get("cache_write_tokens") or 0,
|
||||
)
|
||||
provider = session.get("billing_provider")
|
||||
base_url = session.get("billing_base_url")
|
||||
else:
|
||||
model = session_or_model or ""
|
||||
usage = CanonicalUsage(
|
||||
input_tokens=input_tokens,
|
||||
output_tokens=output_tokens,
|
||||
cache_read_tokens=cache_read_tokens,
|
||||
cache_write_tokens=cache_write_tokens,
|
||||
)
|
||||
result = estimate_usage_cost(
|
||||
model,
|
||||
usage,
|
||||
provider=provider,
|
||||
base_url=base_url,
|
||||
)
|
||||
return float(result.amount_usd or 0.0), result.status
|
||||
|
||||
|
||||
def _format_duration(seconds: float) -> str:
|
||||
|
|
@ -135,7 +176,10 @@ class InsightsEngine:
|
|||
|
||||
# Columns we actually need (skip system_prompt, model_config blobs)
|
||||
_SESSION_COLS = ("id, source, model, started_at, ended_at, "
|
||||
"message_count, tool_call_count, input_tokens, output_tokens")
|
||||
"message_count, tool_call_count, input_tokens, output_tokens, "
|
||||
"cache_read_tokens, cache_write_tokens, billing_provider, "
|
||||
"billing_base_url, billing_mode, estimated_cost_usd, "
|
||||
"actual_cost_usd, cost_status, cost_source")
|
||||
|
||||
def _get_sessions(self, cutoff: float, source: str = None) -> List[Dict]:
|
||||
"""Fetch sessions within the time window."""
|
||||
|
|
@ -287,21 +331,30 @@ class InsightsEngine:
|
|||
"""Compute high-level overview statistics."""
|
||||
total_input = sum(s.get("input_tokens") or 0 for s in sessions)
|
||||
total_output = sum(s.get("output_tokens") or 0 for s in sessions)
|
||||
total_tokens = total_input + total_output
|
||||
total_cache_read = sum(s.get("cache_read_tokens") or 0 for s in sessions)
|
||||
total_cache_write = sum(s.get("cache_write_tokens") or 0 for s in sessions)
|
||||
total_tokens = total_input + total_output + total_cache_read + total_cache_write
|
||||
total_tool_calls = sum(s.get("tool_call_count") or 0 for s in sessions)
|
||||
total_messages = sum(s.get("message_count") or 0 for s in sessions)
|
||||
|
||||
# Cost estimation (weighted by model)
|
||||
total_cost = 0.0
|
||||
actual_cost = 0.0
|
||||
models_with_pricing = set()
|
||||
models_without_pricing = set()
|
||||
unknown_cost_sessions = 0
|
||||
included_cost_sessions = 0
|
||||
for s in sessions:
|
||||
model = s.get("model") or ""
|
||||
inp = s.get("input_tokens") or 0
|
||||
out = s.get("output_tokens") or 0
|
||||
total_cost += _estimate_cost(model, inp, out)
|
||||
estimated, status = _estimate_cost(s)
|
||||
total_cost += estimated
|
||||
actual_cost += s.get("actual_cost_usd") or 0.0
|
||||
display = model.split("/")[-1] if "/" in model else (model or "unknown")
|
||||
if _has_known_pricing(model):
|
||||
if status == "included":
|
||||
included_cost_sessions += 1
|
||||
elif status == "unknown":
|
||||
unknown_cost_sessions += 1
|
||||
if _has_known_pricing(model, s.get("billing_provider"), s.get("billing_base_url")):
|
||||
models_with_pricing.add(display)
|
||||
else:
|
||||
models_without_pricing.add(display)
|
||||
|
|
@ -328,8 +381,11 @@ class InsightsEngine:
|
|||
"total_tool_calls": total_tool_calls,
|
||||
"total_input_tokens": total_input,
|
||||
"total_output_tokens": total_output,
|
||||
"total_cache_read_tokens": total_cache_read,
|
||||
"total_cache_write_tokens": total_cache_write,
|
||||
"total_tokens": total_tokens,
|
||||
"estimated_cost": total_cost,
|
||||
"actual_cost": actual_cost,
|
||||
"total_hours": total_hours,
|
||||
"avg_session_duration": avg_duration,
|
||||
"avg_messages_per_session": total_messages / len(sessions) if sessions else 0,
|
||||
|
|
@ -341,12 +397,15 @@ class InsightsEngine:
|
|||
"date_range_end": date_range_end,
|
||||
"models_with_pricing": sorted(models_with_pricing),
|
||||
"models_without_pricing": sorted(models_without_pricing),
|
||||
"unknown_cost_sessions": unknown_cost_sessions,
|
||||
"included_cost_sessions": included_cost_sessions,
|
||||
}
|
||||
|
||||
def _compute_model_breakdown(self, sessions: List[Dict]) -> List[Dict]:
|
||||
"""Break down usage by model."""
|
||||
model_data = defaultdict(lambda: {
|
||||
"sessions": 0, "input_tokens": 0, "output_tokens": 0,
|
||||
"cache_read_tokens": 0, "cache_write_tokens": 0,
|
||||
"total_tokens": 0, "tool_calls": 0, "cost": 0.0,
|
||||
})
|
||||
|
||||
|
|
@ -358,12 +417,18 @@ class InsightsEngine:
|
|||
d["sessions"] += 1
|
||||
inp = s.get("input_tokens") or 0
|
||||
out = s.get("output_tokens") or 0
|
||||
cache_read = s.get("cache_read_tokens") or 0
|
||||
cache_write = s.get("cache_write_tokens") or 0
|
||||
d["input_tokens"] += inp
|
||||
d["output_tokens"] += out
|
||||
d["total_tokens"] += inp + out
|
||||
d["cache_read_tokens"] += cache_read
|
||||
d["cache_write_tokens"] += cache_write
|
||||
d["total_tokens"] += inp + out + cache_read + cache_write
|
||||
d["tool_calls"] += s.get("tool_call_count") or 0
|
||||
d["cost"] += _estimate_cost(model, inp, out)
|
||||
d["has_pricing"] = _has_known_pricing(model)
|
||||
estimate, status = _estimate_cost(s)
|
||||
d["cost"] += estimate
|
||||
d["has_pricing"] = _has_known_pricing(model, s.get("billing_provider"), s.get("billing_base_url"))
|
||||
d["cost_status"] = status
|
||||
|
||||
result = [
|
||||
{"model": model, **data}
|
||||
|
|
@ -377,7 +442,8 @@ class InsightsEngine:
|
|||
"""Break down usage by platform/source."""
|
||||
platform_data = defaultdict(lambda: {
|
||||
"sessions": 0, "messages": 0, "input_tokens": 0,
|
||||
"output_tokens": 0, "total_tokens": 0, "tool_calls": 0,
|
||||
"output_tokens": 0, "cache_read_tokens": 0,
|
||||
"cache_write_tokens": 0, "total_tokens": 0, "tool_calls": 0,
|
||||
})
|
||||
|
||||
for s in sessions:
|
||||
|
|
@ -387,9 +453,13 @@ class InsightsEngine:
|
|||
d["messages"] += s.get("message_count") or 0
|
||||
inp = s.get("input_tokens") or 0
|
||||
out = s.get("output_tokens") or 0
|
||||
cache_read = s.get("cache_read_tokens") or 0
|
||||
cache_write = s.get("cache_write_tokens") or 0
|
||||
d["input_tokens"] += inp
|
||||
d["output_tokens"] += out
|
||||
d["total_tokens"] += inp + out
|
||||
d["cache_read_tokens"] += cache_read
|
||||
d["cache_write_tokens"] += cache_write
|
||||
d["total_tokens"] += inp + out + cache_read + cache_write
|
||||
d["tool_calls"] += s.get("tool_call_count") or 0
|
||||
|
||||
result = [
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue